Nanoarchitectonics of BN/AgNWs/Epoxy Composites with High Thermal Conductivity and Electrical Insulation

To promote the construction of the thermal network in the epoxy resin (EP), a certain proportion of silver nanowires (AgNWs) coupled with the hexagonal boron nitride (BN) nanoplates were chosen as fillers to improve the thermal conductivity of EP resin. Before preparing the composites, BN was treated by silane coupling agent 3-aminopropyltriethoxysilane (KH550), and AgNWs was coated by dopamine hydrochloride. The BN/AgNWs/EP composites were prepared after curing, and the thermal conductivity and dielectric properties of the composites was tested. Results showed that the AgNWs and BN were uniformly dispersed in epoxy resin. It synergistically built a thermal network and greatly increased the thermal conductivity of the composites, which increased 9% after adding AgNWs. Moreover, the electrical property test showed that the addition of AgNWs had little effect on the dielectric constant and dielectric loss of the composites, indicating a rather good electrical insulation of the composites.

DEVELOPMENT OF A METHODOLOGYFOR DETERMINING THE BEST OPTION FOR THE ROUTE OF THE HEAT NETWORK AT THE INITIAL DESIGN STAGE

Statement of the problem. Choosing the best option for the route of the thermal network at the initial stage of design is a complex multifactorial task, in addition, due to the lack of a number of necessary design calculations, its solution is accompanied by a limited set of initial data. Thus, it becomes relevant to develop a new methodology for designing the optimal route of the heat supply system considering the qualitative and quantitative characteristics of the discussed object.Results. A mathematical model of a generalized additive vector optimality criterion has been developed, taking into account the material consumption of the heat network, its reliability, construction time, annual thermal losses, heat turnover and temperature dispersion at the consumer. A method is proposed for determining the best option for the route of a thermal network at the initial design stage by jointly solving the optimization problem using vector optimization and matrix generalization methods. The expediency of the joint application of the methods of pairwise comparison and vector optimization in solving the problem under consideration is noted.Conclusions. An important characteristic of the developed mathematical model of the generalized criterion is the possibility of obtaining a more accurate solution to the optimization problem under consideration with an uneven distribution of the heat load by means of a biased estimate of the temperature variance among consumers. A combination of the methods of matrix generalization, pairwise comparison and vector optimization can improve the accuracy of the calculation while solving the optimization problem of choosing the best route of the thermal network.

Experimental analysis of heat prosumers under low temperature thermal network

This study investigated the applicability and thermal performance of heat prosumers in a bidirectional thermal network through experimental analysis. To realize the bidirectional thermal network and heat prosumers, the existing small-scale centralized district cooling and heating system was retrofitted to form a small-scale heat network with three thermal energy prosumers. The existing small-scale centralized district cooling and heating network consists of seven buildings: high schools, management center, childcare center, baby care center, youth center, library, and public health center. Among these, high school and childcare center were retrofitted from heat consumers to heat prosumers. Control logic for the proposed heat prosumer was also demonstrated. For the case study, the operation of the specific day was selected. The amount of heat supplied from the STES in the management center was 798.7 kWh that contained 17% of the total load. The heat supply from the TES connected to the heat pump in the management center was 2,270.5 kWh, the absorption heat pump for high school. The amount of heat supply for public buildings and schools was 824.0 kWh and 513.8 kWh, respectively, and the heat supply from the childcare center through geothermal heat pump was 295.2 kWh.

Using statistical inverse methods for detecting defects in electronic components

The thermal modeling of electronic components is mandatory to optimize the cooling design versus reliability. Indeed most of failures are due to thermal phenomena [1]. Some of them are neglected or omitted by lack of data: ageing, manufacturing issues like voids in glue or solder joints, or material properties variability. Transient measurements of the junction-to-board temperature supply real thermal behavior of the component and PCB assembly to complete these missing data[2]. To complement and supplement the numerical model, inverse methods identification based on a statistical deconvolution approach, such as Bayesian one, is applied on these measurements to extract a Foster RC thermal network. The identification algorithm performances have been demonstrated on numerical as well as experimental dataset. Furthermore defects or voids can be detected using the extracted Foster RC networks.