Search Results (61)

This study presents a simulation-based damage modeling and fatigue risk assessment of a reusable ceramic matrix composite thruster designed for short-duration, green bipropellant propulsion systems. The thruster is constructed from a fiber-reinforced ultra-high temperature ceramic matrix composite composed of zirconium diboride, silicon carbide, and carbon fibers. Time-resolved thermal and structural simulations are conducted on a validated thruster geometry to characterize the severity of early-stage thermal shock, stress buildup, and potential degradation pathways. Unlike traditional fatigue studies that rely on empirical fatigue constants or Paris-law-based crack-growth models, this work introduces a simulation-derived stress-margin envelope methodology that incorporates ±20% variability in temperature-dependent material strength, offering a physically grounded yet conservative risk estimate. From this, a normalized risk index is derived to evaluate the likelihood of damage initiation in critical regions over the 0–10 s firing window. The results indicate that the convergent throat region experiences a peak thermal gradient rate of approximately 380 K/s, with the normalized thermal shock index exceeding 43. Stress margins in this region collapse by 2.3 s, while margin loss in the flange curvature appears near 8 s. These findings are mapped into green, yellow, and red risk bands to classify operational safety zones. All the results assume no active cooling, representing conservative operating limits. If regenerative or ablative cooling is implemented, these margins would improve significantly. The framework established here enables a transparent, reproducible methodology for evaluating lifetime safety in ceramic propulsion nozzles and serves as a foundational tool for fatigue-resilient component design in green space engines. Full article

The escalating demand for efficient thermal management in lithium-ion batteries necessitates precise characterization of their thermal behavior under diverse operating conditions. This study develops a three-dimensional (3D) electrochemical–thermal coupling model grounded in porous electrode theory and energy conservation principles. The model solves multi-physics equations such as Fick’s law, Ohm’s law, and the Butler–Volmer equation, to resolve coupled electrochemical and thermal dynamics, with temperature-dependent parameters calibrated via the Arrhenius equation. Simulations under varying discharge rates reveal that high-rate discharges exacerbate internal heat accumulation. Low ambient temperatures amplify polarization effects. Forced convection cooling reduces surface temperatures but exacerbates core-to-surface thermal gradients. Structural optimization strategies demonstrate that enhancing through-thickness thermal conductivity reduces temperature differences. These findings underscore the necessity of balancing energy density and thermal management in lithium-ion battery design, proposing actionable insights such as preheating protocols for low-temperature operation, optimized cooling systems for high-rate scenarios, and material-level enhancements for improved thermal uniformity. Full article

Medium-deep borehole heat exchanger (BHE) systems represent an emerging form of ground source heat pump technology. Their heat transfer process is significantly influenced by geothermal gradient and soil stratification, typically simulated using segmented finite line source (SFLS) models. However, this approach involves computationally intensive procedures that hinder practical engineering implementation. Building upon an SFLS model adapted for complex geological conditions, this study proposes a comprehensive simplified algorithm: (1) For soil stratification: A geothermally-weighted thermal conductivity method converts layered heterogeneous media into an equivalent homogeneous medium; (2) For geothermal gradient: A temperature correction method establishes fluid temperatures under geothermal gradient by superimposing correction terms onto uniform-temperature model results (g-function model). Validated through two engineering case studies, this integrated algorithm provides a straightforward technical tool for heat transfer calculations in BHE systems. Full article

The degradation of subarctic peatland ecosystems under climate change impacts surrounding landscapes, carbon balance, and biogeochemical cycles. To assess these ecosystems’ responses to climate change, it is essential to consider not only the active-layer thickness but also its thermo-hydraulic conditions. Ground-penetrating radar is one of the leading methods for studying the active layer, and this paper proposes systematically investigating its potential to determine the thermal properties of the active layer. Collected experimental data confirm temperature hysteresis in peat linked to changes in water and ice content, which GPR may detect. Using palsa mires of the Kola Peninsula (NW Russia) as a case study, we analyze relationships between peat parameters in the active layer and search for thermal gradient responses in GPR signal attributes. The results reveal that frequency-dependent GPR attributes can delineate thermal intervals of ±1 °C through disperse waveguides. However, further verification is needed to clarify the conditions under which GPR can reliably detect temperature variations in peat, considering factors such as moisture content and peat structure. In conclusion, our study discusses the potential of GPR for remotely monitoring freeze–thaw processes and moisture distribution in frozen peatlands and its role as a valuable tool for studying peat thermal properties in terms of permafrost stability prediction. Full article

Given the high proportion of global fossil energy consumption, the Ordovician karst water in the North China-type coalfield, as a green energy source that harnesses both water and heat, holds significant potential for mitigating environmental issues associated with fossil fuels. In this work, we collected geothermal water samples and conducted borehole temperature measurements at the Xinhu Coal Mine in the Huaibei Coalfield, analyzed the chemical composition of regional geothermal water, elucidated the characteristics of thermal storage, and explored the influence of regional structure on the karst geothermal system in the northern region. The results indicate that the geothermal water chemistry at the Xinhu Coal Mine is of the Na-K-Cl-SO₄ type, with its chemical composition primarily controlled by evaporation and concentration processes. The average temperature of the Ordovician limestone thermal reservoir is 48.2 °C, and the average water circulation depth is 1153 m, suggesting karst geothermal water undergoing deep circulation. The geothermal gradient at the Xinhu Coal Mine ranges from 22 to 33 °C/km, which falls within the normal range for ground-temperature gradients. A notable jump in the geothermal gradient at well G1 suggests a strong hydraulic connection between deep strata within the mine. The heat-accumulation model of the hydrothermal mine geothermal system is influenced by strata, lithology, and fault structures. The distribution of high ground-temperature gradients in the northern region is a result of the combined effects of heat conduction from deep strata and convection of geothermal water. The Ordovician limestone and extensional faults provide a geological foundation for the abundant water and efficient heat conduction of the thermal reservoirs. Full article

Advective heat fluxes (chimney effect) in porous debris facilitate ground cooling on scree slopes, even at low altitudes, and promote the occurrence of sporadic permafrost. The spatial distribution of ground surface temperature on an overcooled, low-altitude scree slope in the Romanian Carpathians was analyzed using UAV-based infrared thermography in different seasons. The analysis revealed significant temperature gradients within the scree slope, with colder, forest-insulated lower sections contrasting with warmer, solar-exposed upper regions. Across all surveyed seasons, this pattern remained evident, with the strongest temperature contrasts in December and April. February exhibited the most stable temperatures, with thermal readings primarily corresponding to snow surfaces rather than exposed rock. Rock surfaces displayed greater temperature variation than vent holes. Vent holes were generally cooler than rock surfaces, particularly in warmer periods. The persistent presence of ice and low temperatures at the end of the warm season suggested the potential existence of isolated permafrost. The results confirm the chimney effect, where cold air infiltrates the lower talus, gradually warms as it ascends, and outflows at higher elevations. UAV-based thermal imagery proved effective in detecting microclimatic variability and elucidating thermal processes governing talus slopes. This study provides valuable insights into extrazonal permafrost behavior, particularly in the context of global climate change. Full article

Understanding global patterns of tree canopy height and density is essential for effective forest management and conservation planning. This study examines how these attributes vary along latitudinal gradients and identifies key climatic drivers influencing them. We utilized high-resolution remote sensing datasets, including a 10 m resolution canopy height dataset aggregated to 1 km for computational efficiency, and a 1 km resolution tree density dataset derived from ground-based measurements. To quantify the relationships between forest structure and environmental factors, we applied nonlinear regression models and climate dependency analyses, incorporating bioclimatic variables from the WorldClim dataset. Our key finding is that latitude exerts a dominant but asymmetric control on tree height and density, with tropical regions exhibiting the strongest correlations. Tree height follows a quadratic latitudinal pattern, explaining 29.3% of global variation, but this relationship is most pronounced in the tropics (−10° to 10° latitude, R² = 91.3%), where warm and humid conditions promote taller forests. Importantly, this effect differs by hemisphere, with the Southern Hemisphere (R² = 67.1%) showing stronger latitudinal dependence than the Northern Hemisphere (R² = 35.3%), indicating climatic asymmetry in forest growth dynamics. Tree density exhibits a similar quadratic trend but with weaker global predictive power (R² = 7%); however, within the tropics, latitude explains 90.6% of tree density variation, underscoring strong environmental constraints in biodiverse ecosystems. Among climatic factors, isothermality (Bio 3) is identified as the strongest determinant of tree height (R² = 50.8%), suggesting that regions with stable temperature fluctuations foster taller forests. Tree density is most strongly influenced by the mean diurnal temperature range (Bio 2, R² = 36.3%), emphasizing the role of daily thermal variability in tree distribution. Precipitation-related factors (Bio 14 and Bio 19) moderately explain tree height (~33%) and tree density (~25%), reinforcing the role of moisture availability in structuring forests. This study advances forest ecology research by integrating high-resolution canopy structure data with robust climate-driven modeling, revealing previously undocumented hemispheric asymmetries and biome-specific climate dependencies. These findings improve global forest predictive models and offer new insights for conservation strategies, particularly in tropical regions vulnerable to climate change. Full article

Dryness is a critical limiting factor for achieving high agricultural productivity on China’s Loess Plateau (LP). High-precision, field-scale dryness monitoring is essential for the implementation of precision agriculture. However, obtaining dryness information with adequate spatial and temporal resolution remains a significant challenge. Unmanned aerial vehicle (UAV) systems can capture high-resolution remote sensing images on demand, but the effectiveness of UAV-based dryness indices in mapping the high-resolution spatial heterogeneity of dryness across different crop areas at the agricultural field scale on the LP has yet to be fully explored. Here, we conducted UAV–ground synchronized experiments on three typical croplands in the eastern Gansu province of the Loess Plateau (LP). Multispectral and thermal infrared sensors mounted on the UAV were used to collect high-resolution multispectral and thermal images. The temperature vegetation dryness index (TVDI) and the temperature–vegetation–soil moisture dryness index (TVMDI) were calculated based on UAV imagery. A total of 14 vegetation indices (VIs) were employed to construct various VI-based TVDIs, and the optimal VI was selected. Correlation analysis and Gradient Structure Similarity (GSSIM) were applied to evaluate the suitability and spatial differences between the TVDI and TVMDI for dryness monitoring. The results indicate that TVDIs constructed using the normalized difference vegetation index (NDVI) and the visible atmospherically resistant index (VARI) were more consistent with the characteristics of crop responses to dryness stress. Furthermore, the TVDI demonstrated higher sensitivity in dryness monitoring compared with the TVMDI, making it more suitable for assessing dryness variations in rain-fed agriculture in arid regions. Full article

Ground source heat pump (GSHP) systems have been widely used in the field of shallow geothermal heating and cooling because of their high thermal efficiency and environmental friendliness. A borehole heat exchanger (BHE) is the key part of a ground source heat pump system, and its performance and investment cost have a direct and significant impact on the performance and cost of the whole system. The ground temperature gradient, air temperature, seepage flow rate, and injection flow rate affect the heat exchange performance of BHEs, but most of the research on BHEs lacks field test verification. Therefore, this study relied on the results of a field thermal response test (TRT) based on a distributed optical fiber temperature sensor (DOFTS) and site hydrological, geological, and geothermal data to establish a corrected numerical model of buried pipe heat transfer and carry out the heat transfer performance analysis of a buried pipe in the heating season. The results showed that the ground temperature gradient of the test site was about 3.0 °C/100 m, and the temperature of the constant-temperature layer was about 9.17 °C. Increasing the air temperature could improve the heat transfer performance. The temperature of the surrounding rock and soil mass of the single pipe spread uniformly, and the closer it was to the buried pipe, the lower the temperature. When there is groundwater seepage, the seepage carries the cold energy generated by a buried pipe’s heat transfer through heat convection to form a plume zone, which can effectively alleviate the phenomenon of cold accumulation. With an increase in seepage velocity, the heat transfer of the buried pipe increases nonlinearly. The heat transfer performance can be improved by appropriately reducing the temperature and velocity of the injected fluid. Selecting a backfill material with higher thermal conductivity than the ground body can improve the heat transfer performance. These research results can provide support for the optimization of the heat transfer performance of a buried tube heat exchanger. Full article

Surface longwave radiation (SLR) plays a pivotal role in the Earth’s energy balance, influencing a range of environmental processes and climate dynamics. As the demand for high spatial resolution remote sensing products grows, there is an increasing need for accurate SLR retrieval with enhanced spatial detail. This study focuses on the development and validation of models to estimate SLR using measurements from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor. Given the limitations posed by fewer spectral bands and data products in ASTER compared to moderate-resolution sensors, the proposed approach combines an atmospheric radiative transfer model MODerate resolution atmospheric TRANsmission (MODTRAN) with the Light Gradient Boosting Machine algorithm to estimate SLR. The MODTRAN simulations were performed to construct a representative training dataset based on comprehensive global atmospheric profiles and surface emissivity spectra data. Global sensitivity analyses reveal that key inputs influencing the accuracy of SLR retrievals should reflect surface thermal radiative signals and near-surface atmospheric conditions. Validated against ground-based measurements, surface upward longwave radiation (SULR) and surface downward longwave radiation (SDLR) using ASTER thermal infrared bands and surface elevation estimations resulted in root mean square errors of 17.76 W/m² and 25.36 W/m², with biases of 3.42 W/m² and 3.92 W/m², respectively. Retrievals show systematic biases related to extreme temperature and moisture conditions, e.g., causing overestimation of SULR in hot humid conditions and underestimation of SDLR in arid conditions. While challenges persist, particularly in addressing atmospheric variables and cloud masking, this work lays a foundation for accurate SLR retrieval from high spatial resolution sensors like ASTER. The potential applications extend to upcoming satellite missions, such as the Landsat Next, and contribute to advancing high-resolution remote sensing capabilities for an improved understanding of Earth’s energy dynamics. Full article

Geothermal energy exploration, development, and research have been ongoing in Canada for several decades. The country’s cold climate and the push to develop renewable energy sources have driven interest in geothermal energy. Despite this drive, regulatory complexities and competition with other relatively inexpensive energy sources with existing infrastructure have hindered development. As such, interest has grown and waned with changes in the energy economy over several decades, leaving many projects at a standstill. As of January 2023, there are currently no operational geothermal power projects in Canada. Many hot spring pool and spa complexes remain active, and Canada is a leading country in the installation of ground source heat pumps (GSHPs; also called geo-exchange systems). However, in the last decade, the interest in deep geothermal systems has renewed, with many new projects starting up across several provinces and territories. Moreover, projects that had shown limited progress for many years—such as Mount Meager in British Columbia—have begun to renew their development efforts. Research is also expanding within prominent research groups and universities. The areas of focus include both building upon previous studies (such as thermal gradients and the heat flow in sedimentary basins) and researching new methods and resources (such as GSHPs, closed-loop systems, integrated geothermal operations, and hybrid systems, including heat storage). The development is supported by federal, provincial, and territorial governments through grants and the development of regulatory frameworks. Although challenges still remain for Canada to develop its geothermal energy resources, several power, thermal, and co-production projects, ongoing research, funding, and regulatory acts are all moving forward to support geothermal development. This paper aims to study Canada’s geothermal energy update in 2023 regarding the aspects mentioned above. Full article

This study aims to elucidate the influence of meteorological conditions on particle levels in Cergy-Pontoise. It explores the temporal variability of PM10 pollution days by associating them with the vertical temperature profile derived from conventional radiosondes from 2013 to 2022 (regional station). The results indicate that nearly 80% of exceedance days were associated with thermal inversions, primarily observed in winter and typically lasting 1 to 3 days. Analysis of winter thermal inversion characteristics suggests that those linked to pollution primarily occur near the ground, with higher intensity in December (12.1 °C) and lower in February (10.3 °C). Persistent inversions (extended nocturnal by diurnal inversion) account for 91.4% of the total inversions associated with high concentrations. Captive balloon soundings and temperature measurements at different altitudes were conducted during the winter of 2022/2023 to clarify thermal inversion in the Oise Valley at the center of Cergy-Pontoise. The results highlight three nocturnal wind circulation mechanisms in the valley, including downslope flow, circulation influenced by an urban heat island, and mechanical air evacuation under an inversion layer towards the less steep East side of the valley. Analysis of PM with the temperature gradient in the Oise Valley shows a significant correlation, suggesting an increase in concentrations during locally detected inversions and a decrease during atmospheric disturbance. Full article

Due to the continuously growing demands from high-added-value sectors such as aerospace, e-mobility or biomedical bound-abrasive technologies are the key to achieving extreme requirements. During grinding, energy is rapidly dissipated as heat, generating thermal fields on the ground part which are characterized by high temperatures and very steep gradients. The consequences on the ground part are broadly known as grinding burn. Therefore, the measurement of workpiece temperature during grinding has become a critical issue. Many techniques have been used for temperature measurement in grinding, amongst which, the so-called grindable thermocouples exhibit great potential and have been successfully used in creep-feed grinding operations, in which table speed is low, and therefore, temperature gradients are not very steep. However, in conventional grinding operations with faster table speeds, as most industrial operations are, the delay in the response of the thermocouple results in large errors in the maximum measured value. In this paper, the need for accurate calibration of the response of grindable thermocouples is studied as a prior step for signal integration to correct thermal inertia. The results show that, if the raw signal is directly used from the thermocouples, the deviation in the maximum temperature with respect to the theoretical model is over 200 K. After integration using the calibration constants obtained for the ground junction, the error can be reduced to 93 K even for feed speeds as high as 40 m/min and below 20 K for lower feed speeds. The main conclusion is that, following the proposed procedure, maximum grinding temperatures can be effectively measured using grindable thermocouples even at high values of table speed. Full article

This study explores ground-breaking methods for improving engine efficiency by combining cutting-edge materials, theoretical frameworks, and alternative energy paradigms. The paper primarily offers a cohesive framework, built from our variational method which combines thermal and entropic engines. We investigate the fabrication of hydrophobic and other functionally specific surfaces using nanomaterials and sophisticated surface engineering techniques that efficiently utilize entropy gradient forces. Additionally, this publication explores the fields of quantum-based propulsion systems and information-burning engines, creating a connecting link between theoretical foundations and real-world technical implementations. The study emphasizes the multifaceted character of engine research and its crucial role in shaping a future in which sustainability and efficiency are intimately connected. Full article

Global temperatures are continuing to rise as atmospheric carbon dioxide (CO₂) concentrations increase, and climate warming has become a major challenge to global sustainable development. The Cross-Track Infrared Sounder (CrIS) instrument is a Fourier transform spectrometer with 0.625 cm⁻¹ spectral resolution covering a 15 μm CO₂-absorbing band, providing a way of monitoring CO₂ with on a large scale twice a day. This paper proposes a method to predict the concentration of column-averaged CO₂ (XCO₂) from thermal infrared satellite data using ensemble learning to avoid the iterative computations of radiative transfer models, which are necessary for optimization estimation (OE). The training data set is constructed with CrIS satellite data, European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) meteorological parameters, and ground-based observations. The training set was processed using two methods: correlation significance analysis (abbreviated as CSA) and principal component analysis (PCA). Extreme Gradient Boosters (XGBoost), Extreme Random Trees (ERT), and Gradient Boost Regression Tree (GBRT) are used for training and learning to develop the new retrieval model. The results showed that the R² of XCO₂ prediction built from the PCA dataset was bigger than that from the CSA dataset. These three learning models were verified by validation sets, and the ERT model showed the best agreement between model predictions and the truth (R² = 0.9006, RMSE = 0.7994 ppmv, MAE = 0.5804 ppmv). The ERT model was finally selected to estimate the concentrations of XCO₂. The deviation of XCO₂ predictions of 12 TCCON sites in 2019 was within ±1 ppm. The monthly averages of XCO₂ concentrations in close agreement with TCCON ground observations were grouped into four regions: Asia (R² = 0.9671, RMSE = 0.7072 ppmv), Europe (R² = 0.9703, RMSE = 0.8733 ppmv), North America (R² = 0.9800, RMSE = 0.6187 ppmv), and Oceania (R² = 0.9558, RMSE = 0.4614 ppmv). Full article