Call for Abstracts

Modeling and Simulation
will be organized around the theme
Prism of Prospects in Modeling and Simulation

modeling-and-simulation-2017
is comprised of
12
tracks and 78
sessions designed to offer comprehensive sessions that address current issues in
modeling-and-simulation-2017

Submit your abstract
to any of the mentioned tracks. All related abstracts are accepted.

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by choosing an appropriate package suitable to you.

Aerospace engineering is the branch of engineering that deals with the science, design, and construction of aircraft and spacecraft. The first definition of aerospace engineering appeared, considering the Earth’s atmosphere and the space above it as a single realm for development of flight vehicles. Space-systems analysis uses modeling and simulation. and engineers must solve complex problems with reduced budgets, fewer resources, and shorter schedules. Simulation and modeling are well-accepted methods for reducing time and cost, and they progress the effectiveness of systems design, verification, and validation.

- Computational aeromechanics

- Flight dynamic simulation modeling

- Multi-disciplinary modeling and simulation

- Model-based engineering of aerospace systems

- Modeling and simulation air and space vehicles

Artificial intelligence (AI) targets to give computers the capability to think like human beings. It is the behavior of a computer that, if exhibited by a person, would be called intelligent. Some people claim computers will certainly not have intelligence. They reason a computer is an electronic tool that can only process data very quickly but cannot actually think up any new ideas, it does not have any intellect. For a computer to be termed intelligent, its behaviors and capabilities must be compared to our own ways of doing things and thinking.

- Neural networks

- Fuzzy logic

- Evolutionary algorithms

- Expert systems

- Data mining

- Soft sensors

- Ai and control

- Ai and optimization algorithms

Biomedical engineering utilizes computer modeling and simulation as a manifold and range from virtual reality for training purposes to codification of knowledge of complex physiological systems to construct and test the postulates about biological phenomena. While developing the complex simulation tools and comprehensive modeling it requires considerable effort. The use of simple models even with minor investments can be useful to experimenters to organize ideas, scrutinize data efficiently, and plan experimentations.

- Biomechatronics

- Biomedical computing and surgery simulation

- Bio-environmental engineering

- Biomechanics

- Biomedical imaging and optics

- Biomedical and nano medical systems

- Biomedical robotics

Chemical Engineering modeling is a computer modeling method used in chemical engineering process design. It usually involves using purpose-built software to define a system of interconnected components, which are then resolved to the steady-state or dynamic behavior of the system can be predicted. The system mechanisms and connections are exemplified as a Process Flow diagram. Simulations can be as simple as the concoctions of two substances in a tank, or as complex as an entire alumina refinery. Chemical process modeling involves knowledge of the properties of the chemicals involved in the simulation, as well as the physical properties and features of the components of the system, such as tanks, pumps, pipes, pressure vessels, and so on.

- Metallurgical process

- Chemical process modeling

- Chemical process simulation

- Process analysis and simulation in chemical engineering

Modeling and simulation have been used to present architectural and engineering works, showing their final configuration. But, when the clarification of a detail or the constitution of a construction step in required, these models are not appropriate as they do not allow the observation of the construction activity. Models that could present dynamically changes of the building geometry stand a good support on education in civil engineering domain. Techniques of geometric modeling and virtual reality were used to obtain interactive models that could visually simulate the construction activity. The applications describe the construction work of a cavity wall and a bridge. These models allow the visualization of the physical progression of the work following a strategic construction sequence, the observation of details of the form of every component of the works and support the study of the type and method of operation of the equipment applied in the construction.

- Stochastic analysis and optimization

- Modeling and simulation of hydraulic systems

- Optimal evaluation and modelling of Building materials

- Non-linear simulation of material in civil engineering and geo-mechanics

The emergent influence of digital computing in systems modeling and simulation is leading to a rise in the use of discrete mathematical structures for describing models. While it is generally renowned that discrete methods and classical continuous methods both deliver valuable tools for modeling, strong biases exist which depend on the modeling techniques that are traditional within particular disciplines. The choice of a modeling approach occasionally reflects the background of the model builder more strongly than it reflects the character of the problem to be solved.

- Numerical analysis

- Combinatorics and physics

- Discrete event simulation

- Combinatorial optimization

- Discrete mathematical models

- Discrete and computational geometry

- Combinatorics and dynamical systems

Computer simulation modeling is a restraint gaining popularity in both government and industry. Computer simulation modeling can give assistance in the design, creation, and evaluation of complex systems. Designers, program directors, analysts, and engineers use computer simulation modeling to understand and assess ‘what if’ case scenarios. It can model a real or proposed system using computer software and is advantageous when changes to the actual system are difficult to implement, that involve high costs, or are unrealistic. Some instances of computer simulation modeling acquainted to most of us include weather forecasting, car crash modeling and flight simulators used for training pilots.

- Computer modeling

- Computer simulations

- 3D computer graphics

- Computer design and engineering

- Software design and engineering

- Computer networks & cryptography

- Data mining & theory of computation

Modeling and simulation stands a vital part of many areas of engineering, allowing engineers to reason about the expected behavior of a system without having to physically implement it. Simulation pervades considerably of electrical engineering, for instance models of individual electronic devices, circuit simulation, network modeling, compression of speech/audio/image/video signals, design of biomedical devices, and modeling of physical systems for control drives. Modelling allows an abstract representation of a signal or system in a (mathematically) compact and/or basic form that is extremely useful in various fields, including analysis, design, compression, classification, and control. The main high-level aim of the computation in electrical engineering is to to provide a thorough grounding in aspects of constructing and applying models and their simulation using well-known simulation tools (MATLAB and C). In particular, it looks at how continuous-time systems can be signified and simulated using (discrete-time) computers. This also provides an interesting insight into the relationship between physical systems and computing algorithms.

- Design and optimization

- Implementation and analysis

- Modeling and simulation of power systems

- Modeling and simulation of power electronics and drives

- Modeling and simulation of distributed generating systems

- Modeling and simulation of electric machines and transformers

- Simulation methodologies for design and analysis of electromagnetic devices

Industrial engineering was one of the earliest fields to use simulation in the study, evaluation and optimization of complex manufacturing activities. Industrial engineers use computer simulations (specially discrete event simulation) along with wide mathematical modelling and computational methods to determine the best possible design for production and distribution systems. With the integration of artificial intelligence, agents, virtual reality and other innovative modelling techniques, simulation has become an essential decision support tool in many industries such as automotive, aerospace and electronics.

- Simulation interfaces

- Distributed simulation

- Virtual manufacturing technologies

- Stochastic modelling and simulation

- Intelligent design and manufacturing

- Performance evaluation and optimisation

- Simulation in logistics and supply chain design

Mechanical engineering is the restraint that applies the principles of engineering, physics, and materials science for the design, analysis, manufacturing, and maintenance of mechanical systems. It is the branch of engineering that involves the design, production, and operation of machinery. Mechanical engineers use these core ideologies along with tools like computer-aided design, and product life cycle management to design and analyze manufacturing plants, industrial equipment and machinery, heating and cooling systems, transport systems, aircraft, watercraft, robotics, medical devices, weapons, and others.

- Mechatronics

- Solid mechanics

- Micro-technology

- Mechanical design

- Environmental control

- Computational fluid dynamics

Mathematical modeling and simulation are significant research and monitoring tools used to comprehend biological communities and their relationships to the environment. Mathematical models are group of variables, equations, and starting values that form a cohesive illustration of a process or behavior. Because communications among the members of biological communities and components of the abiotic environment are enormously complex, mathematical models are beneficial for understanding how ecosystems function and for making predictions about managing ecosystems.

- Geometry

- Applied mathematics

- Statistical modeling

- Computational mathematics

- Control theory and automation

- Data mining and soft computing

- Mathematical chemistry and biology

- Optimization and operational research

The progressive trends of modern information technologies lead to the constant growth of complexity of information systems and call for their high performance. Stochastic nature of flows that information systems necessity to serve and presence of stochastic internal processes that influence their behavior, rationalizes the use of probabilistic modeling and Statistical simulation when one needs to analyze their performance. Despite increasing complexity evident requirement for system’s high performance which safeguards advanced methods of modeling and simulation.

- Econometrics

- Bioinformatics

- Probability theory

- Stochastic processes

- Multivariate and bayesian Inference

- Decision theory and sampling theory

- Regression analysis estimation theory

- Simulation, parametric and nonparametric inference