Analysis and comparison of a hydraulic and pneumatic system using the Dymola software

This work addresses the modelling of a system using Modelica language and the Dymola software tool. Dymola is a modelling and simulation environment that uses the open Modelica language to map hardware components of physical systems directly into software components. Therefore, this modelling language allows the user to model a system in a physical form, rather than a mathematical fashion, through the use of general equations, objects, and links. This paper as an informative character about a tool for the development of mechatronic systems. The topics covered here are part of a more extensive modelling and simulation work on the dynamics of mechanical systems, within the scope of an Integrated Master in Mechanical Engineering. This study was carried out based on the comparison between pneumatic and hydraulic models of the same system. Therefore, it was modeled a system used in backhoe loaders that can be operated either using a hydraulic or a pneumatic cylinder. The activity focuses, essentially, on the analysis of parameters that describe the behaviour of the system, emphasizing the position, velocity, acceleration and loads observed in both cylinders. The goal is to introduce the reader to the Dymola environment and Modelica language by addressing the modelling of a system. This study also pretends to identify significant differences regarding the behaviour performance of the pneumatic and hydraulic approaches to model the selected system, and the causes that lead to such differences.(undefined)info:eu-repo/semantics/publishedVersio

RuleMonkey: software for stochastic simulation of rule-based models

<p>Abstract</p> <p>Background</p> <p>The system-level dynamics of many molecular interactions, particularly protein-protein interactions, can be conveniently represented using reaction rules, which can be specified using model-specification languages, such as the BioNetGen language (BNGL). A set of rules implicitly defines a (bio)chemical reaction network. The reaction network implied by a set of rules is often very large, and as a result, generation of the network implied by rules tends to be computationally expensive. Moreover, the cost of many commonly used methods for simulating network dynamics is a function of network size. Together these factors have limited application of the rule-based modeling approach. Recently, several methods for simulating rule-based models have been developed that avoid the expensive step of network generation. The cost of these "network-free" simulation methods is independent of the number of reactions implied by rules. Software implementing such methods is now needed for the simulation and analysis of rule-based models of biochemical systems.</p> <p>Results</p> <p>Here, we present a software tool called RuleMonkey, which implements a network-free method for simulation of rule-based models that is similar to Gillespie's method. The method is suitable for rule-based models that can be encoded in BNGL, including models with rules that have global application conditions, such as rules for intramolecular association reactions. In addition, the method is rejection free, unlike other network-free methods that introduce null events, i.e., steps in the simulation procedure that do not change the state of the reaction system being simulated. We verify that RuleMonkey produces correct simulation results, and we compare its performance against DYNSTOC, another BNGL-compliant tool for network-free simulation of rule-based models. We also compare RuleMonkey against problem-specific codes implementing network-free simulation methods.</p> <p>Conclusions</p> <p>RuleMonkey enables the simulation of rule-based models for which the underlying reaction networks are large. It is typically faster than DYNSTOC for benchmark problems that we have examined. RuleMonkey is freely available as a stand-alone application <url>http://public.tgen.org/rulemonkey</url>. It is also available as a simulation engine within GetBonNie, a web-based environment for building, analyzing and sharing rule-based models.</p

: Géoprospective territoriale à l'île de La Réunion

16 p.National audienceThe objective of this paper is to present an approach for experimenting territorial prospective analysis based on spatial modelling. This approach is carried out in the framework of the DESCARTES project which aims at developing a spatial simulation tool to support the design and analysis of different scenarios for land-use allocation in Reunion Island in terms of environmental services. The spatial modelling tool is composed of two complementary applications: (i) the Ocelet modelling language and its land dynamics simulation environment, and (ii) the Margouill@ platform. The first demonstrator, a model of farm land consumption by urbanization, was developed and presented during workshops in order to test the role of the spatial simulation tool in support of a collaborative innovation process among stakeholders, and to foster new research on social learning, spatial simulation of environmental services, and scale change issues.L'objectif de cet article est de présenter une démarche de construction d'un exercice de prospective territoriale basé sur un outil de modélisation spatiale. Cette démarche est mise en œuvre dans le cadre du projet ANR DESCARTES dont l'objectif est de construire un outil de simulation cartographique pour analyser différents scénarios d'affectation de l'usage des sols à l'Ile de La Réunion, en termes de services environnementaux. La plateforme de simulation cartographique est composée de deux applications complémentaires (i) le langage de modélisation Ocelet et son environnement de simulation de paysages dynamiques, et (ii) la plateforme Margouill@. Le développement puis la présentation, en atelier, d'un premier démonstrateur sur la consommation des terres agricoles par l'urbanisation a permis de tester l'outil cartographique comme support d'un processus d'innovation collective entre les parties prenantes, et d'ouvrir de nouveaux champs de recherche sur l'analyse de la démarche par les apprentissages, la spatialisation et la simulation prospective des services écosystémiques, et la prise en compte du changement d'échelle

Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

The Repast Simulation/Modelling System for Geospatial Simulation

The use of simulation/modelling systems can simplify the implementation of agent-based models. Repast is one of the few simulation/modelling software systems that supports the integration of geospatial data especially that of vector-based geometries. This paper provides details about Repast specifically an overview, including its different development languages available to develop agent-based models. Before describing Repast’s core functionality and how models can be developed within it, specific emphasis will be placed on its ability to represent dynamics and incorporate geographical information. Once these elements of the system have been covered, a diverse list of Agent-Based Modelling (ABM) applications using Repast will be presented with particular emphasis on spatial applications utilizing Repast, in particular, those that utilize geospatial data

UAV as a Reliable Wingman: A Flight Demonstration

In this brief, we present the results from a flight experiment demonstrating two significant advances in software enabled control: optimization-based control using real-time trajectory generation and logical programming environments for formal analysis of control software. Our demonstration platform consisted of a human-piloted F-15 jet flying together with an autonomous T-33 jet. We describe the behavior of the system in two scenarios. In the first, nominal state communications were present and the autonomous aircraft maintained formation as the human pilot flew maneuvers. In the second, we imposed the loss of high-rate communications and demonstrated an autonomous safe “lost wingman” procedure to increase separation and reacquire contact. The flight demonstration included both a nominal formation flight component and an execution of the lost wingman scenario

SIRENA: A CAD environment for behavioural modelling and simulation of VLSI cellular neural network chips

This paper presents SIRENA, a CAD environment for the simulation and modelling of mixed-signal VLSI parallel processing chips based on cellular neural networks. SIRENA includes capabilities for: (a) the description of nominal and non-ideal operation of CNN analogue circuitry at the behavioural level; (b) performing realistic simulations of the transient evolution of physical CNNs including deviations due to second-order effects of the hardware; and, (c) evaluating sensitivity figures, and realize noise and Monte Carlo simulations in the time domain. These capabilities portray SIRENA as better suited for CNN chip development than algorithmic simulation packages (such as OpenSimulator, Sesame) or conventional neural networks simulators (RCS, GENESIS, SFINX), which are not oriented to the evaluation of hardware non-idealities. As compared to conventional electrical simulators (such as HSPICE or ELDO-FAS), SIRENA provides easier modelling of the hardware parasitics, a significant reduction in computation time, and similar accuracy levels. Consequently, iteration during the design procedure becomes possible, supporting decision making regarding design strategies and dimensioning. SIRENA has been developed using object-oriented programming techniques in C, and currently runs under the UNIX operating system and X-Windows framework. It employs a dedicated high-level hardware description language: DECEL, fitted to the description of non-idealities arising in CNN hardware. This language has been developed aiming generality, in the sense of making no restrictions on the network models that can be implemented. SIRENA is highly modular and composed of independent tools. This simplifies future expansions and improvements.Comisión Interministerial de Ciencia y Tecnología TIC96-1392-C02-0