Considering the issues related to the usage of fossil fuels namely the environmental pollutants and fluctuations in their cost, development of renewable energy technologies is necessary and inevitable for sustainable energy supply in future. Geothermal energy is advantageous compared with solar and wind in term of availability in all hours of a day. This renewable energy source is applicable for supplying heating, cooling, freshwater and power in a clean way. Aside from direct utilization of geothermal energy for power generation as the main energy source, it is possible to apply it as auxiliary source for preheating in order to reduce greenhouse emissions and fuel saving. In these systems, thermal content of geothermal energy source is used for steam preheating. Furthermore, geothermal energy could be used in other energy systems like hydrogen production unit for preheating electrolysis water consumed in this process. Regarding the advantages of utilization of geothermal energy for preheating purposes, this paper aims to review studies on the applications of geothermal preheating systems. According to the studies on this subject, it can be denoted that there is significant potential for fuel saving and performance improvement by means of geothermal energy for preheating purpose. The performance of the aforementioned systems depends on some factors namely the configuration of the system, specification of the boreholes and temperature of geothermal source. Further improvement of these system is achievable by implementation of optimization.

Nowadays, there is wide acceptance among core energy experts and the research community that solar collectors have a critical role to play in the renewable energy sector. With the high-energy conversion rate associated with this solar energy harvesting technology, there is an urgent need to review various ways through which the heat transfer process can be improved. Researchers have mainly focused their attention on working fluid enhancement, thereby neglecting other techniques that can equally contribute to the heat transfer enhancement process in solar collectors. This has made studies in other directions obsolete. The primary objective of the present study is to provide an up-to-date overview of the latest advancements and novel approaches in enhancing the heat transfer process in solar collectors. Both conventional and innovative techniques were investigated, exploring their effectiveness in enhancing thermal performance and overall system efficiency. A comprehensive literature review of recent studies on heat transfer enhancement techniques in solar collectors was undertaken. Key challenges, knowledge gaps, and limitations were identified, and potential future research options were recommended. This holistic review will serve as a guide for researchers and key energy players, providing insight into the avalanche of research options available in the field of solar thermal collectors.

Generation of power through renewable energy resources is variable in nature due to their intermittence and the generation cost from these resources is also high for developing countries. Supportive policies and schemes like feed-in tariff and net metering are not so much attractive for consumers due to their insufficient rates and unfavorable institutional design. The shortcomings in these schemes can be avoided through self-consumption technique for roof top solar photovoltaic system, as this technique results in cheaper generation of electricity as compared to that of utility or grid. Therefore, prosumers are more attractive to use most of electrical power at cheapest price. In this paper, the cost and feasibility for the on-grid industrial solar photovoltaic system was analyzed. It is found from the results that store on-grid based photovoltaic system will be 0.0086 $/(kW ∙ h) and utility will sell energy to the prosumers at rate of 0.062 $/(kW·h), which will result in 35.23% reduction in annual cost of energy as compared to time of use rating model. Furthermore, 96% of annual energy demand can be achieved by the proposed scheme, which guarantees the security of supply and the proposed model can be adopted for developing countries.

Net zero energy (NZE) buildings obtain their energy from clean renewable resources. The current study aims to design and analyze a pioneering sports complex based on the net zero energy (NZE) concept, incorporating a football stadium and two swimming pools as a case study. Despite the common occurrence of such sports complexes, limited studies have been conducted to develop NZE systems tailored to this type of sports complexes. A solar field with 10000 m² photovoltaic panels installed on the rooftop of the stadium provides the required energy. The generated energy in daytime is stored through compressed air energy storage (CAES) cycle to be used after sunset on demand time. The compressed air runs turbines and generates the required electricity for the stadium. Also, the generated thermal energy is used to warm up the swimming pools. Environmental and meteorological data are used to perform transient studies. Dynamic simulations are done through TRNSYS, and results show that the overall efficiency of the cycle is around 44% which can increase to 98% if using the thermal energy in swimming pools. Due to solar energy fluctuations, on average, 14% of the required energy should be provided from the grid, while more than 26 MW · h a day can be sold to the grid. Results of this study help to design NZE sport complexes to move toward sustainable energy development.

Energy and exergy analysis of an organic Rankine cycle (ORC) power plant driven by solar and geothermal energy in southern Tunisia was conducted. The effects of main operating parameters on the combined solar/geothermal ORC system on two days in winter and summer were studied, where the mass, energy, and exergy balances were determined. Results showed that the main source of irreversibility was the parabolic through collector. Aiming to reduce the exergy destruction and to optimize the system’s performance, a polynomial regression analysis was applied. Hence, a relationship between both the mass flow rate and the inlet temperature of the heat transfer fluid and solar radiation was established. The proposed optimization can improve the system’s exergy efficiency by 2.06% to 5.44% in winter and 1.00% to 4.10% in summer. Also, the analysis revealed an increase in both the overall exergy efficiency and the net power by 26.6% and 21.0%, respectively, in winter.

As the demand for higher specific energy density in lithium-ion battery packs for electric vehicles rises, addressing thermal stability in abusive conditions becomes increasingly critical in the safety design of battery packs. This is particularly essential to alleviate range anxiety and ensure the overall safety of electric vehicles. A liquid cooling system is a common way in the thermal management of lithium-ion batteries. This article uses 3D computational fluid dynamics simulations to analyze the performance of a water-cooled system with rectangular channels for a cylindrical battery pack. A finite volume method is used, validating the results with experimental data. Firstly, the effects of converging and diverging of channels on the thermal and hydraulic characteristics of the considered cooling system are investigated. Then, the co- and counter-flow pattern strategies of the coolant are studied. The results indicate that converging the channels leads to the Nusselt number enhanced by about 21% compared to the conventional design of the system. However, better hydraulic performance is found for the case with diverging channels. The decrement in the friction loss of the cooling system with diverging channels is about 70%. It is also found that the flow pattern is considerably effective in controlling the temperature uniformity of the battery pack. The counter-flow pattern of the channels provides lower temperatures, and the maximum deviation from the co-flow pattern (∼ 5.2 K) can be found for the case with diverging channels.

In this study, phase change process dynamics in a triangular shaped elastic walled vented cavity is explored during nanofluid forced convection in the laminar flow regime. Impacts of Reynolds number (Re), Cauchy number (Ca) and port size of the cavity on the flow field and phase change dynamics are explored by finite element method. It is observed that the flow recirculation below the inlet port and phase change dynamics are affected by the variation of Re, Ca and port size. The phase transition time (TF) is reduced first when increasing Re from 100 to 200 and then increases. Hybrid nanofluid results in fast phase change while TF is reduced by about 26% at Re=100. Up to 12.5% reduction of TF is achieved at the highest value of Ca. The port size has a negative impact on the phase transition while TF is increased up to 19% with varying the port size.

In this research, the multi-layered porous foam is used to improve the performance of a heatsink from the hydrothermal and entropy generation perspectives. The research is done numerically using the computational fluid dynamics method. The results are compared with the case of single-layer metal foam and the case without metal foam. For the multi-layered foam, two modes are considered: the permeability of layers gradually increases or decreases by moving away from the CPU. The analysis showed that if the permeability of foam layers gradually decreases by moving away from the CPU, the heatsink has the best uniformity of temperature distribution, the lowest thermal resistance, the highest convection coefficient, and in general, the best overall hydrothermal performance. Also, it was seen that the multi-layered foam whose layer permeability increases by moving away from the CPU has the lowest frictional entropy, the highest thermal entropy, and the lowest total entropy generation rate. The frictional, thermal, and total entropy generation rates were respectively 64.51%–73.02% lower, 42.80%–220.34% higher, and 19.68%–62.36% lower than that of the heatsink without metal foam.

This study computationally examined the thermal and fluid behavior of Mxene-soya bean oil nanofluids in a single solar tray. A solar energy harvesting device that has an inlet and output is called a solar tray. With a steady heat flux, the Mxene nanofluids were pumped through the solar tray at different volume concentrations. A solar tray was utilized to simulate the thermophysical experimental data of Mxene-based nanofluids using a computational fluid dynamics (CFD) fluid flow radiation model. Temperature, internal energy, Nusselt number, heat transfer rate, surface heat transfer coefficient, and skin friction coefficient were among the several thermal and hydrodynamic parameters investigated. For Mxene nanofluids, the maximum increases in outlet temperature, internal energy, and skin friction coefficient were 3.46%, 1.2% and 11%, respectively. Finally, the solar tray’s efficiency has enhanced by 30%–32%. Moreover, the thermal use offers improved prospects for this newly developed Mxene nanofluid. Afterward, thermophysical values have been ratified by ANOVA analysis interpretation.

This study evaluates the melting and slip effect on mixed convective heat transfer through porous micro channel having electrical conducting and non-conducting walls. The flow mechanics of the fluid injection and ejection through the micro channel under the transverse magnetic field is developed using nonlinear coupled model of higher order ordinary differentials. These are non-sensationalized with the aid of similarity transforms. The model governing the mechanics of thermal fluid transport is analyzed using the Homotopy perturbation method of analytical solution, which is validated for simple conditions using existing literatures that show satisfactory results. The effect of rheological parameters of heat transfer during fluid transport is presented in the bid to enhance system operations lowering energy utilization consequently minimizing cost. Obtained results reveal that combined effect of melt and radiation on the thermal boundary layer steadily lowers its thickness. Also rise in radiation parameter (R) ranging in 1 < R < 5 reveals thermal profile decreases from −0.4804 to −1.3081 at the mid plate of the micro channel. The study provides useful insight in engineering science applications including magneto hydrodynamics molten metal and molten salt pumps among other practical, yet useful applications.

The innovative combination of equal channel angular pressing (ECAP) and cold upsetting (CU) is significant for producing high-strength Al alloy fasteners with ultrafine grains. However, the relationship between microstructure evolution and mechanical strength during composite deformation remains unclear. In this study, using transmission electron microscopy, electron backscatter diffraction, and mechanical property tests, it is found that the mechanical strength increases with each step of composite forming operations due to the accumulation of dislocations. Forest dislocations also contribute to the generation of ultrafine grains within deformed grains, particularly in ECAP-CU processed grains. Moreover, we observe the formation of lamellar structures within the shear bands in the head of the ultrafine grain fastener after final composite deformation, which is full of dense dislocation walls and dislocation cells. The rearrangement of these fine grains and lamellar structures yield a strong (011) <211> (brass) texture during composite deformation under the effect of shear force and accumulation of plastic strain. This study provides a theoretical reference for the manufacture of high-strength aluminum alloy fasteners through composite deformation and helps improve processing technology.

This study investigates the effect of nickel-aluminide on Al-Cu-Mg alloys’ non-isothermal aging behavior. The microstructure, mechanical properties, and corrosion resistance of nickel-aluminide-containing Al-Cu-Mg alloys were evaluated after non-isothermal aging treatment. The results show that the presence of nickel aluminide in the Al-Cu-Mg alloy changes the nature of S-Al₂CuMg precipitates to θ-Al₂Cu precipitates by adding 1.5 wt% Ni to the Al-Cu-Mg matrix. The non-isothermal aging treatment temperature for achieving the maximum mechanical properties during non-isothermal aging shifted from 250 °C to 300 °C. Compared to isothermal artificial aging treatment at 170 °C, the maximum hardness and mechanical properties increased by up to 9% in a nickel-aluminide containing Al-Cu-Mg alloy after non-isothermal aging treatment. The nickel-aluminide containing sample’s maximum hardness and shear strength is HV_0.1(143.4±6.4) and (298.6±9.6) MPa, respectively occurring at 300 °C. After non-isothermal aging treatment, the corrosion current intensity was reduced by approximately 58% and 49% in the nickel-containing coating compared to the AA2024 aluminum alloy substrate and coating without nickel-aluminide, respectively. Compared with the conventional artificial aging treatment, the corrosion current decreased by 16.7% more after non-isothermal aging treatment in the nickel-aluminide-containing coating.

The β/α″ interface in deformation bands was studied using high resolution transmission electron microscopy (HRTEM) observations in β-type titanium-niobium-based (Ti-Nb) alloys, and the elastic stress near the α″ habit plane was estimated using a topological model of martensitic transformation (TM). The results indicate that the elastic stress near the α″ habit plane is too small to cause β to ω transformation. In addition, the {332} <113>_β twin is formed within the stress-induced α″ phase, and is closely related to the

A numerical investigation is carried out by taking into consideration a two-dimensional inclined magnetically driven Casson nanofluid near a stagnation point flowing past a chemically reacting radially stretching sheet to scrutinize the phenomena of conduction, thermal radiation, heat generation and absorption in the light of multiple slips. For the purpose of investigating the characteristics of heat transfer conscientiously, the frequently cited Cattaneo-Christov heat flux model has been taken into consideration. The equations describing the proposed flow problem have been described by employing the Buongiorno nanofluid model to explore the impact of Brownian motion, thermophoresis and thermal and mass slip conditions. A set of some appropriate similarity transformations has been incorporated for converting highly non-linear partial differential equations characterizing the designed flow model to a system of ordinary differential equations. The advantage of the efficiency of the shooting method has been taken for the numerical governance of the proposed flow equations. The impacts of apropos flow parameters on the flow velocity, concentration and temperature configurations have been examined via tables and graphs. It has been remarked that the velocity accelerates significantly and the skin friction coefficient also shows an increasing behavior by escalating the Casson parameter. Furthermore, by increasing the magnitude of the magnetic parameter, the velocity of the fluid decreases.

In-situ stress measurement is a key task in deep underground mining activities. An efficient stress measurement technique is important for determining the safety of the surrounding rock mass. Rock acoustic characteristics can comprehensively reflect rock physical and mechanical properties, structures, and in-situ stresses. Acoustic information, with the wave velocity as a key parameter, is significantly correlated with factors such as stress, deformation, microstructure, and environmental conditions. Recent studies and developments regarding rock acoustic properties were summarized based on numerous research results in regard to four aspects: the wave velocity–stress–strain correlation, the influence of intrinsic factors such as lithology and pore structure, the influence of external factors such as confining pressure and temperature, and theoretical wave velocity models. Equations for the coupled stress–temperature–wave velocity relationship considering the effect of temperature under stress were presented. Finally, suggested research directions for future advances in rock acoustics and in-situ stress measurement for the development of deep mining engineering were described.

Deep-land resource exploitation is a crucial focus of future scientific and technological development in China. However, with the increasing depth of coal mining, rock burst disasters occur frequently, posing significant threats to the safe and efficient mining of coal mines. Therefore, it is of paramount importance to investigate mechanisms of rock burst, develop effective monitoring and warning systems, and explore techniques for pressure relief and shock reduction. This paper begins by summarizing the occurrence mechanisms of rock bursts in coal mines in chronological order and clarifying the interrelationships between these theories. Additionally, the paper presents a comprehensive summary of the mechanisms of rock bursts from a testing perspective, refining the understanding of their generation mechanisms and types. It emphasizes that the material effect and structure effect of coal and rock mass are key influencing factors in rock burst occurrences. Furthermore, the paper compares and analyzes the limitations of existing monitoring and warning by systems for rock bursts by various methods, such as microseismic monitoring, stress monitoring, electromagnetic radiation monitoring, and ground sound monitoring. Based on these findings, a proposed solution is presented: a big data analysis and comprehensive monitoring and early warning system that integrates temporally and spatially relevant precursor information using eigenvectors as weights. Lastly, the paper addresses the challenges faced in China in preventing and controlling rock bursts, including insufficient monitoring accuracy, difficulties in managing complex environments, inadequate optimization of relief and shock reduction schemes, and unsatisfactory support methods. Several suggestions are offered for future rock burst prevention and control efforts. The results of this study can provide valuable references for preventing rock bursts.

The hydraulic lifting pipeline, one of the key components of the slurry pump hydraulic lifting system, is taken as the research object in the paper. Based on the static characteristics of the hydraulic conveying pipeline, the spatial three-dimensional model of the hose is obtained. A geometric non-linear finite element model of the hydraulic lifting pipeline was established, and the static displacement of the hydraulic lifting pipeline under steady state was numerically simulated. The static characteristics of the pipeline were obtained, when the mining machine position, ocean current velocity and wave level were different. The numerical simulation of the response of the hydraulic lifting pipeline under dynamic excitation was performed, and the flow characteristics of the flow field in the pipeline under wave loading were obtained. A solid-liquid two-phase flow control equation for a slurry pump based on the Euler model is established, and the solid-liquid two-phase fluid in the hose is numerically simulated. The results show that the change of the position of the mining machine has little effect on the lateral displacement and bending stress of the hard tube, but has large impact on the pressure distribution, solid-phase velocity field distribution and pressure loss in the pipeline. The change of the ocean current has little effect on the spatial shape of the hose and the lateral displacement of the hard tube, but has great impact on the pressure loss in the pipeline. The wave level has great influence on the spatial shape of the hose and the lateral displacement of the hard tube. The pressure loss caused by changes in ocean current and wave level can be reduced by changing the position of the mining machine.

Microseismic (MS) source location is a critical technology in MS monitoring. Traditionally, P-wave or S-wave travel time-based ray-tracing algorithms are adopted for a mine MS event location. However, only a few data are available for an MS event location usually, which may result in a large location error. A P- and S-wave arrival time combined objective function can obtain a relatively better location result. However, previous studies have encountered several challenges: 1) the combined weighting should be a free parameter determined by the quality of P- and S-wave arrival time data; 2) all the arrival times including bad data are adopted for an MS event location. To handle this, a P- and S-wave arrival time combined Bayesian location (P_SBL) method has been proposed for an MS event location. To reduce the influence of large picking errors, 80% of arrival time data were randomly selected in each iteration. Two synthetic events and eight blasting events were used to test the proposed method. Synthetic results show that the average location error of the P_SBL method is only 9.96 m, when 2 and 4 ms Gaussian noises were separately included for the P-wave and S-wave travel time data. The application results demonstrate that the average location error of the P_SBL method is 31.97 m, which improves the location accuracy by 25.40% and 60.78% compared with the P_BL and S_BL methods, respectively.

The force chain network is the key information of rock materials under loading, which is close to the micro-scale cracking and macroscopic mechanical behavior of rocks. In this paper, a novel 3D grain-based model based on the discrete element method (GBM3D-DEM) is proposed to reproduce the heterogeneous structure of granites, and the dynamic flexural tensile strength test is simulated by the coupled (finite difference method (FDM)-DEM) split Hopkinson pressure bar (SHPB) numerical system. The results show that the value and the number of all general force chains (GF) inside the sample during the loading process indicate the stress level and cracking activity of the sample respectively. The number of high-strength force chains (HF), defined as those with values greater than the average value of all GF at peak load moment, can deeper characterize the stress level applied on both ends of the sample. Also, the main orientation distribution of HF is consistent with the loading direction and is perpendicular to that of cracks. In general, the force chain network is multi-level classified and the cracking activity and mechanical behavior of granite has been investigated from a microscopic perspective. The loading rate effect is also analyzed from the multi-level force chain network perspective.

The combined intensive mining effect of sequential-mining-process of two adjacent longwall top coal caving faces is prone to inducing disasters such as coal and gas outburst, roof caving and surface subsidence. However, it remains a big challenge to explore the mining-induced vertical stress evolution and its role played during such complex mining condition. A physical model with the geometric similarity ratio of 1: 100 was established to explore the mining-induced vertical stress characteristics, their influence on the surrounding rock failure mechanism and the high stress relief method. The results indicated that both coal ribs are the most intensive region of the surrounding roadway in the previous and next working faces. In addition, based on the experimental physical model and field monitoring results using borehole drilling stress device, the feasibility of high stress relief method using narrow pillar layout was technically proven. The research results can shed lights on optimization of coal pillar design, layout of roadways, the supporting schemes within extra-thick coal seam.

Underground multi-layer cavern is a key component in the compressed air energy storage (CAES) engineering and its optimal design is of vital importance for improving the CAES efficiency, while most of the optimization models for CAES cavern only have strength index without consideration of economical index. In this study, a finite element method of the CAES multi-layer cavern under high temperature and high pressure is used to calculate stress and strain fields of each layer (The maximum circumferential strain ε_θmax is experimentally verified to appear at top points of the lining layer) and to demonstrate the necessity of the prestressed lining since ε_θmax of lining layer is little influenced by the structural parameters. Numerical results of the prestressed lining cavern indicate that the applied prestress can effectively decrease ε_θmax and improve the stability of CAES prestressed lining cavern. A new multi-objective optimization model of CAES prestressed lining cavern is established with consideration of safety (minimizing the prestress to satisfy its strength conditions) and economy (minimizing the cavern surface area to decrease the construction cost). Calculation results show that the multi-objective optimization model is superior to the single-objective optimization model (only strength index) since it can obtain a safer and more economical CAES multi-layer cavern structure.

Building a rail transit workshop with efficient data interconnection has become an inevitable trend in the transformation and development of the current rail transit equipment industry. More and more diversified mobile transport robots have become a priority in the process of digital transformation of smart factories. Accurate prediction of robot battery power can guide the control center to adopt scientific and reasonable instructions in advance to ensure efficient and stable operation of the logistics transportation chain. In this study, we propose a hybrid ensemble method of multiple learners based on state-action-reward-state-action (Sarsa) reinforcement learning algorithm. Maximal overlap discrete wavelet transform (MODWT) is used to preprocess the originally measured robot power supply voltage data. This significantly reduces the non-stationarity and volatility of time series data. Gated recurrent unit (GRU), deep belief network (DBN), and long short-term memory (LSTM), are utilized for the prediction modeling of subseries after decomposition. Finally, the Sarsa reinforcement learning ensemble strategy is used to weight the three basic predictors above. The performance of the Sarsa hybrid model is verified on three real mobile robot power data sets. Experimental results elaborate that the transportation robot battery power hybrid forecasting model is competitive in robustness, accuracy, and adaptability.