Monte Carlo Simulation of Electron-Induced Air Fluorescence Utilizing Mobile Agents: A New Paradigm for Collaborative Scientific Simulation

A new paradigm for utilization of mobile agents in a modular architecture for scientific simulation is demonstrated through a case study involving Monte Carlo simulation of low energy electron interactions with molecular nitrogen gas. Design and development of Monte Carlo simulations for physical systems of moderate complexity can present a seemingly overwhelming endeavor. The researcher must possess or otherwise develop a thorough understanding the physical system, create mathematical and computational models of the physical system’s components, and forge a simulation utilizing those models. While there is no single route between a collection of physical concepts and a Monte Carlo simulation based on those concepts, this work develops a new paradigm based on agent-oriented architecture and modular design principles through a case study in which interactions between electrons and molecules are simulated. A methodology that incorporates both distributed and modular computing concepts is shown to facilitate the researcher’s selection of component granularity as well as the connectivity and interaction of the simulation components. The case study is specific, however, the techniques employed in addressing the encountered problems are general and applicable to a much broader range of scientific simulation. A paradigm is developed through which the burden of information management in distributed Monte Carlo simulations is lessened through realization of a modular system of agents that may be augmented as a virtual collaborative community. An understanding of the physics to be simulated is a prerequisite of model development. Research has been conducted to provide the required understanding of the associated knowledge domain. The separable nature of the processes involved in air fluorescence provide suitable processes for a modular distributed simulation. Physical processes that can be decoupled and implemented as modular physics agents have been identified. Models suitable for decoupling are implemented as OSGi bundles used by JADE agents. The OSGi architecture is used to define the types of data consumed and produced by models of a given physical process with no concern of specific implementation of the model. This allows third party developers freedom to implement models to their required level of detail with only the restriction of the model’s input and output upholding the contract defined by the framework. Agents for simulation of physical processes are based on published physics models and experimental data identified by a literature search. Agents simulating random processes employ a statistical technique known as the Monte Carlo Method. The significance of this work extends beyond demonstrating the new paradigm for agency-oreinted Monte Carlo simulation that is both modular and extensible. The production of air fluorescence via interactions of ionizing radiation with atmospheric gases is a subject ongoing research. Development of Monte Carlo simulation of electron impact induced air fluorescence is of considerable value to related research efforts. Therefore, an opportunity exists not only to demonstrate the use of a modular agent-based paradigm for Monte Carlo simulation, but also to provide new capabilities for the investigation of physical phenomena

Bowed string synthesis with force feedback gesture interaction

International audienceThe CORDIS ANIMA formalism allows to model physical objects according to a modular methodology which guaranties, at each step of modeling, the energetic consistency of the behavior of the model. Maintening this energetic consistency is a crucial point in the use of interactive simulation by means of Physical Modeling and Force Feedback Gesture Devices. This paper presents a CORDIS-ANIMA model of bowed string, which closely links the properties of the produced sounds to the gesture and energetic investment of the player. A pertinent feature of real bowed instruments is their high sensitivity to the gesture dynamic. The proposed model restitutes this sensitivity providing high musical quality and nuances in the synthetic sounds. In addition, the use of the consistent physically-based modular designing presented here, allows the designer to lead towards a minimal physical model able to restitute this so pertinent feature

Graphical modelling of modular machines

This research is aimed at advancing machine design through specifying and implementing (in "proof of concept" form) a set of tools which graphically model modular machines. The tools allow mechanical building elements (or machine modules) to be selected and configured together in a highly flexible manner so that operation of the chosen configuration can be simulated and performance properties evaluated. Implementation of the tools has involved an extension in capability of a proprietary robot simulation system. This research has resulted in a general approach to graphically modelling manufacturing machines built from modular elements. A focus of study has been on a decomposition of machine functionality leading to the establishment of a library of modular machine primitives. This provides a useful source of commonly required machine building elements for use by machine designers. Study has also focussed on the generation of machine configuration tools which facilitate the construction of a simulation model and ultimately the physical machine itself. Simulation aspects of machine control are also considered which depict methods of manipulating a machine model in the simulation phase. In addition methods of achieving machine programming have been considered which specify the machine and its operational tasks. Means of adopting common information data structures are also considered which can facilitate interfacing with other systems, including the physical machine system constructed as an issue of the simulation phase. Each of these study areas is addressed in its own context, but collectively they provide a means of creating a complete modular machine design environment which can provide significant assistance to machine designers. Part of the methodology employed in the study is based on the use of the discrete event simulation technique. To easily and effectively describe a modular machine and its activity in a simulation model, a hierarchical ring and tree data structure has been designed and implemented. The modularity and reconfigurability are accommodated by the data structure, and homogeneous transformations are adopted to determine the spatial location and orientation of each of the machine elements. A three-level machine task programming approach is used to describe the machine's activities. A common data format method is used to interface the machine design environment with the physical machine and other building blocks of manufacturing systems (such as CAD systems) where systems integration approaches can lead to enhanced product realisation. The study concludes that a modular machine design environment can be created by employing the graphical simulation approach together with a set of comprehensive configuration. tools. A generic framework has been derived which outlines the way in which machine design environments can be constructed and suggestions are made as to how the proof of concept design environment implemented in this study can be advanced

Hybrid Prototypes to Assist Modeling Automotive Seats

The development of new modular seats is an important issue in the automotive industry. However, is very time consuming and costly. Virtual models and hybrid prototypes could accelerate the car seats development process. The hybrid prototypes are mainly manufactured by rapid prototyping with multi materials. The objective of this paper is to establish a methodology to develop innovative lightweight multi-functional, modular car seats to be used in Multi-Purpose Vehicles (MPV), by means of FEA simulation and rapid prototyping additive/subtractive technologies utilizing multi materials. A case study is presented to validate the developed methodology. The manufactured hybrid prototype’s reproduces the main functionalities of the MPV modular seat, namely its three key positions: normal, stored and table.Mechanical Engineerin

Special Session on Industry 4.0

No abstract available

STOP-IT: strategic, tactical, operational protection of water infrastructure against cyberphysical threats

Water supply and sanitation infrastructures are essential for our welfare, but vulnerable to several attack types facilitated by the ever-changing landscapes of the digital world. A cyber-attack on critical infrastructures could for example evolve along these threat vectors: chemical/biological contamination, physical or communications disruption between the network and the supervisory SCADA. Although conceptual and technological solutions to security and resilience are available, further work is required to bring them together in a risk management framework, strengthen the capacities of water utilities to systematically protect their systems, determine gaps in security technologies and improve risk management approaches. In particular, robust adaptable/flexible solutions for prevention, detection and mitigation of consequences in case of failure due to physical and cyber threats, their combination and cascading effects (from attacks to other critical infrastructure, i.e. energy) are still missing. There is (i) an urgent need to efficiently tackle cyber-physical security threats, (ii) an existing risk management gap in utilities’ practices and (iii) an un-tapped technology market potential for strategic, tactical and operational protection solutions for water infrastructure: how the H2020 STOP-IT project aims to bridge these gaps is presented in this paper.Postprint (published version

Inverse Uncertainty Quantification using the Modular Bayesian Approach based on Gaussian Process, Part 2: Application to TRACE

Inverse Uncertainty Quantification (UQ) is a process to quantify the uncertainties in random input parameters while achieving consistency between code simulations and physical observations. In this paper, we performed inverse UQ using an improved modular Bayesian approach based on Gaussian Process (GP) for TRACE physical model parameters using the BWR Full-size Fine-Mesh Bundle Tests (BFBT) benchmark steady-state void fraction data. The model discrepancy is described with a GP emulator. Numerical tests have demonstrated that such treatment of model discrepancy can avoid over-fitting. Furthermore, we constructed a fast-running and accurate GP emulator to replace TRACE full model during Markov Chain Monte Carlo (MCMC) sampling. The computational cost was demonstrated to be reduced by several orders of magnitude. A sequential approach was also developed for efficient test source allocation (TSA) for inverse UQ and validation. This sequential TSA methodology first selects experimental tests for validation that has a full coverage of the test domain to avoid extrapolation of model discrepancy term when evaluated at input setting of tests for inverse UQ. Then it selects tests that tend to reside in the unfilled zones of the test domain for inverse UQ, so that one can extract the most information for posterior probability distributions of calibration parameters using only a relatively small number of tests. This research addresses the "lack of input uncertainty information" issue for TRACE physical input parameters, which was usually ignored or described using expert opinion or user self-assessment in previous work. The resulting posterior probability distributions of TRACE parameters can be used in future uncertainty, sensitivity and validation studies of TRACE code for nuclear reactor system design and safety analysis