Minh Thai

Frédéric Truong

Benoit Amblard
email: frederic.amblard@ut-capitole.fr

Christophe Gaudou

Sibertin-Blanc

Viet Xuan Truong

Alexis Drogoul
email: alexis.drogoul@gmail.com

Hiep Xuan Huynh

Minh Ngoc Le
email: minhle@cse.hcmut.edu.vn

An Implementation of Framework of Business Intelligence for Agent-based Simulation

Keywords: BI Solution, Data Warehouse, Multi-Agent Simulation, Agent-Based Model, Brown Plant Hopper, Decision Support System

Integrated environmental modeling approaches, especially agentbased modeling ones, are increasingly used in large-scale decision support systems. A major consequence of this trend is the manipulation and generation of a huge amount of data in simulations, which require to be efficiently managed. In this paper, we present a Combination Framework of Business intelligence solution and Multi-agent platform (CFBM) and its implementation on the GAMA platform. CFBM is a logical framework dedicated to the management of the input and output data of simulations, as well as the corresponding empirical datasets in an integrated way and the analysis on integrated data, which we propose as a coupling of two major methodologies: Multi-Agent Simulation (MAS) on one hand and Business Intelligence (BI) solution on the other. An integrated model of a surveillance network and Brown Plant Hopper (BPH) invasion is presented. This model is used throughout the paper as a case study of CFBM regarding to the database accesses, the integration of internal and external processing, and the model validation tasks. We show how the proposed combination framework can be an appropriate choice for all decision-support systems with a huge data, hence the modelers can be also encouraged to develop the big model in a large scale.

INTRODUCTION

Integrated socio-environmental modeling in general and multiagent based simulation approach applied to socio-environmental systems in particular are increasingly used as decision-support systems in order to design, evaluate and plan public policies linked to the management of natural resources [START_REF] Laniak | Thematic issue on the future of integrated modeling science and technology[END_REF]. For example, in our research about invasion of Brown Plant Hoppers (BPH) and their effects on rice fields in the Mekong Delta region of Vietnam, we must develop and integrate several models (e.g. BPH growth model, light-trap model, rice growth model, BPH migration model). We must also integrate data from different data sources and analyze the integrated data at different scales. In such integrated simulation system involving high volume of data, we are not only concerned with modeling driven approachthat is how to model and combine coupling models from different scientific fields -but also with data driven approachthat is how to handle big data from different data sources and perform analyses on the integrated data from these sources.

The basic statement we can make is that currently, the design and simulation of models have greatly benefited from the advances in computer science through the popularized use of simulation platforms such as Netlogo [START_REF] Wilensky | Netlogo[END_REF], Repast [START_REF] Collier | Repast: An extensible framework for agent simulation[END_REF] or GAMA [START_REF] Taillandier | GAMA: a simulation platform that integrates geographical information data, agent-based modeling and multi-scale control[END_REF]. This is not yet the case for the management of data, which is still managed in an ad hoc manner, despite the advances in the management of huge datasets (data warehousing solutions for instance). Such a statement is rather pessimistic if we consider recent tendencies toward the use of data-driven approaches in simulation aiming at injecting more and more data available from the field into simulated models. These are the reasons why we propose a robust handling data solution of huge datasets for multiagent based simulations.

In our research, the first question, we must tackle is "What is the general architecture that can adapt several purposes: model and execute multi-agent simulation, manage input/output data of simulations, integrate data from different sources and analyze high volume of data?". To solve this problem, we studied on several researches and solutions, related to simulation, management and analysis on big data. We argue that BI solution is a good way to handle and analyze big data. Because a BI solution contains a data warehouse, integrated data tools (Extract-Transform-Load tools) and Online Analytical Processing tools (OLAP tools), they are very adapted to manage, integrate and analyze on huge amounts of data. Our answer for the first question is the combination framework proposed in Section 3.

The second problem that needs to be solved in our research is "How to combine the power of the two disciplines (BI and MAS) into a multi-agent based simulation system with a huge amount of data?" The solution was proposed in this article is improve agentbased platforms by adding new features, such as deep interactions with data warehouse systems.

In the following sections, we first present the state of the art of works linking BI and MAS in Section 2. The global architecture of the combination framework of BI solution and multi-agent platform and its implementation in GAMA is presented in Section 3. In Section 4, we present the integrated model of Brown Plant Hopper invasion as a case study for the application of CFBM. Discussion on advantages and disadvantages of our framework will conclude this article.

RELATED WORKS 2.1 Multi-agent Platform

The basic features of a general computer simulation platform or specifically of a multi-agent based simulation platform are the capability to write models, run simulations of these models and handle results for analysis and/or validation [5][7]. Most simulation platforms (Netlogo, Repast, and GAMA) strongly support these features. But they do not concern on database functions or, when they do, these platforms support database functions with inflexibly in use. For instance, Nelogo has an external package (Netlogo-sql) that supports the execution of SQL statements but "There is no "deep" support for the Netlogo paradigm" 1 . Repast is a toolbox for agent-based modeling in Java, it has numerous libraries to connect the simulator to useful technologies (statistical analysis, GIS, SQL, etc.) 2 . But for using them, users need to have very good java programming skill. GAMA 3 pays a great deal of attention to the modeling of the environment and the use of GIS data but it only supported access GIS data on shape file, did no support features to query GIS data in database managements. That is inflexible for users when they only need to access on a subset of data.

These platforms support good tools for modeling driven approach but they still need additional features for data driven approach.

Integration of BI Solution into a Simulation System

Technologies or tools from different fields used within integrated systems become a common trend today. In particular, for the development of decision support systems or prediction systems based on simulation approaches, data warehouse (DW), online analytical processing (OLAP) technologies and simulation often represent a good solution. Data warehouse and analysis tools as a BI solution can help users to manage a large amount of simulation data and make several data analyses that support the decisionmaking processes [START_REF] Inmon | Building the Data Warehouse[END_REF] [START_REF] Kimball | The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling[END_REF]. The combination of simulation tools and DW is increasingly used and applied in different areas. In [START_REF] Madeira | The OLAP and data warehousing approaches for analysis and sharing of results from dependability evaluation experiments[END_REF] collecting and analyzing simulation results of a system [START_REF] Sosnowski | Developing Data Warehouse for Simulation Experiments[END_REF]. Although [START_REF] Madeira | The OLAP and data warehousing approaches for analysis and sharing of results from dependability evaluation experiments[END_REF] [START_REF] Sosnowski | Developing Data Warehouse for Simulation Experiments[END_REF] are only applications of OLAP technologies to a special problem, these works demonstrate that a multidimensional database is suitable to store several hundreds of thousands of simulation results. Simulation models, DW and analysis tools with OLAP technologies were also involved in decision support systems or forecast systems [START_REF] Ehmke | Interactive analysis of discreteevent logistics systems with support of a data warehouse[END_REF] [START_REF] Vasilakis | A decision support system for measuring and modelling the multi-phase nature of patient flow in hospitals[END_REF]. Not only their researches solve specific problems but they also demonstrated a promising use of gathering and analyzing simulation results by using data warehouse and OLAP technologies. In [START_REF] Mahboubi | A Multidimensional Model for Data Warehouses of Simulation Results[END_REF], Mahboubi et al. also use data warehouse and OLAP technologies to store and analyze a huge amount of output data generated by the coupling of complex simulation models such as biological, meteorological and so on. In particular, they propose a multidimensional data schema of a data warehouse for storing and analyzing simulation results.

The state of the art demonstrates therefore the practical possibility and the usefulness of the combination of simulation, data warehouse and OLAP technologies. It also shows the potential of a general framework that has, as far as we are aware, not yet proposed in the literature.

Model of BPH Invasion

To build a dynamics system of the BPH propagation, the migration laws play an important role in the model. Coupled map lattice approximations are introduced in [START_REF] Brännström | Coupled map lattice approximations for spatially explicit individualbased models of ecology[END_REF]; this model is based on an Individual-Based Model to simulate the reaction of individuals via a cellular automaton. Two different agent-based BPH migration models have also been developed in [START_REF] Nguyen | On weather affecting to brown plant hopper invasion using an agent-based model[END_REF] and [START_REF] Phan | An agent-based approach to the simulation of Brown Plant Hopper (BPH) invasions in the Mekong Delta[END_REF]. In addition, some investigations for the surveillance network model (SNM) are introduced in [START_REF] Truong | Modeling a Surveillance Network Based on Unit Disk Graph Technique--Application for Monitoring the Invasion of Insects in Mekong Delta Region[END_REF]. In agent-based modeling, the data can be modeled as a Gaussian process [START_REF] Rasmussen | Gaussian processes for machine learning[END_REF] by using Kriging estimation [3][14].

In mathematics, Ordinary Differential Equations (ODE) is a popular approach for growth models. The "Larvae-Pupae-Adult" (LPA) model is a typical model for insects growth model [START_REF] Dennis | Estimating chaos and complex dynamics in an insect population[END_REF]. However, this approach has its own disadvantages, caused by the need to simplify the number of variables. In most cases the limit of parameter number can lead to the uncertainty of model.

In [START_REF] Nguyen | On weather affecting to brown plant hopper invasion using an agent-based model[END_REF] and [START_REF] Phan | An agent-based approach to the simulation of Brown Plant Hopper (BPH) invasions in the Mekong Delta[END_REF], authors succeeded in applying agent-based modeling approach to model growth of BPH and its invasion on the rice field with different factors. In [START_REF] Truong | Modeling a Surveillance Network Based on Unit Disk Graph Technique--Application for Monitoring the Invasion of Insects in Mekong Delta Region[END_REF] and [START_REF] Truong | Optimizing an Environmental Surveillance Network with Gaussian Process -An optimization approach agent-based simulation[END_REF], Truong et al. also succeeded in using agent-based modeling approach to simulate the Surveillance Network and optimization the light trap network system in Mekong Delta. But all of the models in these researches got some problems when users need to manage input/or output of simulation, to integrate simulation data with empirical data for validation, calibration or other analysis requirements as we present in Section 4.1.

In this paper, we aim at proposing a logical framework to combine data warehouse, OLAP technologies and multi-agent simulation platform to build integrated multi-agent based simulation system with large data. The logical framework and its implementation in GAMA are explained in the next section and the case study is demonstrated in Section 4.

COMBINATION FRAMEWORK OF BI SOLUTION AND MULTI-AGENT PLATFORM 3.1 Computer Simulation System

Fishwick (1997) defined that computer simulation is the discipline of designing a model of an actual or theoretical physical system, executing the model on a digital computer, and analyzing the execution output. On the basis of Fishwick's definition, we can define a computer simulation system as below: A Computer simulation system is a computation system with four components and the intercommunications between them:

-Model design tool: a software environment that supports a modeling language, notations and user interface for modeling an actual or theoretical physical system. -Model execution tool: a software environment that can run models. -Execution analysis tool: a software environment that supports statistical analysis features for analysis of output data of models. -Database tool: a software environment that supports appropriate database and database management features for overall components in the system.

The components of a computer simulation system and their intercommunications are illustrated in Figure 1. This computer simulation system definition deals with two approaches: modeling driven approach and data driven approach.

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CFBM -a Logical Framework to Combine BI Solution and Multi-agent Platform

The CFBM is based on three major systems and divided into seven layers. The function of each part is detailed in following sections.

Simulation System

The simulation system is composed of a multi-agent platform with a relational database. This system helps to implement models, execute simulations and handle their input/output data. This part plays the role of an Online Transaction Processing (OLTP) or of an operational source system. It is an outside part of the data warehouse [START_REF] Kimball | The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling[END_REF].

Three layers with five components compose the simulation system. The simulation interface is a user environment that helps the modeler to design and implement his models, execute simulations and visualize results. Multi-agent simulation models are used to simulate phenomena that the modeler aims at studying. The SQL-agent plays the role of the database tool and can access to the relational database. It is a particular kind of agent that supports Structured Query Language (SQL) functions to retrieve simulation inputs from simulation data or reality data, to store output simulation data into simulation data databases and to transform data (in particular the data type) from simulation model to relational database, and conversely. Reality data and Simulation data are relational databases. Reality database is used to store empirical data gathered from the target system that are needed for the simulation and analysis phases. Simulation data is used to manage the simulation models, simulation scenarios and output results of the simulation models. These two data sources will be used to feed the second part of the framework, namely the Data warehouse system.

Data Warehouse System

The data warehouse system is understood as a part of the BI solution. It is very important part to integrate data from different sources (simulation data, reality data and others external data) and it is used as data store to feed data for decision support systems. The data warehouse system is divided into three parts. ETL (Extract-Transform-Load) is a set of processes three responsibilities. First, it extracts all kind of data (empirical data and simulation data) from the simulation system. Second, ETL transforms the extracted data into an appropriate data format. Finally, it loads the transferred data into the data warehouse. Data warehouse is a relational database used to store historical data loaded from simulation systems and from other sources by the ETL. Data mart is a subset of data stored in the data warehouse and it is a data source for the concrete analysis requirement. We can create several data marts depending on our analysis requirements. Data mart is a multidimensional database, which is designed based on multidimensional approach. It uses star join, fact table and dimension table to present the structure data mart. With multidimensional structure, data mart is particularly useful to help users to improve the performance of analytic processes.

Decision Support System

In CFBM, the decision support system component is a software environment supporting analysis, decision-making features and visualization of results. In our design, we propose to use existing OLAP analysis tools, a multi-agent platform with analysis features or a combination of both options. The decision support system of CFBM is built with four parts. Analysis interface is a user interface used to handle analysis models and visualize results.

Multi-agent analysis models are a set of agent-based analysis models. They are created based on analysis requirements and handled via the analysis interface. One of the key points of our framework is the fact that multi-agent analysis models and multiagent simulation models are implemented with the same modeling language in the same platform hence they can communicate easily with each others. MDX-agent is a special kind of agent, which supports MultiDimensional eXpressions (MDX) functions to query data from a multidimensional database. MDX-agent is a bridge between multi-agent analysis models and data marts. It is used to retrieve data from the data marts in the data warehouse system. Multi-agent analysis models can use SQL agents (same SQL-agents as in the simulation system) or MDX agents to access data appropriately. OLAP analysis tools are analysis softwares that support OLAP operators.

The key points of the CFBM architecture are that it contains and adapts the four features of a computer simulation system (model design, model execution, execution analysis and database management). All these functions are integrated into one multiagent platform. The data warehouse manages the related data. The analysis models and simulation models can interact with each other. Using the CFBM architecture, we can build a simulation system not only suitable for modeling driven approach but also for data driven approach. Furthermore, CFBM brings special benefits for building simulation system with complex requirements such as integrating and analyzing on high volume of data.

Implementation of CFBM in GAMA

In the previous section, we have described two kinds of multiagent based models (multi-agent simulation model and multiagent analysis model), which can be built in a multi-agent platform and can retrieve or update many kinds of data via special agents (SQL agents and MDX agents). We have chosen to implement CFBM into the GAMA platform following the software architecture illustrated in Figure 3.

Software Architecture of CFBM in GAMA

Presentation tier plays the role of view layers in the CFBM architecture. In our implementation, the GAMA user interface plays this role. It can be used to write models or to analyze models by using agent based approach, execute models and visualize results of models in different modes of views (text, chart, GIS or 3D).

Logic tier coordinates the application process commands, as it plays the role of two layers in the CFBM architecture (simulation layer and analysis layer). In our implementation, it contains four components. The Analysis-agent is designed to supply statistical analysis functions. The statistical functions may be built-in functions or called functions from an external application (e.g. R via RScript). The Analysis-agent is responsible of the analysis of data that are generated by models or data retrieved from a database. An SQL-agent is responsible of the retrieval as well as the update on relational database. A MDX-agent is binding on retrieval data from data marts. SQL agents and MDX agents were implemented as plug-in of GAMA. A modeler can easily use them via primitives of the GAma Modelling Language (GAML), the language used to write models in GAMA. The GAMA-database API is responsible for translating database requirements from GAML to SQL query or MDX query appropriately, transforming retrieved data type to GAMA data type and vice versa. The API has been developed as an application library of the CFBM. In addition, we can add several database functions in the same way we did with the SQL-agent and MDX-agent based on this API.

Data tier plays two roles in the framework: data source layer and data warehouse layer. The main functions of this tier are to store and retrieve data from a database or a file system. JDBC is a Java API allowing connecting to and querying data from relational databases. OLAP4J is also a Java API to connect to and query data from a multidimensional database. RDBMS plays different roles (Real data, Simulation data or Data warehouse). Data mart plays the same role as described in Section 3.1of this section.

Database Access Features in GAMA

Thanks to added database features of GAMA, we can create agents and define the environment of the simulation by using data selected from database or store simulation results into relational databases. It helps us to gain flexibility in the management of simulation models and the analysis of simulation results. In this part, we only demonstrate some basic SQL related functions, which have been implemented in GAMA. using SQL functions, we must define at least an agent that is endorsed by the SQLSKILL skill 4 or inherits from SQL agent. For example:

entities { species toto skills: [SQLSKILL] { //insert your descriptions here } } Then all access database requirements of simulation model will be done via the defined agent using the SQLSKILL skill to query data. Depending on the activity (reading from database or writing into database), the defined agent will auto transform data from data type of database to data type of GAMA or on the contrary from GAMA type to database types.

For example, we can select data from a database and use selected data to create agent location as following steps:

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Step ] ; } } The database access features in GAMA support most common query statements (CREATE, UPDATE, INSERT, DROP) and do not request a deep knowledge in SQL query language and database management from the user. The main benefit of our implementation in GAMA is the fact that the database access is directly integrated into the GAML modeling language, SQLSKILL can access with almost GIS database such as SQLite, PostgreSQL, MySQL and SQL Server and MDXSKILL can interact with multidimensional databases. More details can be found in "Database access user guide" 5 of GAMA version 1.5.1.

APPLYING THE CFBM TO AN ENVIRONMENTAL SURVEILLANCE NETWORK MODEL FOR INSECT ECOSYSTEM 4.1 Motivation

This section introduces a study case of CFBM for an environment surveillance network model applied in an insect ecosystem. An integrated model of the surveillance network and the BPH prediction one is presented in Section 4.2. Before applying CFBM, this integrated model worked as a stand-alone model and required many single operations for almost all works: data preparation, data analysis, data aggregation, etc. With CFBM, we have more support to couple these operations into a uniform framework and the application is really more flexible and portable. Some main conveniences according to which CFBM can be a good choice for our model, and also for other big models:

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Data preparation: An integrated model of an environment surveillance network on an insect ecosystem is built for an application at the regional scale. The input data of this model are divided into four main groups: Insect sampling data (daily sampling data of about 10 insect species at more than 300 light-traps in the Mekong Delta region of Vietnam), Administrative regions (province, district and small town scales), Land uses (seasonal crops of multiple tree species of the region), Natural phenomena (wind, temperature, humidity, etc). In the case of a development of the model without using CFBM, for an example with only one insect species in three provinces (as in our scenarios in this paper), we need to manually filter the data by some tools and the selected data can be stored in some individual files. These files will be used as the input of the model. With CFBM, these works are just replaced by some queries applied on database as presented in Section 3.3.2. This flexibility allows the modelers to easily change their temporal or spatial scale of their scenarios. In other words, CFBM supports to select and update the appropriate data at every micro scale of the model for every simulation step. Furthermore, the input and output data are also distributed and portable. ! Data analysis & processing: Beside built-in operators of GAMA, a model can use many libraries of operators from both the RDBMS (with the storage procedures) and the RScript service (with data mining operators). For example, in a same simulation process we can apply the Kriging by adding the Gaussian noises with support of RScript, but apply the smooth processing in GAMA. ! Data aggregation: Almost all agent-based models are stochastic. Therefore, a research question is often answered by an aggregation of multiple simulation results. With CFBM, the status of each simulation can be archived in the database, and then easily aggregated after executing a batch of simulations.

Integrated Model of BPH Prediction Model and Surveillance Network Model

This section aims at introducing the main process for implementing a specific agent-based model with support of CFBM. This integrated model is composed of two sub-models and both are implemented on the GAMA platform (Figure 4): ( 1

BPH Prediction Model

To predict the BPH density, we propose a BPH prediction model. This model contains two sub-models: BPH Growth Model and BPH Migration Model.

In stochastic model, the studied region is modeled as a cellular automaton. Each cell in the stochastic model represents a square in the real context. A cell k in the model keeps its own local parameters: Z k (s, t) and two additional parameters (attractiveness index and obstruction index). In fact, the prediction model composes the interactions between two sub-models:

(1) BPH migration model:

The migration process of BPHs in a study region is modeled by a dynamic moving process in a cellular automaton. In agent-based model, each cell becomes an agent which contains all important parameters of the environment, such as the trap-density vector and two combinational indices: obstruction and attractiveness indices.

Denoting that x(t) is the number of adult BPHs at the time point t.

The migration model is essentially concerned with the outcome x out (t) of the next time point (t + 1) from a specific source cell and the rate r of x out (t) on the existing number of BPHs, which moves to all destinations at time point (t + 1). The destination cells are determined by the semi-circle under the wind, the radius of circle is the multiplication of wind velocity and the migration time in a day.

Assuming that there are n destination cells found at the time point t for a source cell i. The ratio of BPHs from i to the destination j is decided by the attractiveness index (a combinational and standardized index calculated from different environmental factors, such as the rice cultivated regions, weather, etc). If the attractiveness index is high, then the outcome ratio of BPHs will be high, and to the contrary. The detailed explanation of attractiveness index is presented in [START_REF] Truong | Optimizing an Environmental Surveillance Network with Gaussian Process -An optimization approach agent-based simulation[END_REF].

(2) BPH growth model:

In the growth model, we apply a deterministic model of T variables where T is the life cycle of the insect. For example, BPH has a life cycle of 32 days in maximum, then we have T = 32. To simplify the implementation process, these variables will be stored in an array variable V of length T where an element V[t] marks the number of insects at age t (i.e. i th day of BPH life cycle).

For each simulation step, all elements of V will be updated by the following equation:

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Surveillance Network Model (SNM)

This model is presented in several publications [21][22]. SNM is based on the Unit Disk Graph technique and autocorrelation between different surveillance devices. In [START_REF] Truong | Modeling a Surveillance Network Based on Unit Disk Graph Technique--Application for Monitoring the Invasion of Insects in Mekong Delta Region[END_REF], the surveillance network is modeled as a Correlation & Disk graph-based Surveillance Network (CDSN) where the edges of the graph are defined by two conditions: spatial distance and autocorrelation coefficient. We only treat the inputs and outputs of this network model in this paper. Each surveillance device contains the trapdensity at a specific geographic location.

Surveillance network model is used to measure the trap-density in the prediction model. Each surveillance device agent monitors the trap-density based on the location of its cell agent. We define the trap-density as equivalent to the number of adult BPHs located in this cell agent.

Validation of Prediction Data

All related operations for validation in Analysis Model (Figure 4) are shortly introduced in this section. As mentioned, the prediction data (collected by the surveillance network model) and empirical data of all surveillance devices will be compared by several validation techniques to assess the precision of the prediction model. Some possible techniques used in this module include:

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Analysis of the correlation level between ! ! and ! ! . ! Error analysis between ! ! and ! ! (e.g. by RMSE).

Experiments

Three Scenarios of the Environment

This section presents three different results of prediction validation relevant to three specific scenarios for BPH cycle (BPH growth model) and wind (BPH migration model). The prediction process by simulation is applied in a short period of one month. In all three scenarios, the wind direction is set to the north-east with a velocity of 9.4±3.5 km/h. We used the data from 48 light-traps of three typical provinces in the Mekong Delta region: Soc Trang, Hau Giang and Bac Lieu. Figure 8 shows the real trap-density data for January 1, 2010. We used the data of the first 32 days (T = 32) to apply T Kriging estimations by adding the Gaussian noises. These estimations simultaneously assign the values for vector V[1..T] of each cell. The prediction data are taken from the (T+1) th simulation step.

In Figure 8, T i denotes the i th of these light-traps. These data are stored in the REALITY DATA database.

As aforementioned, the R language can be called from GAMA with support of CFBM. We need the R language to estimate the BPH density by using Kriging technique. R code files can be applied 8 Empiri l data f Ja 01 2010 in thr vectorParam) operators of GAMA. We develop R code file to read the coordinates of all light-traps and their trapdensities at a specific time point from GAMA, then returns the estimation data to this platform. The estimation data also contain some Gaussian noises. The krige function of gstat library is used for this work [START_REF] Pebesma | Multivariable geostatistics in S: the gstat package[END_REF]. This process is repeated T times to assign the values of vector V[1..T] of all cells in the cellular automaton. Figure 9 demonstrates the simulation data of scenario 1. The wave of prediction data in this figure is significantly smooth (like a sinusoidal form). The same sinusoidal wave form is found in [START_REF] Hung | Principles and Applications in Mathematical model for Biological[END_REF]. However, the form of empirical data is too shocked, as it looks like a pick of insects in a short time.

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Simulation data

The BPH prediction co-model is implemented for scenarios 2 & 3. In Figure 10, the form of BPH trap-density is more similar to real data. This phenomenon is caused by migration process implemented in BPH migration model.

All simulation data are stored in the SIMULATION DATA database. They will be recalled in the validation process.

CONCLUSION& FUTURE WORK

In this paper, we proposed a conceptual framework, which is adapted to multi-agent models with high volume of data. CFBM solves two problems listed in the introduction section. CFBM supports experts not only to model a phenomenon and to execute the models via a multi-agent platform, but also to manage a set of models, input and output of models, to aggregate and analyze output data of models via data warehouse and OLAP analysis tools.

The key features of CFBM are that it supplies four components:

(1) model design, (2) model execution, (3) execution analysis and (4) database management. These components are coupled and combined in a uniformed simulation system. The most important point of CFBM is the integration power of data warehouse, OLAP analysis tools and a multi-agent based platform that is useful to develop complex simulation systems with a large amount of input/output data. These systems can be a what-if simulation system, a prediction/forecast system or a decision support system.

In addition, CFBM has some advantages listed below:

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CFBM is an open and modular architecture. As for the implementation of the CFBM, we can use any BI solution and multi-agent platform depending on which technology is the most adapted. We can choose open source software or a commercial one. For instance, GAMA has succeeded on interaction with Pentaho Analysis Service (Mondrian) and SQL Server Analysis Service (SSAS). ! CFBM can be used to deploy in distributed environment.

Assuming that there are many modelers and analyzers who work together on the same project but they are located in different locations, we can setup a simulation system and an analysis system in each location and all the data from each location can be integrated and shared via a centralized data warehouse.

!

In practice, we recognize that CFBM allows handling a complex simulation system. In particular, we can build several simulation models to simulate the same phenomenon, conduct a lot of simulations for each of them and compare these simulation results (e.g. to determine which one is better for which parameters value domain). In this case, it is very difficult for modelers to manage, analyze or compare the output data of simulations if modelers do not have an appropriate tool. With help of SQL agents and relational data in the simulation system of CFBM, modelers can create a database to manage and store simulation models, scenarios and outputs of simulation models easily. In our case study, we have fully handled on input/output simulation data of models. Selecting and comparing output data between different replications or between simulation data and empirical data can be done in easier and shorter way. Although CFBM has many advantages, it still has some drawbacks such as:

!

It is very hard to implement CFBM. Because CFBM is a mix system of different applications, multi-agent platform, BI solution and analysis tools, the integration of all these software components and expertise is a complex work. However, a similar complexity is actually presented when working on integrated modeling. ! CFBM is not suitable for building a simple simulation system such as one or two models with a small amount of data because it may take more time and workforce than other approaches. From a conceptual framework, CFBM is realized by a concrete implementation of the framework in GAMA and an application to Brown Plant Hopper Prediction model.

By mean of the implementation CFBM in GAMA, it has succeeded in interacting with several database management systems (SQLite, PostgreSQL, MySQL and Microsoft SQL Server) and its extension is not too complex. In addition, GAMA with database access features has also special operations due to spatial databases.

In our case study, an integrated model of Surveillance network model and a BPH prediction co-model (BPH Growth & Migration Model) is implemented as a typical application of CFBM. The validation process with three different scenarios is also executed. Applying the CFBM for this integrated model allows for a more flexible and portable mechanism in querying, updating and analyzing the simulation data for numerous questions.

As future works, on the one hand we will continue develop and improve features for special agents (SQL-agent, OLAP-agent and Analysis-agent) in GAMA described in Section 3. On the other hand, we will also apply CFBM on calibration and evaluation simulation model, multi-scale in multi-agent simulation or building what-if system, prediction system and decision support system. In addition, we will study to apply our framework to manage different simulation models, their input/output, validation and evaluation models of DREAM project 6 . The project aims at building integrated models, dealing thus with several models and huge quantities of data.

ACKNOWLEDGMENT

This work was partially supported by the French ANR project EmoTES.

Figure 1 :

 1 Figure 1: Computer simulation systemThe Combination framework of Business Intelligence Solution and Multi-agent platform (CFBM) was designed based on our computer simulation system definition. It means that we have designed CFBM with four major components: The model design tool, the model execution tool, the execution analysis tool and the database tool and the interconnections between. The architecture of the CFBM is summarized in Figure2. In this framework, we use a BI solution as a database tool, a multi-agent platform as model design tool and model execution tool. For the execution analysis tool, we can either use OLAP analysis tool or use analysis features of the platform (implemented as an external plug-in for the platform, for instance R scripts).

Figure 2 .

 2 Figure 2. Combination framework of BI solution and multi-agent platform (CFBM) architecture.

Figure 2

 2 Figure 2 Combination framework of BI solution and

Figure 3 .Figure 3 .

 33 Figure 3. Software architecture of CFBM in GAMA. . Figure 3. Software architecture of CFBM in GAMA

  ) BPH Prediction Model, a co-model of Growth and Migration models and (2) Surveillance Network Model (SNM). Input and output of the integrated model are handled via the CFBM in GAMA. REALITY DATA (Empirical data) such as administrative boundary (region, river, sea region, land used), light-trap coordinates, daily trap-densities, rice cultivated regions, general weather data (wind data), station weather data (temperature, humidity, etc.), river and sea regions are used as input of simulation model and they are also used as validation data for the model. The SIMULATION DATA essentially contains the trapdensities collected by the surveillance network model. This integrated model reads the BPH trap-density data from real context and returns the simulated data for the future time. The input data also contain different related parameters, which directly affect the dynamics of BPH, such as the rice-cultivated regions, different kinds of weather and river/sea regions. The BPH trapdensity is the main parameter of this prediction model. The surveillance network model reflects the plant protection activity in Vietnam, with a light-trap network to monitor the densities of multiple adult insects.

Figure 4 .Figure 4 .Figure 6 ..Figure 5 .

 4465 Figure 4. Architecture of the integrated model. .Figure 4. Architecture of the integrated model

  denotes the number of insects at age i, ! ! !" denotes the ratio of egg number able to become the nymph, ! ! !" denotes the ratio of nymph number able to become the adult, ! ! ! denotes the ratio of eggs can be produced by an adult, ! m denotes the ratio of natural mortality, ! ! ! denotes the egg giving time span, ! ! ! denotes the egg and time span. ! ! ! denotes nymph time span.

Figure 7 .

 7 Figure 7. Integrated model.

Figure 8 .

 8 Figure 8. Empirical data from Jan 01, 2010 in three provinces: Soc Trang, Hau Giang and Bac Lieu.

Figures 9 &

 9 Figures 9 & 10 show the simulation data corresponding to the real data of Figure 8. The first 32 days are related to the estimation of trap-densities at the cells located by light-traps and the prediction data is considered from the 33th day.

Figure 9 .

 9 Figure 9. Simulation data from Jan 01, 2010 in three provinces (Growth model is applied).

Figure 10 .

 10 Figure 10. Simulation data from Jan 01, 2010 in three provinces(Co-model is applied).

  , Madeira et al. proposed a new approach dedicated to the analysis and comparison of large amounts of output data from different experiments or from similar experiments across different systems. Data warehouse and OLAP tools were recommended for

	1 https://code.google.com/p/netlogo-sql/

2 http://repast.sourceforge.net/docs/RepastJavaGettingStarted.pdf

3

GAMA version 1.5 or earlier version.

Table 1 . List of agents of model

 1

	Param	Scenario 1	Scenario 2	Scenario 3
	eters	(Growth model)	(Co-model)	(Co-model)
	! !	7	7	7
	! !	13	13	13
	! !	6	6	12
	!	32	32	32
	r en	0.42	0.42	0.40
	r na	0.42	0.42	0.40
	r b	250.0	250.0	350.0
	m	0.245	0.245	0.35
	4.3.2 Validation with RMSE

!

Empirical data

Table 2

 2 shows the RMSE of three scenarios listed in Table1. The RMSE values are independently calculated for two stages of simulation data:

	!	RMSE (Estimation): Between the empirical data and Kriging
		estimation (first 32 days of simulation data).
	!	RMSE (Prediction): Between the empirical data and
		prediction (from the 33th day of simulation data).

Table 2 . RMSE of three scenarios

 2

	Validation result	Scenario 1	Scenario 2 Scenario 3
	RMSE (Estimation)	614.3536	657.2320	323.9902
	RMSE (Prediction)	535.5026	524.7963	443.3628

https://code.google.com/p/gama-platform/wiki/Ext_DB_SQL151


Benoit Michel
email: benoit.michel@insa-lyon.fr

Nicolas Dufour

Clémentine Börtlein

Camille Zoude

Elodie Prud'homme

Laurent Gremillard

Marc Clausse

First experimental characterization of CaCl 2 coated heat exchanger for thermochemical heat transformer applications in industrial waste heat recovery

Keywords: Thermochemical Heat Transformer, Waste Heat, Salt coated heat exchanger -

First experimental characterization of CaCl2 coated heat exchanger for thermochemical heat transformer applications in industrial waste heat recovery

) R reactor Greek symbols s salt free Gibbs energy (J•mol -1 s ) 0 dehydrated salt standard enthalpy of reaction (J•mol -1 v ) standard entropy of reaction (J•mol -1 v •K -1 ) Exponents stoichiometric coefficient (mol v .mol s

Introduction

Upgrading waste heat to higher temperatures is a lever to dramatically increase the energy efficiency of the industrial sector. In this sector which is a major energy consumer, the worldwide heat losses below 100 °C represent 3 722 TWh/year [START_REF] Forman | Estimating the global waste heat potential[END_REF]. Thus, there is a great potential for reducing costs and increasing efficiencies in this sector. However, two main drawbacks are identified to valorize the available waste heat: the temperature level is too low to satisfy directly process requirements and the phase shift to the heat demand. To overcome these issues, several technologies such as heat storage and heat to heat conversion systems (heat pumps and heat transformers) have been studied in recent years [START_REF] Xu | Perspectives for low-temperature waste heat recovery[END_REF][START_REF] Zhang | Thermal energy storage: Recent developments and practical aspects[END_REF][START_REF] Arpagaus | High temperature heat pumps: Market overview, state of the art, research status, refrigerants, and application potentials[END_REF]. Electrical Heat Pumps (EHP) have shown promising results in industrial heat recovery applications, but they still suffer from various drawbacks: excessive electricity consumption, low temperature lift, limited high temperature (most of EHP available on market can only achieve 130 °C as operating temperature), the lack of available refrigerants in the high temperature range with low GWP (Global Warming Potential) [START_REF] Arpagaus | High temperature heat pumps: Market overview, state of the art, research status, refrigerants, and application potentials[END_REF]. Additionally, process integration may require to store heat to handle variations in supply or demand, which in only achievable by adding a dedicated heat storage system while sorption heat transformer can deliver heat storage service to the process without adding an additional component [START_REF] Zhang | A comprehensive review on advances and applications of industrial heat pumps based on the practices in China[END_REF].

Hence, sorption heat transformers, which use the heat generated by reversible absorption (liquid/gas), adsorption (solid/gas) or chemical (solid/gas) reactions, could be a good alternative to electrical heat pumps (EHP) in some cases. Absorption Heat Transformers (AbHTs) have been widely studied and are technologically mature, they still suffer from many drawbacks: corrosion or the complexity of the cycles to achieve high temperature lifts [START_REF] Zhang | A comprehensive review on advances and applications of industrial heat pumps based on the practices in China[END_REF][START_REF] Parham | Absorption heat transformers -A comprehensive review[END_REF]. Compared to absorption systems, Thermochemical Heat Transformers (THT) (using a solid/gas chemical reaction) are far from being technologically mature and have not been extensively studied to date. Nevertheless, few studies have shown the potential of this technology [START_REF] Li | A target-oriented solid-gas thermochemical sorption heat transformer for integrated energy storage and energy upgrade[END_REF][START_REF] Wu | Experimental investigation on a novel solid-gas thermochemical sorption heat transformer for energy upgrade with a large temperature lift[END_REF][START_REF] Esaki | Experimental evaluation of the heat output/input and coefficient of performance characteristics of a chemical heat pump in the heat upgrading cycle of CaCl2 hydration[END_REF][START_REF] Yu | Energy upgrading by solid-gas reaction heat transformer: A critical review[END_REF][START_REF] Richter | Heat transformation based on CaCl2/H2O -Part A: Closed operation principle[END_REF][START_REF] Stengler | Thermodynamic and kinetic investigations of the SrBr2 hydration and dehydration reactions for thermochemical energy storage and heat transformation[END_REF][START_REF] Michel | Design of thermochemical heat transformer for waste heat recovery: Methodology for reactive pairs screening and dynamic aspect consideration[END_REF], highlighting their potential to obtain high temperature lift (> 50 °C), using a simple system architecture and without crystallization or corrosion problems [START_REF] Yu | Energy upgrading by solid-gas reaction heat transformer: A critical review[END_REF]. As presented more in details in section 2.2, 1-salt or 2-salts cycles (also called resorption cycle) are mainly used in THT, water and ammonia being the most common working fluids. In these systems, salt/ammonia couples have been the most widely studied [START_REF] Yu | Energy upgrading by solid-gas reaction heat transformer: A critical review[END_REF][START_REF] Manente | Organic Rankine cycles combined with thermochemical sorption heat transformers to enhance the power output from waste heat[END_REF][START_REF] Jiang | A hybrid resorption-compression heat transformer for energy storage and upgrade with a large temperature lift[END_REF][START_REF] Wu | Advanced thermochemical resorption heat transformer for high-efficiency energy storage and heat transformation[END_REF][START_REF] Hinmers | Resorption Thermal Transformer Generator Design[END_REF][START_REF] Hinmers | Modelling and Analysis of Ammonia Sorption Reactions in Halide Salts[END_REF]. Other couples, such as salt/methanol, salt/CO 2 and salt/H 2 O have been studied, with encouraging results for the latter two [START_REF] Wongsuwan | A review of chemical heat pump technology and applications[END_REF][START_REF] Kato | Kinetic feasibility of a chemical heat pump for heat utilization of high-temperature processes[END_REF][START_REF] Kyaw | Applicability of Carbonation/Decarbonation Reactions to High-Temperature Thermal Energy Storage and Temperature Upgrading[END_REF][START_REF] Li | Thermo-economic assessment of salt hydrate-based thermochemical heat transformer system: Heat upgrade for matching domestic hot water production[END_REF]. Among these couples, those using water vapor as reactive gas seem to be very suitable for THT applications in industry (low cost, non-toxicity), CaCl 2 being one of the most interesting salt candidate [START_REF] Michel | Design of thermochemical heat transformer for waste heat recovery: Methodology for reactive pairs screening and dynamic aspect consideration[END_REF][START_REF] Richter | A systematic screening of salt hydrates as materials for a thermochemical heat transformer[END_REF].

Currently, one of the main drawbacks of sorption systems in general and THTs in particular, is the solid reactive material implementation. Although many studies have been carried out, the use of bed of pure material presents many disadvantages, such as heat and mass transfer limitations, performance degradation due to microstructure change, melting and aggregation after excess hydration, etc. [START_REF] Michel | Thermochemical process for seasonal storage of solar energy: Characterization and modeling of a high density reactive bed[END_REF][START_REF] Stengler | Thermal energy storage combined with a temperature boost: An underestimated feature of thermochemical systems[END_REF]. In order to limit these problems, different approaches have been studied. Most of them focus on increasing the heat and mass transfer parameters by improving the heat exchanger or confining the reactants in a matrix (expanded natural graphite, metallic foams, adsorbents, etc.), thus obtaining composite materials with improved mass and heat transfer parameters [START_REF] Scapino | Sorption heat storage f or long-term low-temperature applications: A review on the advancements at material and prototype scale[END_REF]. For THT applications, Esaki et al. [START_REF] Esaki | Experimental evaluation of the heat output/input and coefficient of performance characteristics of a chemical heat pump in the heat upgrading cycle of CaCl2 hydration[END_REF] experimented a packed bed reactor containing around 500 g CaCl 2 . Different reactor designs have been considered to evaluate the impact of various devices to enhance the heat (addition of fins) and mass transfer (addition of a vapor diffuser) in the packed bed. Significant gain was achieved by improving both transfers, the mean specific power increasing from 106 to 293 kW/m 3 . Stengler and Linder [START_REF] Stengler | Thermal energy storage combined with a temperature boost: An underestimated feature of thermochemical systems[END_REF] introduced a tree-like exchanger structure to enhance thermal conductivity of a salt bed of SrBr 2 . The same authors performed a numerical thermal sensitivity analysis on the same geometry [START_REF] Stengler | Performance analysis of a gas-solid thermochemical energy storage using numerical and experimental methods[END_REF]. They concluded that after enhancement of the thermal conductivity of the bed, a further way of improving performances is to increase the heat transfer coefficient between reactive solid and heat exchanger. A more recent work performed by Esaki and Kobayashi [START_REF] Esaki | Study on the cycle characteristics of chemical heat storage with different reactor module types for calcium chloride hydration[END_REF] proposes a comparison of the impact of packed bed width, use of compound material (powdered CaCl 2 , 300-500 µm in particle size, and expanded graphite with particle diameter of 7 µm in average) and water vapor diffuser (porous Ni plate inserted in the middle of the packed bed channel). While the reactor filled the compound material performs slightly better than its equivalent filled only with salt, the highest peak performances in terms of temperature and specific power are achieved for the reactor with the lowest channel width (2 mm). However, the configuration with a 4 mm width channel, exhibits more flat evolutions of the reactor temperature and specific power which could be more interesting for the development of a complete heat transformer. For the largest width (8 mm), the drop in specific power is noticeable with a constant decrease of about 25% compared to the 4 mm case. This work highlights clearly that heat transfer limitation due to reactant thickness is the main cause of performance limitation but also that a trade-off has to be found between the achievement of high peak performance and more stable ones. A possible way to improve the heat transfer is to deposit a layer of reactive solid (of micrometric to millimetric thickness) directly on the surface of the heat exchanger. Some studies have been carried out, mainly for adsorbents dedicated to cooling applications and promising results have been obtained [START_REF] Freni | An advanced solid sorption chiller using SWS-1L[END_REF][START_REF] Calabrese | Development and characterization of silane-zeolite adsorbent coatings for adsorption heat pump applications[END_REF][START_REF] Kummer | Versatile siloxane based adsorbent coatings for fast water adsorption processes in thermally driven chillers and heat pumps[END_REF][START_REF] Bahrehmand | The effects of graphite flake on specific cooling power of sorption chillers: An experimental study[END_REF]. Thus, high specific power, up to several hundred W/kg, have been measured [START_REF] Freni | An advanced solid sorption chiller using SWS-1L[END_REF] and confirmed recently by McCague et al. [START_REF] Mccague | Lab-scale sorption chiller comparison of FAM-Z02 coating and pellets[END_REF]. However, as highlighted recently by He et al. [START_REF] He | Thermal performance improvement of AHP using corrugated heat exchanger by dip-coating method with mass recovery[END_REF] and by Venegas et al. [START_REF] Venegas | Critical review and future prospects for desiccant coated heat exchangers: Materials, design, and manufacturing[END_REF] the coating method and the binder content and behavior can highly impact the performance. Despite the high potential benefit that can be expected from the direct coating of the reactant material on the heat exchanger for THT applications, this approach has only been scarcely explored so far to the best knowledge of the authors. For example, in recent reviews on thermochemical systems [START_REF] Cabeza | Review on sorption materials and technologies for heat pumps and thermal energy storage[END_REF][START_REF] Desai | Thermochemical energy storage system for cooling and process heating applications: A review[END_REF], the focus is clearly put on heat storage applications for which coating is considered as a possible way to contain the reactant in a matrix (e.g. [START_REF] Van Ravensteijn | Encapsulation of Salt Hydrates by Polymer Coatings for Low-Temperature Heat Storage Applications[END_REF]) rather than as a way to deposit it at the surface of a heat-exchanger for heat-pumping applications.

Hence, the paper main contribution lies in taking a first step forward in developing a salt-coated heat exchanger for high temperature of thermochemical heat transformers (i.e. for applications such as waste heat upgrade in the industry). This is achieved by experimentally assessing the performance of a THT using water vapor as reactive gas and CaCl 2 as reactive solid, for operating temperature up to 150 °C (heat supply to the industrial process) and temperature lift between 40 and 80 K. Two configurations are tested: a reference one representative of a packed bed, i.e. a thick layer of salt in contact with a model heat exchanger plate and one with a deposit of CaCl 2 /PVA (PolyVinyl Alcohol used as binder) to model a coated reactor. After a brief description of the developed experimental test bench, the dynamic behavior of the two configurations during hydration is compared and the impact of operating conditions assessed. Repeatability experiments, to assess the ageing of the deposit, are discussed. Finally global performances are compared to values available in the literature.

Principle of solid/gas sorption processes for thermochemical heat transformer

Solid/gas reaction for thermochemical heat transformer

The thermochemical heat transfer involves a monovariant reversible chemical reaction between a solid and a gas:

(1)
The equilibrium conditions (p eq , T eq ) of this solid/gas reaction follow the Clausius-Clapeyron relation (equation 2). Assuming the reactive gas follows an ideal gas behavior, the thermodynamic equilibrium conditions are determined by only one intensive variable: the equilibrium pressure p eq or the equilibrium temperature T eq :

(2) p 0 is the reference pressure (1 bar), and are respectively the standard enthalpy and entropy of reaction.

Operating of thermochemical heat transformers

Among the operating cycles of THT using water as working fluid, the 1-salt and 2-salts are the two main configurations [START_REF] Yu | Energy upgrading by solid-gas reaction heat transformer: A critical review[END_REF]. The 1-salt cycle consists of two reactors alternately connected to an evaporator and a condenser (see Fig. 1a). The cycle is described by a liquid/vapor equilibrium line (L/G line) and a solid/gas reaction equilibrium line (S/G line) in a Clapeyron diagram (see Fig. 1b). First, during the upgrade temperature phase waste heat (Q mLT ) at intermediate temperature (T m at around 90 °C) is supplied to the evaporator allowing the water evaporation at "high pressure" P h (e.g. 70 kPa for an evaporation temperature of 90 °C). This water vapor allows to realize the exothermic hydration reaction of the reactive material, releasing high-grade heat (Q HT ) at T H . The temperature lift during this phase corresponds to the temperature difference between the intermediate temperature, T m , and the high temperature, T H : ΔT lift = T H -T m . The theoretical maximum temperature lift attainable by this system is achieved for adiabatic operation and corresponds to the temperature difference between the equilibrium temperature of the salt and the evaporation temperature at the "high pressure". In real systems, a gap from this value is necessary in order to obtain a suitable heat power from the reaction. When the hydration reaction in the reactor finishes, the charging phase (or regeneration phase) of the reactor begins. Waste heat (Q mHT ) at T m is supplied to the reactor while it is connected to a condenser maintained at low temperature (usually ambient temperature). This allows the reactive material dehydration at low pressure, P L . In order to decrease the required pressure lift when high temperature lifts are sought, Goetz et al. [START_REF] Goetz | The structure and performance of single effect solid -gas chemical heat pumps[END_REF] proposed a 2-salts cycle, also called resorption heat pump. In this case, the evaporator and the condenser are replaced by two reactors filled with a so-called low temperature salt (see Figure 1c). In the Clapeyron diagram an S/G line has replaced the L/G line of the 1-salt configuration (Fig. 1d).

Materials and methods

Experimental set up

An experiment was carried out to characterize the heat transfer and the kinetic reaction of reactive materials samples dedicated to THT application. The experimental setup is depicted in Figure 2. It is composed of two main elements: the reactor (2) and the Evaporator/Condenser (E/C) [START_REF] Forman | Estimating the global waste heat potential[END_REF]. Those two components are stainless steel tanks. The reactor is a double skin envelope tank of 350 mm inner diameter and 500 mm length, insulated with 1 cm of fiberglass. The E/C tank is a vessel of 200 mm inner diameter and 360 mm length insulated with 1.2 cm of Armaflex® foam. Their respective temperatures are controlled by two thermostatic baths. The "cold" thermal bath (IsoTemp 6200R28) (5) drives the temperature of the E/C using a spiral coil heat exchanger with an external area of around 0.025 m 2 . The "hot" thermal bath (4 -Julabo HE-4) drives the flow in the reactor's double skin envelope and in a heat plate exchanger (HX) contained in the reactor [START_REF] Li | A target-oriented solid-gas thermochemical sorption heat transformer for integrated energy storage and energy upgrade[END_REF]. This reactor heat exchanger of 200 x 200 x 70 mm, enables to impose the temperature to the tested reactive sample [START_REF] Wu | Experimental investigation on a novel solid-gas thermochemical sorption heat transformer for energy upgrade with a large temperature lift[END_REF]. The vapor exchange between the reactor and the Evaporator/Condenser is carried out through a pipe with a diameter of 40 mm to minimize the pressure drop (3) and a ball valve. Both chambers are fitted with a ball valve for connection with a vacuum pump. -1/T Ln(P)  Within the reactor: five TC are located inside the reactor chamber. Two TC are set in the salt sample: one at the middle of the salt (T s ) and the other one (T s/HX ) at the bottom of the salt sample, at the interface between the salt and the heat plate exchanger (see Figure 3). Two other TC measure the vapor and the internal wall temperatures.

T L T m T H ΔT lift c) d)
The water vapor pressure (p v,R , 10 Pa) is measured using the 0-0.1 bar pressure gauge.

 At the inlet and outlet pipe of the reactor heat plate exchanger: two TC measure the temperature of the heat transfer fluid (thermal oil H20S, Julabo®).  Additionally, the reactive samples are punctually weighed outside of the reactor (m s , 0.05g), to evaluate the reaction advancement (see section 4.2.1).

A NI-DAQ® acquisition unit ( 6) is used for the measures acquisition and measurements are recorded every 5 s.

Reactive material testing device

The choice of a suitable hydrate salt is an essential step in the conception of a thermochemical heat transformer. For the target application of upgrading temperature from around 100 °C to 150 °C, the calcium chloride has been identified as promising in a previous work [START_REF] Michel | Design of thermochemical heat transformer for waste heat recovery: Methodology for reactive pairs screening and dynamic aspect consideration[END_REF]. While corresponding to a favorable operating temperature range, it also has the advantage to be non-toxic, low cost and to be easily available. In addition to the anhydrous form, the calcium chloride presents four stable hydrates: monohydrate, dihydrate, tetrahydrate and hexahydrate [START_REF] N'tsoukpoe | A review on the use of calcium chloride in applied thermal engineering[END_REF], which thermo-physical properties are listed in table 1. In the present work, calcium chloride dihydrate powder was supplied by Sigma Aldrich® with purity higher than 99%. As it can be seen on Figure 3, two salt configurations were tested. In the first one, a bed of pure salt is disposed over an aluminum plate of 10x10 cm 2 and 1 mm of thickness. The achieved bed thickness is about 20 mm (dihydrated mass between 60 and 80 g), using aluminum walls to prevent salt sewing from the plate (see Figure 3a). The low operating pressure (p v < 55 kPa) and the double walled reactor allow to limit the edge effects. Moreover, the thermocouples are placed in the center of the reactive sample. The second configuration consists in a deposit on a thin aluminum plate (1 mm thick and 10x10 cm 2 square) of a compound material made of CaCl 2 and PVA (polyvinyl alcohol) as binder. To achieve this, distilled water and PVA are mixed together at 80 °C. Then the powder of dihydrate salt is added to the solution. It is stirred at 60 °C till full homogenization of the solution is reached. The solution is then deposited on the aluminum plate to obtain a deposit of around 1 cm thick (note that the thickness is not homogenous, it is of around 2 cm in the center and 0.5 mm on the border). The T s/HX T s distilled water is then evacuated from the deposit by heating in an autoclave oven during two days. Several temperature steps are conducted (50 °C, 100 °C, then 120 °C and finally 140 °C) to avoid the melting of the salt (the higher the water content, the lower the melting point as referred in table 1). At the end of the heating process, the reactive material is fully dehydrated and the final salt content of the deposit (in its dehydrated state) is 91 wt% for a total weight of around 20 g. During the deposit process, a thermocouple is placed in the solution before it dries. Another one is placed between the plate and the heat exchanger (figure 3d).

3.4 Experimental protocols

Solid-gas reactions equilibrium study

In order to determine the equilibrium reaction conditions of the different calcium chloride hydrates, the following protocol has been used.

The different experiments conducted to determine the equilibrium relations of the CaCl 2 /H 2 O reactions have been realized with around 80 g of dihydrated salt implemented in packed bed and placed on the reactor heat plate exchanger. The sample was initially dehydrated and then set to the desired initial conditions. Initial salt temperature was 160 °C. The range of initial vapor pressures, fixed by controlling the E/C temperature, varied between 3 and 30 kPa. The initial pressure is chosen so that the salt still is in anhydrous state. The reactor is disconnected to the E/C and progressively cooled down to start the hydration reaction. The temperature is decreased till 40 °C and increased back to 160 °C in order to complete a full hydration-dehydration cycle. If temperature varies slowly enough, it can be considered that the salt is always at equilibrium. Different heating rates have been tested: 0.5 K/min, 0.2 K/min, 0.1 K/min and 0.05 K/min. Experimental results has shown that the decrease of the heating rate has no more influence below 0.1 K/min. Hence, this heating rate has been chosen for all the studies of the reaction equilibrium conditions.

Hydration study

In order to investigate the reactive samples performances (temperature lift, reaction kinetics, cycle stability, etc.) under variant representative operating conditions of a 1-stage 1-salt THT configuration, the following experimental protocol has been carried out. The reactive sample is firstly dehydrated and weighed. During the hydration step, the waste heat temperature T m is imposed to the E/C using the cold bath, while the high temperature bath is used to impose the high temperature T H of the salt heat plate exchanger.

In order to follow the reaction advancement, weighing is performed. In this case, the E/C and the reactor are disconnected. The salt is weighed on the scale outside of the react or. It is then reintroduced inside the reactor and vacuum is made during ten minutes using a vacuum pump. The E/C is then reconnected to the reactor to continue the hydration reaction.

Results and discussion

Solid-gas equilibriums characterization

The CaCl 2 /water reactions equilibriums are important data for thermochemical systems design. Several characterization attempts are found in the literature (see Figure 5), however some references are divergent [START_REF] N'tsoukpoe | A review on the use of calcium chloride in applied thermal engineering[END_REF][START_REF] Molenda | Reversible hydration behavior of CaCl2 at high H2O partial pressures for thermochemical energy storage[END_REF][START_REF] Yu | Evaluation of a three -phase sorption cycle for thermal energy storage[END_REF][START_REF] Ichinose | Dehydration Reaction and its Acceleration for CaCl2 Hydrate for Chemical Heat Storage[END_REF]. The hydration reactions allowing to go from the anhydrous calcium chloride to the dihydrate calcium chloride (i.e. the reaction from CaCl 2 to CaCl 2 •1H 2 O and the reaction from CaCl 2 •1H 2 O to CaCl 2 •2H 2 O) have been experimentally investigated using the method described in the section 3.4.2 in order to determine the corresponding equilibrium relations.

Hydration reaction from anhydrate to dihydrated state of the calcium chloride is plotted on Figure 4. At first, the pressure decreases linearly with temperature, the salt being initially anhydrous, it cannot react until its temperature reaches the first reaction equilibrium curve (between the anhydrous and the monohydrated state, i.e. CaCl 2 to CaCl 2 •1H 2 O reaction). During this step, pressure and temperature of the vapor are linked, following an ideal gas behavior, as shown on Figure 4. When the imposed salt temperature reaches the first reaction equilibrium, the salt hydrates consumes water which decreases the reactor pressure following the hydration reaction from CaCl 2 to CaCl 2 •1H 2 O equilibrium line. Once the fully monohydrated state is reached, the salt cannot be hydrated anymore. Further decrease of the salt temperature leads to reaching the second reaction equilibrium: from CaCl 2 •1H 2 O to CaCl 2 •2H 2 O, the water vapor following an ideal gas behavior. There, the second equilibrium line is followed until saturation. Note that the pressure oscillations observed at high pressure and temperature are due to vapor condensation/evaporation on the wall of the reactor. By changing the initial conditions (i.e. initial vapor pressure), it is then possible to determine the salt equilibriums in a wide range of pressure and temperature. The coefficients of the Clausius-Clapeyron equilibrium reaction equations have been determined using minimization function with differential evolution method. The obtained results are presented in the Figure 5 and compared to results from the literature [START_REF] Richter | A systematic screening of salt hydrates as materials for a thermochemical heat transformer[END_REF][START_REF] N'tsoukpoe | A review on the use of calcium chloride in applied thermal engineering[END_REF][START_REF] Molenda | Reversible hydration behavior of CaCl2 at high H2O partial pressures for thermochemical energy storage[END_REF][START_REF] Yu | Evaluation of a three -phase sorption cycle for thermal energy storage[END_REF][START_REF] Ichinose | Dehydration Reaction and its Acceleration for CaCl2 Hydrate for Chemical Heat Storage[END_REF]. The lines represent the experimental fitted curves and the markers represent the experimental range of measurements. The fitted equations for each reaction, both from this work and literature, are listed in annex (table A1).

Although the obtained equilibriums are close to those of the literature, differences have been highlighted. Thus, Molenda et al. [START_REF] Molenda | Reversible hydration behavior of CaCl2 at high H2O partial pressures for thermochemical energy storage[END_REF] For the data from this work, the lines correspond to the fit with the Clausius-Clapeyron relation and the markers correspond to the experimental range studied [START_REF] Richter | A systematic screening of salt hydrates as materials for a thermochemical heat transformer[END_REF][START_REF] N'tsoukpoe | A review on the use of calcium chloride in applied thermal engineering[END_REF][START_REF] Molenda | Reversible hydration behavior of CaCl2 at high H2O partial pressures for thermochemical energy storage[END_REF][START_REF] Yu | Evaluation of a three -phase sorption cycle for thermal energy storage[END_REF][START_REF] Ichinose | Dehydration Reaction and its Acceleration for CaCl2 Hydrate for Chemical Heat Storage[END_REF].

Furthermore, contrarily to the data from the literature, a hysteresis phenomenon between hydration and dehydration reaction is observed, the larger effect being for the reaction (CaCl2 to CaCl2•1H2O reaction). In the perspective of the THT application, this hysteresis is unfavorable as it will require a lower pressure (i.e. a lower "low temperature") to achieve CaCl2 dehydration during the regeneration phase. Different phenomena could explain this hysteresis. Firstly, as observed by Molenda et al. [START_REF] Molenda | Reversible hydration behavior of CaCl2 at high H2O partial pressures for thermochemical energy storage[END_REF], the determination of the thermodynamic equilibrium in a dynamic way can conduct to overestimate the reaction temperature (for a given vapor pressure) in dehydration and underestimate this temperature in hydration. Indeed, due to the heat and mass transfer resistances inside the salt, the effective temperature hardly corresponds to the targeted operating conditions (temperature or vapor pressure). This phenomenon is all the more important as the heating rate is high. However, in our case a heating rate study has shown that no more impacts on the equilibrium are observed for heating rate equal or inferior to 0.1 K/min. Sögütoglu et al. [START_REF] Sögütoglu | Understanding the Hydration Process of Salts: The Impact of a Nucleation Barrier[END_REF] highlighted another phenomenon called "induction time" that could explain the observed hysteresis. They reported that for some salts there is an inactive metastable zone around the equilibrium were a time is necessary to start the reaction. They explain this induction time due to the presence of a nucleation barrier. The reaction must be therefore initiated far enough away from the equilibrium in order to create a first nucleation of the new hydrate and start the reaction. To investigate this hypothesis with the calcium chloride, a cycle starting from an incomplete hydration has been realized in order to start the dehydration with sample containing monohydrated (CaCl2•1H2O) and anhydrous calcium chloride (Figure 6). No impact of the incomplete hydration is identified on the hysteresis so that the presence of nucleation barrier was not highlighted in the present case. Further investigations have to be performed to better understand the origin of the observed hysteresis phenomenon.

THT performances analysis

This part aims at analysing the dynamic behavior and the performances of packed bed and deposit implementations of salt for a 1-salt THT configuration. Several hydrations were conducted with different realistic operating conditions and salt implementation (packed bed or deposit). All the obtained results are summarized in table A2.

Dynamic behavior

The reactive sample temperature evolutions of a typical hydration experiment for packed bed and deposit implementations are presented on the Figure 7a andb, respectively.

Figure 7a shows that as vapor is injected, salt temperature rises rapidly with the beginning of the exothermic hydration reaction. A bulk salt temperature over 173 °C is reached, meanwhile the peak temperature in the bottom of the crucible does not excess 168 °C. Then, a first salt temperature plateau, at around 170 °C, is observed during around 20 min, followed by a second temperature plateau at lower temperature (around 150 °C) during two hours. Finally, the salt temperature decreases gradually to reach temperature close to the heat transfer fluid temperature (139 °C). Due to the heat losses, salt temperature lower than the inlet heat transfer fluid temperature (T i,htf ) are observed at the end of the experiment. The two rapid falls of temperatures and pressure correspond to the punctual weighing of the reactive bed.

In agreement to the equilibrium temperatures of the two first hydration reactions of the calcium chloride (T eq (0-1) and T eq (1-2)), the salt bed temperature plateaus correspond to the two first hydration reactions of the CaCl When the first exothermal reaction is complete at the thermocouple emplacement, the salt temperature decreases to tend to the equilibrium temperature of the second reaction. Finally, when the second exothermal reaction is complete, the salt temperature reaches the imposed bottom plate temperature (i.e. the inlet heat transfer fluid temperature). For the coated plate, (Figure 7b) a lower salt peak temperature is observed (153 °C) and no plateau occurs. The heat transfer fluid temperature is also reached more rapidly. This reflects directly the decrease in heat transfer resistance with this configuration.

The average reaction advancement, calculated from the equation ( 3) is presented on Figure 8 for both configurations. X corresponds to the average number of mole of water contain in the reactive material per mole of salt. It is equal to 0 in the anhydrous state, 1 for the CaCl 2 •1H 2 O, etc.

(

) 3
m s is the mass of salt and m s,0 is the mass of dehydrated salt, i.e. initial mass of salt. For packed bed configuration, in accordance to the salt bed temperature evolution, the average reaction advancement presented in the Figure 8 shows that both the CaCl 2 to CaCl 2 •1H 2 O and CaCl 2 •1H 2 O to CaCl 2 •2H 2 O hydration reactions have been achieved. Similar results are obtained for the deposit configuration. Moreover, comparable reaction time are observed between the two different implementation though in the case of the deposit, the operating conditions are less favourable (T H = 148.9 °C instead of 138.7 °C for the packed bed experiment). This shows that the deposit implementation allows to enhance the heat and mass transfer inside the reactive material and therefore the reaction kinetic.

Sensitivity to the thermal sources temperature

For each salt implementation, this sensitivity analysis focuses on the salt temperature and reaction kinetic evolutions for different waste heat temperature (T m ) and released heat temperature (T H ). The comparison of three hydration experiments of around one hour (reference case (red), lower T H case (blue) and higher T m case (green)) are presented in the Figure 9a and b respectively for the packed bed and the deposit implementations. Although the reaction temperature is imposed by the vapor pressure and therefore by the waste heat temperature, these peak temperature differences can be explained by several phenomena: the higher heat transfer due to the lower heat plate exchanger temperature (T H ); the different salt initial temperatures (imposed at T H ). Furthermore, as the heat transfer and the equilibrium drop are higher for hydration with lower T H , the reaction kinetics increases when reducing the heat released temperature.

Increasing the waste heat temperature T m leads to an increase of the system vapor pressure and therefore an important increase of the peak temperature and of the plateau temperatures of each hydration reactions (CaCl for both salt implementations (green lines on Figure 9). Moreover, similarly to sensitivity study of T H , the increase of T m leads to an increase of the equilibrium deviation and therefore to the reaction kinetic. It can also be observed that the system is more sensitive to the intermediate temperature T m than to T H . Indeed, as shows Figure 9b, though the higher T m case of the deposit implementation presents also a higher T H of the same order of magnitude (around 10 K) compared to the reference case, an important increase of the reaction kinetic is still observed.

Repeatability

Hydration/dehydration cycles at identical operating conditions have been done for both salt implementations. In order to fully dehydrated the reactive material between each cycle, dehydration with extreme operating conditions (T L /T H = 2/150 °C) have been conducted. No mass monitoring has been conducted for these experiments to avoid the resulting disturbances. Four cycles have been realized with the deposit implementation and due to the higher reaction time with the packed bed implementation only two cycles have been conducted. For the packed bed implementation, no significant changes on the level of temperature peaks and plateaus are observed. However, the salt temperatures of each plateau decrease quicker for the second cycle. This indicates that the hydration reactions are finished earlier at the thermocouple location during the second cycle. It can be due to a faster reaction kinetic or a displacement of the thermocouple in the packed bed due to the reactive bed deformation during hydration/dehydration reaction.

For the deposit implementation, the temperature time course changes during the two first cycles and seems to be stabilized after the third cycle, with a peak of temperature increasing from 145 °C during the cycles 1 and 2 to over 148 °C for the two last cycles. These temperature evolutions can be explained by the deposit ageing during cycles. After few cycles, cracks and problems of adhesion to the heat exchanger appear for the deposit configuration (Figure 11). This can lead higher thermal resistance that can explain the increase of the peak temperature. Furthermore, from the cross-sectional view (Figure 11c), a potential segregation between the salt and the binder is observed, potentially resulting in a drop in performances. Hence, it can be concluded that further development is needed to limit the ageing of the salt/binder compound and improve its adhesion on the heat exchanger surface.

Global performances

The THT performance directly depends on the kinetic reaction. The impact of the waste heat temperature (70 °C < T m < 100 °C) and of the demand temperature (130 °C < T H < 160 °C) is assessed for the two THT implementation (packed bed and deposit). Three criteria are evaluated:

1. The average specific heating power during the first hydration reaction (CaCl 2 to CaCl 2 •1H 2 O reaction). This parameter is calculated using the salt mass variation during the first hydration reaction and the corresponding reaction enthalpy J/mol v [START_REF] Richter | A systematic screening of salt hydrates as materials for a thermochemical heat transformer[END_REF]:

With Δt the time between the measure of m s and the beginning of the CaCl 2 to CaCl 2 •1H 2 O hydration reaction. 2. The thermodynamic driving force. Any change in the operating conditions (T L , T m , T H ) results in a change in equilibrium drop. This can be related to the thermodynamic driving force of the reaction [START_REF] Michel | Design of thermochemical heat transformer for waste heat recovery: Methodology for reactive pairs screening and dynamic aspect consideration[END_REF][START_REF] Obermeier | Thermodynamic analysis of chemical heat pumps[END_REF]. Usually the greater the driving force, the greater the reaction kinetic.

For pure substances and ideal mixtures, the driving force can be described by the Gibbs free energy of the reaction and can be written as:

(5)

3. The temperature lift, that corresponds to the temperature increase:

ΔT lift = T H -T m (6)
Note that the presented values of the driving force and temperature lift are average values during the hydration reaction.

Figure 12 presents the average specific power released by the samples as function of the driving force. A large range of average specific power is obtained, between 36 W/kg and 341 W/kg. This figure shows that the specific power depends to the driving force of the reaction. As it has been already observed numerically [START_REF] Michel | Design of thermochemical heat transformer for waste heat recovery: Methodology for reactive pairs screening and dynamic aspect consideration[END_REF], for a given salt implementation (corresponding to given heat and mass transfer parameters inside the reactive material) the specific power increases with the driving force. This parameter is therefore an interesting parameter allowing to obtain rapidly an estimate of the system performances. Furthermore, for a given driving force the deposit implementation leads in general a higher average specific power than for the packed bed implementation. This highlights the benefit of this configuration in terms of heat and mass transfer enhancement. Nevertheless, the few numbers of tested samples and the discrepancy observed for the results with the deposit implementation cannot allow to define a clear relation between the average specific power and the driving force. This performances variability can be explained by possible degradation (formation of cracks, problems of deposit adhesion, etc.) of the deposit sample during the hydration reaction (see section 4.2.3).

Figure 12: Average specific power vs. driving force for two salt implementations (packed bed and deposit.

The impact of the imposed temperature lift on the average specific power is presented in the Figure 13 for the two salt implementations and for different experimental results from the literature (for 1salt THT configuration). This figure shows that, in a general way the specific power decreases when the temperature lift increases (due to the decrease of the equilibrium drop).

For a packed bed implementation, the obtained results are comparable to that of the literature with a specific power of around 180 W/kg obtained for a temperature lift of 60 K. Although discrepancy is observed with the results of the deposit implementation, Figure 13 shows that with the same THT configuration the deposit implementation can allow to obtain better performances than the packed bed implementation. Thus, for the same temperature lift, performances higher than the one obtained with the packed bed implementation and the one obtained in the open literature are reached with the deposit implementation, with average specific power until 341 W/kg for a temperature lift of 67 K. and the literature [START_REF] Esaki | Experimental evaluation of the heat output/input and coefficient of performance characteristics of a chemical heat pump in the heat upgrading cycle of CaCl2 hydration[END_REF][START_REF] Richter | Heat transformation based on CaCl2/H2O -Part A: Closed operation principle[END_REF][START_REF] Stengler | Thermal energy storage combined with a temperature boost: An underestimated feature of thermochemical systems[END_REF][START_REF] Esaki | Study on the cycle characteristics of chemical heat storage with different reactor module types for calcium chloride hydration[END_REF][START_REF] Zhang | Development and thermochemical characterizations of vermiculite/SrBr2 composite sorbents for lowtemperature heat storage[END_REF].

Conclusion

In this paper, two reactor configurations for thermochemical heat transformers applications for industrial waste heat recovery are evaluated: a packed bed one and a coated heat exchanger. In both cases, CaCl 2 /water is used as working pair while the reported work is restricted to the hydration step (i.e. heat generation at required process demand).

For the packed configuration, the temperature evolution is characterized by a peak of temperature at reaction beginning, followed by a plateau and a decrease towards reaching the secondary fluid temperature. For the coated heat exchanger configuration, the peak occurs as well, but with a lower amplitude and the plateau is replaced by a decay towards the secondary fluid temperature. This behavior reflects directly the decrease in heat transfer resistance for the second configuration.

The performance is assessed using the average specific power and the temperature lift obtained for the first hydration reaction (CaCl 2 to CaCl 2 •1H 2 O reaction) for different operating conditions (T m and T H ). Compared to packed bed, the deposit configuration allows to significantly increase the THT performances with a specific power increasing from 180 W/kg to 341 W/kg for a temperature lift of around 60 K. High sensitivity to temperature lift is also observed with for example a decrease from 140 W/kg to 38 W/kg when ΔT lift increases from 60 K to 77 K for the packed bed implementation. Finally, ageing of the deposit is identified during repeatability experiments leading in a drop in performance (i.e. increase in peak temperature corresponding to an increase in heat transfer resistance due to cracks and partial deposit detachment)

To complete this work, it would be interesting to extend the proposed methodology to the study of the regeneration phase (salt dehydration), to test the deposit implementation at a larger scale. Work as also to be performed to progress in the coating formulation and behavior characterization, in order to improve the deposits durability.

Figure 1 :

 1 Figure 1: a) 1-salt THT working principle, b) 1-salt THT Clapeyron diagram. c) 2-salts THT working principle, d) 2-salts THT Clapeyron diagram (adapted from[START_REF] Michel | Design of thermochemical heat transformer for waste heat recovery: Methodology for reactive pairs screening and dynamic aspect consideration[END_REF]).

Figure 2 :

 2 Figure 2: Photography of the experimental test bench

  Steam supply pipe (4) « Hot » thermal bath (5) « Cold » thermal bath (6) Data logger (7) Heat exchanger (8) Reactive sample

Figure 3 :

 3 Figure 3: Photography of the two salt implementations studied and schema of the thermocouples locations: a) salt bed b) salt deposit c) TC repartition in the salt bed d) TC repartition in the salt deposit

Figure 4 :

 4 Figure 4: Hydration reaction from anhydrate to dihydrated state of the calcium chloride. Equilibrium lines are from the experimental study presented section 4.1.

Figure 5 :

 5 Figure 5: Dehydration and hydration equilibrium line of CaCl 2 hydrate. For the data from this work, the lines correspond to the fit with the Clausius-Clapeyron relation and the markers correspond to the experimental range studied [23,40-43].

  et al., 2015 [40] Ichinose et al., 2020 [43] Yu et al., 2014 [42] Molenda et al., 2013 [41]Richter et al. 2018[START_REF] Richter | A systematic screening of salt hydrates as materials for a thermochemical heat transformer[END_REF] Cristalization line[START_REF] Molenda | Reversible hydration behavior of CaCl2 at high H2O partial pressures for thermochemical energy storage[END_REF][START_REF] Yu | Evaluation of a three -phase sorption cycle for thermal energy storage[END_REF]

Figure 6 :

 6 Figure 6: Comparison between short and long cycle

2 :

 2 CaCl 2 to CaCl 2 •1H 2 O reaction and CaCl 2 •1H 2 O to CaCl 2 •2H 2 O reaction.

Figure 7 :

 7 Figure 7: Pressure and temperature evolution a) of the 1-salt hydration with a packed bed implementation (sample 1: T m /T H = 78.6/138.7 °C); b) of the 1-salt hydration with a deposit implementation (sample 12: T m /T H = 81.8/148.9 °C).

Figure 8 :

 8 Figure 8: Reaction advancement vs. time of the 1-salt hydration with a packed bed (sample 1: T m /T H = 78.6/138.7 °C) and deposit (sample 12: T m /T H = 81.8/148.9 °C) implementations.

Figure 9 :

 9 Figure 9: Salt temperature and reaction advancement evolutions for different operating temperatures(T H and T m ); a) packed bed implementation ("reference" case (sample 6): T m /T H = 62.9/138.[START_REF] Zhang | A comprehensive review on advances and applications of industrial heat pumps based on the practices in China[END_REF] °C, "lower T H " case (sample 8): T m /T H = 61.5/126.5 °C, "higher T m " case (sample 1): T m /T H = 78.6/138.7 °C); b) deposit implementation ("reference" case (sample 13): T m /T H = 60.5/130.9 °C, "lower T H " case (sample 15): T m /T H = 60.7/128.4 °C, "higher T m " & T H case (sample 10): T m /T H = 70.4/138.6 °C).

  2 to CaCl 2 •1H 2 O reaction and CaCl 2 •1H 2 O to CaCl 2 •2H 2 O reaction) is observed 0

Figure 10 :

 10 Figure 10: Salt temperature evolutions during hydration for few hydration/dehydration cycles at identical operating conditions; a) packed bed implementation (sample 9: T L /T m /T H = 2/80.5/147.4 °C); b) deposit implementation (sample 16: T L /T m /T H = 2/66.1/138 °C).

Figure 10a and b present

  Figure10aand b present respectively the salt temperature evolution during hydration for the two cycles with the packed bed implementation and the four cycles with the deposit implementation. For the packed bed implementation, no significant changes on the level of temperature peaks and plateaus are observed. However, the salt temperatures of each plateau decrease quicker for the second cycle. This indicates that the hydration reactions are finished earlier at the thermocouple location during the second cycle. It can be due to a faster reaction kinetic or a displacement of the thermocouple in the packed bed due to the reactive bed deformation during hydration/dehydration reaction.

Figure 11 :

 11 Figure 11: Picture of a PVA-deposit a) before experiment and b) after one hydration-dehydration cycle at T L /T m /T H = 2/65.9/138.1 °C (sample 16) and c) after four cycles.

Figure 13 :

 13 Figure 13: Average specific vs. temperature lifts for different thermochemical systems from this workand the literature[START_REF] Esaki | Experimental evaluation of the heat output/input and coefficient of performance characteristics of a chemical heat pump in the heat upgrading cycle of CaCl2 hydration[END_REF][START_REF] Richter | Heat transformation based on CaCl2/H2O -Part A: Closed operation principle[END_REF][START_REF] Stengler | Thermal energy storage combined with a temperature boost: An underestimated feature of thermochemical systems[END_REF][START_REF] Esaki | Study on the cycle characteristics of chemical heat storage with different reactor module types for calcium chloride hydration[END_REF][START_REF] Zhang | Development and thermochemical characterizations of vermiculite/SrBr2 composite sorbents for lowtemperature heat storage[END_REF].

  . 2017[START_REF] Esaki | Experimental evaluation of the heat output/input and coefficient of performance characteristics of a chemical heat pump in the heat upgrading cycle of CaCl2 hydration[END_REF] Esaki and Kobayashi 2020[START_REF] Esaki | Study on the cycle characteristics of chemical heat storage with different reactor module types for calcium chloride hydration[END_REF] Stengler and Linder 2020[START_REF] Stengler | Thermal energy storage combined with a temperature boost: An underestimated feature of thermochemical systems[END_REF] Richter et al. 2016[START_REF] Richter | Heat transformation based on CaCl2/H2O -Part A: Closed operation principle[END_REF] Zhang et al. 2016[START_REF] Zhang | Development and thermochemical characterizations of vermiculite/SrBr2 composite sorbents for lowtemperature heat storage[END_REF] This study, packed bed 1-salt This study, deposit 1-salt Temperature lift (K) Average specific power (W/kg)

Table 1 .

 1 Properties of calcium chloride hydrates[START_REF] N'tsoukpoe | A review on the use of calcium chloride in applied thermal engineering[END_REF]

	Hydrate	Molar mass	Density	Melting point
		(g.mol -1 )	(kg.L -1 )	(°C)
		111	2.16	773
		129	2.24	187
		147	1.85	176
		183	1.83	45.3
		219	1.47-1.8	28-30

ACKNOWLEDGEMENT

The authors wish to thank the INSA LYON (BQR FATAL RECUP) for funding this study.

Appendixes