Predicting multiple combination of parameters for designing a porous fin subjected to a given temperature requirement

2017

Sādhanā

Self Cite

Determination of the erodibility parameters, such as critical shear stress and erodibility coefficient, are necessary before estimating the annual bank erosion (or bank retreat) at river reaches. However, in many cases, the river site is inaccessible making it difficult to assess the soil parameters either by in situ tests or by laboratory experiments. In this study, Genetic Algorithm (GA)-based optimisation technique was used to estimate the erodibility parameters of middle reaches of the Brahmaputra River in India. Two approaches were followed. At first, erodibility parameters were estimated using daily stage records at a selected site. Secondly, based on the annual observed bank erosions (bank retreat) from satellite images, erodibility parameters were estimated in three different river reaches. All these results were compared with that from a previous study using in situ jet tests. Annual bank erosions (bank retreat) were estimated using the median values of the erodibility parameters. The results agree well with the average observed annual bank erosion of these river reaches. In addition, the effects of measurement errors and optimisation algorithms on the parameter estimation were analysed. Sensitivity analysis of the parameters in GA was evaluated and it was found that GA can be utilised in the data-scarce regions to estimate the average erodibility parameters.

Section: Effect Of Ga Parameters On Optimisationmentioning

confidence: 99%

Estimation of riverbank soil erodibility parameters using genetic algorithm

Karmaker

2017

Sādhanā

Self Cite

“…However, the critical parameters (N, " 1 and " 2 ) are unknown and the task is to estimate the feasible values of the three unknown parameters which shall meet the pre-defined temperature distribution, requirement. For this an inverse problem needs to solved by minimizing the following leastsquares-based objective function, 3,10,19,21…”

Section: Formulationmentioning

confidence: 99%

“…9 For inverse problems, various possible combinations of unknown parameters can exist which may satisfy the same objective. 10 Thus, the exploration of inverse problems is an important and applicable assignment for designing an engineering system for meeting a given requirement, which may be attainment of a particular temperature distribution. 11 It has been noticed that many problems addressing different inverse analyses and optimization of fins are available in the literature.…”

Section: Introductionmentioning

confidence: 99%

Estimation of parameters in a fin with temperature-dependent thermal conductivity and radiation

Proceedings of the Institution of Mechanical Engineers, Part E:

2016

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In this paper an inverse numerical study of a conductive, convective and radiative rectangular fin is carried out with temperature-dependent thermal conductivity. At first, an implicit Runge-Kutta method-based solution is obtained for calculating the temperature distribution, and then an inverse problem is solved for estimation of unknown thermophysical properties. The convection-conduction parameter, variable conductivity parameter and radiative parameter have been simultaneously predicted for satisfying a prescribed temperature distribution. This is achieved by minimizing a least squares-based objective function using a hybrid differential evolution-nonlinear programming optimization algorithm. The results obtained from the forward method are compared with Adomian decomposition and homotopy analysis methods which are found to be satisfactory. It is observed that many feasible combinations of parameters exist which satisfy the same temperature distribution, thus providing an opportunity for selecting any combination from the available alternatives. The effect of convection-conduction parameter on the temperature distribution is observed to be more than other parameters. A case study of different fin materials is also carried out for demonstrating the application of the present methodology.

“…Such cases fall under the purview of inverse prediction problems [11][12][13] and their solution is not necessarily unique. In other words, several possible combinations of unknowns satisfying a given requirement may exist, [14] and thus, the inverse problems are relevant for designing an engineering system [15] and are pertinent to industrial processes. [16] It is observed that for fins, the study of inverse problems is relatively new.…”

Section: Introductionmentioning

confidence: 99%

Identification of materials in a hyperbolic annular fin for a given temperature requirement

Inverse Problems in Science and Engineering

2015

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This article deals with the prediction of parameters in an annular hyperbolic fin with temperature-dependent thermal conductivity. Three parameters such as thermal conductivity, variable conductivity coefficient and the surface heat transfer coefficient have been predicted for satisfying a prescribed temperature distribution on the surface of fin. This is achieved by a hybrid differential evolution-nonlinear programming optimization method. The effect of random measurement errors is also considered. It is observed from the present inverse analysis that many feasible materials exist satisfying the given temperature distribution, thereby providing engineering flexibility in selecting any material from the available choices. For a given material, this is possible by regulating the surface heat transfer coefficient.