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In this study the hydraulic and solute transport properties of an unsaturated soil were estimated simultaneously from a relatively simple small-scale laboratory column infiltration/outflow experiment. As governing equations we used the Richards equation for variably saturated flow and a physical non-equilibrium dual-porosity type formulation for solute transport. A Bayesian parameter estimation approach was used in which the unknown parameters were estimated with the Markov Chain Monte Carlo (MCMC) method through implementation of the Metropolis-Hastings algorithm. Sensitivity coefficients were examined in order to determine the most meaningful measurements for identifying the unknown hydraulic and transport parameters. Results obtained using the measured pressure head and solute concentration data collected during the unsaturated soil column experiment revealed the robustness of the proposed approach.

Cables used in electric power transmission lines are usually composed of layers of stranded metallic wires. Several effects cause a nonuniform distribution of the electric current, which significantly influences heat generation within the cable. The accurate prediction of the cable radial temperature variation is thus of great importance for the design and operation of electric power transmission lines, because of economic and safety reasons. In this work, the Particle Filter method is applied to estimate the transient temperature distribution in the cross section of an Aluminum Conductor Steel Reinforced power cable, by using measurements of the cable surface temperature obtained with an infrared camera. The Sampling Importance Resampling (SIR) algorithm of the Particle Filter method is used for the solution of the state estimation problem, by taking into account uncertainties in the evolution heat conduction model within the cable, as well as in the measured temperatures. The results presented in this work reveal an excellent agreement of the estimated temperatures obtained with the SIR algorithm and temperature measurements from thermocouples inserted into the cable during the manufacturing process, thus validating the proposed approach for the estimation of the radial temperature variation in the power cable. [ABSTRACT FROM AUTHOR]

The present work is aimed at demonstrating and covalidating the experimental and theoretical analysis via infrared thermography and unified integral transforms, respectively, of a partially heated sandwiched plate configuration, recently proposed and employed for space variable thermophysical property identification in heterogeneous media. The plates are heated at their contact with an electrical resistance of known dissipative power, exchanging heat by natural convection and radiation at the external faces. Infrared camera measurements are taken at the external face of one of the plates. Then, a novel open source computational code called UNIT (UNified Integral Transforms), which provides a development platform for finding solutions of partial differential equations by means of integral transforms, is employed in the comparative theoretical analysis. In the corresponding mathematical model, the equation dissipation term suffers an abrupt variation due to the partially applied heat flux (up to half of the plate's height), with the resulting steep heat transfer coefficient at the external surface. The results obtained with the UNIT code show a reasonably good agreement with the experimental data, but also indicate the need for inverse analysis in the proper identification of the abrupt variations in the heat transfer coefficient and of the time lag in the interface heat flux behavior. Thus, a recently developed inverse problem analysis combining infrared thermography, integral transforms and Bayesian inference is here illustrated in simultaneously estimating the thermophysical properties, the applied heat flux, and the heat transfer coefficient functional behaviors. Finally, employing the estimated parameters, an excellent agreement is achieved between experimental and theoretical results. [ABSTRACT FROM AUTHOR]

Inverse heat transfer problems deal with the estimation of parameters or functions appearing in the mathematical formulation of problems in thermal sciences, by utilizing measurements of dependent variables of the formulation. Inverse problems are extremely useful for the indirect measurement of thermophysical properties, in particular for challenging situations involving high temperatures, where coupled multi-physics phenomena and nonlinearities must be taken into account. In this paper, basic inverse problem concepts are reviewed. Solution techniques within the Bayesian framework of statistics are briefly described and applied to two inverse problems related to the authors' experience on the estimation of thermophysical properties at high temperatures. [ABSTRACT FROM AUTHOR]

The article announces that Renato M. Cotta has received the 2022 Luikov Medal from the International Centre for Heat and Mass Transfer (ICHMT).