Inverse and optimization problems in heat transfer

Colaço, Marcelo J.; Orlande, Helcio R. B.; Dulikravich, George S.

doi:10.1590/s1678-58782006000100001

Cited by 131 publications

(72 citation statements)

References 44 publications

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“…The designer must also provide an initial guess to the total number, sizes, shapes, and locations of the internal coolant flow passages. Afterwards, the design process uses a constrained optimization algorithm [31,32] to minimize the difference between the specified and computed hot surface heat fluxes by automatically relocating, resizing, reshaping and reorienting the initially-guessed coolant passages. All unnecessary coolant flow passages will be automatically reduced to very small sizes and eliminated while honouring the specified minimum distances between the neighbouring passages and between any passage and the thermal barrier coating if such exists.…”

Section: Determining Number Sizes Shapes and Locations Of Inclusionsmentioning

confidence: 99%

Inverse Problems in Aerodynamics, Heat Transfer, Elasticity and Materials Design

Dulikravich¹,

Dennis²,

Baker³

et al. 2012

International Journal of Aeronautical and Space Sciences

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A number of existing and emerging concepts for formulating solution algorithms applicable to multidisciplinary inverse problems involving aerodynamics, heat conduction, elasticity, and material properties of arbitrary three-dimensional objects are briefly surveyed. Certain unique features of these algorithms and their advantages are sketched for use with boundary element and finite element methods.

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Section: Determining Number Sizes Shapes and Locations Of Inclusionsmentioning

confidence: 99%

Inverse Problems in Aerodynamics, Heat Transfer, Elasticity and Materials Design

Dulikravich¹,

Dennis²,

Baker³

et al. 2012

International Journal of Aeronautical and Space Sciences

Self Cite

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“…Por otra parte, un problema inverso puede verse como un procedimiento para estimar, a partir de una serie de observaciones, las principales causas que lo producen [6]. Una breve revisión de la literatura acerca de los problemas inversos para la estimación de parámetros muestra que en el trabajo de Dasa [7] se predijo la conductividad térmica y el coeficiente de temperatura superficial de una aleta hiperbólica haciendo uso de un algoritmo de optimización.…”

Section: Introductionunclassified

Algoritmos de optimización en la estimación de propiedades termodinámicas en tiempo real durante el tratamiento térmico de materiales con microondas

García

Amaya

Correa

2017

revuin

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Este artículo puede compartirse bajo la licencia CC BY-ND 4.0 y se referencia usando el siguiente formato: E. García, I. Amaya, R. Correa, "Algoritmos de optimización en la estimación de propiedades termodinámicas en tiempo real durante el tratamiento térmico de materiales con microondas", UIS Ingenierías, vol. RESUMENEste trabajo considera la predicción en tiempo real de parámetros térmicos de una muestra sometida a radiación. Se estimaron la conductividad térmica y la capacidad calorífica. Se modeló el flujo volumétrico interno de calor uniforme y constante en el tiempo. Para resolver el problema inverso se usaron algoritmos de optimización global tales como el método de la espiral, el método de búsqueda en vórtice, el método de pesos ponderados, el método de enjambre de partículas unificado, el método de optimización del campo electromagnético y el método de búsqueda armónica de ancho auto-regulado. Los resultados muestran que todos los algoritmos empleados estiman correctamente estos dos parámetros siempre y cuando, la relación señal a ruido (SNR) de las muestras (simuladas en este trabajo) esté por encima de 30 [dB]. Por ende, para propósitos prácticos, si se dispone de un buen diseño experimental y una buena instrumentación, se podrían estimar con alta precisión estos parámetros en tiempo real. PALABRAS CLAVE:Calentamiento por microondas, Estimación de parámetros, Métodos de optimización global, Problema inverso. ABSTRACTThis work considers the real-time prediction of thermal parameters for a cylindrical sample heated in a uniform electromagnetic field. The thermal conductivity ( ) and the heat capacity ( ) were estimated for the present case. The inner volumetric electromagnetic flux radiation process was modeled as uniform and constant in time. The spiral optimization algorithm (SOA), the vortex search (VS), the weighted attraction method (WAM), the unified particle swarm optimization (UPSO), the electromagnetic field optimization (EFO) and the self-regulated fret-width harmony search algorithm (SFHS) were used to solve the ill-posed inverse problem. Results showed that all employed algorithms correctly estimated these two parameter only if the signal-to-noise-ratio of the measured samples (simulated in this work) were above of 30 [dB]. Therefore, for practical purposes, these parameters can be estimated in real-time if a good experimental design and a correctly specified electronic instrumentation are available.

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“…These ammunitions are filled with explosives that detonate to produce the terminal effect. The presence of pores in the explosive inside these devices is a dangerous problem, since this defect could lead to an undesirable initiation of the explosive in addition to changing the terminal effect, therefore reducing the efficiency of the ammunition (Zhang, Hu, & Liang, 2013, Kumar & Rao, 2014 evolutionary method has been employed in inverse problems for parameters estimation (Colaço, Orlande, & Dulikravich, 2006). The present study deals with the estimation of porosity formed during the solidification process.…”

Section: Introductionmentioning

confidence: 99%

<b>Inverse problem for porosity estimation during solidification of TNT

2016

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ABSTRACT. In the present study, the porosity formed during the solidification process is estimated by an inverse problem technique based on particle swarm optimization. The effective heat capacity method is adopted to model the heat transfer problem. The transient-diffusive heat transfer equation is solved numerically by the finite volume method with an explicit scheme, employing the central difference interpolation function. The solution of the direct problem is compared to reference solutions. The model is applied to trinitrotoluene (TNT) solidification process. The results show that the proposed procedure was able to estimate the porosity for different Stefan numbers. The analysis of the heat flux in the mold is indicated to predict the porosity formation during the casting process.

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Inverse and optimization problems in heat transfer

Cited by 131 publications

References 44 publications

Inverse Problems in Aerodynamics, Heat Transfer, Elasticity and Materials Design

Inverse Problems in Aerodynamics, Heat Transfer, Elasticity and Materials Design

Algoritmos de optimización en la estimación de propiedades termodinámicas en tiempo real durante el tratamiento térmico de materiales con microondas

<b>Inverse problem for porosity estimation during solidification of TNT

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