Inverse problems in the design, modeling and testing of engineering systems

Formulations, classification, areas of application, and approaches to solving different inverse problems are considered for the design of structures, modeling, and experimental data processing. Problems in the practical implementation of theoretical-experimental methods based on solving inverse problems are analyzed in order to identify mathematical models of physical processes, aid in input data preparation for design parameter optimization, help in design parameter optimization itself, and to model experiments, large-scale tests, and real tests of engineering systems

Parametric identification of mathematical models of coupled conductive-radiative heat transfer

In many practical situations it is impossible to measure directly such characteristics of analyzed materials as thermal and radiation properties. The only way, which can often be used to overcome these difficulties, is indirect measurements. This type of measurements is usually formulated as the solution of inverse heat transfer problems. Such problems are illposed in mathematical sense and their main feature shows itself in the solution instabilities. That is why special regularizing methods are needed to solve them. The experimental methods of identification of the mathematical models of heat transfer based on solving of the inverse problems are one of the modern effective solving manners. The goal of this paper is to estimate thermal and radiation properties of advanced materials using the approach based on inverse methods (as example: thermal conductivityλ(T) , heat capacity C(T) and emissivity ε (T )). New metrology under development is the combination of accurate enough measurements of thermal quantities, which can be experimentally observable under real conditions and accurate data processing, which are based on the solutions of inverse heat transfer problems. In this paper, the development of methods for estimating thermal and radiation characteristics is carried out for thermally stable high temperature materials. Such problems are of great practical importance in the study of properties of materials used as non-destructive surface coating in objects of space engineering, power engineering etc. Also the corresponded optimal experiment design problem is considered. The algorithm is based on the theory of Fisher information matrix

Parametric identification of mathematical models of coupled conductive-radiative heat transfer

In many practical situations it is impossible to measure directly such characteristics of analyzed materials as thermal and radiation properties. The only way, which can often be used to overcome these difficulties, is indirect measurements. This type of measurements is usually formulated as the solution of inverse heat transfer problems. Such problems are illposed in mathematical sense and their main feature shows itself in the solution instabilities. That is why special regularizing methods are needed to solve them. The experimental methods of identification of the mathematical models of heat transfer based on solving of the inverse problems are one of the modern effective solving manners. The goal of this paper is to estimate thermal and radiation properties of advanced materials using the approach based on inverse methods (as example: thermal conductivityλ(T) , heat capacity C(T) and emissivity ε (T )). New metrology under development is the combination of accurate enough measurements of thermal quantities, which can be experimentally observable under real conditions and accurate data processing, which are based on the solutions of inverse heat transfer problems. In this paper, the development of methods for estimating thermal and radiation characteristics is carried out for thermally stable high temperature materials. Such problems are of great practical importance in the study of properties of materials used as non-destructive surface coating in objects of space engineering, power engineering etc. Also the corresponded optimal experiment design problem is considered. The algorithm is based on the theory of Fisher information matrix