Lahcen Oubahssi
email: lahcen.oubahssi@univ-lemans.fr

Claudine Piau-Toffolon
email: claudine.piau-toffolon@univ-lemans.fr

Oussema Mahdi
email: oussema.mahdi@univ-lemans.fr

VR-Peas: A Virtual Reality PEdAgogical Scenarisation tool

Keywords: Virtual Reality PEdAgogical Scenarisation tool VRLEs, TEL, VR-PEAS, Pedagogical Scenarios, Authoring Tools, Instructional Design

Introduction

Virtual reality (VR) technologies have become a key component of modern educational technology, and allow educational teams to use interactive means of developing captivating and immersive learning experiences [START_REF] Suri | Systematic literature review: The use of virtual reality as a learning media[END_REF]. Recent technological advances in computer hardware and VR technology offer great potential for the development of different VR learning environments (VRLEs), which are semiimmersive three-dimensional (3D) virtual learning systems [START_REF] Vix Kemanji | Towards Flexible Authoring and Personalization of Virtual Reality Applications for Training[END_REF]. These environments combine characteristics such as representational fidelity, learner interactions and identity construction (Fowler, 2015). However, we observe that the design of a VRLE is a complex and expensive process, posing challenges of both a technical nature, involving interdisciplinary aspects intrinsic to VR (computer graphics, haptic devices, distribution, etc.) and a cognitive nature, such as the need to respect the characteristics of the task to be learned, and transfer of learning to the real world [START_REF] Bossard | Transfer of learning in virtual environments : a new challenge?[END_REF]. VR is not educationally useful in itself, and ad hoc methodological approaches using VR are needed [START_REF] Vergara | On the Design of Virtual Reality Learning Environments[END_REF]Martin-Gutiérrez et al., 2017). In such a rich learning environment, we have to look at activity from both the perspectives of both design and use [START_REF] Wasson | Learning Design: European Approaches[END_REF]. Many research studies have investigated the use perspective of VR, and have demonstrated its educational benefits in different contexts [START_REF] Matovu | Immersive virtual reality for science learning: Design, implementation, and evaluation[END_REF][START_REF] Villena-Taranilla | Effects of virtual reality on learning outcomes[END_REF]Kaminska et al., 2019;[START_REF] Suri | Systematic literature review: The use of virtual reality as a learning media[END_REF][START_REF] Toyoda | VR-based health and safety training in various highrisk engineering industries: a literature review[END_REF]. Our aim is to study the design perspective of VRLEs. According to the model of technology integration [START_REF] Mishra | Technological Pedagogical Content Knowledge: A Framework for Teacher Knowledge[END_REF], the design of a VRLE should combine three sources of knowledge: technology, pedagogy and content. A VRLE includes an educational simulation that is built around a set of educational objectives. The description of an educational simulation must take into account the specificities of the technological environment (its structure and its dynamics); however, to fully describe the learning experience, VRLEs also need to specify pedagogical requirements, meaning that designers need to exactly describe the operationalisation and the control of the activities in the environment.

Instructional design provides a framework for designing and implementing learning experiences with VR. In general, in the domain of technology-enhanced learning (TEL) and hence in VRLEs, the pedagogical situation is considered as a composition of activities carried out by various actors in a specific environment. The sequencing of these activities is described in a hierarchical form, and activities may be organised sequentially or in parallel. The aim of instructional design is to formalise the process of designing pedagogical activities. In our context, this process must take into account the specificity of the learning environment (immersive), the materials used (VR headsets, VR controller, etc.) and the theoretical aspects of implementing a virtual learning environment [START_REF] Vergara | On the Design of Virtual Reality Learning Environments[END_REF]. In view of these aspects, our first aim is to model the scenarisation process of VR-oriented pedagogical activities. Given that research on pedagogical scenarisation in the context of VR is recent, we have extended our study to methods applied in the domain of TEL. This exploration allows us in the first place to identify the characteristics that seem to be essential when designing learning activities in a VR environment for human learning. In addition, we aim to identify the characteristics that a pedagogical scenario tool must possess to enable such environments to be designed and deployed. Learning design involves several steps, and the process consists mainly of (i) specifying a scenario, (ii) making it available to users and (iii) promoting its execution (Abedmouleh et al., 2012;[START_REF] Paquette | The MOT+ Visual Language for Knowledge-Based Instructional Design[END_REF][START_REF] Hernández-Leo | Helping teachers to think about their design problem : a pilot study to stimulate design thinking[END_REF]. In the TEL field, specific research issues are associated with each of these stages. We therefore explore the question of the pedagogical scenario in its totality, with the aim of achieving our main objective of helping and supporting teachers to design, adapt and reuse their educational scenarios based on virtual reality.

Our first research problem thus concerns the design of pedagogical activities in the context of VR. Learning design forms an integral part of teaching practice [START_REF] Goodyear | Teaching as design[END_REF][START_REF] Wasson | Learning Design: European Approaches[END_REF], and consists of specifying and modelling pedagogical situations based on a particular pedagogical approach. It is "above all a work of content design, organization of resources, planning of activity and mediations to induce and support learning, and orchestration" [START_REF] Henri | La scénarisation pédagogique dans tous ses débats[END_REF], taking into account the pedagogical approach used.

Our second issue concerns the operationalisation of VR-oriented pedagogical scenarios and the generation of VRLEs. This second aspect represents an intermediate phase that lies between the learning experience and scenario design, and involves making the scenario described by the teacher usable and manipulable within a VRLE while preserving the pedagogical semantics described [START_REF] Oubahssi | Design and operationalization of patterns: Case of a training situation of personal assistance for public in professional integration[END_REF] [START_REF] Tadjine | A Process Using Ontology to Automate the Operationalization of Pattern-Based Learning Scenarios[END_REF] [START_REF] Bakki | MOOCAT: A Visual Authoring Tool in the cMOOC Context[END_REF] [START_REF] Bakki | Pedagogical Scenario Design and Operationalization: A Moodle-Oriented Authoring Tool for Connectivist Activities[END_REF] (Oubahssi & Piau-Toffolon 2019) [START_REF] Mahdi | Assistance to Scenarisation of VR-oriented Pedagogical Activities: Models and Tools[END_REF] [START_REF] Mahdi | Modèle et outil pour assister la scénarisation des activités pédagogiques orientées RV[END_REF].

In this paper, we will examine how scenario design can be integrated into VRLEs for the creation and use of dynamic and engaging learning experiences by the teachers themselves, without the need for help from a pedagogical assistant or computer engineer. To achieve this, we develop according to an agile approach a tool called the VR-PEAS editor (Virtual Reality PEdAgogical Scenarisation tool), which provides a solution to support and help teacher-designers to design, adapt and reuse their VRoriented educational scenarios. This tool enables the designer to generate a VRLE and to play the scenario produced. This paper is organised as follows. In the next section, a selected literature review of VR-oriented pedagogical design is presented. The section concludes by noting the lack of a model that covers the pedagogical needs of teachers independently of the application area, and which includes the modelling of pedagogical structuring and the consideration of the specificities of the VR environment. Our research proposal for a VR-oriented pedagogical scenario model and the VR-PEAS scenario editor are described in Section 3. The architectural and technical choices that were made are explained in Section 4. In Section 5, we report on an case study evaluation conducted with teachers, and we draw conclusions in Section 6, where some findings, assessments and perspectives for future work from this study are given. Our aim is to contribute to the elaboration of powerful abstraction and to enable models and processes to be run on computers in the TEL domain [START_REF] Tchounikine | A Computer Science Perspective on Technology-Enhanced Learning Research[END_REF].

Scientific Background

In this section, we carry out a literature review of pedagogical activities in VRLE and VR-oriented authoring tools. Bringing these topics together allows us to analyse both the strengths and shortcomings of our VRLE learning design proposal.

VR-oriented educational activities

As mentioned earlier, instructional design involves specifying and modelling the progress of pedagogical situations. In the context of VR, a pedagogical scenario allows teacher-designers to structure the learning context and to organise it in the VRLE and over time. VRLEs are subject to several uncertainties that the scenarisation system cannot control, for example the freedom of action of the learner, the autonomy of virtual characters, and the evolution of the states of VR objects, making it impossible to predict every outcome in the virtual environment, and the learning design system must therefore be resilient to guarantee the smooth unfolding of the educational objectives.

This involves taking into account uncertainties and regenerating the learning scenario in real time. [START_REF] Chen | The theoretical framework for designing desktop virtual reality-based learning environments[END_REF] propose a theoretical framework that identifies four principles for designing VR-oriented pedagogical scenarios: (i) the conceptual principle that guides the learner towards the information that must be taken into account; (ii) the principle of metacognition, which guides the learner's thinking process during learning;

(iii) the procedure, which indicates how to use the information available in the virtual environment; and (iv) the strategic principle that allows the learner to analyse the learning task or the problem to be solved. This research work provides a basis for identifying the different elements that should be taken into account when designing a VRLE (e.g. the type of learning targeted, pedagogical scripting, support systems, and the pedagogy to be implemented). However, it does not take into account the process of learning design of VRLEs by the teachers.

In the approach of [START_REF] Carpentier | Diegetization: an approach for narrative scaffolding in openworld simulations for training[END_REF], the virtual environment is populated by autonomous virtual characters and the user is free to act. The design of a pedagogical scenario is realised in two steps: the dynamic objectives are determined based on the user's activity, and a pedagogical scenario is then generated and implemented through adjustments to the simulation. [START_REF] Marion | Integrating Knowledge from Virtual Reality Environments to Learning Scenario Models-A Meta-modeling Approach[END_REF][START_REF] Marion | Modélisation de scénarios pédagogiques pour les environnements de réalité virtuelle d'apprentissage humain[END_REF]) define a VR-oriented pedagogical activity as a task to be carried out by the learner in the virtual environment and described by the teacher (the 'what'). To this description, the teacher can add pedagogical information with the aim of instrumenting this task based on a specific pedagogical objective (the 'how'). An educational objective is then accomplished by carrying out a series of steps, called learning activities, which include a series of virtual actions.

From a study of these research works, we found that existing scenario models cannot be easily adapted by the teacher to a specific pedagogical situation. A pedagogical model is planned from the earliest stages of the design of a VLRE, and all possible situations must have been considered beforehand. This constraint can not be adapted to the practices of the teacher-designer [START_REF] Goodyear | Teaching as design[END_REF][START_REF] Hernández-Leo | Helping teachers to think about their design problem : a pilot study to stimulate design thinking[END_REF].

VR-oriented authoring tools

In this section, we analyse a selection of VR-oriented authoring tools (also called scenario editors) in order to identify common aspects that can help a teacher to design a pedagogical scenario and to generate a VRLE. An authoring tool is computer software whose primary purpose is to enable, encourage, and assist people without programming skills in designing, editing, configuring, and running virtual content. It allows for the integration of the content of an educational situation designed by educational engineers or teachers (objects, instrumented educational activities, etc.). In the following, we review some examples of VR authoring tools [START_REF] Marion | Modélisation de scénarios pédagogiques pour les environnements de réalité virtuelle d'apprentissage humain[END_REF]Oubahssi & Piau-Toffolon, 2019;[START_REF] Cormier | VirTeaSy a haptic simulator for dental education. The 6th international conference on virtual learning ICVL[END_REF][START_REF] Gerbaud | GVT : a platform to create virtual environments for procedural training[END_REF][START_REF] Lourdeaux | Réalité virtuelle et formation : conception d'environnements virtuels pédagogiques[END_REF].

Proposed by [START_REF] Marion | Modélisation de scénarios pédagogiques pour les environnements de réalité virtuelle d'apprentissage humain[END_REF], the Poseidon scenario editor aims to facilitate the creation of VR-oriented pedagogical scenarios. Functionalities have been designed for creating and modifying the components of a Poseidon scenario (learning environments, pedagogical organisation and pedagogical activities). This tool is based on an explicit business model that describes both the characteristics of the virtual environment (entities, activities, etc.) and the concepts involved in learning, and ensures a link between them. The approach is based on meta-modelling to ensure the genericity of modelling, regardless of the nature or field of the VRLE, and relies on an abstract representation of virtual environments with the MASCARET model [START_REF] Buche | Mascaret : Pedagogical multi-agents system for virtual environment for training[END_REF].

The ARVAD project (a virtual learning environment for the acquisition of orientation skills) (Oubahssi & Piau-Toffolon, 2019) Another tool called VirTeaSy, proposed by [START_REF] Cormier | VirTeaSy a haptic simulator for dental education. The 6th international conference on virtual learning ICVL[END_REF], allows for the design of virtual teaching situations dedicated to implantology, and makes it possible to generate learning/teaching situations for students on surgical or dental courses to train on the placement of implants. Using the VirTeaSy tool, the teacher first builds the virtual environment, and then identifies the 3D objects that constitute it (such as a dental tool, a tooth, a chair, etc.) and their interactions. VirTeaSy makes it possible to modulate the virtual environment according to the elements of the conceptual structure of the situation, such as the density, shape and thickness of the bone, the location of the implant site, and the adjacent anatomical structures. In addition, functions, aids, and the dental instruments available for the learning activities can be defined. The VirTeaSy project provides an effective solution to the well-known difficulties in practical training in implantology, but it cannot be used in other contexts. [START_REF] Mollet | Storytelling in Virtual Reality for Training. Technologies for E-Learning and Digital Entertainment[END_REF], and a scenario model called LORA [START_REF] Mollet | Storytelling in Virtual Reality for Training. Technologies for E-Learning and Digital Entertainment[END_REF]. The description of a virtual environment for learning with GVT is organised around two aspects: a description of the VR objects and their interactions, and a description of the procedure to be realised. The generation of scenarios describing the progress of these activities in a well-defined order is a complicated task in GVT, and to achieve this, [START_REF] Mollet | Storytelling in Virtual Reality for Training. Technologies for E-Learning and Digital Entertainment[END_REF] used the LORA language. GVT is reusable thanks to its generic STORM model. A distinction is made between the activity scenario, which describes the procedures to be realised in the virtual environment, and the pedagogical scenario, which promotes the reusability of existing scenarios. One limitation of GVT is that it can only be applied to learning procedures in the design of specific industrial context, and can rarely be applied in other contexts.

Proposed by [START_REF] Lourdeaux | Réalité virtuelle et formation : conception d'environnements virtuels pédagogiques[END_REF], the FIACRE project was designed to be used in the industrial context of high-speed train operation. A prototype training simulator using VR design techniques was created. Although train drivers use this simulator, FIACRE is not a driving simulator but a learning system for the control and manipulation of switchblades on high-speed railway lines. The trainer identifies the components of the virtual environment for the learner. FIACRE describes the activity characteristics to be offered to learners, depending on the cognitive and behavioural components that the trainer seeks to reproduce in the virtual environment. This allows the trainer to specify which behavioural interfaces can be used and how, for each activity. FIACRE uses an intelligent pedagogical agent called HAL (Help Agent for Learning) to assist trainers and offer the appropriate assistance for learners. However, FIACRE can only be used in the industrial context in which the project took place.

Findings and discussion

Our review of the state of the art has focused mainly on the various works on the design of learning environments, and we note that many issues, both theoretical and methodological, remain to be explored. We identified (as illustrated in Table 1) a lack of a model that covers the pedagogical needs of teachers, aim The solutions proposed are too often rigid, making it difficult to design reusable and adaptable scenarios. Our aim is to provide a methodology that ensures best practices for the integration of Virtual

Reality in an educational context. This literature review helped us to propose a process of design and production of virtual Reality learning environments based on pedagogical aspects and taking into account technological aspects.

Table1. Analysis of the VR-oriented models and tools

A VR-oriented Pedagogical Scenario Model

The literature review presented above allowed us to define a list of characteristics that seem to be useful and interesting in terms of answering our research questions in relation to the teachers' learning design activity. These characteristics are as follows:

• Abstract modelling of virtual actions to ensure genericity;

• Modelling of pedagogical resources (VR-oriented pedagogical objects) and their relationships with the actions realised in the virtual environment;

• A flexible structure to help teachers to adapt or create new pedagogical situations without reinventing the VRLE design process for each new environment;

• A reusable structure that is modifiable, with configurable components, allowing it to be adapted to different contexts for the realisation of a scenario without the need to modify its description.

To validate our choices, we considered four examples of educational situations, as follows:

• Virtual animal experimentation, where the objective is to sensitise students to protocols and various actions related to animal experimentation.

• Realisation of a volumetric assay, where the objective is to control the steps necessary to determine the concentration of an unknown solution by volumetric assay.

• An investigation using ion recognition tests in solution, where the objective is for the student to identify the presence of ions in a solution using test products (reagents).

• Relativity of movement, where the objective is to understand that the nature of the movement depends on the chosen frame of reference.

The analysis and design of these different pedagogical situations made it possible to obtain a clearer vision of the essential elements for the modelling of a domain-free VR-oriented pedagogical scenario. It also allowed us to identify the pedagogical concepts necessary to express a VR-oriented pedagogical scenario, such as the activities and actions used in a virtual environment, the pedagogical objects necessary for their realisation, and the animations associated with these objects.

Following prior research [START_REF] Fuchs | Three levels of Immersion and Interaction in a Approach of the VR Design[END_REF][START_REF] Fuchs | Virtual reality: concepts and technologies[END_REF][START_REF] Richir | How to design compelling Virtual Reality or Augmented Reality experience[END_REF][START_REF] Schlemminger | Réalité virtuelle et jeux: de nouveaux outils pour des apprentissages plurilingues[END_REF], we consider that activities can be grouped into four basic behaviours called virtual behavioural primitives (VBPs). This concept has been described in detail by [START_REF] Mine | Virtual environment interaction techniques[END_REF] and [START_REF] Fuchs | Virtual reality: concepts and technologies[END_REF]. There are four types of action in a VBP: (i) techniques for observing the virtual world; (ii) techniques for moving within the virtual world; (iii) techniques for acting within the virtual world, and

(iv) techniques for communicating either with others or with the environment. To achieve our research goals, we refine the VBPs into sub-categories, each representing a group of specific VR actions. We also associate some of the most frequently recommended VR devices with each category. For example, for the category 'acting within the virtual world', we identify two subcategories, 'selecting' and 'manipulating', and three devices that can be used (VR gloves, a VR controller, or a VR headset).

Unlike training simulators, a VRLE mainly consists of virtual devices; this offers the advantage that the user can detach from realism when this can improve learning.

The results of our analysis have led us to the design of a VR-oriented pedagogical scenario model (Figure 1) to reflect the concepts that are most relevant and necessary for the description of an action and hence of an activity in a virtual environment. Our proposal is based on a detailed description of activities (use of the VBP concept) in which the learner interacts with a device, in order to take into account the specificities of the conduct of these activities in a virtual environment. Our model is organised based on four levels: the User, Scenario, Business pedagogical concepts and Technical levels.

Business pedagogical concepts level:

The VRActivity entity has a reflexive association, where a lambda pedagogical activity may have a beta parent action. The beta will be activated only when the lambda is validated. Activities that do not have a parent activity can be performed at any time. Educational activities are made up of a set of VR actions, represented by the VRAction entity. Each VRAction is characterised by a pedagogical objective for the learner, a description that details the virtual action, and the steps that must be followed by the learner in order to realise the action correctly. We note that some virtual actions must be realised in a predefined order. The reflexive association of the VRAction class indicates that a virtual action Action2 may have a parent action Action1, meaning that Action2 will only be triggered when Action1 is validated. Similarly, Action3 will only be triggered when Action2 and Action1 are validated. If Action1 does not have a parent action, it does not depend on the trigger conditions, and can be executed at any time during the educational activity. To further describe these virtual actions, we use reference shapes called checkpoints, a technical concept used and developed in several prior research works [START_REF] Djadja | Modeling and Evaluating of Human 3d+t Activities in Virtual Environment[END_REF][START_REF] Gil | Unity3D-based Neuro-Evolutive Architecture to Simulate Player[END_REF][START_REF] Mahdi | Modèle et outil pour assister la scénarisation des activités pédagogiques orientées RV[END_REF][START_REF] Oubahssi | VEA: A Virtual Environment for Animal experimentation[END_REF]. Four types of checkpoints have been identified that correspond to the state of the action, as follows: (i) StartCheckpoint Depending on the values assigned to the parameters, the properties associated with each VR object may change; for example, this virtual object will have the property of a container.

Technical level: This level groups the objects and concepts needed to realise VR actions, as well as the animations produced in the VRLE. For example, a learning environment (represented by the entity Environment) contains VR objects (VRObject) that may be necessary for the learner's interaction or understanding of the learning concept. The VRObject class allows us to describe two types of objects: technical and pedagogical VR objects. We use the term raw object to indicate a technical VR object, which is also referred to as a 3D object or graphic object. A raw object is an entity used to acquire knowledge, whereas a pedagogical object is a teaching resource or learning object (IEEE, 2002) and is represented as a reusable educational entity that can be aggregated, stored, searched for and reused in different learning environments [START_REF] Wiley | The instructional use of learning objects[END_REF].

VR objects aggregate entities that support the progress of VR actions. Each VR object can have one or more Property characteristics and one or more Animation behaviours.

Properties are used to store values associated with these objects. Some technical properties are common to all objects (especially those that govern the position, shape, or colour of objects), while others are properties specific to the object or learning domain;

for example, a hydrochloric acid solution (as a pedagogical object) has properties such as concentration, volume and vaporisation temperature. These pedagogical objects and their properties allow for the creation of VR actions and the triggering of their animations. The parameters of the action and the checkpoints can be set by the teacher in order to flesh out the description of the pedagogical actions. The Animation class enables the dynamic behaviour of raw objects. Animations define the values of the object's properties based on the actions exerted on the object or on the environment in which it is used. For example, a cube (representing a raw object) must have the technical properties of weight and position: if it is dropped, it falls and deforms. We can associate it with educational properties such as gravitation for use in an educational context as a physics course.

To achieve this, we associate a model in JSON format (Figure 2) with each VR object, and predefine the animations that should be developed. Each animation has an identifier, a name, a description, and a set of compatible actions: for example, the animation corresponding to the "cut action" shows the skin opening. The defined objects (including their contours and trajectories) are flagged with checkpoints to trigger the corresponding animation when the learner achieves or misses the respective checkpoint (Figure 3). We define a list of animators for each animation. The animator depends on a specific object, a trigger variable, an animation type, and a Boolean condition that stops the animation when the learner passes the checkpoint. In other words, a checkpoint includes the rules that describe the dynamic behaviour of raw objects. These rules define the animation associated with an object, based on the actions performed on it or on the environment. 1. User level: used to define and manage the users involved in the design process, this level is independent of the learning domain.

2. Scenario level: used to define the learning scenario, its pedagogical actions and to associate virtual actions to it, it is also independent of the learning domain.

3. Pedagogical business concepts level: this level is specific to the domain, because each domain has its own business concepts. This level makes it possible to associate virtual actions with domain activities. For example, in the chemistry domain, the actions "Fill the burette and pour water" can be linked to the activity "Choose the reagents needed to carry out the test".

4. Technical level: Allows the use of technical or educational objects specific to the domain, as well as the virtual animations associated with each object. For example, in the chemistry domain, the teacher can use the objects (H2O, burette, beaker) and the animation simulating the filling of the beaker.

In order to use VR-Peas in a new domain, it is necessary to develop virtual objects and animations specific to that domain. The prospects of this research are to define mechanisms to automate the addition of objects and their animations in the VR-Peas editor.

VR-PEAS: Architecture and Elements

In this research, one of our objectives is to offer teachers an easy-to-use visual modelling tool to create or adapt an existing scenario, based on the scenario model presented in the previous section. In particular, we consider the question of the description of the VR-oriented learning activities and their organisation. This visual modelling tool must be able to provide an overall view of the entire scenario to be implemented, and should allow teachers to automatically deploy the pedagogical scenarios that they have designed with the editor tool. We have developed a tool called VR-PEAS that allows trainers to create and edit VR-oriented pedagogical scenarios, in order to help teachers to design operational VRLEs.

Architecture of VR-PEAS

We observed that in an interactive context, the pedagogical scenario no longer consists solely of scenario modelling, but also involves the establishment of the mechanisms necessary for the realisation of this scenario. Figure 4 shows the overall architecture of our editor, and its different modules are discussed in the following sections.

Pedagogical environment management module:

The learning environment management module is necessary to help the teacher to prepare the chosen environment, and makes it possible to instantiate the pedagogical objects loaded in the VR data manager. It also makes it possible to display and use pedagogical objects via the educational object manager. This module is equipped with a pedagogical properties manager, which allows each object to be assigned suitable pedagogical properties.

VRLE model module:

This is used to implement the scenario model described in the previous section. The VR-PEAS module and the VR data manager use this module to structure the models of VR-oriented educational scenarios.

VR data manager module:

This ensures the connection to the database, where the scenario data is stored via the Scenario manager. The latter includes two modules, called DB manager and JSON manager. The first module is used to exchange scenario data with the database, and the second is responsible for loading and unloading data from a scenario provided in JSON format. The sub-module entitled Data loader is composed of a VR environment loader, which is responsible for the loading of virtual environments, and a VR objects loader, which loads VR-oriented educational objects.

The current scenario data retrieved in the Scenario manager are stored in a sub-module called Global data.

VRLE module:

This allows for playing of the scenario. It is used by the teacher to test the execution of the scenario via the generated VRLE, and is also accessible to learners during the learning phase. The VRLE module makes it possible to control the actions of the learner thanks to a sub-module called the Actions validator. The latter includes the list of actions to be performed and generates the learning traces.

Functionalities of VR-PEAS

As illustrated in Figure 5, the main functionalities of VR-PEAS are:

• Graphic manipulation functionalities in the user interface, in particular:

o Drag-and-drop of pedagogical objects from the inventory of objects to add or remove elements from the environment;

o Reorganisation by modifying the position of objects in the user interface and defining the desired alignments and rotations;

o Resizing of objects to adapt their size as needed via the graphic manipulation palette. We note that the manipulation of an entity (object, checkpoint, etc.) of the environment in order to associate a particular configuration with it can be realised either directly from the editor or in the immersive mode (with a VR headset and controllers);

• Functionalities for navigation of the environment and adjustment of visualisation. Our editor offers different views (immersive and non-immersive) according to the needs of the teacher;

• Notifications about the learner's mission, to let them know at all times what they are expected to do;

• Management of the sequence of VR actions associated with a pedagogical activity and the sequence of pedagogical activities within the virtual environment, via a checkbox that allows the designer to specify whether the current action (or activity) must be preceded by another action (or activity);

• Functionalities for reloading an existing scenario or a partially designed scenario by importing various components created beforehand, such as virtual environments, pedagogical activities and VR actions. The objective is to promote the reuse of existing components, both to speed up the design and to capitalise on the use of components that already have been proved in other VRLEs;

• A VLRE trigger functionality that is used to generate the target VLRE and test the pedagogical scenario;

• A backup functionality that allows the scenario to be saved at any time during modelling.

The teacher can prepare the virtual environment and model a scenario by identifying the educational objects and the parameters necessary for carrying out the VR actions, via the environment preparation interface. This interface is provided with an inventory of VR-oriented pedagogical objects related to the educational situation.

Teachers then proceed to the creation and configuration of instrumented educational activities via the modelling interface. This interface is equipped with the activity management palette, as illustrated in Figure 5. The overall features of VR-PEAS can be previewed on the demo video available from the link given below.1

1 https://lium-cloud.univ-lemans.fr/index.php/s/SX8agkGB2CLYxML

Figure 5. VR-PEAS: Scenario modelling interface

Scenario operationalisation service in VR-PEAS

Our editor offers the teacher not only the means to design a pedagogical scenario but also to operationalise and generate their own VRLE. With this dual function, a teacher can automatically deploy the scenario that has been designed and also allow learners to play the scenario and perform the various instrumented activities. Once the scenario has been designed, all its data are exported via an operationalisation service to the scenario database. The operationalisation service is then responsible for importing the current scenario and its various components. It also makes it possible to load virtual environments and pedagogical objects in the Global data module (Figure 4) before proceeding to their instantiation. Using the data associated with the current scenario, the operationalisation service instantiates the 3D environment and the pedagogical scenario objects in the VRLE. We note that the teacher may modify the scenario, save it and deploy it again. Figure 6 illustrates the service for operationalising VR-oriented pedagogical scenarios. This approach is consistent with our research methodology and teachers are engaged in an iterative and participatory design process where development and evaluation phases are intertwined (Figure7). We organised the development process with four teachers involved in 3 domains of expertise (2 in chemistry, 1 in physics, 1 in biology). During the first iteration, a pre-evaluation phase was proposed where the researchers' team presented the objective and concept ideas of the research work and they was asked to propose a pedagogical scenario limited to five activities to get started. Then after each development process iteration, we organised an evaluation session with the four teachers, in order to identify their suggestions for improvement and the new functionalities to be realised. We organised an average of six iterations. The number of iteration depended of the teachers and their domains of expertise. For example, with the biology teacher we validated two VR actions at each iteration. At the methodological level, we defined evaluation criteria based on the definitions of utility and usability given by [START_REF] Tricot | Utilité, utilisabilité, acceptabilité : interpréter les relations entre trois dimensions de l'évaluation des EIAH[END_REF]. Utility refers to the objectives that an artefact makes it possible to achieve in specific situations when used by a given user [START_REF] Tricot | Utilité, utilisabilité, acceptabilité : interpréter les relations entre trois dimensions de l'évaluation des EIAH[END_REF], whereas usability refers to the possibility of using a device at the level of its interface, its navigation, and its coherence with the objective.

To evaluate the usability, we applied the System Usability Scale (SUS) model [START_REF] Bangor | Determining What Individual SUS Scores Mean : Adding an Adjective Rating Scale[END_REF][START_REF] Lewis | Item benchmarks for the system usability scale[END_REF]. In our case, we consider that VR-PEAS is:

• Useful if it allows a trainer to design a VR-oriented pedagogical scenario. We use this criteria to validate whether our scenario model, and in particular the representation of its pedagogical structuring (design of activities and pedagogical actions), makes it possible to produce a VRLE which responds to the initial needs of the teacher;

• Usable by teachers if it is easy to use (allows simple and easy navigation), that is, if it provides a scenario creation interface with functionalities that facilitate its use. Validation is therefore a question of exploring the satisfaction of the teachers with the realisation of the tasks;

• Useful if it can be applied in different contexts. In addition to the evaluation of usability and usefulness perceived by teachers, we aim to check that it allows us to create VR-oriented pedagogical scenarios that can be used in different educational contexts.

Our evaluation phase took place in three steps. We started by validating our pedagogical scenarios model with the teachers, in order to get their feedback. We then carried out intermediate tests, in which the teachers were asked to design and deploy the educational activities for their scenarios. One of the primary purposes of this evaluation phase was to allow the teachers to interact with the tool (the editor) in order to improve the development iteration in progress. Discussions with teachers were also held to provide them with VR objects adapted to their needs. A test phase was applied to validate the different activities that had been designed and to validate the entire scenario in the last iterations. Finally, we sought to validate the usefulness and usability of the tool via a questionnaire submitted to each teacher participating in the final evaluation.

This led into an analysis phase in which we interpreted the feedback collected from the teachers via the questionnaire.

In the last step, we analysed the results obtained during the evaluation of VR-PEAS. The questionnaire consisted of two types of questions: (i) closed questions concerning the usefulness and usability of VR-PEAS, where each teacher was asked for scores on a scale of one to five (from strongly disagree to totally agree); and (ii) open questions, whose objective was to let users express themselves freely and to present their feelings and suggestions for improvement. The results showed general satisfaction with the VRLE generated over the iterations. The usefulness of VR-PEAS was also considered satisfactory, since the teachers were able to design and generate goodquality teaching scenarios. This also supported our proposed scenario model. Although our results are not statistically representative, the results confirmed the usability of our editor and its usefulness in different contexts. Using VR-PEAS, the teachers were able to design a variety of activities, and were able to provide clear and detailed specifications.

Three teachers felt more comfortable with the tool and gave better marks than the fourth, who did not have time to really get used to the immersive mode and exploit the full potential of VR. However, despite the new concepts that the teacher-designers had to assimilate, this teacher still managed to understand the functionalities of our scenario tool, which validates its intuitiveness. The others quickly transcribed their scenarios and used the VR-PEAS functionalities more appropriately, with less practice time than the fourth teacher. Finally, although the results of the evaluations validate our objectives, the VR-PEAS tool in its current version has certain shortcomings, particularly related to its ergonomics. Another point raised by the teacher-designers was the need to review the captions used for the elements of the palette, as they may cause some uncertainty among teachers who do not have strong pedagogical skills.

Conclusion

In this research work, we addressed the issue of designing and deploying VRoriented educational scenarios. To provide practical and theoretical solutions, we reviewed various models in the literature and existing tools to assist teachers in the design and deployment of a VRLE. We identified a lack of a model that covers the pedagogical needs of teachers, including the modelling of pedagogical structuring and the specificities of the VR environment. A VR-oriented pedagogical scenario model was designed based on our findings from the literature, and designs for four different pedagogical situations were considered in order to establish the information necessary for the description of a pedagogical activity in a virtual environment. The objective was to provide scenarios that could meet the needs of the teachers and that could be designed by them. We organised our approach around two central elements of the VR-oriented pedagogical scenario: the VR action, which acts as a link between the use of a virtual environment and the pedagogical activity [START_REF] Mellet D'huart | Virtual Environment for training: An art of enhancing reality[END_REF], and the VRoriented educational object necessary for its realisation. To ensure that the scenarios created in this process were sufficiently generic and reusable, we focused on the concept of design patterns. This approach allowed for adaptability to the complexity and context-dependence of the scenario [START_REF] Mor | Design approaches in technology enhanced learning[END_REF]. To enable the design and operationalisation of pedagogical scenarios in a VR environment, we developed a VRoriented pedagogical scenario editor called VR-PEAS that reified the design and production process of a VRLE. The tool was designed to be easy to handle by teachers who are not expert in VRLE design, and is rich in functionalities to enable various scenario contexts to be handled. In order to validate our theoretical and technical contributions, we proposed a development approach based on an agile mode, with iterative test and evaluation phases that took place in three steps: a pre-evaluation stage, intermediate evaluations in parallel with the development phase of VR-PEAS, and a final evaluation of the tool based on empirical evaluative case studies and using a qualitative method with the administration of a questionnaire. This allowed us to assess the usefulness and usability of the VR-PEAS tool. The results from the various evaluations and our analysis of the answers from the teacher-designers to the questionnaires revealed that each teacher successfully designed a VRLE that aligned with the pre-defined scenario. Although we did not obtain statistically significant results, we saw positive trends in the responses regarding usefulness. Using the VR-PEAS editor, teachers were able to design pedagogical scenarios that involved complex and varied activities. In addition, the teachers seemed to develop skills in the use of VR-PEAS, as they were able to apply their learning to subsequent designs. This research opens up many possibilities for future development, such as improving VR-PEAS,

  focuses on the design and operationalisation of learning situations in a VR environment. Its objective is to facilitate learning through digital means, and to provide trainers of Local Units for School Inclusion (LUSI) classes with an educational toolkit that allows them to create and adapt or modify VR scenarios and assess the learners' progress. LUSI classes welcome pupils with cognitive or mental learning disabilities. As a follow-up to this project, an authoring tool called EditoVLAN (Editor of VIrtuaL environment to Acquire orientatioN skills) was developed to allow teachers of LUSI classes to develop exercises based on plans or a labyrinth and visual indices (to help with navigation and displacement). The teacher can also gradually increase the levels of difficulty using more complex plans and courses, reduced visual indices, etc. The editor interfaces are simple and ergonomic, with drag and drop mechanisms at the main interface. However, this tool only makes it possible to model scenarios related to the activities undertaken in LUSI classes.

Figure 1 .

 1 Figure 1. The proposed VR-oriented pedagogical activity model User level: The User class includes any person involved in the design process.

  identifies the start of the action start; (ii) ProgressCheckpoint represents the progress of the action; (iii) EndCheckpoint identifies the end of the action; and (iv) FailCheckpoint reflects an unsuccessful action realised by the learner. These checkpoints can be cubic or spherical, depending on the teacher's needs. To represent these checkpoints, we use a non-instantiable class structure interface. In addition to checkpoints, VR actions have parameters with specific values; for example, in the activity entitled "anaesthesia of the animal via intraperitoneal injection", we define the parameter associated with the action of injecting a liquid as the volume of the contents of the syringe object.

Figure 2 .

 2 Figure 2. Extract from the JSON file describing the properties of a VR-oriented pedagogical object

Figure 4 .

 4 Figure 4. Architecture of VR-PEAS Authentication module: The authentication module allows the teacher to create

Figure 6 .

 6 Figure 6. Operationalisation service in VR-PEAS

Figure 7 .

 7 Figure 7. Intertwinned development and evaluation process

  creating a platform of VR-oriented pedagogical objects, tracking analysis, exploring collaborative learning, and larger-scale experimentation involving learners. Our development approach was exploratory implementing development and evaluation phases iteratively as we intended to elicit basic concepts to design VR oriented training scenario. Further development should be improved in regard to the proposal of Vix et al (2023) of a method for developing VR training applications.

  [START_REF] Gerbaud | GVT : a platform to create virtual environments for procedural training[END_REF] developed the Giat Virtual Training (GVT) platform, which aims to simplify the development of virtual environments for training sessions and can help in applying procedures within a specific learning domain. It is based on two main models: a model of behavioural objects and interactions, called STORM

Acknowledgements

We would like to thank persons who participated in the experiment of the VR-Peas tool.

Availability of data and material

VR-Peas

tool is available on the link: https://lium-cloud.univlemans.fr/index.php/s/qxjtwrcbe6n8dkx

Funding

The authors did not receive support from any organization for the submitted work.


F Sartor

A Burlot

M Méheut

Numerical Simulations of Fan/Airframe Interaction with and without Active Flow-Control

This paper presents a numerical study of a Ultra High Bypass Ratio turbofan (UHBR) with and without active flow control in isolated conditions. Steady and unsteady Reynolds-Averaged Navier-Stokes equations are solved on a 360 • representation of the isolated engine, where the rotating fan and the outlet guide vane (OGV) are fully modelled to analyse the interaction with the airframe. Spatial and temporal resolution are discussed, and different approaches are proposed providing increasing levels of fidelity. The configuration is first investigated without control for various angles of attack at low-speed conditions. Then, the angle of attack is increased until massive flow detachment is observed, and active flow-control technique is proposed to mitigate the impact of the separated zone using flow-suction upstream of the fan. A parametric study is proposed using steadystate simulations, aiming at evaluating the most efficient configuration that allows a gain in the overall performance of the engine while limiting the costs induced by the control device. This work has been conducted in the framework of the European funded Clean Sky 2 project ASPIRE, aiming at demonstrating the ability of existing numerical and experimental methods to accurately assess the aerodynamic and acoustic performance of UHBR engines thanks to a reliable modelling of fan/airframe physical interactions.

I. Introduction

Reduction of fuel consumption and environmental impact are driving the design of the current engines for civil aviation. Increasing the bypass ratio further towards UHBR technology is expected to bring substantial improvement. The use of innovative technologies, such as new light-weight materials, allows a shift to higher values of the optimal bypass ratio, which is driven by a compromise between propulsive efficiency, aerodynamic drag and weight. Reaching this high BPR leads to a major modification in the nacelle and fan designs. In order to increase the flow in the secondary duct, the diameter of the nacelle must be increased, while the length is reduced to limit the overall weight. This reduction leads to a diminution in the air intake length, which is designed to stabilize the flow in front of the fan blades. These modifications may have a strong impact on the aerodynamic field in the intake and could lead to a loss of performance and undesirable flow separation upstream of the fan.

The design of this new type of UHBR engines is a complex process, where multiple elements composing the turbofan have to be adapted in order to find the most efficient solution that satisfy the requirements. The interaction between the main elements composing the engine (intake, fan, OGV, nozzle) can lead to a complex flow field: the non axial-symmetric geometry of the nacelle implies that the flow is three-dimensional even at zero angle of attack. In addition, design at take-off conditions must take into account the high angle of attack of the incoming flow, leading to a highly three-dimensional field. The consequence is the need of a 360 • representation of the whole configuration, where each fan and OGV blade is modelled inside the engine. Many low-fidelity approaches are currently used to evaluate the overall performance of the turbofan, 1 but they often come with hypothesis that limit the application for complex cases where an accurate description is needed, for example when a high angle of attack produces a massive separation that is ingested by the fan. In addition, the flow inside the engine is unsteady, and time-accurate simulations are necessary to reproduce the interaction between the flow around the rotating fan and the rest of the stationary engine.

The intake is usually designed to have high-efficiency in cruise conditions, where the incoming flow is uniform and normal to the fan face. However, the intake must be capable of providing the fan with as uniform flow as possible also in other conditions, for example take-off with cross wind. In this case the angle of attack of the engine can be high and, for an installed engine, this is even locally increased by the deflection caused by the wing, so even more severe incidences must be considered in the design process. Intakes designed for cruise condition are prone to separation at high angle of attack. For the UHBR engines considered in this study, the length of the intake duct is reduced, and the separation is ingested by the fan. This represent a strong limit for the overall performance of the engine (surge can appear) and is a dimensioning factor for the structural strength of the fan blades. Thus, reducing the separation in short intakes has an interest for the design of new engines, where a compromise must be found between short inlets, with limited drag at cruise, and separation-free inlets at take-off, with better propusion efficiency at high angles of attack. [START_REF] Peters | Ultrashort Nacelles for Low Fan Pressure Ratio Propulsors[END_REF] The suppression of flow separation by active flow control techniques is a promising technology for future transport aircraft [START_REF] Gad-El Hak | Flow Control: Passive, Active, Reactive Flow Management[END_REF] and is subjected to a growing interest even for industrial applications. [START_REF] Mclean | Study of the application of separation control by unsteady excitation to civil transport aircraft[END_REF] In the past years, noise reduction techniques have been proposed for high-bypass ratio engines, and many efforts have led to the currently implemented solution based on passive devices. [START_REF] Callender | Far-field acoustic investigation into chevron nozzle mechanisms and trends[END_REF] Active flow-control devices, such as fluidic systems made of impinging micro jets, have also been proposed for high BPR engines. [START_REF] Henderson | Fifty years of fluidic injection for jet noise reduction[END_REF] Another solution, commonly used for laminar flow control, 7 is boundary-layer suction through porous walls. It has been shown that this method can be applied not only for drag-reduction purposes, but also for separation control. [START_REF] Yousefi | Three-dimensional suction flow control and suction jet length optimization of NACA 0012 wing[END_REF] Additionally, in the case of shock-wave/boundary-layer interaction, it has been proven that shockinduced separation can be more effectively controlled via downstream suction rather than mechanical vortex generators, or impinging micro jets in the incoming supersonic boundary layer. [START_REF] Bur | Study of passive control in a transonic shock wave/boundary-layer interaction[END_REF] In this paper we will consider an isolated UHBR turbofan, representative of a modern engine typical of a large passenger aircraft. The elements composing the engine, such as the intake, each fan and OGV blades and the nozzle, are geometrically represented. The configuration is numerically investigated with both steady-state and time-accurate RANS at increasing incidence. The configuration is firstly considered without flow control, where massive separation appear when the angle of attack is high. For the most separated case, flow-control is considered, and a parametric study is proposed in order to find the most efficient configuration that allows a gain in the overall performance of the engine while limiting the cost of the control device.

The activities presented in this paper were conducted in the frame of the European Clean Sky 2 project ASPIRE in collaboration with Airbus, DLR and NLR. The test case is a 360 • representation of the turbofan, presented in Section II with a description of the meshing strategy as well as the numerical approach used for the computational fluid dynamics. The steady-state and time-accurate solutions obtained solving RANS equations are first presented in Section III for the configuration without control devices, then with flow control in Section IV. Particular attention is given to the evaluation of the overall aerodynamic performances of the controlled and uncontrolled cases, aiming at assessing the efficiency of the proposed flow-control technique. Section V will summarise the results of the investigation.

II. Numerical approach

The configuration investigated in this paper is depicted in figure 1. It is composed of an isolated doublestream turbofan with a bypass ratio around 16. The diameter of the nacelle is higher than in conventional engines, the fan is composed of 16 blades and 36 OGV are present downstream to straighten the swirling flow. The configuration was designed within the EU Clean Sky 2 research project ASPIRE as a generic engine for numerical studies, representative of future UHBR turbofan. The nacelle, air-intake and nozzle shapes were delivered by Airbus, while the fan/OGV blades were designed by DLR based on specifications provided by Airbus (including specifications for the core flow). The nacelle features an air-inlet with a droop angle and a very small length-to-diameter ratio.

The aerodynamic conditions are the following: Mach number of 0.30, total pressure and temperature at zero altitude, which leads to a Reynolds number based on the nacelle diameter of around 6 million. The considered angles of attack vary between 15 • and 40 • , matching take-off conditions and enhance separation. The fan rotation is imposed at a rotation speed typical of take-off conditions. The mass-flow rate in the primary stream is the same for all angles of attack, as well as core pressure and temperature ratio.

II.A. CFD simulation with elsA

The simulations were performed with the ONERA-Airbus-SAFRAN elsA software, whose developments are partially funded by Airbus, Safran, and ONERA which are co-owners of this software. It solves the compressible Navier-Stokes equations on structured, unstructured and hybrid multi-block grids using finitevolume formulation. For the simulations carried out in this study, the structured solver is used. Moving bodies are treated with mixing plane or sliding mesh condition, without Chimera. For the spatial integration, a second-order centred scheme is used for the diffusive fluxes, while the convective terms are treated with Roe scheme. The time integration is performed using an implicit backward Euler scheme, with second-order backward Gear scheme for the time-accurate simulations. The time step size allows to perform 16 iterations for each degree of fan rotation. This has been obtained imposing a number of time step per revolution equals to the number of fan blades, times the number of OGV blades times 10. For each time step, the number of sub-iterations is adjusted to reach a convergence of one order of magnitude of the inner iteration residuals. For the present simulations, this is usually the case after 5 to 10 Newton sub-iterations, depending on the grid refinement. A time-step convergence study is presented in section III to assess the possibility of using a coarser temporal definition.

The turbulence model used for all simulations is the k-ω Wilcox, 11 although other models like the k-ω with SST correction or the Spalart-Allmaras 12 with and without Quadratic Constitutive Relation (QCR) were considered for one specific angle of attack to check the impact of turbulence modelling on the solution.

Cassiopé(e) in-house software [START_REF] Benoit | Cassiopee: A CFD pre-and post-processing tool[END_REF] is used for all pre-and post-processing operations. A coupling between elsA and Cassiopé(e) is used for on-the-fly post-processing during the time-accurate simulations. This allows the extraction of quantities like index of distortion, overall mass-flow rates at different locations, probes and wall-pressure distributions, essential for the evaluation of the engine performance during the simulations. All simulations were run in parallel on 112, 448 and 784 cores of the ONERA cluster for the coarse, medium and fine grids, respectively. The time needed to obtain each steady-state solution was around 3, 10 and 50 hours for the three levels of refinement, while in URANS the time needed to simulate a fan revolution was around 2, 6 and 28 hours. At least three fan revolutions are necessary to initialise the time-accurate solution, making the URANS simulation more than twice as expensive as the RANS. A typical simulation on the medium grid (steady-state computation and 8 fan revolutions for one angle of attack) takes roughly 25,000 CPU hours.

II.B. Meshing strategy

The nacelle is meshed alone with ANSYS ICEM/Hexa mesh generator, without the inner elements. The rest of the grid is obtained by rotating and duplicating each fan and OGV stage, meshed with Autogrid. The grid is refined at the walls consistently with the RANS modelling used for the attached boundary layers. Three grid levels (coarse, medium and fine) were tested in order to assess the mesh convergence of the different approaches. The sizes of the different grids are detailed in Table 1. The medium grid was defined by coarsening the fine grid by a factor 2 in each direction. The same approach was applied to build the coarse grid from the medium one. The y + value was set at 1 for the medium case. The choice was made to have 60 points in the boundary layer on the fine grid to have an accurate description of the boundary layers. The 36 OGV meshes lead to a number of azimuthal points close to 1,200 which ensures to correctly capture the interactions between fan and OGV blades. The decision was made to restrain to 800 points in the same direction for the nacelle mesh to limit the total size of the grid. Overall, the finest grid is composed of 250 millions nodes, and is shown in figure 1, where one over 8 points on the skin is represented. The medium and coarse grids are composed of 40 and 6 millions nodes, respectively. The domain size has 20 diameters upstream and downstream of the nacelle, 12.5 in the vertical direction.

Coarse Medium Fine

II.C. Boundary conditions

The presence of the rotating fan implies that three interfaces between fixed and moving parts must be specified: the first between the nacelle intake and the fan face, the second between the end of the fan and the beginning of the OGV, and the last at the exit of the OGV, where the flow enters in the nozzle. In the case of steady-state computations, a mixing-plane boundary condition can be applied at these three interfaces: an azimuthal averaging is performed on the interface corresponding to the boundary and the averaged flowfield is transmitted from the upstream interface to the downstream one. For the URANS computations, an interpolation on the sliding mesh is performed in order to take into the account the unsteady effect. This sliding mesh method allows transporting the conservative and turbulent field of each grid point from one interface to the other one with great accuracy and is much cheaper than the overlapping blocks used when adopting the Chimera method. The main difference between the mixing plane and the sliding mesh condition is that the RANS approach can only be used with mixing plane. With this condition all the non symmetry in the flow filed are averaged in each of the three planes. This implies that the effect of the asymmetry of the nacelle, the incoming incidence of the flow, and the wakes of each blade are not transported between each interface. When performing a URANS simulation all informations are transferred from one interface to the other, allowing for a more accurate evaluation of the engine performance.

Since the combustion chamber is not present, primary flow inlet and outlet are modelled as boundary conditions. The total pressure and temperature are specified by the user. A coupling procedure is then adopted, allowing for an adjustment of the static pressure in order to achieve the desired mass-flow rate taking into the account the radial equilibrium due to the flow rotation.

II.D. Flow-control device

In the configuration with active control presented in section IV, boundary-layer suction through porous wall is proposed. First, based on the results of the clean case with the highest angle of attack, a zone in the intake is selected where the flow is the most separated. Then different sub-zones of the intake, with roughly the same size, are selected: these zones have two positions in the stream-wise direction (one down-stream close to the fan, the other upstream close to the nacelle lip), and four azimuthal extension. Figure 2 shows the summary of the selected cases. Each case is identified by two numbers: the first indicating the azimuthal extent of the porous walls close to the fan and the second indicating those of the walls close to the nacelle lip. Shape of the porous walls is always symmetric with respect to the vertical symmetry plane of the nacelle. There are in total 18 configurations studied, all with the same suction velocity. In each configuration, the suction velocity is then increased, so that different mass-flow rates are obtained through the cavity.

III. Results without control

This section will present all the results for the configuration without flow control. Steady-state solutions are obtained with a mixing plane condition between the rotating fan and the fixed airframe. This approach allows to obtain a good estimation of the flow field taking into the account the rotating fan, without needing to actually perform any grid motion. The flow inside the nacelle will be axial-symmetric, and is used as starting point for the time-accurate simulations. Instantaneous and time-averaged unsteady solutions are then presented and the unsteady features of the flow are discussed. For both RANS and URANS simulations, the angle of attack is increased until massive separation is observed in the intake. Then, the case where the boundary layer is the most detached is selected for flow control and discussed in the next section. Grid refinement, turbulence model dependency and robustness of the results with respect to the time-step size are also investigated in this section.

Figure 3 presents the evolution of the Mach number on the y = 0 plane. The result is an instantaneous solution of time-accurate simulation on the medium grid for three angles of attack. Stream-traces are superposed to enhance the difference in the flow incidence and highlights the displacement of the stagnation point downstream while increasing the angle of attack.

Overall, the asymmetrical intake and the angle of attack of the incoming flow causes non-uniformity of the flow upstream of the fan. A supersonic region can be observed on the lower side of the nacelle, where a shock-induced separation appears at α = 40 • . The inlet flow accelerates around the inlet lip, resulting in a supersonic flow region followed by a shock. Previous studies have shown that a thinner leading edge shape is required in the short-inlet design to limit the external flow acceleration at cruise. [START_REF] Peters | Ultrashort Nacelles for Low Fan Pressure Ratio Propulsors[END_REF] As a result, the over-speed along the inlet internal surface is increased at high-angles of attack. Local region of high Mach number shifts toward the fan face, similarly to the cruise condition.

At low angles of attack, the flow can be considered fairly uniform inside the engine. Then, the separation is ingested by the fan and a deficit of velocity is transported through the OGV. Important differences can be seen for the most separated case between the upper and lower part of the secondary flow in the nozzle. The jet in the fan nozzle has also an influence on the primary stream, which however remains attached to the plug even for the highest angle of attack.

The main consequence of such a short intake is the proximity of the fan to the external flow. In nacelles with very short intakes, flow-through calculations indicate that the presence of the rotor increases the separation-free angle of attack, underlining the importance of capturing the influence of the rotor when studying fan-inlet coupling. [START_REF] Peters | Ultrashort Nacelles for Low Fan Pressure Ratio Propulsors[END_REF] Furthermore, a comparison study between an isolated intake and a powered intake have shown that the fan stage has the beneficial effect of increasing tolerance to flow incidence and decreasing distortion. [START_REF] Carnevale | Lip Stall Suppression in Powered Intakes[END_REF] In figure 3(c) the jet-stream downstream of the nozzle bends upward because of the elevated angle of attack of this configuration. Separation is not observed on the external part of the nacelle. In order to compare global values obtained using the available grids at different angles of attack, Table 2 summarizes the results obtained using both steady-state simulations (thus with mixing-plane condition between fixed and rotating parts) and time-accurate simulations (thus with sliding-mesh approach). All mass-flow rates have been divided by a reference value, that is the mass-flow rate obtained with the URANS simulation on the fine grid for α = 15 • .

Mass flow

Focussing on the first line of Table 2, it can be seen that the coarsest grid underestimates the mass-flow rate by 1%. On the contrary, the medium grid presents an excellent agreement with the results on the finest mesh. For this particular case at low angle of attack, the RANS solution yield values of mass-flow rates through the fan very similar to those predicted by the URANS simulation. The agreement deteriorates while increasing the angle of attack (first column of the table), which introduces asymmetries in the flow field that are not correctly transported using the mixing-plane approach.

Focussing on the last lines of Table 2, it can be seen that at high angle of attack the mass-flow rates are significantly lower than the reference value, obtained on the fine grid for α = 15 • . This behaviour is due to the flow separation on the lower part of the intake, which deteriorates the performance of the engine. Due to the unsteady effects, non captured by the RANS simulation, the solution obtained with mixing-plane condition predicts a sensitively different mass-flow rate with respect of the solution obtained with a URANS approach. 4(c) and 4(f) are an instantaneous result of the URANS simulation, obtained with the sliding mesh approach (the upstream and downstream planes are the same). On the top figures, when the angle of attack is small, no separation is present at the end of the intake. The flow is fairly symmetrical and RANS and URANS results (figure 4(b) and 4(c)) are similar. Obviously the trace of each fan blade is not visible upstream of the interface because their effect has been averaged by the mixing plane.

Figure 4(d), 4(e) and 4(f) present similar plots, obtained when α = 40 • . A separation on the lower part of the nacelle is visible figure 4(d), but the total-pressure loss are averaged by the mixing plane immediately downstream of the interface (figure 4(e)). The unsteady simulation with sliding mesh is necessary to simulate the interaction between the separated zone upstream the interface and the rotating parts downstream of it. The RANS simulation in the rotating frame presented in figure 4(e) can capture the trace of each fan blade, but does not reproduce the separated flow in the intake. This artificial flow reattachment induced by the mixing plane is the reason why at high angle of attack the URANS simulation with sliding mesh is needed. Figure 4(f) presents an instantaneous result of the time-accurate simulation, where we can observe the interaction between the fan blade and the separated zone. In addition, the sliding-mesh approach allows to simulate the asymmetry of the flow, which is visible in the pressure distribution of the blades, which has higher peaks on the right side because of the rotating fan. The spatial evolution of the total pressure can be used to compute the distortion coefficient upstream of the fan. URANS simulations not only allow the use of the sliding mesh to accurately reproduce the interaction between the rotating and the fixing components, but give access also to a time-accurate solution. In those cases the distortion coefficient is a function of time and oscillates due to the rotation of the fan blades and due to the unsteady motions of the separated zones, if present. Figure 5 presents the circumferential distortion index (IDC) for various angles of attack, on a vertical plane at y = -0.3m, upstream of the fan. The figure presents the steady results obtained with RANS approach (dash-dotted line) as well as the time-accurate results obtained with URANS simulation (solid lines).

Figure 5 shows that, as previously mentioned, RANS and URANS results are in good agreement for low angles of attack. In the time-accurate solution, 16 peaks can be seen for each fan revolution period, indicating effect of the 16 fan blades. As the incidence is increased, the steady-state solution underestimates the distortion because of the failure to transport the separated zone from the intake to the the fan: this creates an artificial flow reattachment as consequence of the spatial averaging caused by the mixing plane. For the highest angles of attack (α = 35 • and α = 40 • of figure 5), the evolution of the IDC indicates also the presence of unsteady loads and flow non-uniformity that can cause periodic forcing on the fan blades, which can provoke fatigue failure. In the next session flow control will aim at reducing separation in order to increase the propulsion efficiency and also attenuate the unsteady loads.

Figure 6 presents the pressure coefficient (Cp) distribution on two blades for the case at α = 25 • . On the top, figure 6(a) and figure 6(b) have been obtained with a RANS simulation: the mixing plane approach yield a symmetric flow, so the same pressure coefficient is observed on all blades. Each line of the figure presents the pressure evolution obtained with a different turbulence model. It can be seen that the k-ω of Wilcox yields a result which is very similar to the one obtained using k-ω with SST correction. Similarly, the Spalart-Allmaras with and without QCR correction predict very close distribution. The results obtained with the k-ω models predicts a more downstream shock than the results obtained with the SA models. However, similar variations are observed for the pressure side of the profiles, so the estimation of the total lift produced by the blades is very close.

Figure 6(b) presents a similar plot, with Cp values closer to the fan shroud (90% of the radius). A similar behaviour is observed, with the k-ω models predicting a more downstream shock (close to the fan tip, a second shock is present also on the pressure side of the profile. Two turbulence models have also been considered in URANS simulation, where the sliding mesh interface allows to represent the differences that can arise between a blade on the lower and upper part of the nacelle. Figure 6(c) presents a comparison of the pressure distribution at 50% of the radius: the effect of the turbulence model is small, while more differences can be seen when comparing a blade on the upper part of the nacelle with one on the lower part. A similar conclusion can be drawn for figure 6(d), presenting the pressure distribution closer to the fan tip.

Overall, despite some differences in the location of the shock wave, it is believed that the considered turbulence model give similar results, with the differences between the model less important than the differences due to the available approaches for modelling the interface between fixed and rotating parts of the engine. Robustness of the results with respect to the time-step size are now investigated for the medium grid at α = 15 • . Figure 7 shows the evolution of the normalised mass-flow rate obtained when increasing the time-step size, measured downstream of the OGV. The reference time step is τ = 7.5µs, which corresponds to 5760 steps per fan period. Figure 7 (a) indicates that a large time-step could have been used, allowing for a cheaper simulation. However, Figure 7 (b) indicates that a slightly different behaviour is observed when focussing on the mass-flow rate oscillations in the wake of the OGV. The figure also presents the case where the time step has been kept the same as the reference, but more inner iterations have been performed to allow a further convergence between time steps: the difference in the evolution of the mass-flow rate is barely visible, so the chosen level of convergence is deemed correct.

IV. Results with active flow control

The results of the previous section have shown that despite some differences in the mass-flow rate and total-pressure distortion, the mixing plane condition can give a good appraisal of the flow field for all angles of attack in the complete configuration and particularly in the intake region where separation may occur. As mentioned before, this condition allows the use of RANS simulations to obtain a steady-state solution with limited costs. In this section the most separated case, corresponding to α = 40 • , is selected for flow control. RANS simulation is therefore used to define the most efficient configuration, which is then simulated in URANS to verify the effect of flow control using sliding-mesh approach on the interfaces between fixed and rotating elements. The configuration considered in this study is an UHBR turbofan with a very short intake, designed for cruise conditions. Focussing on figure 3 (c), two main features can be observed on this particular configuration: the first one is that at high angle of attack, the separation of the boundary layer is induced by a shock wave that appears inside the nacelle. The second one is that the separation is interacting with the fan, which ingests the recirculation zone. Two conclusion can consequently be drawn: first, aspiration of the separated zone downstream of the shock can be a more efficient way of applying flow-control, [START_REF] Keerthi | Effectiveness of vortex generator jets and wall suction on separated flows in serpentine-duct diffuser[END_REF] rather than upstream vortex generators or micro-jets, which are more adapted to leading-edge separations. [START_REF] Wakelam | Separation Control for Aeroengine Intakes, Part 1: Low-Speed Investigation of Control Strategies[END_REF] Second, the fan must be taken into the account for the evaluation of the flow-control effectiveness, since the reattachment points is determined by the interaction between the separation bubble and the fan blades in the lowest position.

A parametric study is here proposed on the complete configuration using the coarse grid, with mixing-plane conditions. First, all cases presented in figure 2 are considered imposing the same uniform velocity magnitude through the porous wall. Most of the porosity parameters are taken from the characteristics of a typical control device, for example those used for hybrid laminar flow control: porosity coefficient of 8%, size of the holes of 1 mm with no inclination with respect to the wall normal and a wall thickness of 1 mm. Then, the velocity magnitude through the porous wall is increased and all results are compared between each other. For numerical reason, some of the cases with high suction velocity could not converge: those cases are not considered while looking for the optimal flow-control configuration.

Figure 8 shows the skin-friction inside the intake with control obtained for all considered configurations, with constant suction velocity equals to 8 m/s. The black region on the lower side of the nacelle indicates the location of the porosity (i.e. where the velocity through the wall is not equal to zero), as in figure 2. Vectors are coloured by the stream-wise skin-friction coefficient, and indicate where separation occurs. Whilst none of the selected case can completely suppress the separation, great reduction of the flow detachment with respect to the uncontrolled case (top right corner of figure 8) can be achieved by some configurations.

The most effective configurations seem to be those where the porous wall has a great extent, such for example those on the bottom right corner of figure 8. On the contrary, when the suction is in a zone with limited azimuthal extent (as for example in the first row of figure 8) or far from the nacelle lip (first column of figure 8), the separation is barely reduced from the case without control. Some interesting flow patterns arise when considering configurations with non-rectangular shapes, as for example in the last two columns of figure 8. When increasing the suction velocity the beneficial effect on the separation is also increased. Similar separation patterns remain for each configuration, but with a reduced size of the separated zone. In terms of performances of the engine, a smaller separation translates into a higher mass-flow rate through the fan, which is here considered as one of the key parameters to evaluate the effectiveness of the control device. However, when evaluating the global performance of the engine, one should take into the account also the fact that the suction velocity is directly linked to the mass-flow rate thorough the control device, which is not unlimited and free of costs. Since the different configurations considered have different extent of the porous zone, it is useful to compare the gain in mass-flow rate trough the fan to the mass-flow rate needed by the control device. This quantity is obviously linked to the suction velocity and the extent of the porous zone, but also depends on the location of the control device: strong density gradients are present in the shockinduced separation, so that a control device upstream of the shock will have, for a given suction velocity, less mass-flow rate than a control device placed on the supersonic region, because of the difference in density of the flow before and after the shock wave. 2). Some interesting cases exist when the mass-flow of the control device is between 0.7% and 0.9%, where it can be more convenient to use higher suction velocity through a smaller surface rather than a larger surface with lower suction velocity. For reasons linked to the power available for the control device, the cases where the mass-flow rate is greater than 1% of the fan mass-flow rate are discarded.

Another important factor for the choice of the optimal control device is the total-pressure distortion of the flow upstream of the fan. Figure 9 (b) presents a comparison of the distortion index of all cases versus the mass-flow rate through the porous wall. The uncontrolled case is represented again by a black circle. The lines and dots, corresponding to the configurations as in figure 2, are coloured by the fan mass-flow rate, normalised by the mass-flow rates without control. It can be seen that the control device has a tendency to increase the distortion, especially when the fan mass flow is above 104%. However it should be kept in mind that the parametric study discussed in this section is based on RANS simulations with mixing plane conditions; as shown in figure 5, when massive separation is present the flow field is highly unsteady and the steady-state simulation underestimates the distortion. The selection of the best candidate for the flow control is made using the information on the two plots of figure 9. The case corresponding to 3.3 in figure 2 is considered the best compromise between cost, increase of performance and distortion. This particular case needs a flow rate thorough the porous wall corresponding to 0.75% of the fan mass flow and allows for an increase of 4% in the fan mass-flow, while keeping the distortion upstream of the fan lower than all other cases that deliver a greater increase in performance. This optimal point is highlighted in figure 9 by a black cross.

The optimal control location and suction velocity is then simulated in URANS with the sliding mesh approach. The result of the time-accurate simulation is presented in figure 10 and figure 11. Figure 10 (a) and 10 (b) present the wall-pressure distribution on the intake and fan for the case without and with control. An iso-surface of stream-wise velocity equals to zero indicates the flow separation, which is sensitively reduced in the case with flow control. The suction through the porous wall is not able to completely reduce the separation, especially close to the fan face, where the suction is not active. Small separations are also present in the most external part of the blades, especially those in the lowest azimuthal position. Another zone where separation persists is on the suction side of the fan blade in the lowest position. Figure 10 (c) and figure 10 (d) presents the Mach-number distribution on the symmetry plane located in y = 0. Similar flow fields have been observed in a previous study when investigating the behaviour of ultrashort nacelles for low fan-pressure-ratio propulsors. [START_REF] Peters | Ultrashort Nacelles for Low Fan Pressure Ratio Propulsors[END_REF] The separation in the controlled case has a reduced size, allowing for a greater supersonic region inside the nacelle. In the case with suction through the porous wall, more horizontal stream-traces indicate that the intake is more effective in straightening the flow before the fan.

Figure 11 presents the distortion coefficient upstream of the fan for the case with and without control. As indicated in figure 9 (b), the RANS solution indicates that the control device increases the distortion. However, the more accurate URANS simulation indicates the opposite, proving the effectiveness of the proposed flow-control technique. Moreover, the time-accurate simulation not only indicates that the controlled case has a lower averaged distortion, but the peaks corresponding to the unsteady motions of the separated zone are no longer present. A comparison with figure 5 shows that the level of distortion is comparable to the case at α = 30 • , where figure 3 (b) indicated similar separation sizes.

V. Conclusion and Outlook

Requirements of fuel efficiency and environmental impact have rose the interest towards the UHBR engines. Increasing the values of bypass ratio leads to major modifications of the fan and the nacelle, which will have intakes with large diameters and reduced lengths. In order to allow the design of engines with great performances, CFD codes must provide reliable tools able to accurately predict the flow field and the strong interactions between the elements composing the engine. In off-design conditions, this new type of engine could be subject to undesirable separation, and active flow control could be used to assure the operability of the intake even in presence of massively separated flow.

In this paper an isolated engine representative of a UHBR turbofan is numerically investigated. Intake, fan, OGV and nozzle were present in the numerical grid, with rotating bodies fully modelled. Three levels of grid refinement and various turbulence models were considered to assess convergence and robustness of the results. The configuration has been considered in RANS simulation, with steady-state solutions obtained using mixing plane between fixed and rotating parts providing a quick estimation of the flow-field. Unsteady simulations have then been completed, using sliding-mesh approach to accurately predict the time-resolved behaviour of the engine. Overall, mixing-plane plane simulations can be considered relatively quick and cheap, but not adapted to cases with separation, since they do not allow to capture non-symmetric features of flow. However, despite some differences in the mass-flow rate and total-pressure distortion, the mixing plane condition can give a good appraisal of the flow-field for all angles of attack in the complete configuration and particularly in the intake region where separation may occur. For a more accurate prediction of the flow, URANS simulations with sliding-mesh between fixed and rotating parts must be used. Parallel computations have shown the ability of modern codes to handle complex simulations and estimate the performance of those engine where the interaction between all elements composing the turbofan play a central role.

The UHBR turbofan has been simulated in take-off conditions at increasing angles of attack. Separationfree flow is observed at low incidence, while at high incidence the intake, optimised for cruise conditions, does not present a typical leading-edge separation but more a shock-induced separation inside the nacelle. Due to the limited length of the intake, the proximity of the rotating fan to the nacelle lip, typical in this particular UHBR configuration, has a beneficial effect on the separated zone, allowing the flow to re-attach even at high angles of attack. A further increase in the incidence causes massive separation to appear, with dramatic unsteady effects on the flow distortion. In this case, flow control can be applied to limit the undesirable effects, with aspiration of the separated zone downstream of the shock, using a porous wall that could be fitted in the intake. This technique can be more efficient than control by upstream vortex generators or micro-jest, which is more adapted to leading-edge separation. A parametric study has thus been proposed in order to find the optimal location of the control device using steady-state simulation, and a time-accurate result has been compared with the case without control in order to evaluate the performance of the proposed device.

It has been shown that the control device has a positive effect on the total mass-flow rate of the engine thanks to a reduction of the separated zone, which is proportional to the suction velocity. However, the distortion upstream of the fan can be increased by too powerful control devices. Overall, it has been shown that suction from a porous wall can provide a beneficial effect on the intake at very high angle of attack where massive separation occurs. The next steps will be a comparison with experimental data in order to validate the numerical results and a study on the implementation and integration concept in order to provide an evaluation at aircraft level.

Figure 1 .

 1 Figure 1. Numerical grid of the considered test case.

Figure 2 .

 2 Figure 2. Location of the porous walls for active flow control and corresponding name of the configuration. The first number identifies the size of the porous wall in its most downstream position, the second the most upstream.

  (a) α = 20 • . (b) α = 30 • . (c) α = 40 • .

Figure 3 .

 3 Figure 3. Mach-number distribution on the symmetry plane of the engine for the medium grid.

  (a) Upstream mixing plane, 15 • (b) Downstream mixing plane, 15 • (c) Sliding mesh, 15 • (d) Upstream mixing plane, 40 • (e) Downstream mixing plane, 40 • (f) Sliding mesh, 40 •

Figure 4 .

 4 Figure 4. Total pressure distribution on the intake/fan interface: upstream the mixing plane (left), downstream (center) and on the sliding mesh window (right). Angle of attack α = 15 • (top) and α = 40 • (bottom), medium grid.

Figure 4

 4 Figure 4 shows the evolutions of the total pressure in correspondence of the interface between the intake and the fan, obtained using different approaches. The figure presents on the top the configuration with the lowest angle of attack and on the bottom the configuration with α = 40 • . Figure 4(a), figure 4(b), figure 4(d) and figure 4(e) have been obtained with a RANS simulation, and show the distribution upstream and downstream the mixing plane.Figure 4(c) and 4(f) are an instantaneous result of the URANS simulation, obtained with the sliding mesh approach (the upstream and downstream planes are the same). On the top figures, when the angle of attack is small, no separation is present at the end of the intake. The flow is fairly symmetrical and RANS and URANS results (figure 4(b) and 4(c)) are similar. Obviously the trace of each fan blade is not visible upstream of the interface because their effect has been averaged by the mixing plane.Figure 4(d), 4(e) and 4(f) present similar plots, obtained when α = 40 • . A separation on the lower part of the nacelle is visible figure 4(d), but the total-pressure loss are averaged by the mixing plane immediately downstream of the interface (figure 4(e)). The unsteady simulation with sliding mesh is necessary to simulate

Figure

  Figure 4 shows the evolutions of the total pressure in correspondence of the interface between the intake and the fan, obtained using different approaches. The figure presents on the top the configuration with the lowest angle of attack and on the bottom the configuration with α = 40 • . Figure 4(a), figure 4(b), figure 4(d) and figure 4(e) have been obtained with a RANS simulation, and show the distribution upstream and downstream the mixing plane.Figure 4(c) and 4(f) are an instantaneous result of the URANS simulation, obtained with the sliding mesh approach (the upstream and downstream planes are the same). On the top figures, when the angle of attack is small, no separation is present at the end of the intake. The flow is fairly symmetrical and RANS and URANS results (figure 4(b) and 4(c)) are similar. Obviously the trace of each fan blade is not visible upstream of the interface because their effect has been averaged by the mixing plane.Figure 4(d), 4(e) and 4(f) present similar plots, obtained when α = 40 • . A separation on the lower part of the nacelle is visible figure 4(d), but the total-pressure loss are averaged by the mixing plane immediately downstream of the interface (figure 4(e)). The unsteady simulation with sliding mesh is necessary to simulate

Figure 5 .

 5 Figure 5. Evolution of the distortion coefficient upstream of the fan for different angles of attack.

  (a) Fan blade pressures with RANS simulation at 50% height. (b) Fan blade pressures with URANS simulation, 90% height. (c) Fan blade pressures with RANS simulation at 50% height. (d) Fan blade pressures with URANS simulation, 90% height.

Figure 6 .

 6 Figure 6. Pressure coefficient on two different location on the fan blades in the highest and lowest position. Effect of the turbulence model for the case at α = 25 • , mixing plane (RANS) and sliding mesh (URANS) approach.

  (a) Mass-flow rate through the fan for different time-step sizes. (b) Mass-flow rate through the fan, zoom.

Figure 7 .

 7 Figure 7. Effect of the time-step size and convergence level of the inner-iteration in the time-resolved simulation.

Figure 8 .

 8 Figure 8. Skin-friction in the intake with control for different configurations, minimal suction velocity. The black region indicates the location of the porous wall. Vectors coloured by the stream-wise skin friction, separation in red.

  (a) Mass-flow through the fan vs. suction intensity. (b) Distortion upstream the fan vs. suction intensity.

Figure 9 .

 9 Figure 9. Result of the parametric study on the control device location, size and suction velocity.

Figure 9 (

 9 a) shows a plot with the gain of mass-flow rate through the fan with respect to the uncontrolled region versus the mass-flow rate through the porous wall (normalised by the fan mass-flow rate). The configuration without control is represented by a black circle, with obviously no mass flow through the walls, and mass-flow rate of the fan equals to 100%. The figure indicates that an increase of the mass-flow rate through the control device has a positive effect on the engine performance. As indicated by the labels, each line of figure 9 (a) corresponds to a configuration of figure 2 or figure 8 , coloured by the surface of the porous wall (same symbols indicate same arrangement of the porous zone, as each column of figure

  (a) Wall-pressure distribution with iso-surface of zero streamwise velocity, without control.(b) Wall-pressure distribution with iso-surface of zero streamwise velocity, with control.(c) Mach number on the plane y = 0, without control.(d) Mach number on the plane y = 0, with control.

Figure 10 .

 10 Figure 10. Time-accurate simulation, comparison at α = 40 • without (left) and with (right) control.

Figure 11 .

 11 Figure 11. Evolution of distortion coefficient at α = 40 • with and without flow control.

Table 1 .

 1 Number of million grid points for different levels of grid refinements.

	Fan (rotating)	0.8 M	6.2 M	47.3 M
	OGV (fixed)	0.6 M	4.1 M	31.5 M
	Nacelle (fixed)	2.8 M	21.1 M 161.5 M
	Total	4.2 M	31.4 M 240.2 M

Table 2 .

 2 Normalised mass-flow rate through the engine, effect of grid refinement for different angles of attack.

		Coarse	Coarse	Medium	Medium	Fine	Fine
	[kg/s]	Mix. Plane Slid. mesh Mix. Plane Slid. mesh Mix. Plane Slid. mesh
	α = 15 •	-1.05%	-0.92%	-0.02%	-0.14%	+0.19%	0.00%
	α = 20 •	-1.31%	-1.23%	-0.20%	-0.39%	+0.02%	-
	α = 25 •	-1.68%	-1.67%	-0.51%	-0.80%	-0.27%	-
	α = 30 •	-2.41%	-2.45%	-1.14%	-1.64%	-	-
	α = 35 •	-10.00%	-4.42%	-1.90%	-2.69%	-	-
	α = 40 •	-13.43%	-8.70%	-3.59%	-5.57%	-	-

Acknowledgements

The studies presented in this article have used the ONERA-Airbus-SAFRAN elsA software whose development is partially funded by Airbus, Safran and ONERA, which are co-owners of this software. This project has received funding from the Clean Sky 2 Joint Undertaking under the European Union's Horizon 2020 research and innovation program under grant agreement No 681856-2 -ASPIRE.