This research introduces a novel framework integrating stochastic finite element analysis (FEA) with advanced circular statistical methods to optimize heat pump efficiency under material uncertainties. The proposed methodologies and optimization focus on balancing the mean efficiency and variability by adjusting the concentration parameter of the Von Mises distribution, which models directional variability in thermal conductivity. The study highlights the superiority of the Von Mises distribution in achieving more consistent and efficient thermal performance compared to the uniform distribution. We also conducted a sensitivity analysis of the parameters for further insights. The results show that optimal tuning of the concentration parameter can significantly reduce efficiency variability while maintaining a mean efficiency above the desired threshold. This demonstrates the importance of considering both stochastic effects and directional consistency in thermal systems, providing robust and reliable design strategies.

Heat removal has become an increasingly crucial issue for microelectronic chips due to increasingly high speed and high performance. One solution is to increase the thermal conductivity of the corresponding dielectrics. However, traditional approach to adding solid heat conductive nanoparticles to polymer dielectrics led to a significant weight increase. Here we propose a dielectric polymer filled with heat conductive hollow nanoparticles to mitigate the weight gain. Our mesoscale simulation of heat conduction through this dielectric polymer composite microstructure using the phase-field spectral iterative perturbation method demonstrates the simultaneous achievement of enhanced effective thermal conductivity and the low density. It is shown that additional heat conductivity enhancement can be achieved by wrapping the hollow nanoparticles with graphene layers. The underlying mesoscale mechanism of such a microstructure design and the quantitative effect of interfacial thermal resistance will be discussed. This work is expected to stimulate future efforts to develop light-weight thermal conductive polymer nanocomposites.

The use of saline water in agriculture is a viable alternative, considering the increased demand for fresh water. The objective of this study was to evaluate the growth and phytomass production of sugar beet under irrigation with water of different saline concentrations in a field experiment on the campus of the Federal University of Alagoas in Arapiraca. The treatments were five levels of electrical conductivity (1.0, 2.0, 3.0, 4.0 and 5.0 dS m^-1). The design was in randomized blocks, with four repetitions. The maximum yield of sugar beet at 27 days after the application of saline treatments was obtained with a salinity of 3.0 dS m^-1, for the variables plant height (PA), stem diameter (CD), root length (RC), aboveground dry phytomass (FSPA) and total dry phytomass (FST). At 42 days after the application of saline treatments, the variables aboveground fresh phytomass (FFPA), root fresh phytomass (FFR), total fresh phytomass (FFT), aboveground dry phytomass (FSPA) and total dry phytomass (FST) increased with increasing water salinity. Rain may have influenced the results obtained for the evaluations, performed at 42 days after the application of the saline treatments.

In this paper, electrically conductive composites comprised of silicone rubber and titanium diboride (TiB₂) were synthesized by conventional mixing methods. Fine particles of TiB₂ (in micron size) and 10 parts per hundred parts of rubber (phr) proportion of carbon black (XC-72) were used to make the composites with HTV silicone rubber. The composites were cured at appropriate temperature and pressure and the effect on the electrical properties was studied. The resistance of the silicone rubber is ~ 10¹⁵Ω which decreases to 1–2 kΩ in case of composites with negligible effect of heat ageing. The hardness increases by ~ 35% simultaneous to the decrease of ~ 47% in the tensile strength. Morphological characterization indicates the homogeneous dispersion of the fillers in the composite.

We present an innovative enthalpy method for determining the thermal properties of phase change materials (PCM). The enthalpy-temperature relation in the “mushy” zone is modelled by means of a fifth order Obreshkov polynomial with continuous first and second order derivatives at the zone boundaries. The partial differential equation (PDE) for the conduction of heat is rewritten so that the enthalpy variable is not explicitly present, rendering the equation nonlinear. The thermal conductivity of the PCM is assumed to be temperature dependent and is modelled by a fifth order Obreshkov polynomial as well. The method has been applied to lauric acid, a standard prototype. The latent heat and the conductivity coefficient, being the model parameters, were retrieved by fitting the measurements obtained through a simple experimental procedure. Therefore, our proposal may be profitably used for the study of materials intended for heat-storage applications.