Search Results (1,245)

Hydraulic fracturing can significantly enhance coalbed methane production, with in-situ stress playing a crucial role in this process. Our study focuses on calculating in-situ stress in the deep 8+9# coal seam in the north-central Zijinshan block. Leveraging data from acoustic logging and hydraulic fracturing tests, we developed a stress prediction model tailored to the area’s geology. We analyzed stress’s impact on fracturing behavior and the origins of mechanical anisotropy in deep coal reservoirs using μ-CT imaging. Our results show that the Anderson-modified model, accounting for transverse isotropy, offers greater accuracy and applicability than traditional models. The study area exhibits a normal faulting stress regime with significant stress contrasts and maximum horizontal principal stress aligned with the east-west geological stress direction. After hydraulic fracturing, fractures form a complex fracture system resembling elongated ellipses in the coal reservoir, primarily extending in the vertical direction. To control fracture height and prevent penetration through the roof and floor, regulatory measures are essential. μ-CT analysis revealed the distribution of primary fractures, pores, and minerals in the coal, contributing to mechanical anisotropy. This research advances CBM development in the Zijinshan block and similar regions by refining stress prediction and fracturing propagation methods. Full article

High dust loading significantly impacts air quality, climate, and public health. Early warning is crucial for mitigating short-term effects, and accurate dust field estimates are needed for forecasting. The Copernicus Atmosphere Monitoring Service (CAMS) offers global reanalysis datasets and forecasts of particulate matter with a diameter of under 10 μm (PM₁₀), which approximate dust, but recent studies highlight discrepancies between CAMS data and ground in-situ measurements. Since CAMS is often used for forecasting, errors in PM₁₀ fields can hinder accurate dust event forecasts, which is particularly challenging for models that use artificial intelligence (AI) due to the scarcity of dust events and limited training data. This study proposes a machine-learning approach to correct CAMS PM₁₀ fields using in-situ data to enhance AI-based dust event forecasting. A correction model that links pixel-wise errors with atmospheric and meteorological variables was taught using gradient-boosting algorithms. This model is then utilized to predict CAMS error in previously unobserved pixels across the Eastern Mediterranean, generating CAMS error fields. Our bias-corrected PM₁₀ fields are, on average, 12 μg m⁻³ more accurate, often reducing CAMS errors by significant percentages. To evaluate the contribution, we train a deep neural network to predict city-scale dust events (0–72 h) over the Balkans using PM₁₀ fields. Comparing the network’s performance when trained on both original and bias-corrected CAMS PM₁₀ fields, we show that the correction improves AI-based forecasting performance across all metrics. Full article

A small experimental setup for in-situ measurement of the load-transferring strains during the curing process of thermosets is proposed. Combining the output from an unconstrained and a kinematically constrained setup, it is possible to design a cure profile for the first time, lowering the residual stresses in the final product while keeping the cure time short based on the output from a few simple experiments. The stress relaxation during the curing process under a kinetically constrained condition is accounted for by comparing the final cure-induced strain during a kinetically unconstrained and constrained cure experiment. The constrained polymer is curing between two laminates where the constraining layer is removed after finalizing the cure profile, making it possible to measure the final cure-induced strain for that case as well. The temperature at which the load-transferring point is reached is found to be a key process parameter from which the final cure-induced strains can be predicted for the unconstrained case. From the corresponding constrained cure experiments, the final residual stresses can be measured. Full article

Ichthyophthirius multifiliis, a parasitic ciliate, causes “white spot disease” in freshwater fish and poses a significant threat to global freshwater aquaculture. Eliminating the free-swimming theront stage from the aquaculture environment is a critical measure for controlling I. multifiliis infections. The natural predator of I. multifiliis theronts in fish-farming ponds were identified using fluorescent dye-labelled live theronts and quantitative PCR; meanwhile, the zooplankton community composition in the positive ponds of I. multifiliis detected by quantitative PCR were analyzed by eDNA metabarcoding assay. The results revealed predation on theronts by cyclopoid copepods, including Cyclops vicinus, Thermocyclops taihokuensis, Cyclops sp., Thermocyclops sp., Eucyclops sp., and Mesocyclops sp. from the in-situ predation aquatic ecosystem, and among these copepods, C. vicinus was identified as a natural dominant predator of I. multifiliis. This study provides a scientific basis for further exploration and utilization of natural predators to enhance sustainable and environmentally friendly control strategies against I. multifiliis. Full article

Different sulfates (Ca-, Mg, and Fe- sulfates) have been extensively detected on the Martian surface. As one of the Martian sulfates, the presence of ferrous sulfates will provide valuable clues about the redox environment, hydrological processes, and climatic history of ancient Mars. In this study, three hydrated ferrous sulfates were prepared in the laboratory by heating dehydration reactions. These samples were analyzed using X-ray Diffraction (XRD) to confirm their phase and homogeneity. Subsequently, Raman, mid-infrared (MIR) spectra, visible near-infrared (VNIR) spectra, and laser-induced breakdown spectroscopy (LIBS) were measured and analyzed. The results demonstrate that the spectra of three hydrated ferrous sulfates exhibit distinctive features (e.g., the v₁ and v₃ features of ${\mathrm{S}\mathrm{O}}_4^{2-}$ tetrahedra in their Raman and MIR spectra) that can offer new insights for identifying different ferrous sulfates on Mars and aid in the interpretation of in-situ data collected by instruments such as the Scanning Habitable Environments with Raman & Luminescence for Organics & Chemicals (SHERLOC), SuperCam, and ChemCam, etc. Full article

This study examines the in-situ lateral static load behavior of a closed-diaphragm wall foundation, aiming to better understand its load–displacement response, structural behavior, and soil interaction under horizontal loading. An in-situ static load test was conducted with a maximum applied load of 70 MN, revealing that the diaphragm wall initially exhibits a linear load–displacement response, which becomes increasingly nonlinear as the load increases. The horizontal displacement of the lateral walls is nearly identical to the overall displacement of the diaphragm wall, making it a reliable indicator of the wall’s load state, particularly when it is challenging to measure total displacement. The wall behaves as a rigid body with minimal relative displacement between sections, and overturning failure is identified as the primary failure mode. Earth pressure distribution varies around the wall: passive earth pressure is observed at the front edge, while active and passive pressures alternate at the rear edge. These findings provide valuable insights into the design of diaphragm wall foundations, emphasizing the importance of lateral displacements. Full article

Formaldehyde (HCHO) is known as one of the important indoor organic pollutants. How to remove and decompose the low concentration of formaldehyde at room temperature is important for indoor environments. Catalytic ozonation is an efficient method to thoroughly remove HCHO at room temperature, with high efficiency and few byproducts. A series of MnO_x/γ-Al₂O₃ catalysts were prepared in this work via the impregnation method and treated with different reagents (acid, alkali, and H₂O₂) to evaluate their catalytic activity for HCHO removal. The results showed that MnAl-II (acid treatment) performed well in activity tests, reaching a nearly 100% HCHO conversion at an O₃/HCHO of 2.0 and attaining a CO₂ selectivity of above 95% at an O₃/HCHO of 3.0 at 30 °C, with almost no ozone residual existing. The larger specific surface area, abundant oxygen vacancies, and higher number of acid sites contributed to the excellent performance of MnAl-II. Stability and H₂O resistance tests of MnAl-II were also conducted. To reveal the intermediate product formation and further investigate the reaction mechanism of HCHO ozonation, in-situ DRIFTS measurement was carried out combined with DFT calculations. Full article

The latest satellite in the Landsat series, Landsat-9, was successfully launched on 27 September 2021, equipped with the Operational Land Imager-2 (OLI-2) sensor, continuing the legacy of OLI/Landsat-8. To evaluate the uncertainties in water surface reflectance derived from OLI-2, this study conducts a comprehensive performance assessment of six atmospheric correction (AC) methods—DSF, C2RCC, iCOR, L2gen (NIR-SWIR1), L2gen (NIR-SWIR2), and Polymer—using in-situ measurements from 14 global sites, including 13 AERONET-OC stations and 1 MOBY station, collected between 2021 and 2023. Error analysis shows that L2gen (NIR-SWIR1) (RMSE ≤ 0.0017 sr⁻¹, SA = 6.33°) and L2gen (NIR-SWIR2) (RMSE ≤ 0.0019 sr⁻¹, SA = 6.38°) provide the best results across four visible bands, demonstrating stable performance across different optical water types (OWTs) ranging from clear to turbid water. Following these are C2RCC (RMSE ≤ 0.0030 sr⁻¹, SA = 5.74°) and Polymer (RMSE ≤ 0.0027 sr⁻¹, SA = 7.76°), with DSF (RMSE ≤ 0.0058 sr⁻¹, SA = 11.33°) and iCOR (RMSE ≤ 0.0051 sr⁻¹, SA = 12.96°) showing the poorest results. By comparing the uncertainty and consistency of Landsat-9 (OLI-2) with Sentinel-2A/B (MSI) and S-NPP/NOAA20 (VIIRS), results show that OLI-2 has similar uncertainties to MSI and VIIRS in the blue, blue-green, and green bands, with RMSE differences within 0.0002 sr⁻¹. In the red band, the OLI-2 uncertainties are lower than those of MSI but higher than those of VIIRS, with an RMSE difference of about 0.0004 sr⁻¹. Overall, OLI-2 data processed using L2gen provide reliable surface reflectance and show high consistency with MSI and VIIRS, making it suitable for integrating multi-satellite observations to enhance global coastal water color monitoring. Full article

Multicomponent gas mixture diffusion in a microscale confined flow in the transition gas regime at Knudsen numbers (Kn) above 0.1 has potential engineering applications in gas-phase microfluidics. Although the calculation of the diffusion coefficient accounts for the influence of the concentration of other species in a multicomponent gas mixture, the higher rate of gas-wall collision at 0.1 < Kn ≤ 10 introduces additional complications not predicted by conventional calculation methods. Thus, simultaneous measurement of diffusion coefficients for multiple gas species ensures accurate estimation of the diffusion coefficient of a particular species that includes the effect of interactions with other species and wall surface conditions in a multicomponent gas mixture at Kn > 0.1. However, most experimental methods for measuring the diffusion coefficient are not species-specific and therefore cannot directly differentiate between the species diffusing in a gas mixture. Thus, this paper demonstrates a new experiment methodology consisting of a two-bulb diffusion configuration accompanied by a tunable diode laser absorption spectroscopy detection technique for species-specific, in-situ, simultaneous measurement of the effective diffusion coefficient for a CO₂-N₂O gas mixture in the transition gas regime. The experimental results are compared against direct simulation Monte Carlo calculations and the Bosanquet approximation showing a deviation that has not been reported in the literature before. Full article

The objective of this study is to evaluate the ability of inverse techniques to estimate the resistance and the capacity of a highly insulated multilayer wall under real weather conditions. The wall is equipped with temperature sensors inside and on its inner and outer surfaces, and the boundary conditions have been measured over a 14-day period. Uncertainties on various parameters of the model are evaluated, including internal and external convective heat transfer coefficients (±20% and ±7 W.m^-².K⁻¹ respectively), external long-wave heat transfer coefficient (±0.15 W.m⁻².K⁻¹) and solar absorption coefficient (±0.06). A sensitivity analysis demonstrated the high correlation with some parameters defining the thermal performance of the walls (thermal resistance or capacity). A solution is proposed to limit the number of identified parameters, while allowing the identification of the thermal resistance and the thermal capacity of the walls. There are two cases: either the weather conditions are accurately measured (temperature, short- and long-wave radiation) and the thermal characteristics can be assessed, or intrusive sensors are installed, and the thermal characteristics can be evaluated more accurately. Full article

The degree of rock mass discontinuity is crucial for evaluating surrounding rock quality, yet its accurate and rapid measurement at construction sites remains challenging. This study utilizes fractal dimension to characterize the geometric characteristics of rock mass discontinuity and develops a data-driven surrounding rock classification (SRC) model integrating machine learning algorithms. Initially, the box-counting method was introduced to calculate the fractal dimension of discontinuity from the excavation face image. Subsequently, crucial parameters affecting surrounding rock quality were analyzed and selected, including rock strength, the fractal dimension of discontinuity, the discontinuity condition, the in-situ stress condition, the groundwater condition, and excavation orientation. This study compiled a database containing 246 railway and highway tunnel cases based on these parameters. Then, four SRC models were constructed, integrating Bayesian optimization (BO) with support vector machine (SVM), random forest (RF), adaptive boosting (AdaBoost), and gradient boosting decision tree (GBDT) algorithms. Evaluation indicators, including 5-fold cross-validation, precision, recall, F1-score, micro-F1-score, macro-F1-score, accuracy, and the receiver operating characteristic curve, demonstrated the GBDT-BO model’s superior robustness in learning and generalization compared to other models. Furthermore, four additional excavation face cases validated the intelligent SRC approach’s practicality. Finally, the synthetic minority over-sampling technique was employed to balance the training set. Subsequent retraining and evaluation confirmed that the imbalanced dataset does not adversely affect SRC model performance. The proposed GBDT-BO model shows promise for predicting surrounding rock quality and guiding dynamic tunnel excavation and support. Full article

The investigation of new composite materials possessing low weight but not at the expense of their mechanical performance is of great interest in terms of reducing energy consumption in many industrial applications. This study is focused on the nanomechanical characterization of high-density polyethylene (HDPE)-based composite specimens modified with equal loadings of graphene nanoplatelets (GNPs) and/or multiwall carbon nanotubes (MWCNTs). Quasi-static nanoindentation analysis revealed the impact of the carbon nanofillers on the receiving of nanocomposites with higher nanohardness and reduced modulus of elasticity, reaching values of 0.146 GPa and 3.57 GPa, respectively. The role of the indentation size effect in elastic polymer matrix was assessed by applying three distinct peak forces. Nanoscratch experiments depicted the tribological behavior of the composite samples and inferred the influence of the carbon nanofillers on the values of the coefficient of friction (COF). It seems that the incorporation of 4 wt% GNPs in the polymer structure improves the scratch resistance of the material, resulting in a higher value of the exerted lateral force and therefore leading to the detection of a higher coefficient of friction at scratch of 0.401. A considerable pile-up response of the scratched polymer specimens was observed by means of in-situ SPM imaging of the tested surface sample area. The sway of the carbon nanoparticles on the composite pile-up behavior and the effect of the pile-up on the measured friction coefficients have been explored. Full article

Trophic state index (TSI) is a critical ecological and environmental issue in water resource management that has garnered significant attention. Given the complexity of optical characteristics in aquatic environments, this study employs fuzzy classification methods (FCM) and composite nutrient status indices to meticulously classify in-situ remote sensing reflectance data, aiming to develop evaluation models for different nutrient status categories to facilitate the assessment of the Daihai River in Inner Mongolia, China. Subsequently, we applied this model to MSI data to analyze the nutrient status of Daihai Lake from 2016 to 2021. Furthermore, a structural equation model (SEM) was utilized to explore the primary driving factors influencing nutrient status. The results indicated that the water bodies in Daihai Lake can be broadly classified into three categories, with the nutrient status models demonstrating robust performance for each category (R² = 0.80, R² = 0.83, and R² = 0.74). Comparisons were made between nutrient status accuracies obtained through the NCM and FCM based on measured data, yielding R² values of 0.74 and 0.85, respectively. Furthermore, the TSI results derived from MSI inversion were validated, with NCM achieving an R² of 0.49, RMSE of 6.88, and MAPE of 10.36%, while FCM exhibited an R² of 0.55, RMSE of 8.89, and MAPE of 13.18%. An SEM–based analysis revealed that over the long term, human activities exerted a more substantial impact on eutrophication in Daihai Lake, while climatic factors played an accelerating and reinforcing role. These results are consistent with prior research in the Daihai area, indicating a state of mild eutrophication and the potential of the fuzzy classification method and comprehensive trophic status index method in eutrophication assessment. Full article

The exhaustion of conventional light oils necessitates the shift towards unconventional sources such as biomass, heavy oil, oil shale, and coal. Non-catalytic thermal cracking by a free radical mechanism is at the heart of the upgrading, prior to refining into valuable products. However, thermal pyrolysis is hindered by the formation of asphaltenes, precursors to coke, limiting cracking, causing equipment fouling, and reducing product stability. Free radicals are inherently present in heavy fractions and are generated during thermal processes. This makes these reactive intermediates central to understanding these mechanisms and limiting coking. Electron spin resonance (ESR) spectroscopy facilitates such mechanistic studies. Over the past decade, there has been no review of using in-situ ESR for studying thermal processes. This work begins with a brief description of free radicals’ chain reactions during thermal reactions and the wealth of information ESR provides. We then critically review the literature that uses ESR for mechanistic studies in thermal pyrolysis of biomass, heavy oil, shales, and coal. We conclude that limited literature exist, and more investigations are necessary. The key findings from existing literature are summarized to know the current state of knowledge. We also explicitly highlight the research gaps. Full article

Shock-induced vibrations transmitted from the racket to the tennis player’s upper limb have interested researchers, whether for investigating their effect on injury risk, or for designing new equipment. Measuring these vibrations is, however, very challenging in an ecological playing situation: sensors must be of very high quality in order to precisely measure high-energy and broad-frequency signals, as well as non-invasive in order to allow the players to perform their usual movements. The working hypothesis of this paper is that contactless sound recordings of the ball/racket impact carry the same information as direct vibratory measurements. The present study focuses on the tennis serve, as being tennis’ most energy-demanding stroke, therefore possibly being the most traumatic stroke for the upper limb. This article aims (a) to evaluate the propagation of vibration from the racket to the upper limb; and (b) to identify correlations with acoustic signals collected simultaneously. Eight expert tennis players performed serves with three rackets and two ball spin effects. Accelerometers measured the vibration on the racket and at five locations on the upper limb, and a microphone measured the impact sound. Resulting signals were analyzed in terms of energy and spectral descriptors. Results showed that flat serves produced louder sounds, higher vibration levels, lower acoustic spectral centroids, and higher vibratory spectral centroids than kick serves. The racket only had a marginal influence. Similarities between acoustic and vibratory measurements were found (levels were correlated), but so were differences (spectral centroids tended to be negatively correlated), encouraging further studies on the link between sound and vibration for the in situ measurement of shock-induced vibration. Full article