Modeling and simulation

About: Modeling and simulation is a research topic. Over the lifetime, 10273 publications have been published within this topic receiving 111550 citations.

Modeling and Simulation Support for System of Systems Engineering Applications: Rainey/Modeling and Simulation Support for System of Systems Engineering Applications

Abstract: A little longer than a decade ago, the community of systems engineers started to seriously deal with a category of challenges: system of systems (SoS). Systems Engineering (SE) is now better understood since its official birth as a discipline in the middle of the last century. It is widely understood to control the total systems life cycle process: definition, development, deployment, and retirement of a system. SE ensures that solutions are reliable, maintainable, and cost-effective. But its solutions focus on a system made up of components born from a common set of user requirements. Interactions with other systems was always possible, but these other systems were external and beyond the central systems boundaries.

Nonlocal elasticity theory for graphene modeling and simulation: prospects and challenges

Abstract: Abstract: This paper presents a literature review of recent research studies on the applications of nonlocal elasticity theory in the modeling and simulation of graphene sheets (GSs). The history, development and excellent properties of GSs are introduced. The details of nonlocal elasticity theory are also presented. A systematic introduction to the application of nonlocal elasticity on linear modeling and nonlinear modeling for single-layer graphene sheets (SLGSs) and multilayered graphene sheets (MLGSs) is also provided. The necessity of determining mechanical parameters and nonlocal parameters is discussed. Recommendations for future work are particularly presented. This work is intended to review the development of GSs, give an introduction to the research studies on nonlocal elasticity theory in the modeling of GSs, and provide recommendations for future research.

Application of Modeling and Simulation Tools for the Evaluation of Biocatalytic Processes: A Future Perspective

Abstract: Modeling and simulation techniques have for some time been an important feature of biocatalysis research, often applied as a complement to experimental studies. In this short review, we report on the state-of-the-art process and kinetic modeling for biocatalysis with the aim of identifying future research needs. We have particularly focused on four aspects of modeling: (i) the model purpose, (ii) the process model boundary, (iii) the model structure, and (iv) the model identification procedure. First, one finds that most of the existing models describe biocatalyst behavior in terms of enzyme selectivity, mechanism, and reaction kinetics. More recently, work has focused on extending these models to obtain process flowsheet descriptions. Second, biocatalysis models remain at a relatively low level of complexity compared with the trends observed in other engineering disciplines. Hence, there is certainly room for additional development, i.e., detailed mixing and hydrodynamics, more process units (e.g., biorefinery). Third, biocatalysis models have been only partially subjected to formal statistical analysis. In particular, uncertainty analysis is needed to ascertain reliability of the predictions of the process model, which is necessary to make sound engineering decisions (e.g., the optimal process flowsheet, control strategy, etc). In summary, for modeling studies to be more mature and successful, one needs to introduce Good Modeling Practice and that asks for (i) a standardized and systematic guideline for model development, (ii) formal identifiability analysis, and (iii) uncertainty analysis. This will advance the utility of models in biocatalysis for more rigorous application within process design, optimization, and control strategy evaluation.

Modeling and simulation of an electronic component manufacturing system using hybrid Petri nets

Abstract: Modelling and analysis for the design and operation of manufacturing systems is a vital need. For semiconductor manufacturing systems, which are large scale systems, discrete Petri nets do not constitute an adequate tool for modeling and analysis. In fact, use of discrete Petri nets is confronted with tile state explosion and the high cost of simulation. In this paper, hybrid Petri nets are presented as powerful tools for modeling and simulation of semiconductor manufacturing systems. This model has been used for modeling and simulation of a real life electronic components manufacturing system. It provides an accurate and first simulation of this system.