Gauthier Quesnel

The Virtual Laboratory Environment - An operational framework for multi-modelling, simulation and analysis of complex dynamical systems

The cross-disciplinary activity of modelling and simulation is the core of the scientific activities addressing the complexity of nature. In this context, we need reliable computational environments to integrate heterogeneous representations coming from different scientific fields. Therefore, such environments must be able to integrate heterogeneous formalisms in the same model and assist the modeller for the design and implementation of models, the definition of the experimental frames and the analysis of simulation results. The aim of this article is to introduce a tool supporting all these features, the Virtual Laboratory Environment (VLE). VLE is a software and an API which supports multi-modelling, simulation and analysis. It addresses the reliability issue by using recent developments in the theory of modelling and simulation proposed by Zeigler. We present VLE in the context of the modelling and simulation cycle and show the effectiveness of the tool with a multimodel of fireman fighting a fire spread.

An open platform to build, evaluate and simulate integrated models of farming and agro-ecosystems

Due to significant changes in agro-ecological contexts, farmers need new solutions to produce goods. Modelling complements field experiments in the design of new farming systems. French researchers involved in such design issues developed a specific modelling platform to help model, simulate and evaluate cropping systems. After testing several existing environments, the RECORD platform was developed under the VLE environment, allowing the design of atomic and coupled models. It integrates different time steps and spatial scales and proposes some standard formalisms used to model agro-ecosystems (e.g. difference equations, differential equations, state charts...). A graphic user interface was designed to simplify coding tasks. A variety of research projects already use this platform. Examples are given showing the ability to recode simple models, encapsulate more complex models, link with GIS and databases, and use the R statistical package to run models and analyse simulation outputs. The option to use web interfaces enables application by non-scientist end-users. As the models follow a given standard, they can be placed in a repository and used by other researchers. Linking RECORD to other international platforms is now a compelling issue.

A Generic Model to Simulate Air-Borne Diseases as a Function of Crop Architecture

In a context of pesticide use reduction, alternatives to chemical-based crop protection strategies are needed to control diseases. Crop and plant architectures can be viewed as levers to control disease outbreaks by affecting microclimate within the canopy or pathogen transmission between plants. Modeling and simulation is a key approach to help analyze the behaviour of such systems where direct observations are difficult and tedious. Modeling permits the joining of concepts from ecophysiology and epidemiology to define structures and functions generic enough to describe a wide range of epidemiological dynamics. Additionally, this conception should minimize computing time by both limiting the complexity and setting an efficient software implementation. In this paper, our aim was to present a model that suited these constraints so it could first be used as a research and teaching tool to promote discussions about epidemic management in cropping systems. The system was modelled as a combination of individual hosts (population of plants or organs) and infectious agents (pathogens) whose contacts are restricted through a network of connections. The system dynamics were described at an individual scale. Additional attention was given to the identification of generic properties of host-pathogen systems to widen the models applicability domain. Two specific pathosystems with contrasted crop architectures were considered: ascochyta blight on pea (homogeneously layered canopy) and potato late blight (lattice of individualized plants). The model behavior was assessed by simulation and sensitivity analysis and these results were discussed against the model ability to discriminate between the defined types of epidemics. Crop traits related to disease avoidance resulting in a low exposure, a slow dispersal or a de-synchronization of plant and pathogen cycles were shown to strongly impact the disease severity at the crop scale.

A new plug-in under RECORD to link biophysical and decision models for crop management

Developing sustainable crop systems is a major challenge. Presently, management practices are simulated using either biophysical models or simple farmer decision models. As a result, there is a lack of generic models integrating both biophysical parameters and farmer decision parameters. Here, we developed an original graphical plug-in to sketch and implement decision-making models and to link them with biophysical models. For that, we used the RECORD platform, standing for REnovation and COORDination of agro-ecosystem modeling. Different pop-up windows allow to create the model using a decision formalism then to implement the model under the RECORD platform. The sequence of technical operations is formally modeled as a direct multi-graph without retroaction. The plug-in allows defining activities, relation between activities, and decision rules to trigger the different activities. The resulting model is independent of any biophysical model and can then be linked with different crop models. An example is given on an innovative cropping systems part of the MicMac-Design project. The decision-making model is then linked with the STICS crop model.

A Package System for Maintaining Large Model Distributions in VLE Software

The Modeling and Simulation (M&S) is becoming a central activity in order to build, study and analyze new systems. To improve activities of M&S, we need to develop collaborative technologies. In this context, we develop the application software Virtual Laboratory Environment (VLE) to model, simulate and analyze dynamic systems. VLE is based on the Discrete Event System specification (DEVS) formalism, a widely recognized specification for modeling and simulating discrete events systems. The main features of the DEVS formalism are a modular and hierarchical approach of the M&S and a relative simplicity to develop the simulation algorithms. Researchers and engineers from different communities used VLE to develop and study models. However, the modelers need to share source code in order to reuse, couple and combine models. It is not sufficient because they are not helped for maintenance and version upgrades issues. In this paper we present a package system manager that greatly helps modelers to publish source code, binary code, exchange models, data and software application in VLE.

Optimization of Parallel-DEVS Simulations with Partitioning Techniques

With the emergence of parallel computational infrastructures at low cost, reducing simulation time becomes again an issue of the research community in modeling and simulation. This paper presents an approach to improve time of discrete event simulations. For that, the Parallel Discrete EVent System formalism is coupled to a partitioning method in order to parallelize the graph of models. We will present the graph partitioning method to realize this cutting and quantify the resulting time savings of parallel implementation. This article highlights the importance of considering the dynamic of the model when partitioning to improve performances. Many tests are performed from graphs with different sizes and shapes on several hardware architectures.

Decision in agroecosystems advanced modelling techniques studying global changes in environmental sciences

Abstract In recent years, the sustainable management of agricultural and ecological systems has become a major challenge. Sustainable management has to solve crucial environmental problems linked, in part, to rapid changes in context: climatic changes, agricultural policy objectives changes, and so on. Solving this challenge involves the joint development of research in modelling, simulation, and virtual experimentation. In this chapter, we present some recent work devoted to the modelling and simulation of complex systems involved in agroecosystem management. Then, we present new formalisms for management strategies design, based on the weighted constraint satisfaction problems or the Markov decision processes frameworks. We also show how simulation and conception of strategies can be integrated. Finally, we illustrate the use of the presented approaches on several case studies in agroecosystems management, jointly tackled with research teams in agronomy.