Diego Fuentealba
email: d.a.fuentealbacid@pgr.reading.ac.uk

Kecheng Liu
email: k.liu@henley.ac.uk

Weizi Li
email: weizi.li@henley.ac.uk

Organisational Responsiveness through Signs

Keywords: Organisational Semiotics, Autopoiesis, Responsiveness

Organisational Semiotics is a discipline that studies signs of organisations, and how these signs aid an analysis and design of technical information systems. The responsiveness of organisations has been discussed as a key feature to adapt the organisational behaviour in turbulent environments, but there are not studies about the implication of these capabilities on Information Systems. Organisational Semiotics can be used as a good approach to understand relationships between living things and organisations in order to develop their responses to the organisation. The purpose of this paper is the proposition of a preliminary model of organisations as living systems, using the concept of organisations as information systems. This paper articulates the information interactions between the border of the system, the environment and the activities of the organisation that maintain this border by methods of organisational semiotics. The future study will focus on the implementation of the proposed framework.

Introduction

Small and Medium Enterprises (SMEs) are facing constant changes in consumer preferences. A number of competitors and a market size are some factors which impact on how SMEs should respond to changes in the competitive environment [START_REF] Liao | Organizational Absorptive Capacity and Responsiveness: an Empirical Investigation of Growth-Oriented SMEs[END_REF]. The definition of responsiveness has been used in a wide range of fields as quality to react positively and quickly [START_REF] Stevenson | responsiveness. In: Oxford Dictionary of English[END_REF], and responsiveness of organisations has been seen as the ability to recognise changes and act on them [START_REF] Yaghoubi | Assessing Organizational Agility via Fuzzy Logic[END_REF]. However, the current approaches of responsiveness have been focused on reactions to certain changes, such as customer needs [START_REF] Nidumolu | The effects of customizability and reusability on perceived process and competitive performance of software firms[END_REF], suppliers [START_REF] Wang | A Virtual Integration Theory of Improved Supply-Chain Performance[END_REF][START_REF] Choi | The supply base and its complexity: Implications for transaction costs, risks, responsiveness, and innovation[END_REF] and supply chain [START_REF] Williams | Leveraging supply chain visibility for responsiveness: The moderating role of internal integration[END_REF], without providing a holistic understanding of which degree of the organisation can support these changes and why. Although responsiveness of organisations is not seen as a competitive advantage like agility, which included the speed of change and the flexibility of infrastructure to change [START_REF] Yaghoubi | Assessing Organizational Agility via Fuzzy Logic[END_REF], responsiveness should be seen as a basic capability of organisations that allows adaptations and modifications without affecting their current strengths.

Autopoiesis as an explanation of life in living systems reveal why living things maintain their inner-organisations in spite of the environment's changes, and provide a basic explanation of which kind of responsiveness can be expected from living systems in order to survive. Current studies about autopoiesis in Information Systems (IS) point out some challenges of preservation of an identity after several changes [START_REF] Huysman | Autopoiesis and the Evolution of Information Systems[END_REF] where the organisational image can play a significant role in the definition of the main features of the IS [START_REF] Bača | Autopoietic Information Systems in Modern Organizations[END_REF][START_REF] Kay | Toward an Autopoietic Perspective on Information Systems Organization[END_REF]. These definitions explained some properties of an autopoietic system that can be applied to technical IS, e.g. avoiding a concrete analysis of the concept of production of signs and information to maintain an organisational border that response to the environment with components of IS. This paper provides a preliminary model of organisation based on the definition of autopoiesis to understand why organisations can be seen as living systems, and how their responsiveness should be analysed and designed in order to maintain the autopoietic relationships and structure. This paper starts with the definition of responsiveness for organisations and living systems, using the definition of autopoiesis as the main engine of responsiveness in Section 2. Section 3 analyses the semiosis of organisation as an autopoietic process, followed by the proposition of the preliminary model of organisation in Section 4, using the cell-structure as a functional basis. Section 5 discusses the application of this theory, and followed by conclusions and future work in Section 6.

Responsiveness from Living Systems

Responsiveness of living systems can be defined as the ability of a living-thing to undergo a response [START_REF] Cammack | responsiveness. In: Oxford Dictionary of Biochemistry and Molecular[END_REF]. This reaction must maintain the network of processes that allows the life or the autopoiesis of the living system [START_REF] Maturana | Autopoiesis and Cognition. The Realization of the Living[END_REF]. Autopoiesis can explain why living systems define a set of thresholds to maintain this network of processes. For example, in the case of a cell, its autopoiesis needs a membrane to perform this network, which at the same time produces lipids and proteins to maintain the membrane [START_REF] Mingers | Self-producing systems implications and applications of autopoiesis[END_REF]. The responsiveness of a cell could be defined as the threshold of an external stimulus until the cell reacts to maintain the autopoiesis. An example of this threshold is the Heat shock response to avoid protein damage, which is a biochemical response of cells to mild heat stress. In this case, the cell response is the production of the protein HSF1 that repair some protein damage, developing thermos-tolerance [START_REF] Fulda | Cellular Stress Responses: Cell Survival and Cell Death[END_REF]. This reaction cannot be explained without the principle of autopoiesis to maintain the membrane. Thus, the definition of autopoiesis in the organisation can help the development of thresholds and capabilities to improve the responsiveness of organisations.

Kinds of Autopoietic Systems

According to [START_REF] Maturana | The Tree of Knowledge : the Biological Roots of Human Understanding[END_REF], depending on a level of autonomy and dynamic, autopoietic systems can be classified in first, second and third order. First order autopoietic systems are basic forms of life like a prokaryote or eukaryote cell [START_REF] Mingers | Self-producing systems implications and applications of autopoiesis[END_REF]. They possess the main features of autopoietic systems, which is the capability to produce their components (self-production) as a result of a network of processes. Some features of this kind of systems such as the maintenance of border and the relationship of their components can be found in the autopoietic test proposed by [START_REF] Varela | Autopoiesis: the Organization of Living Systems, its Characterization and a Model[END_REF]. Second-order autopoietic systems are meta-cellular organisms that are multicellular systems with the same lineage and structural couplings among them. This is possible if the regular interactions among autopoietic systems are sources of perturbations and compensations, where the participated systems do not lose their identity, creating a new unity. Examples of this kind of systems are human beings, animals and plants, which possess their own form of autopoiesis. Meta-cellular organism with nervous systems shows new forms of interactions such as abstract interactions and new innerstates as a result of their self-conscious, which at the same time is able to represent the world with abstract representations. Third-order autopoietic systems are societies of second-order autopoietic systems, which coordinate their acts by language.

Communication makes the social coupling by means of linguistic perturbations and compensations among individuals, creating inner-regular interactions in the form of cultural acts [START_REF] Maturana | The Tree of Knowledge : the Biological Roots of Human Understanding[END_REF].

Minimal Autopoietic Structure

The definition of autopoiesis does not say anything about the components, because autopoiesis emphasises the organisation or the network of processes of production of components over the structure [START_REF] Maturana | Autopoiesis and Cognition. The Realization of the Living[END_REF]. However, it is possible to describe a basic structure of cells based on the concept of minimal cells, which use the self-production property to define the basic components to self-produce a membrane [START_REF] Fleischaker | Autopoiesis: the Status of its System Logic[END_REF][START_REF] Luisi | Self-replicating micelles -a Ahemical Aersion of a Minimal Autopoietic System[END_REF]. The semi-synthetic minimal cell is an extension of this concept that defines the DNA, enzymes, ribosome, RNA, membrane and cytoplasm as basic components for selfmaintenance, self-reproduction and possibility to evolve [START_REF] Stano | Semi-synthetic Minimal Cells: Origin and Recent Developments[END_REF].

Additionally, according to [START_REF] Maturana | Autopoiesis and Cognition. The Realization of the Living[END_REF] there are three kinds of relations of productions that constitute some basic structure. They proposed the following relations:

 Production of constitutive relations: there are components that maintain the topology or physical space. The network of processes of production of these elements constitutes the topology of the autopoietic system  Production of specificity relations: There are components that specify the creation of other components. The network of processes of production of these elements determines the identity of the components of the autopoietic organisations  Production of relations of Order: There are components that regulate the points of meeting among processes. The network of processes of production of these elements determines the relations of order among the other processes These relations describe the following components:  Topological Components: The main function is the topological deployment of other components. Although membrane is a good example of these components, there are active sites in enzymes that fit with this description  Creational Components: There are components such as DNA, RNA and enzymes with the capability to produce other components  Control Components: There are components such as metabolites and enzymes with the capability to control the speed of the production of elements Thus, there are components such as enzymes with more than one function. Table 1 classifies the components of the minimal cell with the components described from the autopoietic relations, and the function of these components into the cell. Therefore, it is possible to define components based on the three relations of production, where creational and control components can be divided into message, control and production components. The creation of components in an autopoietic system conjugates these three relationships, because it is created a specific component in a specific physical space controlled by components produced by the cell.

3

Information Systems as Organisational Semiosis

Semiotics Implications of Sign, Data, Information and IS

The understanding of information, data and interpreter can be made with the division of Peirce among interpreter, sign and object [START_REF] Liu | Organisational Semiotics for Business Informatics[END_REF]. Signs from the perspective of semiotics can be anything determined by an external object and the effect of them upon a person (interpreter). This division defines an object with an independence of the observer and his/her knowledge, where the full understanding of an object can be made with a chain of signs [START_REF] Atkin | Peirce´s Theory of Signs[END_REF]. According to [START_REF] Mingers | An Integrative Semiotic Framework for Information Systems: the Social, Personal and Material Worlds[END_REF], there are intrinsic relations among information, events and signs. Events like objects are independent of an observer, and they can be stored and transmitted as signs by the environment and people. Data of an event can be seen as a collection of signs, which can be stored or transmitted as information. Thus, data is a kind of representation of events. On the other hand, information is a human process of sense making related to semantics, pragmatics and social world, which interprets signs or data as events in the daily life [START_REF] Stamper | Semiotic Theory of Information and Information Systems[END_REF]. Fig. 1 shows this relationship among events, data, sign and information, where the process of semiosis in the organisation is the process of sense making or understanding of external events, which are perceived as a collection of signs. The organisation has a role of interpreter of these signs to see the events as objects, which could be an abstract representation of the event or another sign that trigger the process of semiosis again. The organisation as the interpreter is affected by previous knowledge, which can be norms, culture and other events that restrict the behaviour or the possibility for reaction. This background knowledge can be updated as a result of this process and the information about events can open the possibility to react in the form of action or events that at the same time creates new signs. Examples of previous events that can shape the organisational behaviour could be the membership of people in different positions, the acquisition of new technology, changes in the regulation or changes in the competence. For this reason, the responsiveness of external perturbations is limited to the understanding of events or previous semiosis, which restricts or enables this capability for reaction. According to [START_REF] Liu | Organisational Semiotics for Business Informatics[END_REF], organisations can be seen as IS, where a set of norms can define the manner of behaving. There are informal, formal and technical norms, where the informal norms are beliefs and goals which are the first definition of the phenomenon named organisation. When a set of clear agreements are made, formal and technical norms formalise the messages of organisations, but in practical terms, they are the understanding and control of this phenomenon. This process of understanding of the organisation as a phenomenon, which starts from the informal layer shapes a set of data from events as formal and technical norms, creating information as a constant process of semiosis.

First Order Autopoietic System

Responsiveness of organisations depends on capabilities to response through signs, which can be analysed from the biologic perspective of autopoiesis. Organisational onion can simplify the analysis, focusing on the technical and formal layer [START_REF] Stamper | Semiotic Theory of Information and Information Systems[END_REF]. The algorithm of six points proposed by [START_REF] Varela | Autopoiesis: the Organization of Living Systems, its Characterization and a Model[END_REF] can help to analyse systems as an autopoietic system, starting with the analysis of the border and finishing with the analysis of interaction in the network of interactions. Information systems can be seen as autopoietic systems, because the lack of physical boundaries results in a boundary based on the information that is produced by the organisation. Referring to Fig. 1, technical and formal activities are not possible without an understanding (information) of previous events (data). Fig. 2 shows the self-definition of identifiable components such as contracts and inventory that can be used in the activities that interact with the environment. These components lead deterministic interactions from previous data or agreements, which can be connected in specific contexts. For instance, the sale activity as a context contains pre-defined signs such as contracts or inventory (norms, tasks or data) that are linked with components of the border, resulting in actions that create signs and information (receipt). Finally, the components that are not self-produced by the Information System are directly related to the process of generation of information. For instance, the inventory represents the acquisition event and participates in the sales action as a response to customer needs.

Fig. 2. The Role of Signs in Autopoiesis

Although IS has fitted their features with the autopoietic test, this analysis was made under ideal conditions. For instance, the theoretical division in layers of technical IS can be argued if a technical IS does not have this division. Therefore, the responsiveness of autopoietic systems can be summarised as the capability to maintain its border in spite of environmental perturbations.

Preliminary Model of Organisations as Living Systems

Under the assumption that organisation can behave as living systems, Fig. 3 shows an autopoietic model of organisations based on the division of functional components of a minimal cell and the components of an organisation based on organisational semiotics such as the definition substantive, control and communication behaviour.

Fig. 3. Autopoietic Model of Organisation

The main components of the model described as follows.

 Interfaces: These components are inspired in the membrane and represent the interactions that the IS must consider with the external environment such as the interchange of matter and energy. The main sources of interactions are customers, suppliers and other stakeholders such as government (i.e. custom and revenues) and partners. Initially, the border of the organisation is defined by the purpose of the organisation, and the activities that interact with the environment with physical and social consequences. The components of the organisation that participate in the border activity are agents, substantive activity, control and communication.  Creation Components: These components are inspired on the DNA, and they define the aim of the organisation. Some examples are which product or service is produced, which raw material or organisational product/activity is needed to interact with other stakeholders. It is important to highlight that DNA or creation components control the specification of each component of the organisation and the internal coherence in the form of meta-norms [START_REF] Stamper | Understanding the Roles of Signs and Norms in Organisations[END_REF]. Meta-norms self-regulate the organisation as a result of the process of adaptation from the environment, because they look the environment in order to prepare or change Meta-norms of organisation for new interactions. For instance, the (re)definition of the strategy is not directly involved in the production, but it would affect the production activities.  Inner Structure Components: These components are inspired by the Cytoplasm. The inner structure is composed of structural components that define order or hierarchy of the organisation such as hierarchy of communication, the division of departments and the assignation of agents in certain positions. This inner structure is mainly static and defines who the boss of whom is.  Communication Activities: These activities are inspired by the RNA. These activities are named coordination tasks, because they are not directly involved in the production of product/services, but they are also significant to the organisation. These activities can be basic activities to coordinate processes, but in a complex organisation, there are workflows, which is a composition of communication power and tasks.  Production Activities: These activities are inspired by the Ribosome. These activities are the substantive tasks that are involved in the creation of product/service of the organisation.  Control Activities: These activities regulate task and behaviour of the members. There are several classifications of norms, for instance, it is possible to classify according to the control of human behaviour, the effect of execution and the object that is applied [START_REF] Liu | Organisational Semiotics for Business Informatics[END_REF]. Thus, norms are capable of controlling every aspect of the organisation from their informal conception to their technical application.

These components can create a structure of the organisation, which is based on the minimal components to perform the autopoiesis of a cell. Although, the autopoiesis of organisations have been explained from the perspective of Information Systems and the generation of information, the self-description of these components are the image of the organisation, and their relationships can define a new form of autopoiesis from an abstract perspective. For instance, goals are related to tasks, and the strategy can define new goals. These cycles that generate new organisational signs and new information can be seen as a new perspective of autopoiesis.

Discussion

The autopoietic model represents an abstract level of the organisation, but its general features can be applied to any organisations. Companies with several changes during their life can be experimented to study the activity change after different states. An example of this kind of company is Rolls-Royce, which has changed its border activities from a good-dominant (GD) logic to a service-dominant (SD) logic due to the decreasing of the original equipment market. The competitive market with high investment in technology and R&D has pushed to Rolls-Royce into the implementation of the total customer's care system, which means that the business is also focused on the services of aftermarket such as maintenance and repairs of jetengines [START_REF] Royce | Competing within a Changing World[END_REF]. The autopoietic components of Rolls-Royce are:

 Interfaces of Rolls-Royce: Every division of Rolls-Royce provides contracts that include the maintenance, repair and overhaul of their products, making the 50% of the revenue of the company [START_REF] Tiwari | An Exploration of Supply Chain Management Practices in the Aerospace Industry and in Rolls-Royce[END_REF]. The customer's activities are related to the selling of product and services, which are focused on the creation of customer solutions in the form of product and service such as flight hours. The strategy of suppliers of Rolls-Royce is more complex than the procurement of products, but this activity can be seen as a key activity of the border.  Production Activities: The production of engines is the main activity of civil aerospace division, but also they need goods from the suppliers. For the procurement activity, the supplier selection and segmentation are the activities that can provide new suppliers to maintain this dynamic. The maintenance activity as the border needs the data and strategy from engine health monitoring.  Control Activities: Part of the control activities are the management of portfolio products, Inventory Management, Inventory Management for Aftermarket service parts and Production Management [START_REF] Tiwari | An Exploration of Supply Chain Management Practices in the Aerospace Industry and in Rolls-Royce[END_REF]. All processes of Rolls-Royce are controlled by the flow of cash and financial indicators [START_REF] Yusuf | Enterprise Information Systems Project Implementation: a Case Study of ERP in Rolls-Royce[END_REF]. Additionally, Rolls-Royce works with several quality standards such as six Sigma, robust design and optimization [START_REF] Foden | Technology Management At Rolls-Royce[END_REF] that measure the production activities.  Communication Activities: Communication activities can be seen as a part of production and controls activities. For example, production activities are connected with a central ERP system, which spread the current state of inventory [START_REF] Yusuf | Enterprise Information Systems Project Implementation: a Case Study of ERP in Rolls-Royce[END_REF].  Inner-Structure: The inner-structure of Rolls-Royce is the division of business units. There is a strong relationship among the production of engines and the maintenance or after service activities.  Meta-Norms: The meta-norms of the organisation can be seen in the strategy that is focused on the customers, innovation and growth [START_REF]Annual Report[END_REF]. An example of this application is the innovation, which is reflected in all activities like the collaborative product development. The autopoietic capabilities of Rolls-Royce are reflected from 1) their management of the suppliers, including the selection and segmentation of new suppliers, in order to maintain this dynamic; and 2) the application of meta-norms, like innovation, to govern their collaboration with the suppliers. Therefore, it is possible to find some behaviour of cells into organisations, and organisations with good practices like Rolls-Royce shows internal activities that maintain the border of the organisation.

Conclusion and Future Work

Autopoiesis can explain why living-things have responsiveness, and the definition of autopoiesis from the organisational semiotics can be useful to describe the elements of organisations that are essential in the maintenance of border through the change.

The definition of interfaces as the core activities that interchange matter and energy, the set of activities to control, communicate and produce the elements of the border can be seen as an approach to review and understand organisations, their elements and relationships that allow the adaptation. The role of signs is the understanding of organisations as autopoietic systems, which create signs, depending on the current sign structure. Under these conditions, the responsiveness of organisations can be improved with the analysis of the impact of signs and their changes between technical and formal layers, and also among the signs in the interfaces with other kinds of activities in the autopoietic model of organisation. The next stage of this work is the identification of the relationship among these components, and the application of these elements in the analysis of signs of organisations. One of the problems in the design of technical information systems and the analysis of the capability to change is how the connections in the formal layer can be reflected into the technical layer. It is accepted that technical information systems can promote the adaptation, which can be seen in the communication activities, but there are several technical solutions such as three layers architecture or service oriented architecture that promote the flexibility of technical IS, without considering the real capability of the organisation. This work is the first attempt of this understanding.

Table 1 .

 1 Relation between component and their classification

	Component Function	Kind of Component	Specification Relation
	DNA	Replication	Creational	Specification
	RNA	Message of protein synthesis	Creational	Specification
	Enzymes	Catalysis	Creational and	Specification
			Control	and Order
	Ribosome	Protein Synthesis (translation of RNA	Creational	Specification
		into protein)
	Membrane	Maintenance of cellular environment	Topological	Constitutive
	Cytoplasm	Provide a Solver System and help the	Topological	Constitutive
		movement of food

Acknowledgements. This research is partial supported by CONICYT (BCH72130542/2012).


Ni Yingzi
email: niyingzi@foxmail.com

Qin Zheng
email: qin.z@sustc.edu.cn

A Study on the Individualized Information Service Mode and its Application in the Manufacturing and Supply Chain

Keywords: Individualized information service, Supply chain, Key customer, Enterprise system

Customer, information and functions are in the same level in the traditional computer application systems, and all customers are treated by the same interface to implement the standardized service functions. However, in general, 80 % of the profits come from 20 % of the key customers. These key customers should deserve better services. Therefore, the enterprises have to response quickly to their needs of individualized information service. In this paper, a detailed case of individualized information service in the field of iron and steel manufacturing supply chain is introduced, and valuable content is extracted and pushed from mass data to constitute a business environment of information sharing that creates value for the customers. The individualized information push mode for the key customer is studied and a functional frame and an operating system for the information service system based on the workflow are introduced.

Introduction

In the era of knowledge-based economy, it is becoming ever-increasingly difficult for organizations to create and maintain their competitive advantage [START_REF] Zack | Developing a knowledge strategy[END_REF]. Certain knowledge owned by an organization forms its competitive advantage, and the lack of certain knowledge weakens this very organization. And usually, the lack of knowledge is caused by demand of knowledge and imbalance between demand and supply [START_REF] Fan | Enterprise Knowledge Management Strategy based on SWOT Analysis[END_REF]. Generally for a manufacturing enterprise, 80% of the profit is created by the key customers which are 20% of all customers. These strategic users should be granted outstanding service, but in most enterprise information systems, key customers and common customers are provided with the same information service, and the individualized information service demand from the key customers can hardly be satisfied rapidly. The reason is that customers, information and functions are in the same level in the traditional computer application systems, and all customers are treated by the same interface and standardized service functions [START_REF] Zhang | The Study on Information Service for Strategy Customer in B-B e-Business Model[END_REF]. This paper analyzes the features of collaborative operation of key customers, discusses the technical features and technical key points, and provides the functional framework of a collaborative business system for key customers and a collaborating case between an iron and steel enterprise and an automobile enterprise based on the collaborative business platform for key customers.

2

Background of Theories

About Information Push Service

Along with the advent of intelligent information era and ever-improving web data, "matching plus push" comes to replace "search", and is becoming the core of future information service. Information push technology is basically classified into two categories: automatic pulling technology and event-driven technology. In this regard, WU Jianxia 4 analyzes the application of information push technology in a library system while Tong-Seng [START_REF] Tong-Seng | Push selling-Multicast messages to wireless devices based on the publish / subscribe model[END_REF] carry out an analysis into push service delivery that is based upon wireless technology.

Based on previous studies, we come to notice two distinctive features: one is that one can draw advantages by combing push and pull technologies in order to achieve synergy of push and pull of information, and the other is that push technology augmented with artificial intelligence, which is signified by: Intelligent search agent technology, Automatic classification information processing technology and Intelligent information filtering technology. And particularly for the latter feature, those academic observations were applied into the study of Push technology.

About the Individualized Push System

The individualized information push system introduced by Zhang [START_REF] Zhang | Individualized Knowledge Push System based on Search Engine[END_REF] and Qiu [START_REF] Qiu | WEB-Based Knowledge Management and design of its software system structure[END_REF] consists of an intelligent and complicated decision making and reasoning feedback mechanism which is used to help the user fix the information so that the user can obtain the most updated information without visiting the fixed website repeatedly, and it has solved the defects in the search engine and retrieving tool by which usually excessive but not exact enough information can be found. By making the user the key focus and providing customized information push service to the user, this individualized information push system connects the user with more affinity and bridges the gap between the enterprise and the user, which is key to the improvement of user satisfaction [START_REF] Li | Study on Quality Assessment System of Client-focused Digital Information Push Service[END_REF].

The individualized information push system described by Chen et al. [START_REF] Wei | On Measuring Cloud-Based Push Services[END_REF] basically consists of six modules: data integration, data normalization treatment, information analysis, information matching, and user utilization evaluation.

About the Information Push Application

According to the related references about information push, the practice of information push in most Chinese and foreign enterprises is supported by the push technology and realized by the information push system. Based upon observations on the performance of data service of The Johns Hopkins University of the U.S. by SHEN and Virgil [START_REF] Shen | Developing Data Management Services at the Johns Hopkins University[END_REF], Davidson [11] analyzes data management programs that are currently carried out in the U.K., and concludes that the information push takes the dominant place in individualized libraries , but less so in the supply chain of the manufacturing industry.

Features of Collaborative Business for Key Customers

A strategic cooperating partnership is created by the enterprise with key customers to reduce the operation cost and improve the management efficiency, and a collaborative business platform is built for key customers with the electronic business technology. By the information exchange between strategic partners, barriers of information communication in the business flow are pushed down, the capability of rapid response is enhanced, the processing cycle of each business link is shortened, the management cost is reduced, the operating efficiency of the mutual supply chain is heightened, and the satisfaction degree of key customers is improved by the individualized and allaround customer service and business collaboration. The collaborative business of key customers is all-around and involved in many fields including research, development, distribution, manufacturing, material circulation, and service, e.g., 1. Highly effective product research and development: the enterprise studies the technology for using, and participates in the customer's research and development workflow so that the products can be matched with the device, design and production workflow in downstream enterprises to improve the "using quality" of products. 2. Dynamic plan collaboration: the customer's plan is also the enterprise's plan, by sharing the strategic customer's production plan and production achievement and creating a material demand computing model of the supply chain between the enterprise and the customer a reasonable and exact stock quantity for varies products can be obtained, the net demand for each type can be known, and a reliable basis for material purchase can be provided to key customers. 3. Convenient information tracing: the customer can inquire about the production progress, material circulation, quality information and settlement information of the contract related in the office via electronic business. Such transparent operating mode can standardize the internal management of the enterprise. 4. High quality after-sales service: in case of any product quality problem, the customer can trace all information from project establishing, processing, claiming for compensation, correcting and completing.

Individualized Information Service Mode

Main Features of Individualized Information Service

The individualized information service demand from key customers is presented on the individualized interface design, business collaboration and information push service.

1. Individualized operating interface: the computer interface design is individualized according to the business features of the key customer in consideration of the way orders are placed, operating time and interface distribution, etc. For example, Shanghai Baosteel has two key customers: Guangdong Galanz Group (the largest microwave oven manufacturer in China) and FAW (a large automobile manufacturer in China). As steel material ordered by Galanz is usually transported along the water way, Galanz may ask to select water way preferentially other than the railway on the ordering interface; but FAW usually asks to select railway transportation to Changchun Station. Furthermore, the interface distribution and menu settings are optimized, frequently used information can be searched by clicking a key once, the functional menu is arranged in a flow chart, and the correlation among all service functions can be known by the user conveniently. In all, the operating interface is simple and clear with minimal operating time and clicking times. 2. Individualized service information collaboration: a shared data collection interface is created for both cooperating parties, the product research, development and production plan and production achievement from both parties are acquired timely to organize business collaboration. For example, steel is researched and manufactured with the upgrading with car types in FAW. Once the demand for car model is fixed, a steel material certification plan with material type classified will be created in the system, the process design plan will be adjusted rapidly, and production will be spread effective to provide new steel material product for trial using. And meanwhile, shearing, punching and welding of steel in FAW can be traced by the system so that the product quality can be continuously improved before the whole car is certified. 3. Timely information push service: an individualized information space opened for each key customer all related information and functions are centralized as per the business flow, and the customized service is provided via the Internet (Web or special SLD). For example, if the globally most updated information about steel research and development is needed by Shanghai Volkswagen, information about new material and new technology released by major steel corporations and major steel magazines (e.g., Metal Abstract or Metal Engineer, etc) can be automatically searched before confirmed and pushed to the individualized information platform of Shanghai Volkswagen. Modern communication technology such as short messaging can be used by the system to inform the related person of processing the information at the first time when a demand (opinion or query) is delivered from the customer via the collaborating business platform automatically so that the time delay in information transmission and communication can be reduced and rapid response can be realized effectively.

Key Technology in Individualized Information Service

The front operating interface must be a customized system to satisfy the individualized information service demand from the key customers, but how to design the back-end application processing system? It will not be economical and cannot be managed effectively if a background system is independently customized for each key customer. In fact, the customers' demand for information can be satisfied by the current system data resources except there are some tiny differences in interface mode, arrangement, function and content. Therefore, it is necessary to create a uniform background information processing center by which information push service is provided, all customers' demands are further concluded into workflows and forms for format conversion, bill exchange and workflow control to realize the flexible system management.

1. Format conversion: automatic conversion between individualized bills and standard bills for each enterprise can be realized in the bill format conversion center so that each partner in the supply chain can only focus on his own related data content and format during the data interface development. 2. Bill exchange: when the address code to be delivered with the business data is given from the application system, the data can be transmitted to the system at the other end by the exchange center via the function of "address registering and automatic address searching", the difference in data integration is shielded, and the system expandability is improved effectively. 3. Workflow control: format bills are described by business bills and definitions so that they can be transferred among different partners and the business information can be transferred more timely, reliably and intelligently. The relationship of information transfer is maintained by the workflow control center to follow the change of business rules and information demands among enterprises.

5

Functional Frame of the Collaborative Service System for Key Customers

Core Functions of the Collaborative Service System for Key Customers

The collaborative service system for key customers is highly different from the traditional information system. The internal information is extended to the customer and supplier via an electronic business platform to promote the informationization of the whole supply chain, realize the information integration and share among enterprises, reduce the process management cost between the upstream and downstream units, and create value for all customers. Based on the original internal business system, three core application supporting systems including an electronic business system, a supply chain decision making and supporting system and a client service knowledge base system Electronic business systemcreate a bridge between the enterprise and the customer. An electronic business platform is created for the enterprise by the electronic business technology to realize the connection from the internal system of the enterprise to the customer. Firstly, products can be ordered via the Internet conveniently. Secondly, inquiring via the Internet can be realized, the contract with customer, production progress, material circulation and transportation, quality information and settlement information of the customer's contract can be inquired by the customer in his own office. Such transparent operating mode constitutes the supervision by the clients for internal employees and standardizes the internal management. For example, if the customer finds no production is timely arranged for this contract, he can urge the arrangement via the "Hotline for Customers" so that products can be delivered on time. Thirdly, once any dispute on product quality happens and a dispute on product quality is submitted by the customer, the whole course from dispute establishing, processing, claiming for compensation and correcting can be traced.

Supply chain decision making and supporting systemsupport rapid responses to the customer. An order from the customer usually involves small batches and many types which must be actualized in a short time but frequently changes. In the past, such demand was usually from the least customers, and it can be treated fully in a manual mode. But now, such demand becomes frequent for the enterprise. To solve the contradiction between "individualized customer's demand" and "scaled enterprise production", it is necessary to develop an enterprise information system for supply chain management. The enterprise will actively participate in the customer's organization's production, estimate the customer's demand exactly, create a B2B information connection, and use the model technology to optimize the own organization for production. Information technology is used to create a system collaboratively operated with the customer's business, the scale advantage of industrialized production can be realized by the enterprise, the customer's contract can be completed and all customers' demands can be satisfied in quality, quantity and time. A model for estimating the customer's demand is developed to analyze the integrated optimization of supply chain between the customer and manufacturer, for example, what material and when it will be used by the customer's production line, and how to ensure the supply for production before optimizing the stock structure timely, i.e.: the own sales plan is fixed according to the customer's production plan, once the customer's plan is modified, the steel sales plan will be adjusted correspondingly. A production model will be developed and optimized, the internal ordered production and optimized organization will be studied, the contradiction between the "individualized customer's demand" and the "scaled enterprise's production" will be solved to realize the large scale customization. The production for the contract will be reasonably arranged according to the customer's demand and the own production conditions by optimized computer tools to realize the dynamic response of the delivery period.

Customer service knowledge base systemintegrate the customer service information resources for knowledge sharing. To support the customer's query for ordering, the salesman has to know the product's sales history, price information, production capacity, quality assurance capacity, claim for compensation and customer's credit, etc. The information is controlled by the sales, manufacture, financial and other departments separately, the salesman in the past can only master the sales information and other information has to be replied by other departments in a long time and low efficiency. Information technology is used to integrate and share the information, a knowledge base is created for customer consultancy, any information can be inquired by the front sales and service men timely on line, the customer's demand for ordering can be replied at the first time, and thus rapid response and scientific decision making can be realized effectively.

Information Correlation between the Electronic Business Platform and the Internal Management System

The spatial and temporal distance between manufacturer and the customer is shortened by the application of the Internet and electronic business technology. The online marketing service provided by the electronic business platform for the enterprise has created an information bridge between the enterprise and the customer.

The electronic business platform is closely integrated with the integrated manufacture subsystem, data warehouse subsystem, rapid response subsystem and other special management subsystems in the enterprise to answer the customer's demand and share manufacture information with the customer. For example of steel products, the main information exchange is involved with: Sales management: customers can directly query for ordering and order on line, by the connection between the network and integrated manufacture subsystem, data warehouse subsystem and rapid response subsystem, the interaction between business and information can be realized effectively, and the management efficiencies for both parties can be improved.

Material circulation management: GPS/GPRS technology is used to position and trace the truck or ship, share the sales and material circulation information with the customer, and realize the informationized management for the transporters. The transferring speed of packet data, work instructions, coded bill information, transportation bill information and contract settlement speed are accelerated by the electronic transmission of bills based on the code bar technology of steel products.

Service management: the service system of the online marketing subsystem is functioning through the whole business flow before, during and after distribution, involved with production introduction, standard inquiry, contract trace, quality assurance inquiry, quality dispute, user's hotline, satisfaction degree investigation, and provides all-around service to the customer. In the collaborative business for key customers, the satisfaction degree of key customers is improved by the fully individualized and all-around service and business collaboration, a closer strategic partnership is created between the enterprise and the customer, and a powerful support is provided.Case of application

Collaborative Business between Baosteel and FAW-Volkswagen

Baosteel is one of the largest iron and steel group in China, and one of the major products is the cold rolled steel panel for automobiles. FAW-Volkswagen is a key customerof Baosteel, the automobile steel panels of Jetta, Bora and Audi, etc. are mainly from Baosteel, more than 6,000 tons of steel is supplied from Baosteel monthly.

In 2003, a strategic cooperation agreement was signed between Baosteel and FAW to create a collaborative business platform, to reduce the material circulation cost and improve management efficiency. The management of the steel sheet roll warehouse of FAW-Volkswagen is authorized to Baosteel. Therefore, the management of Baosteel is extended from the plant to the customer, the warehouse is created at the door to the customer, as shown in Fig. 1.

Fig. 1. Schematic drawing of business workflow between Baosteel and FAW-Volkswagen

A steel supply chain computing model is created between Baosteel and FAW-Volkswagen by the computer system, by sharing the car production plan and achievement with FAW-Volkswagen, the steel stock in the whole supply chain from Changchun to Shanghai can be dynamically balanced, the steel production plan can be adjusted timely, the contract actualization, manufacture, and finished product transportation in Baosteel can be reasonably arranged, and the demand for car production from FAW-Volkswagen can be satisfied. A "Just In Time" supply mode is realized to solve the trouble back at FAW-Volkswagen.

By the mutual effort, the steel stock in FAW-Volkswagen becomes more reasonable, the material purchase cycle is highly shortened, and the delivery accuracy is effectively improved. By the high efficiency supply chain management and informationized collaboration platform, the cooperation level between both parties is improved, and a promising benefit is brought to both parties. In this way, a stable and reliable strategic customer is obtained by Baosteel with value is created for the customer.

Production Plan Collaboration between Baosteel and FAW-Volkswagen

The core of production plan collaboration is a material demand management system for the supply chain, and the system is used to calculate the net demand (from FAW-Volkswagen). The core modules are supply chain material circulation information model, production demand calculation model and purchase demand calculation model, etc. All business links including car production plan, net material demand calculation, purchase plan confirmation, steel purchase contract generation, manufacture, contract trace, material circulation, transportation and product delivery are realized on the collaborative business platform for key customers between Baosteel and FAW-Volkswagen, and the effective contract data can be directly accepted by the internal business system of Baosteel.

1. The customer's stock information is integrated with the steel stock information of Baosteel production, delivery, and transportation, and a material circulation information model for the whole supply chain is created between Baosteel and FAW-Volkswagen. 2. A production demand calculation model is created according to the car production plan and fixed consumption of FAW-Volkswagen to obtain the corresponding steel demand via conversion. 3. A net demand for purchase is fixed by the purchase demand calculation model according to the safe stock days, railway transportation cycle and steel stock deducted, and finally a purchase plan is reviewed, approved and fixed. 4. The purchase plan is automatically converted into a steel ordering contract and transmitted into the internal business system of Baosteel via electronic processing. 5. The manufacture information and railway transportation achievement of Baosteel can be timely fed back to the collaborative business platform, and the stock structure of the whole supply chain can be dynamically traced by both parties.

Conclusion

The individuality of any customer is not specially treated in the traditional information system, the positions of key customers and ordinary customers are same and same functions are used in the system. Therefore the individualized customer's demand is restricted by the common system functions. Differentiated information service will become more and more popular with the improvement of customer's level. A customized and individualized information service system is created for FAW-Volkswagen by Baosteel based on the supply chain collaboration theory for business collaboration and information share. From the case of production and material circulation collaboration between Baosteel and FAW-Volkswagen, we find: the material demand calculation for the whole supply chain is more accurate than the independent MRP calculation in the enterprise because of the expansion of calculation range and the improvement of information transparency, and the customer's raw material stock becomes more reasonable. And meanwhile by the mutual all-around information collaboration, paperwork is greatly reduced, the production plan flexibility and response level are improved, and the operation is simplified effectively. Therefore, a larger value space is created for both parties by the individualized information service for key customers.


Marie Rastello
email: marie.rastello@ec-lyon.fr

Alexi Bouchet
email: alexi.bouchet@univ.u-3mrs.fr

Surface oscillations in channeled snow flows

Keywords: snow, channeled flows, surface oscillations, saint-venant equations

Surface oscillations in channeled snow flows.

Introduction

In the past, many models have been used to describe the behavior of dense snow avalanches [START_REF] Voellmy | ber die zerstrungskraft von lawinen[END_REF][START_REF] Perla | A two-parameter model of snow-avalanche motion[END_REF][START_REF] Dent | A biviscous modified bingham model of snow avalanche motion[END_REF][START_REF] Norem | A continuum model for calculating snow avalanche velocities[END_REF][START_REF] Savage | The motion of a finite mass of granular material down a rough incline[END_REF][START_REF] Naaim | Dry granular flows: erosion and deposition modelling[END_REF]. Since snow avalanches are very destructive and cannot be controlled, it is very difficult to fully test these models experimentally. Direct measurements on avalanches do exist [START_REF] Dent | Density, velocity and friction measurements in a dry-snow avalanche[END_REF] but are rare and must be completed by "laboratory experiments" to study the rheology of snow [START_REF] Nishimura | Contribution of viscous forces to avalanche dynamics[END_REF][START_REF] Casassa | Shear cell experiments of snow and ice friction[END_REF][START_REF] Kern | The rheology of snow in large chute flows[END_REF]. The main problem is that snow grains are very fragile. This brittleness makes it very difficult to use a large amount of snow in the laboratory. In consequence, as described in previous papers (Bouchet, 2003a;Bouchet et al., 2003b) we chose to work with an in situ rheometer, to use snow directly from the field. To stay as close as possible to naturally occurring flows in avalanches, we studied free surface snow flows in an inclined channel.

1 Experiments over a wide range of slopes and thicknesses were performed to measure velocity profiles and friction laws in the flow. Results are fully reported in [START_REF] Bouchet | Experimental study of dense snow avalanches: velocity profiles in quasi-permanent and fully developed flows[END_REF] and are briefly presented in section 2.2. One of the main purpose of the present article is to test the obtained snow flows with regards to a commonly used Saint-Venant model to see if the model can help in understanding and predicting the behavior of such flows.

As described later in the article the snow flow consists of a short first phase (2 to 3 seconds) of transient regime followed by a fully developed regime which lasts until the end of the experiment (around 30 seconds). The fully developed part of the flow is made on the one hand of a steady component non uniform in the streamwise direction but which tends to become uniform asymptotically (x-uniform asymptotic regime) as will be shown in the article. On the other hand, added to the steady component is a periodic one which will be studied in detail when looking to the surface oscillations that are present on top of the flow. The whole experimental and numerical results presented in the present paper are all focused on the fully developed regime leaving apart the transient one. The steady component of the fully developed flow is studied in detail in this article using the analytical and numerical results. As mentioned before, in all cases, oscillations on the surface of the flow were observed. The question of the origin of these oscillations has not been addressed up to now and is another main concern of this paper. Are they roll waves intrinsic to the flow like those observed in granular flows by [START_REF] Louge | On dense granular flows down flat frictionnal inclines[END_REF]? Are they engendered by the feeding system as direct observations suggest? Numerical simulations and analytic solutions are used to get a better understanding of the flow characteristics.

Section 2 briefly presents the experimental set-up and results. The simulation technique is presented in section 3; it is based on the resolution of the shallow water Saint-Venant equations. The behavior of the flow with increasing streamwise distance, and in particular the way it approaches the x-uniform, fully developed regime, is then studied numerically and analytically. An estimate of the distance needed to attain the asymptotic regime is derived. Section 4 concerns the study of the oscillations on the surface of the flow, and the validation of the model.

Experimental set-up and results

The experimental facility and results are summarized in Bouchet et al. (2003b[START_REF] Bouchet | Experimental study of dense snow avalanches: velocity profiles in quasi-permanent and fully developed flows[END_REF]. A more detailed technical description of the set-up, and complete results, can be found in Bouchet (2003a).

The experimental device

A photograph of the experimental apparatus is shown in figure 1. The device consists of a 10 m long, 20 cm wide, 20 cm high channel, fed with snow by an Archimedes's screw from a hopper at the top of the channel. The screw is driven by a thermo-hydraulic engine, so that its rotation speed f is constant during an experimental run. Such a system is able to produce fully developed flows with a typical duration of 30 seconds. The floor of the channel is covered with sandpaper to create a rough surface. The slope angle of the channel, θ, ranges from 27 o to 45 o , in steps of 2 o . A second adjustable parameter is the mean flow thickness (h) which is controlled by the value of the rotation speed f (f ranges from 0 rpm to 60 rpm). Twelve different flows were studied. Many types of snow can be found in the field. As a first study the repeatability of the experiments was privileged and thus flows were performed in the following conditions. In each case:

-to avoid snow melting the temperature of both snow and air was below -15 • C; -snow grains were small and rounded with diameters between 0.2 and 0.4 mm; -snow was sieved with a 3 cm mesh.

Figure 1: The experimental set-up is designed to perform free surface snow flows in a channel (length: 10 m, width: 20 cm, thickness: 20 cm). The coordinate system associated to describe the flows (see figure 4) is the following: the x axis is along the main direction of the channel, orientated downward; the z axis is perpendicular to the bottom of the channel, orientated towards the surface of the flow.

The velocity profile was measured 6 m downstream from the top, on one of the sidewalls. The flow thickness was measured at the same location (h L ) and also 1.5 m upstream (h L-1.5 ).

Velocities are deduced [START_REF] Dent | Density, velocity and friction measurements in a dry-snow avalanche[END_REF] from the delay between signals at two identical opto-electronic sensors, one 2 cm downstream from the other. Each of these sensors consists of a photo-transistor and an LED. The latter emits an IR light beam which is reflected by the snow and collected by the photo-transistor. The signal produced by the photo-transistor is thus characteristic of the snow pack flowing in front of the sensor. Because the distance d between the two sensors is small enough to avoid deformation of the snow pack, the signals are identical but delayed by an amount of time τ . A cross-correlation method enables measurement of τ , and hence to deduce the velocity v = d/τ .

The flow thickness measuring device (Leuze ODSM/V-5010-600-421) consists of an optical distance sensor positioned above the flow. It emits an IR light beam (a few degrees) which is reflected by the free surface of the flow and collected by a CCD sensor. The measured position of the reflected beam on the CCD sensor, is a function of the distance between the sensor and the surface. Knowing the distance between the sensor and the bottom of the flow allows the calculation of the flow thickness.

The main characteristics (slope angle, average thickness and frequency of the thickness oscillations) of the flows are listed in a Fourier transform of the signal received from the thickness's sensor.

Thickness oscillations, velocity profile and mean velocity

Initially the channel is empty. The beginning of the experiment consists of a transient phase, while the front of the flow goes throughout the channel. After this transient phase, as shown in figure 2, at any given location the flow thickness oscillates in time around a mean value < h x > defined as a time average (steady component of the flow). As also illustrated in figure 2, the variations of h L follows those of h l-1.5 with a constant delay τ : h L (t) ≈ h L-1.5 (t -τ ). It thus appears that the steady component of the flow is x-uniform at the location of the probes. The frequency of the thickness oscillations mentioned above is always close to the rotation speed of the screw, as illustrated by figure 3. Indeed, the rotation speed of the screw can be calculated The straight line is given by F = f . according to the formula: f = V -1 × Q with Q the flow rate (obtained from the velocity profile as described below) and V ≈ 0.14 m 3 (information given by the manufacturer). f is calculated with a 10% error.

Special attention was payed to side wall effects on the flow. First the existence of a transverse velocity gradient was qualitatively looked for. To that purpose the flow was filmed from above. The observation show a displacement of the snow as a block without slowdown toward the walls. More quantitatively [START_REF] Louge | On dense granular flows down flat frictionnal inclines[END_REF] measured velocity gradients in a granular channeled flow and obtained less than 10% in velocity between the center of the flow and the side walls. Because in the present case the material is cohesive the gradient should be even less than these 10%. Side walls could also be responsible for a global slowdown of the flow. [START_REF] Ericksson | Medens friktion mot sn och is (friction of runners of snow and ice). U. S. army snow ice and permafrost research establishment[END_REF] performed measurments of friction coefficients between snow and different materials. The friction coefficient between snow and plexiglas was measured to be around 0.05 which is ten times lower than the friction between snow and the sandpaper sticked on the bottom of the channel. Thus, it can be assumed that the effect on the mean velocity is negligible. From these two points, the flow can be considered as uniform in the direction perpendicular to the flow.

The mean velocity profile is written V (z), where z is the distance from the bottom of the channel. The results for the twelve different flows are all satisfyingly fitted by a linear profile [START_REF] Bouchet | Experimental study of dense snow avalanches: velocity profiles in quasi-permanent and fully developed flows[END_REF]):

V (z; θ, h) = V s + Γ 0 z (1)
where:

V s (θ) = V 0 [tan θ -tan θ 0 ] (2)
and

   V 0 = 9.1 m.s -1 tan θ 0 = 0.28 (θ 0 = 15.6 o ) Γ 0 = 12.5 s -1 (3)
Such a linear profile is not usual but has already been observed in some granular flows [START_REF] Douady | From a grain to avalanches: on the physics of granular surface flows[END_REF]Bonamy et al., 2002a). Bonamy et al. (2002b) explained this uniformity of the velocity gradient by the presence, in the flow, of aggregates of many different sizes without one typical scale. In the present flow, aggregates were also detected (Bouchet, 2003a). It should be mentioned that the behavior of the flow near the ground was not explored. Indeed, the first transducer is located more than ten to twenty particles diameters above the ground. Thus, it is here impossible to know if there is a basal sliding or a strong basal shear. The presence of the sandpaper on the bottom makes the second hypothesis the more believable. Nevertheless in the present article we are only interested in the averaged velocity over the flow thickness which is quite insensitive to this basal behavior. Moreover, during the numerical calculation the shape factor is taken equal to one (see section 3). The integral of equation ( 1) gives the averaged velocity over the flow thickness:

u (θ, h) = V s (θ) + 1 2 Γ 0 h (4)
or, using equation 2,

u = V 0 [tan θ -tan θ 0 ] + 1 2 Γ 0 h. ( 5
)

Friction law

Because the mean flow near the probes is fully developed and x-uniform, the friction force exerted by the channel on the flow balances the weight of the snow. The effective friction coefficient µ, defined as the ratio between the shear stress and the normal stress at the bottom of the channel, is thus equal to the tangent of the slope angle θ. Using equation ( 5), the friction law can be written as:

Ü Þ Ä « À Ü Ö Ø ÓÒ È Ü È Ü• Ü ´ µ Ö Ú ØÝ ´ µ
µ = µ 0 + u V 0 - h H 0 (6) with µ 0 = tan θ 0 = 0.28 H 0 = 2V 0 /Γ 0 = 1.45 m (7)
It must borne in mind that this friction law is here established for the particular dynamical conditions of a fully developed and x-uniform flow. Another point is that this friction law has been established in a given range of slope angles and flow thicknesses corresponding to those of the experiments and should not be extrapolated to some others too far as for example too large values of the thickness. The non-transient phase of the following simulations is performed close to this range of validity. The initial transient phase corresponds to small flow thicknesses. Thus, the friction law is supposed valid even during this phase in our simulations.

Study of the steady component of the flow

In this section we study in detail the behavior of the steady part of the fully developed flow. To that purpose we use the laterally unconfined Saint-Venant equations solving them first numerically and in a second time analytically.

The Saint-Venant equations

Originally used for hydraulic studies of shallow water flows, the Saint-Venant equations were first applied to granular flows by [START_REF] Savage | The motion of a finite mass of granular material down a rough incline[END_REF]. This approach is now commonly employed to model dense snow flows. The equations are derived by averaging the mass and momentum conservation equations over the flow thickness. Two assumptions are employed:

• the typical flow thickness is assumed to be small compared to the streamwise variations (short wavelength hypothesis);

• the flow density is taken as constant and uniform.

Hence, the dominant component of flow velocity, u, is parallel to the bottom of the channel. The flow is described by its thickness h(x, t) and average velocity u(x, t) = ( h 0 u(x, z, t)dz)/h. Mass and momentum equations for a thin slice can be written:

∂h ∂t + ∂hu ∂x = 0 (8) ∂hu ∂t + α ∂hu 2 ∂x = gh cos θ(tan θ -µ -k ∂h ∂x ) (9)
where

• α is the shape factor: α = h h 0 u 2 dz/ h 0 udz 2 ;
• k is the ratio between the normal stress parallel to the ground, σ xx , and the normal stress perpendicular to the ground, σ zz .

In what follows, the stress tensor is supposed to be isotropic and thus k is taken equal to one. In granular flows, the precise value of k does not appreciably affect the flow behavior. For commonly encountered velocity profiles (uniform, linear, parabolic), α takes values between 1 and 2. The flow is also insensitive to the precise value used for α; here we take α = 1. Finally friction law (6) is used.

Description of the numerical solution procedure and result

The 6-meter long channel upstream of the measuring device is discretized in x with points every five centimeters. The time step is dt = 5 × 10 -3 s, and we run the model for thirty seconds. The numerical scheme used is an explicit finite difference MacCormack scheme.

Both steady-inlet and initial conditions are needed for h and u. As regards the steady-inlet conditions (h(0), u(0)), once the flow becomes steady equation ( 8) implies a constant volume flux:

h(0)u(0) = h(L, t)u(L, t) = Q (10)
Experimental values of h L and u L (given by ( 5)) allow Q to be determined. h(0) is taken as an input parameter for the simulation and u(0) calculated using u(0) = Q/h(0). These constant values of h(0) and u(0), which apply strictly to the steady component of the flow, are imposed throughout the calculation. As can be observed in section (3.3) the value used for h(0) has no influence on the asymptotic flow of the end of the channel. The values used for θ and h L are the mean of those encountered during the experiments:

h L = 7.6 cm (11) and θ = 35 • (12)
When the model is run, an initial unsteady, non-uniform phase is observed, corresponding to the passage of the front along the channel (see figure 5). This phase is not discussed because the Saint-Venant equations cannot deal well with rapid changes in thickness and velocity. The only thing that can be noticed is that the passage of the transient phase lasts around 2 to 3 seconds both in the experiments and in the numerics. Once the front has passed, a fully developed steady regime is observed (see for example figure 6). Near the end of the channel the flow is found to be x-uniform. This is an important point for the exploitation of the experimental results in general and of the friction law in particular. This regime is examined in more detail in the following section. Just for information, the initial values are h(x > 0, t = 0) = 1 cm and u(x > 0, t) = 0. The non-zero value of h was introduced to avoid a division by zero. We choose these values for the sake of simplicity and because the fully developed flow (the one which is relevant to study here) is not sensitive to them.

Analytical study of the steady component of the flow

In this section, we solve analytically the Saint-Venant equation for the steady component of the flow. This enables us to quantify when the asymptotic x-uniform regime is reached. For steady flows, the Saint-Venant equations (equations ( 8) and ( 9)) take the form:

uh = Q (13) α dhu 2 dx = gh cos θ(tan θ -µ 0 - u V 0 + h H 0 -k dh dx ) (14)

Values of the x-uniform asymptotic regime

Let h ∞ and u ∞ be the flow thickness and flow velocity when the x-uniform, asymptotic regime is reached. From equations ( 13) and ( 14), h ∞ and u ∞ are given by:

   h ∞ u ∞ = Q µ 0 + u ∞ V 0 - h ∞ H 0 = tan θ (15)
This system admits only one set of positive solutions:

         h ∞ = H 0 (tan θ -µ 0 ) 2 -1 + √ 1 + ε u ∞ = V 0 (tan θ -µ 0 ) 2 1 + √ 1 + ε (16)
where

ε = 4Q V 0 H 0 (tan θ -µ 0 ) 2 (17)

Distance needed to reach the x-uniform asymptotic regime

We next study the development of the flow with streamwise distance x. To that purpose we integrate the differential equations ( 13) and ( 14) analytically using the following reduced variables

: h = (h -h ∞ )/h ∞ , ũ = (u -u ∞ )/u ∞ , with x = (x + x 0 )/h ∞ with x 0 a constant value.
Details can be found in appendix 1. The integration leads to ln h

k-αF r 2 h + 1 αF r 2 (1-1/β 2 ) h + 1 + β kβ+αF r 2 /β 2 -αF r 2 1 + β β 1 h + 1 = (1 + β) h ∞ H 0 x (18) with                              h ∞ = H 0 (tan θ -µ 0 ) 2 -1 + √ 1 + ε u ∞ = V 0 (tan θ -µ 0 ) 2 1 + √ 1 + ε ε = 4Q V 0 H 0 (tan θ -µ 0 ) 2 F r 2 = u 2 ∞ gh ∞ cos θ β = u ∞ H 0 h ∞ V 0 = 1 + √ 1 + ε 2 ε (19)
and

x 0 = H 0 1 + β ×(ln[| h(0)| k-αF r 2 | h(0)+1| αF r 2 (1-1/β 2 ) | h(0)+1+β| kβ+αF r 2 /β 2 ]- αF r 2 (1 + β) β( h(0) + 1) ) (20)
Using equation ( 18) we plot h as a function of x in figure 7. The entire curve has three branches.

Because the thickness of the flow is limited by the vertical size of the channel (h < 20 cm) and because the flow thickness decreases experimentally throughout the flow we only keep the part of the curve which fits these conditions. Looking at the curve, one can see that when x becomes large enough, the flow reaches asymptotically its x-uniform state. This confirms what the numerics seem to predict. The question is now to know whether the asymptotic x-uniform regime is reached before the end of the channel. To that purpose we simplify equation ( 18) for the case of large x. It can be rewritten in: The typical length scale is then:

h = (1 + β) -(kβ+ αF r 2 β ) exp - (1 + β)h ∞ H 0 (αF r 2 -k) x (21)
L = H 0 (αF r 2 -k) (1 + β) = 4 m (22)
when taking the experimental value Q = 0.32 m 2 .s -1 . It is therefore relevant to consider the flow as x-uniform at the location of the measuring device, 6 m downstream from the top of the channel.

Origin of the oscillations -validation of the model

In this section we show that the model gives an explanation about the origin of the oscillations observed in the experiments.

Frequency of the oscillations

The oscillations induced by the screw which feeds snow into the channel are modeled by the boundary condition h(0, t) = h 0 + h 1 cos(ωt) with f = ω/2π the frequency of the screw. To study what happens at the end of the channel we use the following scheme:

• First, the model is run for 5 seconds with h(0, t) = h 0 + h 1 cos ωt to allow time for the initial transient phase to have finished.

• After these 5 seconds the model is run for a further 30 seconds and the temporal Fourier transform of h(L, t) is taken.

An example of the results is shown in figure 8, which also gives the result for h(0, t). In addition to the fundamental frequency f and the zero frequency peak representing the mean value, the harmonics 2f , 3f , ... are also present in h(L, t) due to nonlinearity of equations ( 8) and ( 9). The amplitude of these frequency components is always less than 10% of the amplitude of the fundamental peak.

Comparison between model and experiments

The Fourier transform of h(L, t) in the experiments also shows the presence of the frequencies 2f , 3f ... (cf figure (9)). However, the ratio of the amplitude of these secondary peaks to that of the fundamental differs in the model and in the experiments. In both cases (numerical and experimental) the secondary peaks are weak and can thus be neglected.

Let us now compare the ratio of the amplitude of the fundamental peak to that at zero frequency. This ratio is plotted in figure 10. With h 0 = 15 cm and h 1 = 4 cm the model gives good results compared with the experimental values. The curves given by the extreme values of the parameters are also plotted on figure 10 (h 0 = 12 cm, h 1 = 6 cm (eg) h 0 /h 1 = 2 and h 0 = 16 cm, h 1 = 2 cm (eg) h 0 /h 1 = 8). By "extreme values" we mean the larger or smaller values of the parameters the experimental observations allow to use. When plotting the curves what appears to be important is not the values of h 0 and h 1 separately but the ratio h 0 /h 1 . Indeed, with the same ratio, two sets of values (h 0a , h 1a ), (h 0b , h 1b ) give merely the same curves. This is the reason why we have plotted only two "extreme" cases. One can see that if the experimental values are close to the predictive curve they are also all included in the space between the two extreme curves. This allows for different conclusions. The majority of points (those that are close to the predictive curve) show that the model well predicts the behavior of the flow. The model is run in each case with fixed parameters (θ = 35 • , h L = 7.6 cm). These values are the mean of the 11 first experimental values (see table 1), the twelfth amplitude was not usable. Hence it seems reasonable that some of the points are not strictly close to the predictive curve. Nevertheless they are still between the extreme curves. All of this confirm the hypothesis that the model well predicts the phenomenon and the flow and that the oscillations are due to the screw.

Conclusion

The dense snow flows studied during the experiments exhibit thickness's oscillations. Though experimental facts suggest that they are generated by the feeding system of the set-up, the origin of these oscillations remain a priori uncertain. The friction law for dense snow flows deduced from the experiments is used in numerical resolutions of Saint-Venant's equations. The initial conditions given to the thickness at the entrance of the channel consist in sinusoidal oscillations with an amplitude h 1 , around a mean value h 0 . The simulations performed lead to the following results:

• the mean flow is x-uniform at the location of the measuring device. This is a crucial point for the validation of the results of the experiments in which the hypothesis of x-uniformity was the central hypothesis;

• the oscillations engendered at the channel's entrance propagate and are still present with the same frequency (harmonics can be neglected) at the measurements' position;

• numerical and experimental results are in a good agreement when using an oscillation ratio h 1 /h 0 = 4/15. From direct observations, this ratio seems very reasonable;

• the relative intensity of these oscillations (given by the FFT of h(x, t)) reduces from about 15 % at the top of the channel to approximatively 5 % to 10 % at the studied position.

Appendix 1

Using the mass conservation equation (equation ( 13)), equation ( 14) can be rewritten in:

d dx αQu + kg cos θ 2 h 2 = gh cos θ tan θ -µ 0 - u V 0 + h H 0 (23)
Let δu and δh be the deviations from the x-uniform regime:

u = u ∞ + δu h = h ∞ + δh (24)
Equation ( 23) becomes:

d dx αQδu + kg cos θ 2 2h ∞ δh + δh 2 = g(h ∞ + δh) cos θ δh H 0 - δu V 0 (25)
We now turn all lengths and velocities without dimension by dividing them respectively by h ∞ and by u ∞ and define:

   x = x/h ∞ h = (h -h ∞ )/h ∞ ũ = (u -u ∞ )/u ∞ (26)
Mass conservation (equation ( 13)) implies:

hũ + h + ũ = 0 (27)
At this stage let's notice that if h tends to zero, because of equation ( 27), ũ also tends to zero (consequence of mass conservation) (eg) the x-uniform regime is reached. Hence in what follows we focus our study on h. For its part, equation ( 25) becomes:

d dx αF r 2 ũ + k h + 1 2 k h2 = (1 + h)( h ∞ H 0 h - u ∞ V 0 ũ) ( 28
)
with F r the Froude number of the x-uniform regime:

F r = u ∞ √ gh ∞ cos θ (29)
Substituting, in equation ( 28), ũ by its expression obtained from equation ( 27) and introducing the parameter β = u ∞ H 0 /(h ∞ V 0 ), gives:

d dx k h + k 2 h2 -αF r 2 h h + 1 = h ∞ H 0 h h + 1 + β ( 30
)
which can be rewritten in:

k h + 1 h( h + 1 + β) -αF r 2 1 h( h + 1 + β)( h + 1) 2 d h = h ∞ H 0 dx (31)
A straightforward integration of equation ( 31) leads to: ln h k-αF r 2 h + 1 αF r 2 (1-1/β 2 ) h + 1 + β kβ+αF r 2 /β 2 -αF r 2 1 + β β

1 h + 1 = (1 + β) h ∞ H 0 x + cst (32) with                              h ∞ = H 0 (tan θ -µ 0 ) 2 -1 + √ 1 + ε u ∞ = V 0 (tan θ -µ 0 ) 2 1 + √ 1 + ε ε = 4Q V 0 H 0 (tan θ -µ 0 ) 2 F r 2 = u 2 ∞ gh ∞ cos θ β = u ∞ H 0 h ∞ V 0 = 1 + √ 1 + ε 2 ε (33)

Figure 2 :FFigure 3 :

 23 Figure 2: Example of thickness variations. h L (full line) is measured 1,5 m downstream from h L-1.5 (dashed line). The figure corresponds to a laps of 10 seconds taken from a flow lasting approximately 30 seconds.

Figure 4 :

 4 Figure 4: Sketch of the flow and of the applied forces.

Figure 5 :

 5 Figure 5: Saint-Venant model's results using h 0 = 15 cm. thickness h (in m), velocity u/10 (in m/s) and flow rate uh (in m 2 /s) are plotted versus position x. These results concern the beginning of the flow when the front is crossing the channel before the establishment of the fully developed regime. (a): t = 0.5 s, (b): t = 1 s, (c): t = 1.5 s.

Figure 6 :

 6 Figure6: Saint-Venant model's results using h 0 = 15 cm, thickness h (in m), velocity u/10 (in m/s) and flow rate uh (in m 2 /s) are plotted versus position x(m). These results are obtained in the fully developed regime.

Figure 7 :

 7 Figure 7: Plot of the relative deviation of the flow thickness h as a function of the relative distance x.

Figure 8 :

 8 Figure 8: Fourier-transform amplitude of the thickness of the flow obtained by the Saint-Venant model. ---Fourier-transform amplitude of h(0, t), -----------------Fourier-transform amplitude of h(L, t).

Figure 9 :

 9 Figure 9: Fourier-transform amplitude of h(L, t) with h(L, t) measured during one experiment.

Figure 10 :

 10 Figure 10: Ratio between the amplitude of the fundamental peak and the amplitude of the peak at zero frequency versus frequency. * results from experiments, -----------------results of the Saint-Venant model with h 0 = 15 cm and h 1 = 4 cm, • • • • • • results of the Saint-Venant model with h 0 = 12 cm and h 1 = 6 cm, ---results of the Saint-Venant model with h 0 = 16 cm and h 1 = 2 cm.

table 1 .

 1 The frequency F of the oscillations was obtained by

	slope angle	average value of	F: frequency of the
	(degrees)	the thickness h L (cm) thickness oscillations (Hz)
	31	8.5	0.50
	31	7.3	0.39
	33	7.4	0.44
	33	8.35	0.48
	35	8.25	0.55
	35	7.6	0.50
	37	8	0.68
	37	9.55	0.84
	39	6.25	0.42
	39	6.05	0.38
	39	6.8	0.50
	39	9.35	0.68

Table 1 :

 1 Slope angle, average thickness and frequency of the thickness oscillations for each analyzed flow.

The results presented in this paper agree with the experimental observations. They suggest that:

1. in the experiments, the mean value of the thickness of the flow at the entrance of the channel can be changed as wanted without affecting the x-uniformity of the flow at the end of the channel and thus the validity of the measurements;

2. reasonable oscillations generated by the feeding system can propagate all along the channel and have the same intensity as the one observed in the experimental results;

The present study reveals that, as many other flows, such channeled flows of dry snow can be described using a Saint-Venant like model. Such numerical studies can help in the future in preparing other configurations of the device to test other caracteristics of those channeled snow flows and thus rheology of snow.

A. Bouchet thanks the Cemagref for providing a major financial support to his phd-thesis. The authors thank the ETNA research unit for supplying the experimental device. Special thanks are due to Mohamed Naaim for the idea of the experiment and for the money to realize it. This work was partially supported by an "ACI Risques Naturels" grant and by two grants of the "Pôle Grenoblois sur les Risques Naturels". Jean-Louis Marié is thanked for his advices during the improvement of the manuscript, and many thanks are due to Professor Julian Scott for the improvement of the english wording and of the article in general.


Xu Jing
email: 13491299@qq.com

Research on Association Rules Reasoning and Application of Geosciences Data Based on Ameliorated Trapezoidal Cloud Transformation

Keywords: Trapezoidal Cloud, MLAR algorithm, Chengdu Office

 is also adopted to reason and predict unknown faults and fault properties in Chengdu Office zone. The result shows that the MLAR algorithm enhanced an association mining between fault types with their classified attributes.

Introduction

As a series of systems deep geochemical exploration, space remote sensing and geodetic survey, were established and improved. Vast amounts of data have been gradually accumulated in the area of earth science, and these data need to be made use of by scientists. Association rules is a data mining method. It was first put forward by Agrawal [START_REF] Agarwal | Mining Association Rules Between Sets of Items in Large Databases[END_REF] in 1993. Now it has become one of the most widely used algorithms in the field of data mining. Li [START_REF] Li | Cloud model and cloud model generator[END_REF] has proposed a new method for conversion-cloud information instead of "hard" division which divides a cloud environment into several quantitative concepts based on cloud model considering fully fuzziness and randomness of data. Subsequently, the cloud conversion has been used in many fields. Hu [START_REF] Hu | Mining weights of land evaluation factors based on cloud model and correlation analysis[END_REF] proposes a new way of figuring out the weight of land evaluation factors by mapping qualitative linguistic words into a fine-changeable cloud drops and translating the uncertain factor conditions into quantitative values with the uncertain illation based on cloud model. Yu [START_REF] Fang | The Economic Evaluation of the Wind Power Projects Based on the Cloud Model[END_REF] attempts to evaluate the economics of wind power projects based on the cloud model. Han [START_REF] Han | Research on Multi-Level Association Rules Based on Geosciences Data[END_REF] imports the conceptual partition algorithm based on cloud model to finish the exchange from qualification to quantification. Expectation of some concept is not just a numeric value but in a sequence, so trapezoidal cloud makes description more accord with contiguous data. Wang [START_REF] Wang | Application of Cloud Theory in Association Rules[END_REF] uses trapezoidal cloud model to advance the concepts of division, and transforms qualitative data in to quantitative conception which is proved to be effective. Complexity of geosciences data behaves as not only fuzziness and uncertainty but also large amount in quantities and global continuity.

In this paper, a traditional trapezoidal cloud transformation is described in order to avoid a lack of information about data mutation and to carry out a reasonable and sensitive exchange from qualification to quantification.

Construction of Association Rules Mining Model Based on Ameliorated Trapezoidal Cloud Transformation 2.1 Concept Partition Algorithm Based on Ameliorated Trapezoidal Cloud Transformation

According to the basic idea of data fitting and a certain rule [START_REF] Han | Research on Multi-Level Association Rules Based on Geosciences Data[END_REF], spatial data of any irregular distribution are mathematically transformed so as to generate a set of atomic concepts and make the distributed spatial data become the superposition of several concept of different size, the basic idea is expressed in Eq. ( 1).

(

) 1
Geosciences data bears global continuity. As the concept is described, its expectation is not just a numeric value but in a sequence, so trapezoidal cloud makes description more accord with the features of geoscience data. In this paper, trapezoidal cloud is adopted to assist concept division, i.e., dividing a concept into atomic concepts in a number field. Fig. 1 shows the structure of trapezoidal cloud.

Fig. 1. Diagram of structure of trapezoidal cloud

The function is used to search for entropy and hyper entropy of cloud droplets. The idea of backward cloud generator [START_REF] Li | Cloud model and cloud model generator[END_REF] is applied during the search.

Association Rules Mining Algorithm Based on Multi-Level Association Rules Algorithm (MLAR)

Association rules is an important branch in the research area of data mining. It is aimed at mining correlations hidden behind massive data. As a large amount of data is collected and stored, it is increasingly demanded by scientists to discover knowledge from the data.

Prediction Model of Fault Property in Chengdu Office Area

In this paper, we will take Chengdu Office area (28°~32° E, 102°~108° N) as research zone to determine and predict nature, position and scale of simulated faults by the model of multilevel association rules algorithm based on improved trapezium-cloud model according the geophysical information 1:1,000,000 geologic map of this area conveys.

Data Preparation and Attribute Extraction Simulation

In this paper, we take fault in Chengdu Office area (28°~32° E, 102°~108° N) as the research subject in processing known fault data. Fig. 2 presents the spatial data this work used.

Fig. 2. Satellite image of known faults in Chengdu Office zone

Current findings in the field of earth science are built on the fusion of previous space data. According to prior knowledge of experts, subjective judgments on new knowledge are made by using visual interpretation, field measurements and other methods. Rare automated discoveries on new knowledge of earth science are achieved by the degree of inference through association rules, the methods previous adopted are difficult and inefficient.

Prediction of Faults Property in Chengdu Office Area Based on Ameliorated Trapezoidal Cloud Transformation

According to the data distribution curve of attributes of known and simulated faults (the blue curve in the Fig. 3), the threshold value of error is set at 0.5.It is defined as the input item, when the respective discretization of the number attribute of the 32 attributes in the table is implemented. After that, the trapezium-cloud concept of every attribute is built.

Fig. 3. Line graph of normal distribution fitting data distribution

Result Validation

In order to judge the quality of association rules, we introduced the scoring mechanism [START_REF] Han | Research on Multi-Level Association Rules Based on Geosciences Data[END_REF]: Score = 40%*support + 60%*confidence and the higher score the better quality on simulated faults. Table 1 presents the top 12 association rules used for the experiment on disposal of simulated faults. It is important to note that unclassified faults mean that they do not conform to any one of the 12 association rules above. The superposition of the part verified by the simulated faults and the satellite image of this area is shown in Fig. 4.

Conclusion

This paper proposed the association rules reasoning model based on ameliorated trapezoidal cloud transformation, which is aimed primarily at complexity and randomness geosciences data bears. The traditional trapezoidal cloud transformation is improved in order to avoid lack of data mutation information and to finish reasonable and sensitive exchange from qualification to quantification. The attributes of simulated faults extraction algorithm was designed to overcome the limitations of traditional visual interpretation to ensure the effectiveness and completeness of the test data. MLAR model was adopted to reason and predict the unknown faults and fault property in Chengdu office zone. The result supports the judgements other academics made for the faults and their attributes in probability perspective, further explains it acts better in association mining between fault types and its attribute data automatically, through which the model's reliability has been testified.

Fig. 4 .

 4 Fig. 4. Satellite image of simulated faults verified

Table 1 .

 1 Association rules

	No	Succeeding item	Antecedent item	Support (%)	Confidence (%)	Score
	1	ATTR =F	STDMAG_3 =8 2 3 and AVGMAG0_2 = 5 3*	31.645	95.82	70.15
			AVGDEM_3=5 2 1 and
	2	ATTR =F	AVGMAG_2=2 9 3 and	27.34	97.89	69.67
			AVGGRA_3=6 3*
	3	ATTR = C	AVGGRA_3 = 10 1 3 and STD_GRA0_3 = 21 1 2	26.09	98.54	69.56
	4	ATTR =C	AVGMAG0_2 = 5 1* and AVG_GRA45_2 = 12 3*	29.195	94.62	68.45
	5	ATTR =D	AVGDEM_3 = 3 1 3 and AVGGRA45_2 = 21 3*	24.01	97.31	67.99
	6	ATTR = F	STDDEM_3 = 4 1 3 and AVGGRA45_3 = 15 1 6	28.11	93.81	67.53
	7	ATTR = A	AVRGRA_3=10 1 3 and AVG_MAG0_2=6 1*	35.87	88.12	67.22
	8	ATTR = E	AVRGRA_3=10 1 3 and AVG_MAG=6 3* and	26.35	92.75	66.19

Table 2

 2 shows the simulation results. When the length of 40 steps (about 60 kilometers) is chose as a parameter, 42444 simulated faults in each angel were covered. After successive adjustments, it is inferred that 2305 faults are in a north-east direction(35-50°)and most of them are in 40°; 295 faults are in north-south direction; 354 faults are in a north-west direction (270°-360°).

Table 2 .

 2 Fracture property and direction proportion

	Fracture	Direction	Fracture property	Property
	direction	proportion		proportion
	NE trend	78%	general fault	32.46%
	(30°-50°)		klippe	1.36%
			thrusting-nappe fault	42.16%
			transpressional fault	17%
			general reverse fault	7.48%
	NS trend	10%	general fault	59.32%
	(0°)		transpressional fault	40.68%
	NW trend	12%	thrusting -nappe fault 14.29%
	(270°-360°)		general fault	85.71%

Acknowledgments. Our appreciation goes to Qin Zheng, Wen Wang, Dongmei Han for their valuable comments to improve the quality of the paper.