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Grinding is a crucial process in machining workpieces because it plays a vital role in achieving the desired precision and surface quality. However, a significant technical challenge in grinding is the potential increase in temperature due to high specific energy, which can lead to surface thermal damage. Therefore, ensuring control over the surface integrity of workpieces during grinding becomes a critical concern. This necessitates the development of temperature field models that consider various parameters, such as workpiece materials, grinding wheels, grinding parameters, cooling methods, and media, to guide industrial production. This study thoroughly analyzes and summarizes grinding temperature field models. First, the theory of the grinding temperature field is investigated, classifying it into traditional models based on a continuous belt heat source and those based on a discrete heat source, depending on whether the heat source is uniform and continuous. Through this examination, a more accurate grinding temperature model that closely aligns with practical grinding conditions is derived. Subsequently, various grinding thermal models are summarized, including models for the heat source distribution, energy distribution proportional coefficient, and convective heat transfer coefficient. Through comprehensive research, the most widely recognized, utilized, and accurate model for each category is identified. The application of these grinding thermal models is reviewed, shedding light on the governing laws that dictate the influence of the heat source distribution, heat distribution, and convective heat transfer in the grinding arc zone on the grinding temperature field. Finally, considering the current issues in the field of grinding temperature, potential future research directions are proposed. The aim of this study is to provide theoretical guidance and technical support for predicting workpiece temperature and improving surface integrity. The temperature field is divided into uniform continuous segment and nonuniform discontinuous counterpart. The heat source distribution model is summarized for different cutting depths. The energy proportional coefficient and convective heat transfer coefficient models are summarized. The application and implementation of temperature field and grinding thermal mode are summarized.

As additive manufacturing (AM) becomes a viable manufacturing solution, demand for an accurate thermo-structural model of the process increases. Iteratively correcting discrepancies between the CAD model and additively manufactured product through trial and error can be an expensive and time-consuming process, taking up to several hours to build and costing up to tens of thousands of dollars Lindgren et al. (Addit Manuf 12:144–158, 2016 ). A numerical model reduces manufacturing cost and time considerably by predicting discrepancies that will arise due to the complex thermal history induced by the AM process, thus reducing the need for iterative manufacturing. An important part of any additive manufacturing model is the heat source model. The heat source model is a mathematical function which represents how much of a heat source’s power actually goes into heating the powdered metal and how this heat is distributed across the heat-affected zone (HAZ). This paper provides a review and analysis of heat source models in the AM literature to date in order to alleviate some of the confusion and provide emerging researchers in the field with perspective on the issue. Both two-dimensional surface models and three dimensional volumetric models are explored. Next, an analysis of the models was performed and presented in an effort to validate their physical accuracy and mathematical usability. This analysis consisted of checking for sensible boundary conditions and ensuring that energy conservation is upheld. In surface models, the TEM 00 model is a classic representation of the Gaussian power distribution of most heat sources used in AM. Researchers interested in simply modeling the heat distribution, without accounting for any other phenomena that intervene in the heat transfer process (such as molten pool dynamics) will find the TEM 00 model suitable. The literature also shows cases where the TEM 00 model has been modified to have a sharper radial gradient, and these modifications can be suitable for high-powered heat sources. For volumetric models, Goldak’s ellipsoidal model (Metall Trans B 15(2)299–305, 1984 ) remains a straightforward and accurate model that is physically sound and applicable to a variety of cases. The Gaussian cone model presented by Rogeon et al. [ 48 ] also performs well, meeting all the required physical and mathematical restrictions. This model’s linearly decaying penetration is better suited for high-energy applications. The non-Gaussian cone proposed by Tsirkas et al. (J Mater Process Technol 134(1):59–69, 2003 ) imposes inaccurate boundary conditions and violates the first law of thermodynamics, and is thus deemed an inadequate model. Other novel models have been introduced in recent years, most notably the line model and the elongated ellipsoidal model presented by Irwin and Michaleris (J Manuf Sci Eng 138(11):111004, 2016 ). Both of these models are based on Goldak’s ellipsoidal model and attempt to maintain the accuracy of that model while allowing for fewer time steps and requiring less computational resources. These models appear to function well and can be used effectively in some applications, but could benefit from further study and validation. Care must be taken to ensure that the parameters used with these models do not result in averaging errors or a discontinuous thermal field. These tools must be used carefully with a thorough understanding of the underlying mathematics.

The thermal effect of the Tibetan Plateau (TP) on the northern hemisphere climate has long been a hot topic of scientific research. However, the global effects of the TP heat source are still unclear. We investigate the teleconnection patterns coincident with the TP heat source in boreal summer using both observational data and numerical models including a linearized baroclinic model and an atmospheric general circulation model. The western TP shows the most intense variability in atmospheric heating and the most active connection to atmospheric circulations. The surface sensible heating component of the western TP heat source is associated with a high-latitude wave train propagating from North Japan to central North America through the Bering Sea and Canada. The radiative heating component is accompanied by a wavenumber-4 wave train over Eurasia. We focus on the global zonally-oriented pattern that is connected with the latent heat release from the western TP, referred to here as the TP–circumglobal teleconnection (TP-CGT). The TP-CGT pattern is triggered by the western TP latent heating in two parts starting from the TP: an eastward-propagating wave train trapped in the westerly jet stream and a westward Rossby wave response. The TP-CGT accounts for above 18% of the total variance of the circumglobal teleconnection pattern and modulates mid-latitude precipitation by superimposition. The western TP is the key region in which diabatic heating can initiate the two atmospheric responses concurrently, and the heating over northeastern Asia or the Indian Peninsula is unable to induce the circumglobal pattern directly. The unique geographical location and strong tropospheric heating also make the western TP as a “transit area” of transferring the indirect impact of the Indian summer monsoon (ISM) to the TP-CGT. These results enhance our understanding of the relationship between the circumglobal teleconnection and the ISM and is helpful for improving the prediction of the circumglobal teleconnection variability.

Selective Laser Melting (SLM), as a common metal additive manufacturing (AM) technology, achieves high-precision complex part formation by layer-by-layer melting of metal powder using a laser. However, the dynamic behavior of the melt pool during the SLM process is influenced by the heat source model, which is crucial for suppressing porosity defects and optimizing process parameters, directly determining the reliability of numerical simulations. To address the issue of traditional surface heat source models overestimating the melt pool width and volume heat source models underestimating the melt pool depth, this study constructs a three-dimensional transient heat conduction finite element model based on ANSYS Parametric Design Language (APDL) to simulate the evolution of the temperature field and melt pool geometry under different laser parameters. First, the temperature fields and melt pool morphology and dimensions of four heat source models—Gaussian surface heat source, volumetric heat source models (rotating Gaussian volumetric heat source, double ellipsoid heat source), and a combined heat source model—were investigated. Subsequently, a dynamic heat source model was proposed, combining a Gaussian surface heat source with a rotating volumetric heat source. By dynamically allocating the laser energy absorption ratio between the powder surface layer and the substrate depth, the influence of this heat source model on melt pool size was explored and compared with other heat source models. The results show that under the dynamic heat source, the melt pool width and depth are 128.6 μm and 63.13 μm, respectively. The melt pool width is significantly larger compared to other heat source models, and the melt pool depth is about 17% greater than that of the combined heat source model. At the same time, the predicted melt pool width and depth under this heat source model have relative errors of 1.0% and 5.5% compared to the experimental measurements, indicating that this heat source model has high accuracy in predicting the melt pool’s lateral dimensions and can effectively reflect the actual melt pool morphology during processing.

The non-uniform heat generation effect on the flow of magnetized tri-hybrid nanofluid inside a stenotic artery with convective boundary conditions and activation energy is briefly compared in this article. Furthermore, the effects of viscous dissipation, thermal radiation, and Joule heating are considered. The proposed model’s goal is to assess how well Yamada–Ota and Hamilton–Crosser tri-hybrid nanofluid models perform. Employed is a tri-hybrid nanofluid made up of gold ( Au ) , silver ( Ag ) , coper ( Cu ) , and blood as the base fluid. By scrutinizing the heat transfer and fluid dynamics characteristics in constricted arteries, this study offers insights into diagnosing arterial conditions, optimizing medical interventions, and enhancing drug delivery strategies. A method of appropriate similarity variables has been used to transform PDEs into dimensionless ODEs, which have then been solved using the bvp4c built-in solver in the mathematical programmer MATLAB to obtain both numerical solutions and graphical results. Graphs are used to elaborate on the results of physical regulating parameters using concentration, temperature, and velocity profiles. When the volume friction of nanoparticles, thermal radiation, and the heat generation vary more frequently, the thermal distribution profile exhibits a growing behavior. For increasing fluctuations in the reaction rate parameter, the concentration distribution profile exhibits a decrementing behavior. In terms of mass and heat transfer effectiveness, the Yamada–Ota model surpasses the Hamilton–Crosser tri-hybrid nanofluid model. The existing strategy has the potential to be very advantageous for effective blood medication delivery. Graphical abstract

Using abandoned gas wells as geothermal resources for energy production is an effective way to extract geothermal energy from geological formations. These abandoned wells have the potential to significantly contribute in the rising global demand for energy without requiring the land disruption resulting from deep drilling or digging, processes necessary for energy extraction from geological formations via more traditional methods. In this paper, a method to extract geothermal energy from abandoned gas wells is proposed. The method offers an efficient, economical, and environmentally-conscious way to generate electricity. A mathematical model of a thermal and hydraulic coupling process is constructed, and a 3D numerical model is generated to study the process of geothermal energy extraction by retrofitting an abandoned gas reservoir into a geothermal reservoir. Using the model, heat extraction and fluid flow are analyzed over a period of 50 years. The heat production, electricity generation, and thermal recovery over the lifetime of the reservoir indicate that a commercially viable geothermal dual well system can produce geothermal energy effectively. Dual-well systems contain at least one injection well and one production well. They are composed of a two-way flow system in which the fluid flows into the reservoir via an injection well and returns from the production well having absorbed thermal energy from the surrounding rocks. Sensitivity analysis of the main parameters controlling the average outlet temperature of the fluid from the sedimentary geothermal system reveals that abandoned gas wells are a suitable source of geothermal energy. This energy can be harvested via a method whose use of reservoir fluids differs from that of the traditional method of closed-loop circulation via a borehole heat exchanger. Here, it is demonstrated that abandoned oil and gas fields can be repurposed to be geothermal energy sources that provide low-cost electricity and are economically sustainable.

Modelling and simulation are very important for revealing the relationship between process parameters and internal variables like grain morphology in solidification, precipitate evolution, and solid-state phase transformation in laser additive manufacturing. The impact of the microstructural changes on mechanical behaviors is also a hot topic in laser additive manufacturing. Here we reviewed key developments in thermal modelling, microstructural simulations, and the predictions of mechanical properties in laser additive manufacturing. A volumetric heat source model, including the Gaussian and double ellipsoid heat sources, is introduced. The main methods used in the simulation of microstructures, including Monte Carlo method, cellular automaton, and phase field method, are mainly described. The impacts of the microstructures on mechanical properties are revealed by the physics-based models including a precipitate evolution based model and dislocation evolution based model and by the crystal plasticity model. The key issues in the modelling and simulation of laser additive manufacturing are addressed.

Micro-holes are key components of printed circuit boards (PCBs) that enable the interconnections of different signal layers, and their surface quality is crucial to signal transmission performance. However, in the process of PCB micro-hole drilling, an overly high temperature can cause resin melting and the chips to stick to the tool, resulting in micro-hole quality problems such as plugging, burrs, and nail heads. Therefore, this paper studies the heat transfer trends and temperature distribution characteristics of PCBs in drilling processes. Based on the heat source method and finite difference method, a mathematical model of the PCB micro-hole drilling temperature was established first. Through experiments, the drilling force and temperature under different processing conditions were measured, and then, the heat distribution coefficients of a copper foil and an epoxy fiberglass cloth were obtained with a genetic algorithm. Next, the theoretical temperature of PCB drilling was calculated. Finally, the temperature model was verified by comparing the calculated and measured temperatures; the relative error was within 15.95%. The proposed mathematical model accurately describes the PCB micro-hole drilling temperature and provides technological support for improving the quality of micro-holes.

Methane (CH4) is a powerful greenhouse gas, whose natural and anthropogenic emissions contribute ∼20 % to global radiative forcing. Its atmospheric budget (sources and sinks), however, has large uncertainties. Inverse modelling, using atmospheric CH4 trends, spatial gradients and isotopic source signatures, has recently improved the major source estimates and their spatial–temporal variation. Nevertheless, isotopic data lack CH4 source representativeness for many sources, and their isotopic signatures are affected by incomplete knowledge of the spatial distribution of some sources, especially those related to fossil (radiocarbon-free) and microbial gas. This gap is particularly wide for geological CH4 (geo-CH4) seepage, i.e. the natural degassing of hydrocarbons from the Earth's crust. While geological seepage is widely considered a major source of atmospheric CH4, it has been largely neglected in 3-D inverse CH4 budget studies given the lack of detailed a priori gridded emission maps. Here, we report for the first time global gridded maps of geological CH4 sources, including emission and isotopic data. The 1∘×1∘ maps include the four main categories of natural geo-CH4 emission: (a) onshore hydrocarbon macro-seeps, including mud volcanoes, (b) submarine (offshore) seeps, (c) diffuse microseepage and (d) geothermal manifestations. An inventory of point sources and area sources was developed for each category, defining areal distribution (activity), CH4 fluxes (emission factors) and its stable C isotope composition (δ13C-CH4). These parameters were determined considering geological factors that control methane origin and seepage (e.g. petroleum fields, sedimentary basins, high heat flow regions, faults, seismicity). The global geo-source map reveals that the regions with the highest CH4 emissions are all located in the Northern Hemisphere, in North America, in the Caspian region, in Europe and in the East Siberian Arctic Shelf. The globally gridded CH4 emission estimate (37 Tg yr−1 exclusively based on data and modelling specifically targeted for gridding, and 43–50 Tg yr−1 when extrapolated to also account for onshore and submarine seeps with no location specific measurements available) is compatible with published ranges derived using top-down and bottom-up procedures. Improved activity and emission factor data allowed previously published mud volcanoes and microseepage emission estimates to be refined. The emission-weighted global mean δ13C-CH4 source signature of all geo-CH4 source categories is about −49 ‰. This value is significantly lower than those attributed so far in inverse studies to fossil fuel sources (−44 ‰) and geological seepage (−38 ‰). It is expected that using this updated, more 13C-depleted, isotopic signature in atmospheric modelling will increase the top-down estimate of the geological CH4 source. The geo-CH4 emission grid maps can now be used to improve atmospheric CH4 modelling, thereby improving the accuracy of the fossil fuel and microbial components. Grid csv (comma-separated values) files are available at https://doi.org/10.25925/4j3f-he27.

The current study explores a three-dimensional swirling flow of titania–ethylene glycol-based nanofluid over a stretchable cylinder with torsional motion. The heat transfer process is explored subject to heat source/sink. Here, titania–ethylene glycol–water-based nanofluid is used. The Maxwell–Bruggeman models for thermal conductivity and modified Krieger–Dougherty models for viscosity are employed to scrutinize the impact of nanoparticle aggregation. A mathematical model based on partial differential equations (PDEs) is developed to solve the flow problem. Following that, a similarity transformation is performed to reduce the equations to ordinary differential equations (ODEs), which are then solved using the finite element method. It has been proven that nanoparticle aggregation significantly increases the temperature field. The results reveal that the rise in Reynolds number improves the heat transport rate, whereas an increase in the heat source/sink parameter value declines the heat transport rate. Swirling flows are commonly found in many industrial processes such as combustion, mixing, and fluidized bed reactors. Studying the behavior of nanofluids in these flows can lead to the development of more efficient and effective industrial processes.