The use of object oriented modelling and simulation tools in constraint satisfaction for embodiment design

The software package Dymola, which implements the new, vendor-independent standard modelling language Modelica, exemplifies the emerging generation of object-oriented modelling and simulation tools. This paper shows how, in addition to its simulation capabilities, it may be used as an embodiment design tool, to size automatically a design assembled from a library of generic parametric components. The example used is a miniature model aircraft diesel engine. To this end, the component classes contain extra algebraic equations calculating the overload factor (or its reciprocal, the safety factor) for all the different modes of failure, such as buckling or tensile yield. Thus the simulation results contain the maximum overload or minimum safety factor for each failure mode along with the critical instant and the device state at which it occurs. The Dymola "Initial Conditions Calculation" function, controlled by a simple software script, may then be used to perform automatic component sizing. Each component is minimised in mass, subject to a chosen safety factor against failure, over a given operating cycle. Whilst the example is in the realm of mechanical design, it must be emphasised that the approach is equally applicable to the electrical or mechatronic domains, indeed to any design problem requiring numerical constraint satisfaction.

Applying quality control in building energy modelling: Comparative simulation of a high performance building

Quality control is considered from the simulator's perspective through comparative simulation of an ultra energy-efficient building with EE4-DOE2.1E and EnergyPlus. The University of Calgary's Leadership in Energy and Environmental Design Platinum Child Development Centre, with a 66% certified energy cost reduction rating, was the case study building. A Natural Resources Canada incentive program required use of EE4 interface with DOE2.1E simulation engine for energy modelling. As DOE2.1E lacks specific features to simulate advanced systems such as radiant cooling in the CDC, an EnergyPlus model was developed to further evaluate these features. The EE4-DOE2.1E model was used for quality control during development of the base EnergyPlus model and simulation results were compared. Advanced energy systems then added to the EnergyPlus model generated small difference in estimated total annual energy use. The comparative simulation process helped identify the main input errors in the draft EnergyPlus model. The comparative use of less complex simulation programs is recommended for quality control when producing more complex models. © 2009 International Building Performance Simulation Association (IBPSA).

Development of modelling method selection tool for health services management: From problem structuring methods to modelling and simulation methods

Background: There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. Aim. The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. Methods. This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). Results: The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. Conclusions: A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection. © 2011 Jun et al.

Coherent design methodology using modelling, simulation and optimisation

There is an increasing demand for optimising complete systems and the devices within that system, including capturing the interactions between the various multi-disciplinary (MD) components involved. Furthermore confidence in robust solutions is esential. As a consequence the computational cost rapidly increases and in many cases becomes infeasible to perform such conceptual designs. A coherent design methodology is proposed, where the aim is to improve the design process by effectively exploiting the potential of computational synthesis, search and optimisation and conventional simulation, with a reduction of the computational cost. This optimization framework consists of a hybrid optimization algorithm to handles multi-fidelity simulations. Simultaneously and in order to handles uncertainty without recasting the model and at affordable computational cost, a stochastic modelling method known as non-intrusive polynomial chaos is introduced. The effectiveness of the design methodology is demonstrated with the optimisation of a submarine propulsion system.

Numerical modelling of adsorption of metallic particles on graphite substrate via molecular dynamics simulation

A computer-based numerical modelling of the adsorption process of gas phase metallic particles on the surface of a graphite substrate has been performed via the application of molecular dynamics simulation method. The simulation relates to an extensive STM-based experiment performed in this field, and reproduces part of the experimental results. Both two-body and many-body inter-atomic potentials have been employed. A Morse-type potential describing the metal-carbon interactions at the interface was specifically formulated for this modelling. Intercalation of silver in graphite has been observed as well as the correct alignments of monomers, dimers and two-dimensional islands on the surface. PACS numbers: 02.60.Cb, 07.05.Tp, 68.55.-a, 81.05.Tp

Software Products for Modelling and Simulation in Materials Science

Models and software products have been developed for modelling, simulation and prediction of different correlations in materials science, including 1. the correlation between processing parameters and properties in titanium alloys and ?-titanium aluminides; 2. time–temperature–transformation (TTT) diagrams for titanium alloys; 3. corrosion resistance of titanium alloys; 4. surface hardness and microhardness profile of nitrocarburised layers; 5. fatigue stress life (S–N) diagrams for Ti–6Al–4V alloys. The programs are based on trained artificial neural networks. For each particular case appropriate combination of inputs and outputs is chosen. Very good performances of the models are achieved. Graphical user interfaces (GUI) are created for easy use of the models. In addition interactive text versions are developed. The models designed are combined and integrated in software package that is built up on a modular fashion. The software products are available in versions for different platforms including Windows 95/98/2000/NT, UNIX and Apple Macintosh. Description of the software products is given, to demonstrate that they are convenient and powerful tools for practical applications in solving various problems in materials science. Examples for optimisation of the alloy compositions, processing parameters and working conditions are illustrated. An option for use of the software in materials selection procedure is described.