Modeling Of Engineering Systems Research Articles

Maximum-likelihood approach in parametric identification of stochastic differential models of engineering systems

The aim of this paper is to bridge the gap between the mathematical theory of maximum likelihood estimation (MLE) for Itô equations and the practice of identification of engineering systems. A systematic extension of the theory is outlined to enable the ML parametric identification of systems which are not necessarily Markovian, ergodic and stationary, and which may explode in finite time. Accuracy of estimation (consistency) and robustness problems are also investigated. The discussion is illustrated by the analysis of a number of examples, connected with fundamental models of stochastic fracture mechanics and with random vibration.

Modelling applications of spreadsheets

Spreadsheets are essentially software packages for carrying out operations on rows and columns of numerical values. Although originally a financial modelling tool, they also have many applications in modelling engineering systems. The authors show that most commercially available spreadsheets are well provided with trigonometric, exponential and logarithmic functions, as well as with a range of arithmetic and logic operations for combining such functions. As a result, a spreadsheet is often a quick and convenient way of carrying out many types of calculation which commonly occur in electronics, telecommunications and control engineering. Furthermore, the standard graphics packages normally provided with spreadsheets make it particularly easy to display and use the results of such calculations.

A systems theoretic approach to second moment modelling of probabilistic engineering systems∗

Abstract A new approach to modelling probabilistic and stochastic engineering systems using graph theory is outlined. This approach emphasizes the introduction of probabilistic and stochastic concepts at the very beginning of the model building process. This is in marked contrast to past tendencies to add probabilistic concepts to the end of an otherwise deterministic model building process. The development of topological models founded on oriented probabilistic measurements is given. which leads to the identification of some useful statistical properties of the’ random interconnection equations’. The development of probabilistic component models is given, where a component can be characterized independently of other components. Methods for automatically building the second moment representation of the Mixed Nodal Tableau are discussed. The application of the above theory to the probabilistic analysis of a pipe network problem is briefly described.

Mathematical modelling of chemical engineering systems by finite element analysis using PDE/PROTRAN

The use of commercially available software for obtaining finite-element solutions to partial differential equations encountered in engineering and the applied sciences is considered. A particular software package called PDE/PROTRAN that can solve a general class of either time-dependent, steady-state, or eigenvalue type PDEs in two space dimensions is examined from both a theoretical and practical perspective. To illustrate the application of PDE/PROTRAN, two example problems that have an origin in the engineering sciences are posed and translated into a working computer code. Solutions to these mathematical models, which describe diffusion-reaction phenomena and fluid dynamics, are also given and compared to previous solutions where available. Some advantages and limitations of the program and possible enhancements are also discussed.

Mathematical modelling of chemical engineering systems by finite element analysis using PDE/PROTRAN

The use of a commercially available computer software package for obtaining finite element solutions to a general class of either time-dependent, steady-state, or eigenvalue type partial differential equations in two-space dimensions is considered. This package, which is called PDE/PROTRAN, is introduced through two example problems that describe mathematical models of chemical engineering systems. The advantages and limitations of the code for obtaining rapid and accurate solutions to related mathematical models is also discussed.

On the limits of expert systems and engineering models in process control

Abstract The review is based on an analysis of current literature of expert systems and of system engineering models in dynamic process control. It starts with an analysis of the mental operations and cognitive requirements needed for supervisory control. Mental models are discussed as a function of situational requirements as well as of personal strategies. Systems engineering models and expert systems are briefly described and their function as decision support tools evaluated. Criteria are the overall functionality, similarity of knowledge bases and reasoning strategies of the human and the support system, adaptability to the operator's skill level and self-explanation of the support system in the interaction mode. As a result, system engineering models are only of limited value for knowledge-based process control. Expert systems seem to be very valuable tools for augmenting human decision making in process control, if the interaction problem can be solved.

Stochastic modelling of chemical engineering systems. Application of the generalized master equation to the bubble population in a bubbling fluidized bed

The master equation is a stochastic population balance, applicable to most systems composed of discrete entities. More often than not, the solution of the master equation is extremely difficult, if not impossible; thus a rational approximation scheme based on a power series expansion in terms of the inverse volume can be introduced. This enables us to derive equations for means, covariances and correlation functions of the random variables, each representing the number of entities of one type in the system. In this paper, the generalized master equation is applied to model the bubble population in a bubbling fluidized bed. The random variables are the numbers of bubbles of different sizes in various compartments. The fluctuations in the total surface area of the bubble phase are also studied by deriving expressions for the mean, covariance and correlation function.

Bond graphs for modeling engineering systems, by A. J. Blundell, Halstead, Ellis Horwood Limited, London, 1982, 151 pp. Price: $44.95

Bond graphs for modeling engineering systems, by A. J. Blundell, Halstead, Ellis Horwood Limited, London, 1982, 151 pp. Price: $44.95

A review of mechanical reliability modelling in relation to failure mechanisms

Mathematical models can provide a basis for system reliability predictions and this survey aims to identify the main sources of existing information relevant to the different aspects of the modelling of mechanical engineering systems and mechanical components. The survey concentrates on identifying a number of the main sources of information as it would not be possible to identify all relevant sources in a brief paper. The models have been reviewed to identify the conditions in which they are applicable and the areas where further work is necessary. The modelling survey is coupled with a review of degradation processes confined to specific areas considered to be important in mechanical reliability. Basic failure modes due to physical degradation are discussed and the additional information required to relate these to mechanical reliability is identified. The importance of monitoring methods is defined. These ideas are illustrated by reviewing applications of modelling methods to mechanical transmission elements and structures.

Structure Graphs: A New Approach for Interactive Computer Modelling of Multi-Energy Domain Systems

A computer package MEDIEM (Multi-Energy Domain Interactive Element Modelling) has been developed and mounted on a minicomputer for the purpose of interactive modelling of multi-energy domain engineering systems. The basis of the package is a graphical language called “structure graphs” which allows the user to model the “structure” or essential features of a lumped parameter engineering system in close correspondence to a schematic. It is shown that structure graphs arise naturally when modelling is considered within an interactive computer-aided environment. The approach has certain advantages over those based on current techniques such as bond graphs, linear graphs, and signal flow graphs; the main ones being the ease of model construction and the ease of effecting model changes (both structural and parameter changes). The package will handle both linear and nonlinear systems. Some illustrative examples of the use of structure graphs are provided together with a detailed example of the use of MEDIEM for modelling a complex differential pressure transducer. Lastly some special causal problems reported in the bond graph literature are examined and shown not to exist when MEDIEM is used.

Systems engineering models of human-machine interaction

Systems engineering models of human-machine interaction

Review of "Systems Engineering Models of Human-Machine Interaction by William B. Rouse", North Holland.

The author had three goals for the book: "to emphasize the current state of the art", "to provide a treatment of a highly mathematical topic while avoiding calculus, differential equations, Laplace and Fourier transforms, and so on", and, "to include basic tutorials on the modeling methodologies of interest and thus avoid requiring the reader to consult other basic sources." The book is based on the lecture notes of a graduate course in Industrial Engineering offerred at the University of Illinois to mostly engineering and psychology students. The author feels that the material in the book is "nicely complemented by having students pursue a series of small design projects in which they have to choose among the various available models, resolve measurement problems, and so on."

Computer graphics in nuclear engineering education at Queen Mary College

Computer graphical display has been used in teaching nuclear engineering at Queen Mary College since 1971 and has assumed an increasingly important role in the modelling and simulation of engineering systems, not least nuclear engineering systems, for teaching purposes. The role of computer graphics is illustrated by means of examples selected from a suite of nuclear engineering programs in current use, indicating the highly flexible interaction and enhanced presentation of information which can be achieved. The facilities provided at Queen Mary College for the implementation of graphics-based teaching programs are described and the associated laboratory organisation indicated.

Network analysis—a useful but underused tool for modelling of chemical engineering systems?

Network analysis may be used to model a number of chemical engineering systems such as; distribution problems, heat transfer in solids, simultaneous heat and mass transfer in catalyst pellets. Manipulation of simple network representation matrices requires a minimum of core store and generates rapid solutions to a variety of modelling problems. Using methods of tearing and decomposition such as diakoptics there is effectively no limit to the complexity of the network problem which can be solved.

On Gyrobondgraphs and Their Uses

Graphical representations of lumped-parameter models for physical and engineering systems have been in use for some time. A relatively recent arrival is the bond graph, which displays energy flow and energy structure explicitly. Bond graphs are finding increasing use in a variety of applications, including classical electromechanical, hydraulic, and thermal energy systems as well as chemical and biological processes. In addition, there has been some effort to extend the approach to energy-like macroeconomic systems. The standard bond graph approach uses the same basic elements commonly found in network theory, although the graphing scheme is different. This paper defines a specific type of bond graph—the gyrobondgraph—and shows how it serves as a canonical form for a large class of lumped-parameter multiport models. The gyrobondgraph is based on only five elements and a standard graph format. A transformation procedure is described for obtaining a gyrobondgraph from a standard bond graph. The formulation of system equations associated with a gyrobondgraph is discussed briefly, and, as a point of interest, Tellegen’s Theorem in quasi-power form is derived. The gyrobondgraph appears to be an important new tool for the exploration of multiport system theory; furthermore, it is a source of new techniques for the computer simulation of bond graph models.

An Intelligent System For Automated MathematicalModelling And Simulation Of DynamicalEngineering Systems

We describe in this paper a computer program for Automated Mathematical Modelling (AMM) and Automated Simulation (AS) of dynamical engineering systems using Artificial Intelligence (AI) techniques. This computer program is an implementation of a new method for AMM using Fuzzy Logic techniques and Fractal Theory, and a new method for AS using Expert Systems technology. Our new method for AMM consists of three main parts: Time Series Analysis, Developing a set of Admissible Models and Selecting the Best model. Our method for Time Series Analysis consists in the use of the fractal dimension of a set of points as a measure of the geometrical complexity of the time series. Our method for developing a set of admissible models is based on the use of Fuzzy Logic techniques to simulate the reasoning process of the human experts in mathematical modelling of engineering systems. The selection of the best model for the engineering systems is done using heuristics from the experts and statistical calculations. The simulation of the best model can be done by using a new method developed by the authors, that enables automated computer exploration of all the dynamical behaviors of the engineering system. Given a mathematical model for a specific Dynamical Engineering System (DES), this method will automatically select (using a rule base) the best set of parameter values to perform numerical simulations of the system. This simulations will in turn enable the identification of all the dynamical behaviors of the engineering system.