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Adaptive façades, also known as climate-adaptive building shells (CABSs), could make a significant contribution towards reducing the energy consumption of buildings and their environmental impacts. There is extensive research on glazed adaptive façades, mainly due to the available technology for glass materials. The technological development of opaque adaptive façades has focused on variable-thermal-resistance envelopes, and the simulation of this type of façade is a challenging task that has not been thoroughly studied. The aim of this study was to configure and validate a simplified office model that could be used for simulating an adaptive façade with variable thermal resistance via adaptive insulation thickness in its opaque part. Software-to-software model comparison based on the results of an EnergyPlus Building Energy Simulation Test 900 (BesTest 900)-validated model was used. Cooling and heating annual energy demand (kWh), peak cooling and heating (kW), and maximum, minimum, and average annual hourly zone temperature variables were compared for both the Adaptive and non-adaptive validated model. An Adaptive EnergyPlus model based on the BesTest 900 model, which uses the EnergyPlus SurfaceControl:MovableInsulation class list, was successfully validated and could be used for studying office buildings with a variable-thermal-resistance adaptive façade wall configuration, equivalent to a heavyweight mass wall construction with an External Insulation Finishing System (EIFS). An example of the Adaptive model in the Denver location is included in this paper. Annual savings of up to 26% in total energy demand (heating + cooling) was achieved and could reach up to 54% when electro-chromic (EC) glass commanded by a rule-based algorithm was added to the glazed part of the variable-thermal-resistance adaptive façade.

This paper presents a simulation based on the boundary element method for the optimization of the thermomechanical behavior of three-dimensional microchip-dissipator packaging when the heat generation produced is medium-low. Starting from a basic architecture studied in the literature, different modifications affecting both elastic boundary conditions and the contact interface between the microprocessor and the heatsink are included and studied in order to improve heat dissipation. A nonlinear interface material is included at the interface of both solids. Thus, a thermal contact conductance as a function of the normal contact traction is simulated. Finally, all these improvements in both contact interface and boundary conditions are applied to study the maximum heat generation that this kind of architecture can efficiently dissipate, so that the microchip will not be damaged due to thermal deformations.

We used a clothing thermal resistance model to investigate and compare the effects of climate and human variability on human thermal load. To investigate the effect of climate variability, we introduced the mean clothing thermal resistance rcl¯. For characterizing the effect of human variability, we used the standard deviation of clothing thermal resistance ∆rcl. We distinguished people based on their body type. We also defined the average human, a man and a woman, with thermal resistances of rcl,m and rcl,f. The investigation was carried out for the European region in the cold season for the period of 1981–2010. The climate variables were taken from the ERA5 reanalysis database. Our most important results are the following. (1) The macroscale pattern of the rcl¯ and ∆rcl fields are very similar, based on which it can be stated that human variability does not modify the spatial distribution of rcl¯. (2) The ∆rcl values are roughly a quarter of the rcl¯ values. The highest rcl¯ values (3.2–3.4 clo) are in Lapland, and the smallest (1–1.2 clo) in Andalusia. (3) The macroscale pattern of the rcl,m and rcl,f fields is similar to the macroscale pattern of the rcl values of the mesomorphic person rcl,2. The field of rcl,2 can be used for climate classification purposes.

The current review uses the material requirements of a new space propulsion device, the Variable Specific Impulse Magnetoplasma Rocket (VASIMR ® ) as a basis for presenting the temperature-dependent properties of a range of dielectric ceramics, but data presented could be used in the engineering design of any ceramic component with complementary material requirements. A material is required for the gas containment tube (GCT) of VASIMR ® to allow it to operate at higher power levels. The GCT’s operating conditions place severe constraints on the choice of material. An electrically-insulating material is required with a high-thermal conductivity, low-dielectric loss factor, and high-thermal shock resistance. There is a lack of a representative set of temperature-dependent material property data for materials considered for this application and these are required for accurate thermo-structural modelling. This modelling would facilitate the selection of an optimum material for this component. The goal of this article is to determine the best material property data values for use in the materials selection and design of such components. A review of both experimentally and theoretically determined temperature-dependent and room temperature properties of several materials has been undertaken. Data extracted are presented by property. Properties reviewed are density, Young’s, bulk and shear moduli, Poisson’s ratio, tensile, flexural and compressive strength, thermal conductivity, specific heat capacity, thermal expansion coefficient, and the factors affecting maximum service temperature. Materials reviewed are alumina, aluminium nitride, beryllia, fused quartz, sialon, and silicon nitride.

The comfort level of outdoor thermal environments is affected by several factors. Previous studies of thermal comfort have generally investigated the main microclimatic factors as dependent variables, such as the temperature, wind speed, humidity, and thermal radiation, but the influence of the air quality has rarely been explored. In this study, we acquired meteorological element observations and conducted questionnaire surveys in Peach Blossom Park, Hebei University of Technology, and Xigu Park in Tianjin. We analyzed the effects of the outdoor air quality and thermal environment on the thermal comfort in order to provide a theoretical basis for comprehensive evaluations of the outdoor environment and the mechanism. The results showed that thermal resistance of clothing and ambient temperature followed a negative step change, where people generally reduced the minimum amount of clothing when the temperature exceeded 28 °C. One unit change in the thermal sensation vote (TSV) occurred for every 11 °C rise in the physiological equivalent temperature (PET). The neutral PET was 21.68 °C, and the comfortable PET was about 23 °C. The air quality index (AQI) and air satisfaction were negatively correlated, and satisfaction decreased by 1 unit for every change of 230 AQI. The transitional season was most comfortable when the temperature felt slightly cool ( TSV = −0.70). The neutral TSV was 0.507 in the summer and −0.334 in the winter. Air quality had a significant effect on the thermal comfort vote (TCV) ( p = 0.0485 < 0.05). The effect of PET on TCV was highly significant ( p < 0.01).

Purpose This study aims to introduce a deep neural network (DNN) to estimate the effective thermal conductivity of the flat heat pipe with spreading thermal resistance. Design/methodology/approach A total of 2,160 computational fluid dynamics simulation cases over up to 2,000 W/mK are conducted to regress big data and predict a wider range of effective thermal conductivity up to 10,000 W/mK. The deep neural networking is trained with reinforcement learning from 10–12 steps minimizing errors in each step. Another 8,640 CFD cases are used to validate. Findings Experimental, simulational and theoretical approaches are used to validate the DNN estimation for the same independent variables. The results from the two approaches show a good agreement with each other. In addition, the DNN method required less time when compared to the CFD. Originality/value The DNN method opens a new way to secure data while predicting in a wide range without experiments or simulations. If these technologies can be applied to thermal and materials engineering, they will be the key to solve thermal obstacles that many longing to overcome.

A discrete variable topology optimization method of internally finned ducts in heat exchangers for efficient thermal performance is proposed. Fully developed convective heat transfer (FDCHT) model, which has been extensively employed and well checked in practical thermal engineering applications, is considered here. Under the uniform wall temperature boundary condition, the energy equation of the FDCHT model can be mathematically formulated as a generalized eigenvalue equation, and the total thermal resistance reflecting the thermal performance can be related to the eigenvalue. The well-known eigenvalue optimization formulation and sensitivity analysis is applied to this optimization problem. Significantly, the physical reality, such as precise Nusselt number, is maintained by using the discrete variable method, i.e., Sequential Approximate Integer Programming. Here, only the 0–1 densities denoted to solid and fluid are involved so that blurry intermediate zones and interpolation schemes are avoided. The practical engineering conditions of fixed pumping power and fixed fluid volume flow rate are discussed under the unified framework, respectively. Several designs of internally finned ducts without any blurry zone are obtained. The optimized design conforms to the three-dimensional precise Conjugate Heat Transfer calculation. Numerical results show that contrary to the design method by predefined heat transfer coefficient, the proposed method can automatically obtain the optimal shape and spacing of fins since the spatially varying effect of convective heat transfer has been achieved.

Thermal analysis of compressible flow under peristalsis is stimulated by its extensive utility in geophysics, thermal storage devices and in other industrial operations. With regard to these utilities, this work is aimed at heat transfer analysis of unsteady compressible flow of an electrically conducting viscous fluid under peristalsis. Considerations are made for an asymmetric channel with velocity and thermal slip conditions. Thermal analysis has been taking into account in the presence of viscous dissipation and joule heating effects. Mass and momentum conservation laws, equation of state and energy equation are employed to numerically model the current problem. Explicit finite difference method is used to numerically solve the resulting nonlinear partial differential equations. Graphical representations are used to show the effect of pertinent parameters on axial velocity, dimensionless temperature and heat transport rate. It has been demonstrated that the magnetic field trims down the fluid’s velocity. Also, higher Prandtl number exhibit lower thermal diffusivity which in turn causes the fluid temperature to fall. In general, the temperature rises along with the Mach number. This is because, in accordance with the ideal gas law, the compressibility effects increase the pressure and density, which in turn raises the temperature.

This numerical modelling has enabled the prediction of wear rates in different materials and for different sliding conditions. It has also enabled the development of more efficient and reliable wear-resistant materials. Additionally, this modelling has been applied to improve the performance of existing components and to design new ones. The WC-Co coatings are used for wear resistance applications. The paper discusses the numerical modelling approach used for the development of coatings. The different governing equations have been discussed for the development of coatings with respect to process parameters. In this article, discuss the effects of Plasma spraying (PS), cold spraying, HVOF, and DS produce particles with the maximum temperature. WC, WC-12Co, WC-CoCr, WC-(W,Cr), Cr 3 C 2 –NiCr, and TiC feedstock powders cover surfaces in thermal spray coating. HVOF deposition coats a variety of substrates efficiently and economically. HVOF deposits homogeneous coatings with low porosity and great wear and corrosion resistance. Heat treatment can improve thermal spray coatings after processing. As a final point, advances in numerical modelling of sliding wear rate are discussed in this article.

The exploration of various nanoparticles has become a focal point for researchers, driven by its potential applications in both industry and medicine. Nanoparticles can be incorporated in several shapes and sizes, hence this paper examines the nanofluid’s performance in a peristaltic channel under the impact of combined external applied electric and magnetic fields, in addition to thermal radiation and Joule heating effects. The present study also examines the non-isothermal characteristics with no slip convection for four distinct nanoparticles, namely Iron oxide ( F e 3 O 4 ), Copper (Cu), Gold (Au), and Silver (Ag). Shape effects of nanomaterial are also considered. Arising nonlinear system is tackled numerically employing the integrated package NDSolve in Mathematica by the implementation of weaker Reynolds number and long wavelength assumptions. Current findings expose that radiation has a beneficial impact on controlling the velocity and temperature within the channel. Increase in radiation parameter leads to reduce both velocity and temperature by approximately 2 . 39 % and 18 . 18 % respectively. An improvement of up to 2 . 28 % in heat transfer rate can be achieved by utilizing spherical iron oxide nanoparticles for thermal conductivity parameter of range 0 . 00 − 0 . 10 . Furthermore, silver nanoparticles provide better thermal conductivity compared to other nanoparticles.