Relative Thermal Conductivity Research Articles

A unified hybrid micromechanical model for predicting the thermal and electrical conductivity of graphene reinforced porous and saturated cement composites

Graphene fillers have gained widespread attention as functional reinforcements for cement composites due to their excellent physical properties. The prediction of the thermal and electrical properties of graphene reinforced cement composites (GRCCs) is of great importance for developing intelligent and multifunctional civil engineering materials and structures. In this current work, a unified hybrid micromechanical model combining effective medium theory (EMT) and Mori-Tanaka-Benveniste (MTB) is developed to simultaneously predict the thermal and electrical conductivity of the GRCCs with considering pores and saturation, in which mechanisms including phonon transport, electron tunnelling and Maxwell-Wagner-Sillars (MWS) polarization are incorporated. Graphene nanoplatelets (GNPs) reinforced cement composites (GNPRCCs) samples are prepared and tested to validate the developed unified model. The results show that the electrical conductivity of the GNPRCCs is more sensitive to saturation than the thermal conductivity. When the porosity n = 0.2 and the GNP concentration is 1 wt%, the relative thermal and electrical conductivity increases by 5 % and 193 %, respectively, when the saturation index increases from 0.6 to 1. Elongated pores are more favorable for the formation of ionic networks for electrical conductivity in the saturated GNPRCCs, while spherical pores are more beneficial for heat transport. Elongated graphene fillers are preferred for enhancing both the thermal and electrical conductivity of dry and saturated GNPRCCs. The work is envisaged to provide guidelines for developing multifunctional cement composites.

A Comment on the Utility of Nanofluids: Interactive Influence of Nanoparticle Size and Amount at Varying Temperatures

Interactive influence of nanoparticle diameter, dp and volumetric fraction, φ on major thermophysical characteristics of relative thermal conductivity, kr and dynamic viscosity, μr of nanofluids as a primary function of temperature, T is determined to assess the utility of nanofluids. In the case study common base fluids of water (W) and ethylene glycol (EG) are used. Spherical shape Ag and Al2O3 with a selected dp range of (20–100 nm) are used in the covered φ range of (0.25–5%). Influence of T is set by considering T = 293 K and T = 323 K. The referred data ranges are applied for the calculation of kr and μr of nanofluids Ag–W, EG and Al2O3–W, EG in reference to a calculation procedure provided previously by the authors. The calculated magnitudes of kr and μr are expressed as a function of dp, φ and T. The results reveal that kr and μr rise dramatically as dp decrease from 40 nm to 20 nm and φ increase from 2% to 5% at T = 293 K and T = 323 K. The calculations confirm the relevant literature that the required pumping power increase is associated with low dp and high φ. Therefore, here exists limiting magnitudes of dp, φ as a function of T for the effective utilization of nanoparticles in base fluids. In order to generalize the fact non-dimensional parameters of Prandtl Number, Pr and Reynolds Number, Re should be referred due to the definitions of each depend on thermophysical characteristics and the cited dp, φ and T. The calculations herein have the validity range of Re and Pr of base fluids as 0.0002–0.032 and 3.58–210.30, respectively.

Thermo-capillarity of immiscible binary fluids within serpentine micro-confinements

The thermocapillary flow of multiple liquid layers over contoured substrates finds applications in many industrial phenomena via micro-electromechanical systems/nano-electromechanical systems devices. This study theoretically explores the thermocapillary transport of binary-liquid layers in a wavy microchannel with serpentine wall profiles. Sinusoidal profiles are considered for the microchannel walls' temperature and surface topology. Patterned slip conditions at the walls are also accounted for in the analysis to make the problem more realistic. We semi-analytically solve the energy and momentum equations to understand the system's thermal and hydrodynamic characteristics for the limiting conditions of Ma, Re, and Ca. The leading- and higher-order solutions of the temperature and flow field are separately shown to demonstrate the advection terms' contribution to the transport equations. The circulatory flow obtained due to periodic thermal stimuli can be used to enhance the mixing efficiency of the system. We also present how the parameters like phase difference between the thermal stimulus, relative thermal conductivity, and relative film thickness ratio of the liquid layers can be altered to control the flow characteristics to obtain the most potent thermocapillary effect.

Multiscale modelling for the thermal transport behaviour of ceramic matrix composites with hierarchical structures

Ceramic matrix composites contain many initial defects due to their “ceramic” properties and process characteristics, which presents challenges for the accurate prediction of their material equivalent properties. In this paper, multiscale and high-fidelity modelling of fibre-reinforced C/SiC composites are carried out on a “macro-meso-micro” cross-scale, and the thermal conductivity and relative thermal conductivity of multilevel structure composites based on a hierarchical multiscale model are proposed. The influence laws of SiC porous matrix, carbon fibre volume fraction and temperature on the thermal conductivity of composite materials are given. These findings provide useful insights into equivalent computational methods for material properties under the defect growth of thermomechanical loading.

Novel B4C[sbnd]TiB2 composites with high electrical and low thermal conductivity by selective grain growth in reactive sintering

High electrical conductivity and low thermal conductivity are beneficial for the electrical discharge machining performance of ceramics. In this work, B4C–TiB2 composites were prepared by spark plasma sintering of B4C–TiC–B powder mixture. The chemical reaction between TiC and B, together with subsequent selective matrix grain growth, expelled small in-situ generated TiB2 grains to form conductive interlayers around large B4C grains. The unique microstructure significantly enhances the electrical conductivity of B4C–TiB2 composites, especially at low TiB2 content, while the ultrafine in-situ formed TiB2 grains endow the composites with low thermal conductivity. The effects of TiB2 content on the microstructure, mechanical properties, thermal & electrical conductivity of the composites were investigated. B4C–20 vol% TiB2 composite exhibits excellent comprehensive performance, including a relative density, Vickers hardness, flexural strength, fracture toughness, room electrical and thermal conductivity of 98.6%, 28.15 GPa, 656 MPa, 5.46 MPa⋅m1/2, 1.08 × 105 S/m and 19.37 W/m⋅K, respectively.

Hybrid knitted fabric for electromagnetic radiation shielding: thermo-physical properties

Textile materials for protection against electromagnetic radiation are used now not only for special purposes but in everyday clothing too. In this regard, the thermo-physical properties of such materials are very important. In this study, the hybrid knitted fabrics with electromagnetic shielding properties manufactured on 8E flat-bed machine from 0.12 mm stainless steel wire and 30 × 2 tex cotton yarn have been tested. Fabric samples differ by variant of stainless steel wire incorporation (separately or along with cotton yarn) and their positioning in the structures (loop and/or tuck). Hybrid fabric formed by the alternation of two courses of rib 1 × 1 from cotton yarn and two courses from steel wire has higher porosity and therefore higher relative water vapor permeability and lower thermal conductivity compared with fabric formed from cotton yarn and a steel wire simultaneously. The research results showed that the introduction of stainless steel wire along with cotton yarn into the knitted structure leads to changes in stitch density and therefore in the area of porosity compared with cotton fabric. The thermal conductivity coefficient and evaporative resistance of these fabrics are similar to cotton 1 + 1 rib fabric. Thus, the studied hybrid knitted fabrics with shielding properties against electromagnetic radiation can be recommended for clothing manufacturing. The half-Milano rib fabric knitted from cotton yarn and a steel wire with the greatest electromagnetic interference shielding effectiveness has a good level of comfort similar to cotton fabric.

Enhancing cryogenic thermal conductivity of epoxy composites through the incorporation of boron nitride nanosheets/nanodiamond aerogels prepared by directional‐freezing method

AbstractIn the realm of electronic circuits, materials with high thermal conductivity are sought after as ideal packaging components. It is crucial that such materials not only possess excellent thermal conductivity, but also maintain desirable dielectric properties. To this end, boron nitride nanosheets (BNNS) and BNNS/nanodiamond (ND) aerogels with a three‐dimensional (3D) structure using the ice‐template method were prepared. Subsequently, these aerogels were utilized as a framework to produce 3D‐BNNS/epoxy and 3D‐BNNS/ND/epoxy composites via the vacuum‐assisted impregnation method, which exhibit enhanced anisotropic thermal conductivity. Furthermore, the thermal conductivity exhibited by the 3D‐BNNS/epoxy composites outperforms those containing randomly distributed BNNS. The experiment also reveals sintering the aerogel at elevated temperatures to remove the PVA can significantly improve the thermal conductivity exhibited by the 3D‐BNNS/epoxy and 3D‐BNNS/ND/epoxy composites. Importantly, the 3D‐BNNS/ND/epoxy composites illustrate exceptional thermal conductivity values of 1.326 W/(m·K), indicating a remarkable synergistic effect of BNNS and ND in improving thermal conductivity. It is noteworthy to state that the relative thermal conductivity ratio of the 3D‐BNNS/epoxy and 3D‐BNNS/ND/epoxy composites to pure epoxy resin was markedly higher at lower temperatures than the values measured at room temperature, signifying their superior heat transfer performance at lower temperatures. In addition, the composites depict excellent dielectric properties and lower coefficients of thermal expansion values. Finally, the 3D‐BNNS/ND/epoxy composites also have significantly improved Tg (132.5 and 152.6°C). The high‐performance polymer composites described in this study are envisaged for implementation within the realm of electronic packaging materials.

Predicting the temperature field of thermal cloaks in homogeneous isotropic multilayer materials based on deep learning

Thermal cloaks can realize thermal manipulation and have been widely applied in the engineering field. Traditional methods, like the finite element method (FEM) and finite difference method, obtain the temperature of the thermal cloak with time-consuming. A deep learning model is proposed to predict the temperature field in homogeneous isotropic multilayer materials. The FEM is applied to solve the thermal cloak and the training data are obtained. The layer's properties, including different layers, thickness, relative thermal conductivities and distribution modes, of the thermal control or manipulative ability for temperature and heat diffusion are also investigated. The deep learning mode is developed by mapping the parameters layout to the temperature field as an image-to-image regression task and the relationship between the layer's properties and the cloaking performances is intelligently established. The temperature field of the arbitrary layout composite can be acquired almost with no time cost. The temperature field with the largest node numbers of medium temperature by the FEM and the deep learning model, is exhibited and compared. Furthermore, we extend the surrogate model to different cases with different boundary conditions, which can still achieve good prediction results. Owing to the high efficiency and complete independence from the mesh densities, the proposed method offers a novel and robust technique for predicting the temperature field and suggestion for the design of the thermal cloak.

Marangoni Flows in a Bilayer Liquid Microfilm Interface on Wave-Contoured Hot Substrates.

This study explores the thermal Marangoni hydrodynamics in an immiscible, binary-liquid thin-film system, which is open to the gas phase at the top and rests on a heated substrate with wavy topology. The sinusoidal contour of the heated (constant-temperature) substrate results in temperature gradients along the liquid-liquid and liquid-gas interfaces, causing fluctuations in the interfacial tension, ultimately leading to Marangoni hydrodynamics in the liquid-liquid films. This type of flow is notable in liquid film coatings on patterned surfaces, which are widely used in MEMS/NEMS applications (Weinstein, S. J.; Palmer, H. J. Liquid Film Coating: Scientific Principles and Their Technological Implications; 1997, pp 19-62; Palacio, M.; Bhushan, B. Adv. Mater. 2008, 20, 1194-1198) and biological cell sorting operations (Witek, M. A.; Freed, I. M.; Soper, S. A. Anal. Chem. 2019, 92, 105-131). We solve the coupled Navier-Stokes and energy equations by the perturbation technique to obtain approximate analytical solutions and an understanding of the thermal and hydrodynamic transport in the system domain. Our study explores the parametric influence of the relative thermal conductivity of the liquid layers (k), film thickness ratio (r), and the system's Biot number (Bi) on these transport phenomena. While the strength of the thermal Marangoni effect that is generated reduces with an increase in the relative thermal conductivity (k), the impact of r depends on the k value. We observe that for k > 1 the intensity of Marangoni flow increases with r; however, the opposite holds for k < 1. Furthermore, larger values of Bi induce higher resistance to the vertical conduction from the wavy substrate compared to the convection resistance offered at the top surface, destructively interfering with the ability of the patterned substrate to generate interfacial temperature fluctuations and hence weakening the Marangoni flow.

Artificial intelligence optimization and experimental procedure for the effect of silicon dioxide particle size in silicon dioxide/deionized water nanofluid: Preparation, stability measurement and estimate the thermal conductivity of produced mixture

Recent studies for nanofluids, did not pay enough attention to the effect of the nanoparticle size and nanofluid stability on the heat transfer rate. In this study, the thermal conductivity (TC) coefficient of silica/deionized water (DW) nanofluid with various sizes of nanoparticles and various rates of nanofluid stability was investigated. Validation experiments, including X-Ray diffraction analysis (XRD), FE-Scanning Electron Microscopy (FE-SEM), Dynamic Light Scattering (DLS), and Zeta Potential (Zp), were carried out to examine the particle sizes and the nanofluid stability. The results illustrated that increasing the temperature leads to the augmentation of the TC coefficient of the SiO2/deionized water in all nanoparticle sizes and all volume concentrations. Also, increasing the volume concentration of the nanofluid leads to the augmentation of the TC coefficient of the nanofluid in all nanoparticle sizes and all temperatures. Eventually, increasing the nanoparticle sizes causes the TC coefficient of the nanofluid to be decreased in all volume concentrations. For the 11 nm nanoparticle size, the amount of the Relative TC (RTC) coefficient enhancement by increasing the temperature was 1.2%, 2.5%, 4.7%, and 6.8% for concentrations of 0.0.1%, 0.1%, 0.5%, and 1%, respectively. For the 50 nm nanoparticle size, this enhancement was from 0.7% to 6.5%, and for the 70 nm nanoparticle size, it was from 0.5% to 5.7%. Finally, Artificial Intelligence (AI) optimization was done to find the optimized size and stability.

Shape retention of W-30Cu composites prepared by 20 wt% Cu melt infiltration into W-10Cu green parts made via BJ3DP

In this work, W-30Cu, W-10Cu, and W green parts were fabricated using BJ3DP, and then 0 wt% Cu, 20 wt% Cu, and 30 wt% Cu were infiltrated to prepare W-30Cu composites, respectively. The effects of Cu infiltration content (0–30 wt%) on the shape retention and properties of W-30Cu composites were studied. The experimental results showed that when the Cu infiltration content was 20 wt%, the W-30Cu composite prepared by 20 wt% Cu melt infiltration into W-10Cu green part had the best shape retention, its shrinkage was within 0.5%, and the relative density and thermal conductivity were 97.75% and 218 W·m−1·K−1, respectively. In this work, a high-shape-retention W-30Cu composite was obtained by treating W-10Cu green part prepared by BJ3DP using a combination of sintering technology and infiltration technology, while also providing a high-shape-retention method for other composites.

Tailoring porosity and pore structure of cellular geopolymers for strength and thermal conductivity

Cellular geopolymer is produced by entraining air in alkali-activated low calcium fly ash (AAF) paste. Rheology control with the use of Bentonite clay and surfactant creates stable aeration on adding Aluminum powder to AAF paste. The clay provides yield stress control in the AAF paste that is required for retaining the bubbles in the suspension. The surfactant is used to prevent the coalescence of the air bubbles in the AAF paste that produces a homogenous void network in the cellular geopolymer. The viscosity of the AAF paste is determined by the silica content and modulus (molar ratio of SiO2/Na2O) of the activating solution. Process variables such as Aluminum powder content and size, clay and surfactant dosages and composition of activating solution are considered to tailor the porosity and pore size in the cellular geopolymer. The total porosity of the cellular geopolymer depends on the viscosity of the AAF paste, which is controlled by the silica content and modulus of the activating solution. The mean pore size and its distribution depend on the Aluminum powder size. The mean pore size decreases with an increase in yield stress of the AAF paste and a decrease in the surface tension. Cellular geopolymer with density lower than 1000 Kg/m3 with thermal conductivity in the range of 0.25–0.20 W/m.K and compressive strengths of 11.5 to 8.5 MPa are produced by controlling the process variables. The strength of the cellular geopolymer depends on the mean pore size in addition to the total porosity. The thermal conductivity is dependent only on the total solidity and hence on the total porosity and is not affected by the pore size distribution. The existing models used for predicting the strength and thermal conductivity in relation to porosity and pore characteristics are explored and modifications are proposed for cellular geopolymers.

Enhanced thermal conductivity of Si3N4 ceramics through pyrolytic carbon prepared by gel casting using DMAA

To reduce the lattice oxygen content of Si3N4 green bodies, samples were prepared using an N,N-dimethylacrylamide (DMAA) system. The endothermic and exothermic peaks are related to the decomposition of organic matter and the reaction between pyrolytic carbon and impurity oxides in the sintering process. Multi-step heat preservation during the thermal degreasing process reduced the carbon content and defects. The α→β phase transformation and aspect ratio of grains changed from 89.2% to 4.84:1 at 1640 °C to 96.3% and 7.80:1 at 1700 °C, respectively. The relative density, hardness, fracture toughness, and thermal conductivity of the Si3N4 samples reached 98.5%, 1353 HV, 8.51 MPa·m1/2, and 97.1 W·m−1·K−1, respectively. Pyrolytic carbon can react with SiO2, which reduces the content of the glass phase in the green body and affects the dissolution and precipitation process and lattice oxygen content. In the structure of the Si3N4 sample, carbon particles with sizes of 100–500 nm and near-spherical shapes were observed. Intergranular-phase YMgSi2O5N was formed during the sintering process, which was conducive to improving the thermal conductivity. This article uses lower temperature and no pressure conditions to prepare Si3N4 ceramics, which can provide reference for batch and low-cost production.

Thermal conductivity of MWCNT-TiO2/Water-EG hybrid nanofluids: Calculating the price performance factor (PPF) using statistical and experimental methods (RSM)

Scientists in chemical and mechanical engineering fields have long been interested in the thermophysical characteristics of nanofluids (NFs), and the thermal conductivity (TC) of many NFs has recently been studied. Purpose of research is to evaluate and compare two new and unique NFs using experimental methods and statistical methods (response surface methodology or RSM) to introduce one of them to the industry. In this research, hybrid nanofluid (HNF) “A” with MWCNT and TiO2(25:75) with Water-EG (80:20) formula and HNF “B” with MWCNT-TiO2(15:85)/Water-EG(50:50) formula were synthesized. Their relative thermal conductivity (RTC) was compared. Based on the findings, HNF “A” in solid volume fraction SVF = 1.12% and T = 50°C has a thermal conductivity enhancement of TCE = 36.30%, which is superior to HNF “B” with TCE = 17.90%. The price performance factor (PPF) of the analyzed HNFs has been studied and compared for the first time in this research under the same settings. In addition, the examination of economic and performance indicators shows that HNF “A” has a significantly higher PPF. As a result, it can be said that using this HNF is economical.

Structural, microstructural, and microwave dielectric properties of (Al1-xBx)2Mo3O12 ceramics with low dielectric constant and low dielectric loss for LTCC applications

The (Al1-xBx)2Mo3O12 ceramics with double phases were prepared by solid-phase sintering method at the temperature from 725 to 800 °C for LTCC application. Through XRD pattern and Rietveld refinement analysis, it was confirmed that the (Al1-xBx)2Mo3O12 composition consists of the coexistence of double phase (the monoclinic structure of the P21/a space group and the orthorhombic structure of the Pnca space group), and the orthorhombic phase was increased with boron substitution. The microwave dielectric properties of the (Al1-xBx)2Mo3O12 ceramic series were impacted by double-phase formation (crystal structure ratio), which increases the densification and grain uniformity. With the boron substitution, the (Al1-xBx)2Mo3O12 ceramic series demonstrate outstanding microwave dielectric properties (εr = 4.04, Q × f = 35870 GHz @ 15 GHz, τƒ = 4.2 ppm/°C) with high relative density (ρrel ≈ 98.84%) and thermal conductivity κ = 0.88 W/m.K for x = 0.3 at 775 °C, indicate that it is a promising candidate for LTCC substrate material.

Theoretical -Experimental study of factors affecting the thermal conductivity of SWCNT-CuO (25:75)/water nanofluid and challenging comparison with CuO nanofluids/water

In this theoretical–experimental study, the basic parameters effect such as solid volume fraction (SVF or φ) and temperature on thermal conductivity (TC) of SWCNT-CuO (25:75)/water nanofluid (NF) has been investigated. The used NF in this study has been prepared and used for the first time. Monitoring and investigation of TC were done in T = 28 to 50˚C and SVF = 0.03 % to 1.15 %. The role of SVF effective in relative thermal conductivity (RTC) with changing of the temperature shows the importance of this factor in improving the RTC; results show that the better TC is T = 50 °C compared to other temperatures. Also, the maximum enhancement of TC compared to the base fluid (BF) (36 %) was observed at the mentioned temperature. In addition to the laboratory tests such as the margin of deviation (MOD) and RTC sensitivity within the range of −1.90 %<MOD < 1.42 % in the theoretical section, a new relationship was predicted using the response surface methodology (RSM). A comparison was also made between SWCNT-CuO (25:75)/water NF and other NFs at the same temperature and SVF, which shows the increased RTC of the NF after using SWCNT (25 %).

An empirical model of heat-treated straw bulks’ thermal conductivity based on changes in mass and chemical composition

An empirical model was developed to estimate the thermal conductivity of heat-treated straw bulks based on laboratory experiments. During the measurements, two different types of straw were investigated, barley and wheat. Barley was used to composing our empirical model and define the influencing model parameters, and wheat straw was used for validation. Both straws were heat-treated in a dry oxidative ambient in five temperature steps from 60 to 180 °C. The thermal conductivity was measured at 120 kg m−3 bulk density after every treatment cycle. In addition, we were looking for the most suitable measurement methods to detect changes in material structure related to thermal conductivity in the range of relatively low-temperature treatments. Thermogravimetric measurement was conducted, and the mass loss and elemental composition were measured after every treatment cycle. The measurements showed that the mass percentage ratio of carbon in straw increased, and the mass percentage of oxygen decreased in the investigated temperature range. We identified and separated the following parameters of the model, which can estimate the relative thermal conductivity of heat-treated stem bulks: relative residual mass, relative mass percentage ratio of carbon content and oxygen content. We divided the model into two parts, creating a simpler but worse approximation (the measurements required for this are much easier to perform) and a slightly more complex but better approximation. After the validation, our model achieved good agreement with the relative thermal conductivities calculated by the measured thermal conductivities.

Effect of Si-coated diamond on the relative density and thermal conductivity of diamond/W composites prepared by SPS

In order to improve the thermal conductivity of tungsten, diamonds coated with thin coating of pure Si and W matrix were mixed to fabricate composites with SPS process. The effects of Si coating and volume fraction of diamonds on microstructure including interfacial structure, relative density and thermal conductivity of the composites were investigated with scanning electron microscopy, X-ray diffraction, transmission electron microscopy and laser thermal conductivity instrument. The results showed that the interface bonding, relative density and thermal conductivity of coated-diamond/W composites were improved compared with uncoated-diamond/W composites under the same volume fraction of diamonds. Increasing in volume fraction of coated diamonds from 30% to 60%, the relative density and thermal conductivity of coated-diamond/W composite increased. Under the combined action of reaction diffusion and inter-diffusion at the interfaces of diamond-Si and diamond-W, the 60 vol% coated-diamond/W composite achieved the maximum thermal conductivity of 193 ± 2.12 W m−1 K−1, which was expected to be used for a longer time than that of W under 20 MW/m2 heat load. Its thermal conductivity was increased with the addition of Si-coated diamond compared with pure W sample (121 ± 1.06 W m−1 K−1) prepared via SPS.

Machine learning modeling of polycarbonate ultrafiltration membranes at different temperatures, Al2O3 nanoparticle volumes, and water ratios

The efficacy of novel polycarbonate ultrafiltration, aluminum oxide nanoparticle (Al2O3-NPs) volume fraction, temperature, and water/ethylene glycol (EG) ratio were evaluated to determine the thermophysical properties of the membrane. 5%–10% of Al2O3-NPs have been added to the PC. A machine learning approach was used to compare the volume fraction of Al2O3-NPs, the temperature, and the water-to-ethylene glycol (EG) ratio. To determine the impact of Al2O3-NPs loading on the Response Surface Method (RSM), DOE, ANOVA, ANN, MLP, and NSGA-II, the number of aluminum oxide nanoparticles (Al2O3-NPs), temperature, and water/ethylene glycol (EG) on membranes in PC ultrafiltration are evaluated. Based on the Relative Thermal Conductivity Model (RSM), the regression coefficient of Al2O3 in water and EG was 0.9244 and 0.9170 with adjusted regression coefficients. A higher concentration of EG enhances the thermal conductivity of the membrane when the effective parameters are considered. The effect of temperature on the relative viscosity of the membrane led to the conclusion that Al2O3 water/EG can cool at high temperatures while providing no viscosity change. When Al2O3 is dissolved in water and EG, more EG is necessary to optimize the mode of reactivity. Using the MLP model, the calculated R-value is 0.9468, the MSE is 0.001752989 (mean square error), and the MAE is 0.01768558 (mean absolute error). RSM predicted the average thermal conductivity behavior of nanofluid better. The ANN model, however, has proven to be more effective than the RSM in simulating the relative viscosity of nanofluids. The NSGA-II optimized results showed that the minimum relative viscosity and maximum coefficient of thermal conductivity occurred at the lowest water ratio and maximum temperature.

The Effect of Relative Humidity Dependent Thermal Conductivity on Building Insulation Layer Thickness Optimization

Optimization of insulation layer thickness is a significant factor in energy-efficient building design. Accurate determination of the thickness of the insulation layer will contribute to building energy conservation. In this study, ten typical cities in five thermal zones were selected, and the external thermal insulation of a typical residential building was taken as the research object. Using the degree day method and the economic model of full life cycle cost analysis, the optimal thickness of seven kinds of building insulation materials under absolute dry conditions, the lowest humidity and the highest humidity of the monthly average of the annual daily average were obtained. In addition, the carbon emission, energy saving and recovery period of materials under different working conditions were further obtained through numerical calculation. The results show that the optimum thickness of seven building insulation materials in ten typical cities under three working conditions is 18.21–346.05 mm. Their carbon emission change rate is between −2.7% and 38.6%, energy saving change rate is between −0.4% and 18.4%, and the payback period growth is within 1.5 years. Among them, polystyrene foam is the material least affected by humidity. It is recommended to be the main building insulation material in high humidity areas.