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A significant challenge to hydraulic fracturing is premature particle settling and uneven particle distribution in a formation during injection. Even though various research work were conducted on particle transport, gaps still exist in the fundamental proppant–proppant interaction mechanisms. This study utilizes an experimental approach to understand proppant interactions during gravitational settling in various test conditions. High-speed imaging coupled with particle image velocimetry (PIV) was implemented to provide a space and time-resolved investigation of multi-proppant interactions. The multi-perspective experimental study uncovered the coupled effect of viscosity and multi-particle mix ratio on slurry velocity. The PIV analysis highlights unique agglomeration and particle interactive patterns. The results indicate that the mix ratio has a significant effect on proppant interactive behavior and settling characteristics, especially as the solution viscosity increases. This conclusion was drawn from observing no signs of agglomeration in the low viscosity regime, although slight differences in proppant interactions were noted as the mix ratios were altered. On the other hand, the intermediate regime demonstrates formed agglomerates with unique patterns for different viscosity and mix ratios. The observed patterns were quantified using both velocity and proppant concentration analysis. Finally, the results indicate the existence of a reduced velocity condition at a given viscosity and particle mix ratio. [ABSTRACT FROM AUTHOR]

The elevated energy demand and high dependency on fossil fuels have directed researchers' attention to promoting and advancing hydraulic fracturing (HF) operations for a sustainable energy future. Even though previous studies have demonstrated that the proppant suspension and positioning in slickwater play a vital role during the shut-in stage of the HF operations, minimal experimental work has been conducted on the fundamental proppant–proppant interaction mechanisms, especially a complete mapping of the interactions. This study utilizes high-speed imaging to provide a 2D space- and time-resolved investigation of two-particle (proppant models: 2 mm Ø, 2.6 g · cm − 3 ) interactions during gravitational settling in different initial spatial configurations and rheological properties. The mapping facilitates the identification of various interaction regimes and newly observed particle trajectories. Pure water results at a settling particle Reynolds number (R e p) ~ 470 show an unstable particle–particle interaction regime characterized by randomness while altering pure water to a 25% (v/v) water–glycerin mixture (R e p   ~   200) transitions an unstable interaction to a stable prominent repulsion regime where particles' final separation distance can extend up to four times the initial distance. This indicates the existence of R e p at which the stability of the interactions is achieved. The quantified trajectories indicate that when particles are within minimal proximity, a direct relation between repulsion and R e p exists with varying repulsion characteristics. This was determined by observing unique bottle-shaped trajectories in the prominent repulsion regimes and further highlighted by investigating the rate of lateral separation distance and velocity characteristics. Additionally, a threshold distance in which the particles do not interact (or negligibly interact) and settle independently seems to exist at the normalized 2D lateral separation distance. [ABSTRACT FROM AUTHOR]

Conservation of energy and reduction of carbon dioxide footprint are among the most crucial global challenges faced by humanity. Dozens of solutions have been so far introduced to address this issue. Nano‐phase change materials (nano‐PCMs) are new emerging technology that are vastly being studied which are believed to minimize energy waste. This study focuses on many aspects of nano‐PCMs with applications in the building industry. It was found that carbon‐based nanoparticles have the greatest thermal properties to be integrated into the PCMs. In this work, a summary of the previous review articles regarding PCM and nano‐PCM following the comparison of various types of nano‐particles in terms of their impact on thermal conductivity enhancement of PCMs is reported. Moreover, other influencial thermophyical properties of nanoparticles such as size, concentration, dispersion, shape, and inclination angle and their effect on thermal properties of PCMs are discussed. [ABSTRACT FROM AUTHOR]

An attempt is made to improve the overall performances of channel heat exchangers. The techniques of baffles and nanofluids are combined to enhance the dynamic and thermal behaviors within the channel exchanger. Baffles under various attack angles are used as vortex generators. In addition, oil/multiwalled carbon nanotubes (MWCNT) is used as a working fluid. Both inclinations in the upstream and downstream directions were considered, referenced as Case A (UIB) and Case B (BIB), respectively. While the channel equipped with vertical baffles is referenced as Case C. The proposed models with combined techniques allowed a considerable enhancement in the overall efficiency. The comparison between the three cases revealed that the most significant value of thermal enhancement factor (TEF) of 5.634 was reached with vertical baffles (Case C) at the highest value of Reynolds number. When using inclined baffles, the 75° upstream attack angle (Case A) allowed the highest TEF of 4.814, compared with Case B. [ABSTRACT FROM AUTHOR]

Recently, energy‐related CO2 emissions are considered as one of the most crucial issues and are promptly augmented due to further urbanization. In this paper, in order to model and calculate yearly CO2 emission, an artificial neural network is used. For the first time, the IWO‐SVM method has been applied in modeling energy‐related CO2 emissions. In this regard, consumption of different energy sources such as renewable energy, natural gas, coal, and oil, and GDP of the G8 countries in various years (from 1990 to 2016) are regarded as input in the present study. For the aim of evaluating the exact ability of the SVM and SVM‐IWO models, the performance of these models in three different modes is carried out on the basis of the number of data in the test and train sections. For this purpose, implementations are split into three categories (a = 80% of the data for the train section and 20% for the test section; b = 70% of the data for the train section and 30% for the test section; and c = 60% of the data for the train section and 40% for the test section). Furthermore, five scenarios were selected on the basis of the number of input parameters and input parameters for achieving the best model. As indicated in the results in all scenarios, the correlation of the model with the hybrid invasive weed algorithm based on SVM is more favorable than that in the support vector machine model, due to better training of the SVM‐IWO model than the SVM model. Moreover, the technological orientations of the G8 countries to mitigate CO2 emissions are determined through patent analysis. While the patents have essential information, investigating the published patent by a country could be helpful for determination of technological orientations. Hence, all published patents by these countries are extracted and deeply analyzed. In the next step, to find out main technological approaches, all patents and their intents have been studied. Eventually, the technological life cycles and trends of each main technology are drawn. [ABSTRACT FROM AUTHOR]

The study aimed to enhance the heat transport by improving the hydrodynamic structure of the system by changing and restructuring the duct's internal geometry. Modern fins, of the shape 'V', have been proposed with different dimensions, and they are periodically arranged over the duct surfaces. The most important steps of this research are the change in the V-fin attack-angle (40°–80°), length (Hb/2, 3Hb/4, Hb, 5Hb/4 and 3Hb/2), and separation length (Ds/2, 3Ds/4, Ds and 5Ds/4), as well as the flow rate (6 × 103–3 × 104). The study yielded an optimum case for a 40-degree attack-angle, with a factor of thermal enhancement of 2.163 for the highest value of Reynolds number. On the other hand, improving the length of the V-fins or decreasing in the space between them, increases the flow strength by enlarging the recycling cells, which reflects on the hydrodynamic behavior, and changes the heat transfer. The presence of this new model of fins also highlights a hydrothermal improvement ranging between 1.196 and 23.779 percent compared to the previously indicated models, reflecting the effectiveness of the new system of solar heat exchangers with air V-finned ducts. [ABSTRACT FROM AUTHOR]

This study consists of proposing a new mathematical method to develop a new model for evaluating thermal distributions throughout convergent-divergent channels between non-parallel plane walls in Jeffery Hamel flow. Subsequently, dimensionless equations that govern temperature fields and velocity are numerically tackled via the Runge–Kutta-Fehlberg approach based on the shooting method. Additionally, an analytical study is performed by applying an effective computation technique named Adomian Decomposition Method. Determining the effect of Reynolds and Prandtl numbers on the heat transfer and fluid velocity inside converging/diverging channels can be mentioned as the fundamental purpose of this research. Based on the results obtained for dimensionless velocity and thermal distributions, a supreme match can be observed between numerical and analytical results indicating the adopted ADM method is valid, applicable, and has great precision. [ABSTRACT FROM AUTHOR]

Summary: The major logics resulting in hydrogen production can be mentioned as fossil fuel depletion and climate change. In this way, hydrogen is produced with the help of numerous processes based on traditional and alternative energy resources like coal, natural gas, wind, solar, biomass, and geothermal energy. Over the past decade, the attention of research institutions and industry has been drawn to hydrogen, inspired by developments in renewable energies. Hydrogen production can be considered as an exceptional choice to make complete utilization of the renewable energy. Among diverse technologies, hydrogen production based on geothermal energy offers great promise. In this paper, initially a concise summary of present and advancing hydrogen production technologies is presented, and secondarily a comprehensive review of research associated with hydrogen production based on geothermal energy is provided. Thirdly, the process descriptions of geothermal‐assisted hydrogen production coupled with its technical, economic, and environmental aspects are addressed. Finally, comparative assessments of costs and environmental aspects related to hydrogen production based on different energy sources have been performed. In accordance with the results, the geothermal‐assisted hydrogen production cost based on electrolysis is competitively lower than other sources like wind, solar thermal coupled with natural gas, solar PV, and grid. Also, the same behavior can be seen for geothermal‐assisted hydrogen production cost based on thermochemical process. [ABSTRACT FROM AUTHOR]

Abstract In this study, the CuO/water nanofluid was used to increase the performance of heat pipe heat exchanger. The results showed that the rise in the input power of the heat pipe leads to increase the wall temperature of the pipe, whereas augmenting the concentration of nanoparticles leads to reduce the wall temperature and decrease the temperature difference between the evaporator and the condenser. Using the nanoparticles increases the thermal conductivity of the base fluid and minimizes the temperature gradient within it. Therefore, the thermal power of the heat pipe increases and its resistance decreases. Also, the results showed that with increasing evaporation filling ratio, the resistance reduces (by Fr = 0.45) and then increases. Additionally, experimental data was compared with published data for the heat pipe in order to accurately evaluate the results obtained in this study. The results showed that the measured data are highly accurate. Also, the heat conductivity resistance equation was calculated based on the experimental data. In the next step, the model of neural networks was used to predict thermal performance, FR, the concentration of nanofluid and input power. The results showed that the network with an accuracy of 0.9938 is able to predict the heat transfer coefficient. A review of the predicted and experimental results for the verification part indicated that the residuals are scattered around the zero axis. [ABSTRACT FROM AUTHOR]

One of the auspicious nanomaterials which has exceptionally enticed researchers is carbon nanotubes (CNTs) as the result of their excellent thermal properties. In this investigation, an experiment was carried out on three kinds of CNTs-nanofluids with various CNTs added to de-ionized water to compared and analyze their thermal conductivity properties. The main purpose of this study was to introduce a combination of experimental and modelling approaches to forecast the amount of thermal conductivity using four different neural networks. Between MLP-ANN, ANFIS, LSSVM, and RBF-ANN Methods, it was found that the LSSVM produced better results with the lowest deviation factor and reflected the most accurate responses between the proposed models. the regression diagram of experimental and estimated values shows an R2 coefficient of 0.9806 and 0.9579 for training and testing sections of the ANFIS method in part a, and in the b, c and d parts of the diagram, coefficients of determination were 0.9893& 0.9967 and 0.9974 & 0.9992 and 0.9996& 0.9989 for training and testing part of MLP-ANN, RBF-ANN and LSSVM models. Also, the effect of different parameters was investigated using a sensitivity analysis method which demonstrates that the temperature is the most affecting parameter on the thermal conductivity with a relevancy factor of 0.66866. [ABSTRACT FROM AUTHOR]

Summary: It is believed that fossil fuel sources are exhaustible and also the major cause of greenhouse gas emission. Therefore, it is required to increase the portion of renewable energy sources in supplying the primary energy of the world. In this study, it is focused on application of nanotechnology in exploitation of renewable energy sources and the related technologies such as hydrogen production, solar cell, geothermal, and biofuel. Here, nanotechnologies influence on providing an alternative energy sources, which are environmentally benign, are comprehensively discussed and reviewed. Based on the literature, employing nanotechnology enhances the heat transfer rate in photovoltaic/thermal (PV/T) systems and modifies PV structures, which can improve its performance, making fuel cells much cost‐effective and improving the performance of biofuel industry through utilization of nanocatalysts, manufacturing materials with high durability and lower weight for wind energy industry. The application of nanotechnology in various renewable energies for efficiency improvementIncrease durability of renewable energy technologies by utilizing nanoscienceAchieving sustainable development by applying nanotechnology, which leads to higher efficiency and lower greenhouse gas emissionEnergy resource harvesting by nanotechnology to overcome future issues related to lack of energy [ABSTRACT FROM AUTHOR]

The increase of human population has led to the augmentation of buildings' numbers and high energy consumption. About 30% of the world's energy consumption is in the heating and cooling sector of residential buildings. Due to the increase in energy consumption in the building industry, energy management in this sector would be very significant and it is necessary to provide effective solutions to reduce energy consumption by avoiding waste and reducing the cost of construction and cost of utilization of buildings. One of the most effective method for reducing energy consumption is the use of phase-change materials for energy storage. Their performance is such that with increasing the temperature, their phase is changed and they store the heat energy and release this energy by reducing the temperature. In this research, a geometry in the climate of Tehran is simulated by using the Energy Plus and the Open Studio software. In the present study, four phase change materials (PCM) with different thermo-physical properties were investigated. The results indicated that each of the four utilized PCMs would reduce energy consumption, however, the highest reduction in the energy consumption would be obtained when the PCM 22 is used. Which is 50.75% for cooling and 45.35% for heating purposes, and the amount of energy consumption in buildings can be minimized by increasing the thickness of PCMs. [ABSTRACT FROM AUTHOR]

Surging in energy demand makes it necessary to improve performance of plant equipment and optimize operation of thermal power plants. Inasmuch as thermal power plants depend on fossil fuels, their optimization can be challenging due to the environmental issues which must be considered. Nowadays, the vast majority of power plants are designed based on energetic performance obtained from first law of thermodynamic. In some cases, energy balance of a system is not appropriate tool to diagnose malfunctions of the system. Exergy analysis is a powerful method for determining the losses existing in a system. Since exergy analysis can evaluate quality of the energy, it enables designers to make intricate thermodynamic systems operates more efficiently. These days, power plant optimization based on economic criteria is a critical problem because of their complex structure. In this study, a comprehensive analysis including energy, exergy, economic (3‐E) analyses, and their applications related to various thermal power plants are reviewed and scrutinized. Several thermal power plants in combined cycles are reviewed comprehensively in the present study. Results of the studies based on energy, exergy, and economic analyses are represented for each type of thermal power plants. Integrating thermal power plants with other cycles will enhance the energetic efficiency. Systems integrating will increase investment cost for the power plants. Exergy analysis provide useful information for enhancement of plants' efficiency. [ABSTRACT FROM AUTHOR]

Thermal conductivity and dynamic viscosity play key role in heat transfer capacity of nanofluids. In the present study, thermal conductivity and dynamic viscosity of Fe2O3/water are modeled by applying various artificial neural network algorithms. The applied algorithms are MLP, GA-RBF, LSSVM, and CHPSO ANFIS algorithms. The data for modeling procedure are extracted from several experimental studies. Obtained results by the different algorithms are compared and it was concluded that the highest R-squared values belonged to GA-RBF algorithm which were equal to 0.9962 and 0.9982 for thermal conductivity ratio and dynamic viscosity, respectively. [ABSTRACT FROM AUTHOR]

Negative environmental impact of fossil fuel consumption highlight the role of renewable energy sources and give them a unique opportunity to grow and improve. Among renewable energy sources solar energy attract more attention and many studies have focused on using solar energy for electricity generation. Here, in this study, solar energy technologies are reviewed to find out the best option for electricity generation. Using solar energy to generate electricity can be done either directly and indirectly. In the direct method, PV modules are utilized to convert solar irradiation into electricity. In the indirect method, thermal energy is harnessed employing concentrated solar power (CSP) plants such as Linear Fresnel collectors and parabolic trough collectors. In this paper, solar thermal technologies including soar trough collectors, linear Fresnel collectors, central tower systems, and solar parabolic dishes are comprehensively reviewed and barriers and opportunities are discussed. In addition, a comparison is made between solar thermal power plants and PV power generation plants. Based on published studies, PV‐based systems are more suitable for small‐scale power generation. They are also capable of generating more electricity in a specific area in comparison with CSP‐based systems. However, based on economic considerations, CSP plants are better in economic return. In this paper, both methods of electricity generation are reviewed and compared. Based on published studies, PV‐based systems are more suitable for small‐scale power generation. They are also capable of generating more electricity in a specific area in comparison with CSP‐based systems. However, based on economic considerations, CSP plants are better in economic return. [ABSTRACT FROM AUTHOR]

Owing to the eye‐catching pros of high energy and environmental performances, numerous ground‐source heat pump (GSHP) systems have been employed in domestic and industrial buildings throughout the world. One of the proved renewable energy technologies is the GSHPs which is able to fulfill the gap between cooling and heating. The main contribution of this article is to present a fully description and critical review of the GSHP systems along with their current developments. At first, the energy efficiency and working standard of a heat pump are introduced. Furthermore, an expansive description of the GSHPs and its advances, and a fully explanation of the ground‐couplet (GCHP) heat pumps, ground‐water (GWHP), and surface water (SWHP) are provided. The mainly representative ground thermal response examination approaches and simulation for the vertical ground heat exchangers presently existing are reviewed counting the heat transfer progressions inside and outside the holes. Similarly, various info regarding a different GWHP by a heat exchanger with different structures, and the opportunity to gain the enhanced energy efficiency with joint cooling and heating using GCHP are explained. The numerous hybrid GCHP systems for heating or cooling‐dominated constructions are appropriately illustrated. It can be deduced that the GSHP technology can be employed both in hot and cold weather areas and the potential of energy saving is noteworthy. © 2017 American Institute of Chemical Engineers Environ Prog, 37: 1241–1265, 2018 [ABSTRACT FROM AUTHOR]

In this article, a numerical model for simulation of the heat and mass transfer phenomena in unsaturated soil is presented. The system is provided to evaluate its behavior as a thermal storage system. The model includes a single pipe that is buried under unsaturated media which is connected to a source with the constant heat rate of 20 W/m3 in sandy soils during a specific time. All the numerical results show good agreement with previous results, thus excellent correlation was achieved. Additionally, sensitivity analysis is done to clear up the role of the thermal and isothermal properties respect to volumetric water content and temperature and to assess the effects of related parameters on heat transfer in the media. The results show that as getting far away from the source, in addition to reduce the collected energy, the intensity of increasing the temperature and decreasing the moisture diminished will be more. Generally over time, the cumulative stored energy for each point will tend to a constant quantity. [ABSTRACT FROM AUTHOR]

In this paper, an artificial neural network is implemented for the sake of predicting the thermal conductivity ratio of TiO2-Al2O3/water nanofluid. TiO2-Al2O3/water in the role of an innovative type of nanofluid was synthesized by the sol–gel method. The results indicated that 1.5 vol.% of nanofluids enhanced the thermal conductivity by up to 25%. It was shown that the heat transfer coefficient was linearly augmented with increasing nanoparticle concentration, but its variation with temperature was nonlinear. It should be noted that the increase in concentration may cause the particles to agglomerate, and then the thermal conductivity is reduced. The increase in temperature also increases the thermal conductivity, due to an increase in the Brownian motion and collision of particles. In this research, for the sake of predicting the thermal conductivity of TiO2-Al2O3/water nanofluid based on volumetric concentration and temperature functions, an artificial neural network is implemented. In this way, for predicting thermal conductivity, SOM (self-organizing map) and BP-LM (Back Propagation-Levenberq-Marquardt) algorithms were used. Based on the results obtained, these algorithms can be considered as an exceptional tool for predicting thermal conductivity. Additionally, the correlation coefficient values were equal to 0.938 and 0.98 when implementing the SOM and BP-LM algorithms, respectively, which is highly acceptable. [ABSTRACT FROM AUTHOR]

Nowadays, industrial dryers are used instead of traditional methods for drying. When designing dryers suitable for controlling the process of drying and reaching a high-quality product, it is necessary to predict the gradual moisture loss during drying. Few studies have been conducted to compare thin-layer models and artificial neural network models on the kinetics of pistachio drying in a cabinet dryer. For this purpose, ten mathematical-experimental models with a neural network model based on the kinetic data of pistachio drying were studied. The data obtained was from a cabinet dryer evaluated at four temperatures of inlet air and different air velocities. The pistachio seeds were placed in a thin layer on an aluminum sheet on a drying tray and weighed by a scale attached to the computer at different times. In the neural network, data was divided into three parts: Educational (60%), validation (20%) and testing (20%). Finally, the best mathematical-experimental model using a genetic algorithm and the best neural network structure for predicting instantaneous moisture were selected based on the least squared error and the highest correlation coefficient. [ABSTRACT FROM AUTHOR]

An exergy analysis of a novel integrated power system is represented in this study. A Solid Oxide Fuel Cell (SOFC), which has been assisted with a Gas Turbine (GT) and Organic Rankine Cycle (ORC) by employing liquefied natural gas (LNG) as a heat sink in a combined power system is simulated and investigated. Initially in this paper, the integrated power system and the primary concepts of the simulation are described. Subsequently, results of the simulation, exergy analysis, and composite curves of heat exchangers are represented and discussed. The equations of the exergy efficiency and destruction for the main cycle’s units such as compressors, expanders, pumps, evaporators, condensers, reformers, and reactors are presented. According to the results, the highest exergy destruction is contributed to the SOFC reactor, despite its acceptable exergy efficiency which is equal to 75.7%. Moreover, the exergy efficiencies of the ORC cycle and the whole plant are determined to be 64.9% and 39.9%, respectively. It is worth noting that the rational efficiency of the integrated power system is 53.5%. Among all units, the exergy efficiency of the LNG pump is determined to be 11.7% the lowest exergy efficiency among the other investigated components, indicating a great potential for improvements. [ABSTRACT FROM AUTHOR]

In recent years, many studies have been conducted on hybrid solid oxide fuel cell and gas turbine which fed by renewable fuels to reach the high-efficiency power and the low pollution. In this paper, a thermodynamic study based on energy and exergy analyses of a hybrid solid oxide fuel cell and gas turbine hybrid system has been conducted in the presence of reforming with steam, in which the effects of using natural gas and other biofuels including Sewage biogas, Agricultural and Industrial waste biogas, Syngas, Biofuel and Gasified biomass, have been compared to this system. The purpose of this paper is to investigate the effect of each of the mentioned fuels on the performance of individual equipment and the entire system from the thermodynamic perspective. Initially, the modeling and energy balance of all components in the system were carried out in detail. Further, calculating the exergy destruction of all components of the system and the effects of applying different biofuels on the key parameters of the system, including total production power, operating pressure and temperature, compression ratio, the water-to-fuel ratio in the reforming, energy and exergy efficiency, and the amount of irreversibility of each component in the system have been analyzed. To compare more accurately between different fuels, an equal amount of each fuel is considered, and the effect of each fuel system on the hybrid system is analyzed by calculating the operating parameters of the system. By studying the results of modeling, it was determined that natural gas with 879.03 kW produced the highest production capacity and Gasified biomass with 45.44 kW has the least amount of power generation. By studying the thermodynamics of the system, if it is fed with Natural gas, the highest exergy destruction (687.45 kW) occurs and the lowest total exergy destruction rate is related to the system fed by gasified biomass (101.12 kW). Comparing the fuels, it was concluded that the electrical efficiency of the system fed with natural gas has the highest efficiency (72.71%) and Biofuel has the lowest total electrical efficiency (56.6%). Furthermore, by examining the exergy efficiency of the whole system, it was found that Natural gas with the highest efficiency of 61.29% and Gasified biomass with 46.06% the lowest exergy efficiency can be detected. Finally, the effect of the percentage combination of each fuel on the performance of all equipment from the perspective of energy and exergy has been studied. • SOFC-GT hybrid systems fed by natural gas & various biofuels were modeled and studied. • Energetic & exergetic performances of the hybrid systems were analyzed compared with together. • The systems fed with natural gas and Biofuel had the highest and lowest electrical efficiencies, respectively. • The systems fed with natural gas and Gasified biomass had the highest and lowest exergy efficiencies, respectively. [ABSTRACT FROM AUTHOR]

In this paper, an artificial neural network is implemented for the sake of predicting the thermal conductivity ratio of TiO 2 -Al 2 O 3 /water nanofluid. TiO 2 -Al 2 O 3 /water in the role of an innovative type of nanofluid was synthesized by the sol-gel method. The results indicated that 1.5 vol.% of nanofluids enhanced the thermal conductivity by up to 25%. It was shown that the heat transfer coefficient was linearly augmented with increasing nanoparticle concentration, but its variation with temperature was nonlinear. It should be noted that the increase in concentration may cause the particles to agglomerate, and then the thermal conductivity is reduced. The increase in temperature also increases the thermal conductivity, due to an increase in the Brownian motion and collision of particles. In this research, for the sake of predicting the thermal conductivity of TiO 2 -Al 2 O 3 /water nanofluid based on volumetric concentration and temperature functions, an artificial neural network is implemented. In this way, for predicting thermal conductivity, SOM (self-organizing map) and BP-LM (Back Propagation-Levenberq-Marquardt) algorithms were used. Based on the results obtained, these algorithms can be considered as an exceptional tool for predicting thermal conductivity. Additionally, the correlation coefficient values were equal to 0.938 and 0.98 when implementing the SOM and BP-LM algorithms, respectively, which is highly acceptable.