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Friction stir welding (FSW) is a manufacturing process that many industries have adopted to join metals in a solid state, resulting in unique properties. However, studying aspects like temperature distribution, stress distribution, and material flow experimentally is challenging due to severe plastic deformation in the weld zone. Therefore, numerical methods are utilized to investigate these parameters and gain a better understanding of the FSW process. Numerical models are employed to simulate material flow, temperature distribution, and stress state during welding. This allows for the identification of potential defect-prone zones. This paper presents a comprehensive review of research activities and advancements in numerical analysis techniques specifically designed for friction stir welding, with a focus on their applicability to component manufacturing. The paper begins by examining various types of numerical methods and modeling techniques used in FSW analysis, including finite element analysis, computational fluid dynamics, and other simulation approaches. The advantages and limitations of each method are discussed, providing insights into their suitability for FSW simulations. Furthermore, the paper delves into the crucial variables that play a significant role in the numerical modeling of the FSW process.

Despite having definite ignition points for a substance, auto ignition may be observed at different temperatures and energies. This paper presents a detailed quantitative analysis of anthracite coal ignition probability across various energy and temperatures under classical and quantum frameworks. The objective is to establish a probabilistic framework to describe ignition behavior as a function of thermal and energetic variability rather than as a fixed threshold. Energy temperature distributions are derived using specific heat temperature relations and the black body radiation equation. General equations for calculating ignition probability at different temperatures and energies measured independently or simultaneously are derived from probability theorems, distribution equations and curves. Further, the probability calculations for 500 K and 1000 kJ/kg are depicted. In the quantum approach, the validity of the energy-temperature uncertainty relationship of quantum thermodynamics is checked in the domain of measurement. Results depict that probability increases from 0.0047 at 100 °C to 0.9935 at 5000 °C, crossing 50% at 769.15 °C. Further, the probability increases from 0.0000 at 200 J/g to 0.9930 at 5000 J/g, crossing 50% at 789.86 J/g. The concept of the ignition line, along with its corresponding equation, is also established. Understanding the probabilistic framework of ignition enhances combustion efficiency, safety, and fire prevention in mining and storage by moving beyond deterministic ignition points to account for thermal and energetic variability. Moreover, the integration of quantum probability principles provides deeper insight into fire occurrence mechanisms, enabling the analysis of ignition behavior under inherently uncertain and fluctuating microthermal conditions.

An “inverse‐temperature layer” (ITL) of water temperature increasing with depth is predicted based on physical principles and confirmed by in situ observations. Water temperature and other meteorological data were collected from a fixed platform in the middle of a shallow inland lake. The ITL persists year‐around with its depth on the order of one m varying diurnally and seasonally and shallower during daytimes than nighttimes. Water surface heat flux derived from the ITL temperature distribution follows the diurnal cycle of solar radiation up to 300 W m−2 during daytime and down to 50 W m−2 during nighttime. Solar radiation attenuation in water strongly influences the ITL dynamics and water surface heat flux. Water surface heat flux simulated by two non‐gradient models independent of temperature gradient, wind speed and surface roughness using the data of surface temperature and solar radiation is in close agreement with the ITL based estimates. Plain Language Summary Heat stored in water bodies resulting from the absorption of solar radiation is the energy supply of evaporation and sensible heat flux into the atmosphere from water surface. Transfer of the thermal energy from water body into the atmosphere is only possible when water temperature increasing with depth within the top water layer referred to as the “inverse temperature layer (ITL).” The existence and persistence of the theoretically predicted phenomenon are demonstrated by the field observations of water temperature profile at an inland lake. The ITL depth is found to be comparable to the penetration depth of solar radiation with evident diurnal and seasonal cycles following closely those of solar radiation. Further understanding and analysis of the ITL process require higher resolution data of water temperature and solar radiation profiles within the top‐layer than those commonly collected in previous field experiments. Key Points Inverse temperature layer (ITL) allows transfer of heat from water into atmosphere ITL has prounced diurnal seasonal cycles persisting year‐around Water surface heat flux is simulated using non‐gradient models

Diffusion flames are widely used in industrial combustion systems; however, the influence of baffle-plate air-hole diameter on flame characteristics and combustion performance remains insufficiently quantified through experimental studies. The present work experimentally investigates Liquefied Petroleum Gas (LPG) diffusion flames stabilized by multi-hole baffle plates with varying air-hole diameters. Five baffle-plate configurations with eight radially distributed air holes were tested at a constant thermal load of 32 kW over air–fuel ratios (AFR) of 15–30, while flame stability, temperature distributions, flame length, species concentrations, and combustion efficiency were systematically measured. The experimental facility consisted of an integrated setup linking air and fuel supply lines to the baffle plate and combustor chamber. The study involved the development of an empirical relation expressing flame length in terms of air-hole diameter (d a ) and AFR, where the discrepancy between predicted and experimental results averaged approximately 2.5%. Combustion efficiency decreased with increasing air hole diameters. Specifically, the d a increased from 10 mm to 15 mm, the combustion efficiency dropped by approximately 10.17% at AFR = 15 and 11.04% at AFR = 20.

The aim of this study is to investigate the effects of the separator thickness on not only the heat and mass transfer characteristics, but also the power generation characteristics of a polymer electrolyte membrane fuel cell (PEMFC) with a thin polymer electrolyte membrane (PEM) and thin gas diffusion layer (GDL) operated at higher temperatures of 363 and 373 K. The in-plane temperature distributions on the back of the separator at the anode and cathode, which are the opposite sides to the GDL, are measured using a thermograph at various initial cell temperatures (Tinit), relative humidity (RH) levels, and supply gas flow rates. The total voltage corresponding to the load current is measured in order to evaluate the performance of the PEMFC. As a result, it is revealed that the effect of the RH on the power generation characteristics is more significant when the separator thickness decreases. It is revealed that the power generation performance obtained at high current densities decreases with the increase in Tinit with thinner separator thicknesses. According to the investigation of the in-plane temperature distribution, it is clarified that the temperature decreases at corner positions in the separator with the separator thickness of 2.0 mm, while the temperature gradually increases along with the gas flow with separator thicknesses of 1.5 mm and 1.0 mm.

In practice, industrial exhaust emissions as well as emissions from automobiles, ships, biomass combustion, etc., can be potential application areas for thermoelectric generation (TEG). However, the structural design of heat exchange equipment is usually limited by the internal flow field, resulting in uneven temperature distribution on the heat exchange equipment’s surface. The resulting mismatch power loss is a major challenge for thermoelectric power generation. In this study, based on the characteristics of the surface temperature distribution of heat exchange equipment in the context of gas emissions, a static reconfiguration scheme is proposed for reconfiguring honeycomb (HC) arrays using the symmetric interval crossing (SIC) method. Based on a fixed interconnect array configuration, the solution requires only a change in the location of the modules and no change in the electrical connections, thus reducing mismatch losses while lowering manufacturing costs. Test experiments are conducted for 6 × 6 TEG arrays, mismatch losses are evaluated for four nonuniform temperature distribution cases, and the performance of seven different TEG array configurations is compared. The findings demonstrate that, in nonuniform temperature distribution scenarios, the SIC method can effectively reduce mismatch losses and has a greater output power than alternative array configurations.

The powder bed fusion (PBF) process is increasingly employed by industry to fabricate complex parts with stringent standard criteria. However, fabricating parts “free of defects” using this process is still a major challenge. As reported in the literature, thermally induced abnormalities form the majority of generated defects, and are mainly the result of thermal evolution. Monitoring & controlling the temperature and its distribution throughout a layer under fabrication is an effective and efficient proxy to controlling such an evolution. In this paper, we introduce a novel online thermography and closed-loop hybrid-control (NOTCH) © , a practical control approach, to modify the scan strategy in metal PBF real-time. This system employs different mathematical thermophysical -based models, designed to optimize the printing sequence of different zones throughout a printing layer as well as the islands or stripes within each zone. Moreover, NOTCH uses artificial neural network (ANN) to optimize the energy density applied on each zone in order to avoid or mitigate some prevalent thermal anomalies. NOTCH strategy has two aims. First, producing a uniform temperature distribution throughout an entire layer to mitigate the thermally induced residual stress and its related distortion. In this step, we optimize the printing sequence of islands or stripes in their respective scan strategies. This paper expands on three potential models, explains pros and cons of these models, and presents preliminary results for a printed prototype. Second, controlling the laser specifications in order to avoid heat affected zones (HAZ) and mitigate thermal abnormalities such as the balling phenomenon. This step enables a smart adjustment of energy density by using ANN to avoid or mitigate HAZs, generate uniform microstructure with minimum porosity, and contribute to a more uniform temperature distribution. The completion of the latter step is part of the ongoing research which should be reported in future publications.

The New Energy and Industry Technology Development Organization (NEDO) road map (Japan, 2017) has proposed that a polymer electrolyte fuel cell (PEFC) system, which operates at a temperature of 90 °C and 100 °C, be applied for stationary and mobility usage, respectively. This study suggests using a thin polymer electrolyte membrane (PEM) and a thin gas diffusion layer (GDL), at the same time, to achieve better power-generation performance, at a higher temperature than usual. The focus of this paper is to clarify the effect of separator thickness on the distribution of temperature at the reaction surface (Treact), with the relative humidity (RH) of the supply gasses and initial operation temperature (Tini), quantitatively. In this study, separator thickness is investigated in a system using a thin PEM and a thin GDL. Moreover, this study investigates the difference between the maximum temperature and the minimum temperature obtained from the distribution of Treact as well as the relation between the standard deviation of Treact − Tini and total voltage, to clarify the effect of separator thickness. The impact of the flow rates of the supply gases on the distribution of Treact is not large, among the investigated conditions. It is noticed that the temperature distribution is wider when a separator thickness of 2.0 mm is selected. On the other hand, it is observed that the temperature increases along with the gas flow through the gas channel, by approximately 2 °C, when using a separator thickness between 1.5 mm and 1.0 mm. The impact of the RH on the distributions of Treact − Tini is larger at Tini = 100 °C, when a separator thickness of 1.0 mm is selected. It is revealed that the wider temperature distribution provides a reduction in power-generation performance. This study proposes that the thin separators, i.e., with a thickness of 1.5 mm and 1.0 mm, are not suitable for higher temperature operation than usual.

Control cooling is an essential method for microstructure and mechanical property control in hot rolling strip making. Therefore, it is vital to realize high-precision temperature distribution prediction and control in cooling process to ensure the industrial production. In this paper, a traditional mechanism model based on finite-difference method combined with online cycle velocity calculation strategy was introduced as one of the baseline methods estimating temperature distribution. However, considering calculation time, variable-velocity rolling makes it difficult to rapidly realize temperature and modifying water distribution of all segments in cooling zone. Herein, a temperature distribution prediction method based on recurrent neural network was proposed, by fully considering the variable-velocity rolling dynamic characteristics. And the temperature distribution prediction performance of the model with different recurrent cell and time steps was evaluated. The results indicated that the proposed model could realize temperature distribution prediction, and the model based on bi-LSTM and 48 timesteps has the highest determination coefficient value of 0.976, the lowest root mean square error of 8.03, and a mean absolute error of 5.7. Furthermore, compared with baseline model, the proposed model retained lower computational cost, making it applicable in industrial application by providing real-time temperature distribution prediction.

A thermoelectric generation (TEG) system has the weakness of relatively low thermoelectric conversion efficiency caused by heterogeneous temperature distribution (HgTD). Dynamic reconfiguration is an effective technique to improve its overall energy efficiency under HgTD. Nevertheless, numerous combinations of electrical switches make dynamic reconfiguration a complex combinatorial optimization problem. This paper aims to design a novel adaptive coordinated seeker (ACS) based on an optimal configuration strategy for large-scale TEG systems with series–parallel connected modules under HgTDs. To properly balance global exploration and local exploitation, ACS is based on ‘divide-and-conquer’ parallel computing, which synthetically coordinates the local searching capability of tabu search (TS) and the global searching capability of a pelican optimization algorithm (POA) during iterations. In addition, an equivalent re-optimization strategy for a reconfiguration solution obtained by meta-heuristic algorithms (MhAs) is proposed to reduce redundant switching actions caused by the randomness of MhAs. Two case studies are carried out to assess the feasibility and superiority of ACS in comparison with the artificial bee colony algorithm, ant colony optimization, genetic algorithm, particle swarm optimization, simulated annealing algorithm, TS, and POA. Simulation results indicate that ACS can realize fast and stable dynamic reconfiguration of a TEG system under HgTDs. In addition, RTLAB platform-based hardware-in-the-loop experiments are carried out to further validate the hardware implementation feasibility.