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In this work, transient source terms in advection-diffusion problems are recovered. The solution technique proposed relies on the implicit finite difference method coupled with the method of fundamental solutions, a technique for solving partial differential equations when their fundamental solution is known. The Truncated Singular Value Decomposition was used to overcome the ill-conditioned resulting linear system. The advection-diffusion inverse problem was solved using a Eulerian–Lagrangian method. Several numerical examples were considered for testing purposes by using simulated measurements perturbed with a Gaussian random noise for different Reynolds numbers. Results show that the proposed method provides stable and accurate estimates for the source term. [ABSTRACT FROM AUTHOR]

The Reciprocity Functional method, associated to the Classic Integral Transform Technique, has been successfully applied, obtaining analytical solutions for the inverse heat transfer problem that seeks to estimate the thermal contact conductance (TCC) distribution on the interface of a body composed of two materials. Yet, the theoretical development upon which this approach is based is not limited to the need of this interface to have a regular format. This work proposes to extend the method, thus obtaining an analytical development for the estimation of the TCC distribution on interfaces which are not necessarily regular. Several test problems were solved using the techniques described in this work, leading to very good results, with low CPU time usage by the computational implementation. The stability of the method was also verified, via a Monte Carlo analysis considering uncertainties in geometrical and thermophysical properties. The method presented good estimates even when noises were present in the measured temperatures, thermal conductivities, and geometrical dimensions. [ABSTRACT FROM AUTHOR]

Hybrid optimization algorithms consist of a number of proven constituent optimization algorithms and a control algorithm that performs automatic switching among the constituent algorithms at each stage during the optimization when the rate of convergence becomes unsatisfactory, the process tends towards a local minimum, or some other undesirable aspect of the iterative process appears. Thus, hybrid optimization algorithms that utilize a number of gradient based and non-gradient based constituent optimizers are more robust and converge better than individual constituent optimization algorithms. The logic of designing the automatic switching algorithms in hybrid optimizers is surveyed in this paper focusing on the research performed by the authors in the area of hybrid single-objective optimization initiated in 1997.

The reciprocity functional method, associated to the Classic Integral Transform Technique (CITT), has been successfully applied, obtaining analytical solutions for the inverse heat transfer problem that seeks to estimate the thermal contact conductance (TCC) distribution on the interface of a body composed of two materials. Yet, the theoretical development upon which this approach is based is not limited to the need of this interface to have a regular format. This work proposes to extend the method, thus obtaining an analytical development for the estimation of the TCC distribution on interfaces which are not necessarily regular. Several test problems were solved using the techniques described in this work, leading to very good results, with low CPU time usage by the computational implementation. [ABSTRACT FROM AUTHOR]

AbstractThermal contact conductance (TCC) is a critical factor in various engineering applications involving heat transfer between solid surfaces. Accurate knowledge of TCC enables a more precise thermal system analysis, leading to improved efficiency, reduced energy consumption, and prevention of thermal damages. Moreover, TCC estimation can help to identify material discontinuities or failures. A recent tool for TCC estimation is the Reciprocity Functional Method (RFM) coupled with the Classical Integral Transform Technique (CITT). This method allows the solution of inverse boundary value problems without the need of iterative methods or intrusive measurements, making it valuable for nondestructive testing of interfacial flaws between solid materials. Furthermore, it enables the computation of TCCs using analytical expressions, resulting in a computationally fast procedure. The technique involves the solution of two auxiliary problems: one for the temperature discontinuity estimation, and the other for the interfacial heat flux estimation, both at the inaccessible interface between the two contacting materials. In this study, we applied the RFM and the CITT to estimate different types of TCCs, using a three-dimensional double-layer hollow cylinder geometry as a representative model, like double-layer pipelines used in the oil industry. Temperature measurements for solving the inverse problem were considered available on the outer surface of the pipe which, in the case of a real experiment, could be obtained via an infrared camera. The results demonstrated a good estimate for various analyzed test-cases, even when the measurements were contaminated with Gaussian noises. [ABSTRACT FROM AUTHOR]

Considerable amount of thermal energy can be stored when a material undergoes phase change. Paraffin, water, salt hydrates and sugar alcohols are examples of phase change materials (PCM) commonly used for thermal storage, with melting temperatures that can be suitable for several practical applications. In this work, a state estimation problem is solved by using the Particle Filter method, in a physical problem involving phase change of a material with a dispersed phase, like nanoparticles. The equations of heat and mass transfer are coupled through the interface conditions at the moving phase change boundary. A numerical technique based on the enthalpy method was implemented for the solution of the forward problem. The state estimation problem was solved in this work with simulated measurements of temperature and of the solid-liquid interface position, by using an algorithm that allows for simultaneous estimation of state variables and model parameters. [ABSTRACT FROM AUTHOR]