Model reduction in state identification problems with an application to determination of thermal parameters

2009 ◽  
Vol 59 (5) ◽  
pp. 877-890 ◽  
Author(s):  
Janne M.J. Huttunen ◽  
Jari P. Kaipio
Keyword(s):  
Model Reduction ◽  
Thermal Parameters ◽  
Identification Problems ◽  
State Identification

Determination of thermal parameters of PVDF using a photoacoustic technique

2001 ◽  
Vol 12 (6) ◽  
pp. 671-675 ◽  
Author(s):  
B Bonno ◽  
J L Laporte ◽  
R Tascón d'León
Keyword(s):  
Thermal Parameters ◽  
Photoacoustic Technique

scholarly journals The vector optimization and modeling of a technical systems

2018 ◽  
Vol 224 ◽  
pp. 04020
Author(s):  
Leonid B. Matusov
Keyword(s):  
Parameter Space ◽  
Multicriteria Optimization ◽  
Feasible Solution ◽  
Solution Set ◽  
Identification Problems ◽  
Design Variables ◽  
Technical Systems ◽  
The Mathematical Model ◽  
Term Identification

The construction a feasible solution set with a given accuracy is a main problem in multicriteria optimization and modeling. In order to construct the feasible solution set, a method called the Parameter Space Investigation has been created and successfully integrated into various fields of industry, science, and technology. Multicriteria modeling (identification) is a new direction that is of great value in applications. In the most common usage, the term “identification” means construction of the mathematical model of a system and determination of the parameters (design variables) of the model. The construction a feasible solution set with a given accuracy is a common way for solving multicriteria optimization and modeling problems. The issues of the estimation of the Parameter Space Investigation method convergence rate, the approximation of the feasible solution set are described. Besides these, the multicriteria identification problems of mechanical systems are discussed too.

Determination of Thermal Parameters in Houses

1992 ◽  
Vol 25 (15) ◽  
pp. 561-566
Author(s):  
J. Angeby ◽  
T. Söderström
Keyword(s):  
Thermal Parameters

Determination of Thermal Parameters of a Work-Roll in Warm Rolling Using Inverse Modeling

2018 ◽  
Author(s):  
Vinod Yadav
Keyword(s):  
Inverse Method ◽  
Work Roll ◽  
Rolling Process ◽  
Thermal Parameters ◽  
Shop Floor ◽  
Transfer Coefficients ◽  
Heat Transfer Coefficients ◽  
Convective Heat Transfer Coefficients ◽  
Work Rolls

Thermal parameters of a work-roll play an important role in the modeling of the rolling process, due to periodic thermal loading. The knowledge of thermal parameters is also vital in understanding the fatigue life of the work-roll and the thermal crown. However, estimation of the thermal parameters viz., thermal conductivity, thermal diffusivity and convective heat transfer coefficients at both, inner and outer roll periphery is tough to realize during the rolling process. Various methods employed earlier for measuring the thermal properties of work-rolls in the rolling process requires intrusion in the surface of the work-rolls, mainly to embed the thermocouples inside the rolls. These methods are easy to implement, but it is really hard to achieve truthful estimation. A possible way out is to measure the average thermal parameters of a work roll in the rolling process by utilizing the measured temperature at two specified locations on the work-roll surface. In this work, an inverse method is proposed to estimate the thermal properties and convective heat transfer coefficients of a roll in the rolling process. The inverse method makes use of a direct model of temperature determination considering plane strain problem, which is based on the integral transform method. For minimizing the error between the computed and experimentally recorded data, a quasi-Newton method is used. In lieu of shop floor experiments, a finite element method (FEM) based package ABAQUS 6.10 is used to obtain the temperature distribution in the work-roll. Further, an additive white Gaussian error is added in the FEM simulated measurements to assess the inverse method for stability towards mild measurements. The inverse estimation is successfully validated and can be used in shop floor for the online determination of thermal parameters of the work-rolls in the rolling process.

Dynamic programming, pattern recognition and location of faults in complex systems

1966 ◽  
Vol 3 (01) ◽  
pp. 268-271
Author(s):  
Richard Bellman
Keyword(s):  
Complex System ◽  
Functional Equation ◽  
Pattern Recognition ◽  
Dynamic Programming ◽  
Decomposition Technique ◽  
Extended State ◽  
Identification Problems ◽  
State Variable ◽  
Computational Solution

In a previous paper devoted to an application of dynamic programming to pattern recognition [1], we pointed out that some identification problems could be regarded as generalized trajectory processes. The functional equation technique [2] could then be employed to obtain an analytic formulation of the determination of optimal search techniques. In many cases, however, (for example, in chess or checkers), a straightforward use of the functional equation is impossible because of dimensionality difficulties. In circumventing these obstacles to effective computational solution, we employed a decomposition technique which we called “stratification” [1, 3]. In this paper, we present a different way of avoiding the dimensionality problem, based upon the concept of “extended state variable”. To indicate the utility of the concept, we shall apply it to the problem of finding a fault in a complex system.

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