Search Results (17,222)

The non-thermal plasma-driven cascade process for CO₂-to-methanol conversion shows significant potential in the field of green methanol synthesis. This process innovatively couples a plasma activation module with a catalytic synthesis module via a multi-stage pressurization device, establishing an efficient two-step pathway that converts CO₂ into methanol via a CO intermediate. Such an arrangement establishes an energy conversion system characterized by both low carbon emissions and high efficiency. This work involved an initial technical evaluation employing a custom-built, lab-scale apparatus. The optimum parameters determined through this assessment were a plasma input voltage of 40 V combined with a subsequent reaction temperature of 240 °C. Operation at these specified parameters yielded a CO₂ conversion of 48%, with the methanol selectivity and production rate reaching 40% and 502 g_MeOH·kg−1 cat·h⁻¹, respectively. Furthermore, industrial-scale process design and scale-up were performed, accompanied by process simulation using Aspen Plus and a subsequent techno-economic evaluation. The results indicate that, compared to the conventional direct CO₂ hydrogenation process, the proposed cascade route can reduce the capital investment by approximately 17%. Full article

Shale oil reservoirs are complex multi-scale nanoporous media where fluid transport is governed by coupled micro-mechanisms, demanding a robust modeling framework. This study presents a novel fluid–solid coupling (FSC) numerical model that rigorously integrates the three primary scale-dependent transport phenomena: adsorption in organic nanopores, slip effects in inorganic micropores, and stress-sensitive conductivity in fractures. The model provides essential quantitative insights into the dynamic interaction between fluid withdrawal and reservoir deformation. Simulation results reveal that microstructural properties dictate the reservoir’s mechanical stability. Specifically, larger pore diameters and higher porosity enhance stress dissipation, promoting long-term stress relaxation and mitigating permeability decay. Crucially, tortuosity governs the mechanical response by controlling pressure transmission pathways: low tortuosity causes localized stress concentration, leading to rapid micro-channel closure, while high tortuosity ensures stress homogenization, preserving long-term permeability. Furthermore, high fracture conductivity induces a severe, heterogeneous stress field near the wellbore, which dictates early-stage mechanical failure. This work provides a powerful, mechanism-based tool for optimizing micro-structure and production strategies in unconventional resources. Full article

The development of coal resources has created a large number of underground mined-out spaces, which can be utilized for cross-seasonal thermal storage through underground reservoirs to achieve seasonal heat storage. However, there is currently limited research on the cross-seasonal thermal storage capabilities and thermal storage performance evaluation of coal mine underground reservoirs. This study aims to evaluate the operational stability and long-term performance of a Coal Mine Underground Reservoir Energy Storage System (CMUR-ESS) under realistic geological conditions of the Shendong Coalfield. A multi-physics coupling model, integrating thermal-fluid processes, was developed based on the actual structure of the No. 5-2 coal seam goaf in the Dalinta Mine. Numerical simulations were conducted over five annual cycles, each comprising injection, storage, production, and transition stages. Results demonstrate that the system achieves progressive thermal accumulation, with the volume fraction of water above 70 °C increasing from 75.0% in the first cycle to 88.9% by the fifth cycle at the end of the storage stage. Production temperatures also improved, with peak and final temperatures rising by 6.2% and 6.8%, respectively, after five cycles. The analysis confirms enhanced heat retention and reduced thermal loss over time, indicating robust long-term stability and sustainability of the CMUR-ESS for seasonal energy storage applications. The results of this study can provide a reference for the design and evaluation of CMUR-ESS. Full article

High penetration and output volatility of island wind and photovoltaics (PV) pose challenges to energy consumption and supply–demand balance, and cost-effective energy storage configuration. A coupled dispatch model for a wind–PV–storage system is proposed, which treats multiple canal units as virtual ‘loads’ that switch between generation and pumping under constraints of power balance and available water head model. Considering the variable reservoir–irrigation feature, a multi-objective model framework is developed to minimize both economic cost and storage capacity required. An augmented Lagrangian–Nash product enhanced NSGA-II (AL-NP-NSGA-II) algorithm enforces constraints of irrigation shortfall and overflow via an augmented Lagrangian term and allocates fair benefits across canal units through a Nash product reward. Moreover, updates of Lagrange multipliers and reward weights maintain power balance and accelerate convergence. Finally, a case simulation (3.7 MW wind, 7.1 MW PV, and 24 h rural load) is performed, where 440.98 kWh storage eliminates shortfall/overflow and yields 1.5172 × 10⁴ CNY. Monte Carlo uncertainty analysis (±10% perturbations in load, wind, and PV) shows that increasing storage to 680 kWh can stabilize reliability above 98% and raise economic benefit to 1.5195 × 10⁴ CNY. The dispatch framework delivers coordination of irrigation and power balance in island microgrids, providing a systematic configuration solution. Full article

Real-Time Precise Orbit Determination (RTPOD) of Low Earth Orbit (LEO) satellites relies primarily on onboard GNSS observations and may suffer from degraded performance when observation geometry weakens or tracking conditions deteriorate within satellite formations. To enhance the robustness and accuracy of RTPOD under such conditions, a cooperative Extended Kalman Filter (EKF) framework that fuses onboard GNSS and inter-satellite link (ISL) range measurements is established, integrated with an iterative Detection, Identification, and Adaptation (DIA) quality control algorithm. By introducing high-precision ISL range measurements, the strategy increases observation redundancy, improves the effective observation geometry, and provides strong relative position constraints among LEO satellites. This constraint strengthens solution stability and convergence, while simultaneously enhancing the sensitivity of the DIA-based quality control to observation outliers. The proposed strategy is validated in a simulated real-time environment using Centre National d’Etudes Spatiales (CNES) real-time products and onboard observations of the GRACE-FO mission. The results demonstrate comprehensive performance enhancements for both satellites over the experimental period. For the GRACE-D satellite, which suffers from about 17% data loss and a cycle slip ratio several times higher than that of GRACE-C, the mean orbit accuracy improves by 39% (from 13.1 cm to 8.0 cm), and the average convergence time is shortened by 44.3%. In comparison, the GRACE-C satellite achieves a 4.2% mean accuracy refinement and a 1.3% reduction in convergence time. These findings reveal a cooperative stabilization mechanism, where the high-precision spatiotemporal reference is transferred from the robust node to the degraded node via inter-satellite range measurements. This study demonstrates the effectiveness of the proposed method in enhancing the robustness and stability of formation orbit determination and provides algorithmic validation for future RTPOD of LEO satellite formations or large-scale constellations. Full article

An algorithm named ASR-BL-SA is proposed to solve the impact of a rectangular-part nesting sequence on final material utilization. Based on the Bottom Left principle, a coefficient, k, is defined as the ratio of the shape factor to 0.785 plus the square root of the min–max-normalized area. Parts are sorted in descending order of k. To tackle the flexible adaptation of part width and height via 90° rotation for sheet size and irregular leftover space, the Bottom Left algorithm initially compares utilization of original and rotated placements, selecting the option with higher utilization at each step. Finally, simulated annealing is applied for optimization. Experiments show that in the small-batch test, the proposed algorithm improves utilization by 5.51%, 3.75%, 8.84%, 5.51%, and 3.75% compared to the three baselines; in the mass production test, the improvements are 1.74%, 7.98%, 2.6%, 1.74%, and 7.89% within an acceptable time; in general applicability Test 3, its utilization is basically higher than the five comparative algorithms, achieving certain improvements in utilization. Full article

Weaning age is a critical management decision in beef cattle production, influencing herd productivity, financial outcomes, and overall system sustainability. Commonly practiced in South African beef systems, is where calves are weaned at 6–9 months (conventional weaning), while early weaning (EW) at approximately 90 days remains underutilized. This study presents a farm case study and preliminary financial assessment of EW and CW using a farm calculation model incorporating revenue, weaning costs, supplementation, and labor. Data from 152 Bonsmara cow–calf pairs were analyzed. CW calves achieved higher weaning weights (237 kg) and average daily gains (992 g/day) than EW calves (210 kg; 889 g/day), generating greater revenue (R630,420 vs. R558,600). The Pearson Chi-square test showed an association between weaning system and dam reproductive performance, with EW cows achieving a 94% pregnancy rate compared to 84% under CW. Although CW produced higher short-term gross margins (R6446 per system vs. R3068 for EW), sensitivity analyses indicated that EW becomes financially competitive when price premiums are applied. Simulations showed that an EW price range of R34–R40/kg could yield higher returns despite lower weights. These findings demonstrate that EW, when supported by structured price incentives, can enhance reproductive efficiency and contribute to more sustainable and financially resilient beef production systems in South Africa. Full article

Tracking ecosystem productivity in fast-evolving estuarine wetlands is often constrained by the trade-off between spatial detail and temporal continuity in satellite observations. To address this, we developed a reproducible fusion–VPM framework that integrates multi-sensor data to map Gross Primary Production (GPP) at a high spatiotemporal resolution. By combining the Flexible Spatiotemporal Data Fusion (FSDAF) method with a Time-Series Linear Fitting Model (TSLFM), we constructed a continuous 30 m, 8-day vegetation index record for China’s Yellow River Delta (YRD) from 2000 to 2021. This record was propagated through the Vegetation Photosynthesis Model (VPM) to simulate GPP and quantify the relative contributions of land-use/land-cover change (LUCC) versus environmental factors. The results show a marginally significant increase in total GPP (9.74 Gg C a⁻¹, p = 0.074) over the last two decades. Deconvolution of driving factors reveals that 87.45% of the GPP increase occurred in stable land-cover areas, where the Enhanced Vegetation Index (EVI) was the dominant driver (explaining 79.97% of the variability). In areas undergoing LUCC, the net effect on GPP primarily reflected the combined influences of artificial saline–alkali wetland expansion and cropland expansion: water-to-vegetation conversions enhanced GPP, whereas vegetation-to-water conversions fully offset these gains. This study demonstrates the efficacy of spatiotemporal data fusion in overcoming observational gaps and provides a transferable analytical framework for diagnosing carbon dynamics in complex, dynamic deltaic ecosystems. This study not only provides a critical, high-resolution assessment of carbon dynamics for the YRD but also delivers a generalizable analytical framework for mapping and attributing GPP trends in complex deltaic ecosystems worldwide. Full article

Parcel size strongly influences agricultural production costs, and combining spatial and economic information within a mathematical setting helps to clarify this relationship. In this study, we introduce a Gamma-based stochastic framework to integrate actual parcel size distributions into cost estimates, an approach that, to our knowledge, has not been applied in this context. Using a representative traditional orchard system as a case study, parcel sizes (characterized by strong right skewness) are modelled with a Gamma distribution; for highly fragmented landscapes, a truncated Gamma on $(0.01,1]$ ha yields a mean parcel area of about $0.255$ ha. Results show that parcel-size heterogeneity substantially affects expected per-parcel costs; for example, calibrating ploughing at 800 EUR/ha leads to an average of ∼160 EUR/parcel, whereas intensive vegetable harvesting at 5000 EUR/ha reaches ∼2100 EUR/parcel. In our simulation, in which the main parameters have been roughly fixed with the aim of showing the methodology, results are given on an expected costs scale relative to parcel area and operation intensity. Overall, the framework shows how parcel-size distributions condition cost estimates and provides a transferable basis for comparative analyses, while acknowledging limitations related to the area-only specification. Full article

Due to the world’s rising energy demand and reliance on fossil fuels, exploring cleaner energy sources is urgent. Green diesel from renewable resources, such as waste vegetable oil, is promising because it is compatible with petroleum diesel from fossil fuels. This study examined the simulation of the hydrotreatment process of waste cooking oil (WCO) to produce green diesel. ChemCAD version 8.1 was used to develop the simulation, along with a kinetic model based on the Langmuir–Hinshelwood mechanism (an LH-C-ND model), where fatty acids, such as oleic, stearic, and palmitic acid, in WCO are converted into long-chain hydrocarbons (C15, C16, C17, and C18). The influence of process parameters on green diesel yield was assessed at various temperatures, pressures, and H₂/oil ratios. The best process conditions for green diesel production were identified as a temperature of 275 °C, a pressure of 30 bars, and an H₂/oil ratio of 0.3. Minimising the formation of CO₂, CO, and water. Under these conditions, a high green diesel yield was achieved, with WCO conversion exceeding 90%, and over 80% of the products were suitable for green diesel. This research supports SDG 7, which aims for universal access to affordable, reliable, sustainable, and modern energy, by exploring cleaner energy options, such as green diesel from waste vegetable oil. It is recommended to perform a life cycle assessment to evaluate the overall environmental impact. Full article

The study is dedicated to the accuracy of engineering analyses of virtual prototypes. In particular, it aims to quantify the importance of material models and data consistent with physical tests. The focus is set on the stress–strain material characteristic that is the basis for correct simulation results, and the deviations of its parameters—elasticity module and yield stress—that are assessed. This is performed in three main steps: laboratory measurement of the material properties of a sample material (aluminum alloy), followed by an engineering analysis of a component produced from the same material, using the determined mechanical characteristics. The third step involves physical tests used to validate the virtual prototyping results by comparing them with the physical test results. The material properties used in the virtual prototype are subjected to a sensitivity analysis to determine their influence on the design’s elastic and plastic behavior. The main conclusions of the study are the importance of these material characteristics for achieving an adequate result. A general recommendation is formed that shows the importance of laboratory testing of material properties before virtual prototyping to avoid any influence of factors as production technology or geometry (specimen thickness). Full article

The global shift toward antibiotic-free poultry production has created an urgent need for sustainable feed additives that promote gut health and productivity. This study aimed to develop and evaluate a novel double-layered microencapsulated phytosynbiotic (DMP) comprising Tiliacora triandra extract, probiotics, and cereal by-products using lyophilization. In Experiment 1, we investigated the effects of cell wall materials (corn, defatted rice bran, and wheat bran) and different particle sizes (0.6 and 1.0 mm) on the physicochemical characteristics and probiotic encapsulation efficiency. Results revealed that wheat bran, particularly at the smaller particle size of 0.6 mm, enhanced probiotic viability, probiotic stability under simulated gastrointestinal and thermal conditions, and nutrient retention. Compared with other materials, wheat bran also provided superior powder flowability, lower density, and favorable color attributes. In Experiment 2, we assessed the influence of probiotic strains (P. acidilactici, Lactiplantibacillus plantarum TISTR 926, and Streptococcus thermophilus TISTR 894) on functional properties of the DMP. All strains exhibited high encapsulation efficiency and stability during gastrointestinal simulation, thermal exposure, and storage. However, P. acidilactici had superior fermentation kinetics and produced greater levels of beneficial short-chain fatty acids, especially acetic and butyric acids. Antibacterial activity was strain-dependent, with notable inhibitory effects against Gram-positive pathogens, primarily through bacteriostatic mechanisms. Overall, these findings confirm that the developed DMP formulations effectively stabilize probiotics and bioactive phytochemicals, offering a promising strategy for enhancing gut health and performance in antibiotic-free broiler production systems. Full article

The digital and ecological transition of the industrial sector requires methodological tools that integrate information modelling, performance simulation, and operational decision support. In this context, the present study introduces and tests a semi-automatic BIM-to-BEM framework to optimise human–machine interaction and support critical data interpretation through Graphical User Interfaces. The objective is to propose and validate a BIM-to-BEM workflow for an existing industrial facility to enable comparative evaluation of energy retrofit scenarios. The information model, developed through an interdisciplinary federated approach and calibrated using parametric procedures, was exported in the gbXML format to generate a dynamic, interoperable energy model. Six simulation scenarios were defined incrementally, including interventions on the building envelope, Heating, Ventilation and Air Conditioning (HVAC) systems, photovoltaic production, and relamping. Results are made accessible through dashboards developed with Business Intelligence tools, allowing direct comparison of different design configurations in terms of thermal loads and indoor environmental stability, highlighting the effectiveness of integrated solutions. For example, the combined interventions reduced heating demand by up to 32% without compromising thermal comfort, while in the relamping scenario alone, the building could achieve an estimated 300 MWh reduction in annual electricity consumption. The proposed workflow serves as a technical foundation for developing an operational and evolving Digital Twin, oriented toward the sustainable governance of building–system interactions. The method proves to be replicable and scalable, offering a practical reference model to support the energy transition of existing industrial environments. Full article

Alfalfa (Medicago sativa L.) is an important forage crop with significant economic value. Alternating partial root-zone irrigation (APRI) is a promising water-saving technique that has been shown to improve water use efficiency in various crops. In this study, the effects of APRI on root water uptake, photosynthetic indices, and physiological responses in alfalfa were investigated. Polyethylene glycol (PEG 6000) was used to simulate water stress, and four irrigation treatments were established: conventional irrigation (CI), deficit irrigation (DI), fixed partial root-zone irrigation (FPRI), and APRI. Principal component analysis (PCA) revealed that APRI reduced stomatal conductance (Gs) by 19.82% and transpiration rate (E) by 19.16%, which was associated with increased abscisic acid (ABA) content, thereby enhancing instantaneous water use efficiency (iWUE) by 47.93%. Meanwhile, APRI promoted root growth, leading to a 14.09% increase in root–shoot ratio, which in turn enhanced the photosynthetic rate by 22.06%. APRI enhanced methyl jasmonate (MeJA) content in alfalfa leaves by 45.23%, which was associated with a 24.13% improvement in water absorption capacity. In conclusion, APRI induced positive physiological responses in alfalfa, with the effectiveness ranked as follows: APRI > CI > FPRI > DI. These findings provide a theoretical basis for the rational application of APRI in alfalfa forage production. Full article

Structural insights into methyl-coenzyme M reductase from Methanobrevibacter ruminantium (M. ruminantium) has implications for methane mitigation strategies. Methanogenesis in ruminants is a major contributor to global greenhouse gas emissions, primarily driven by the rumen archaeon M. ruminantium. Central to this process is methyl-coenzyme M reductase (Mcr), an enzyme that catalyzes the final step of methane production. Despite its significance as a chemogenetic target for methane mitigation, the high-resolution structure of M. ruminantium Mcr has remained elusive. Here, we employed homology modeling and CDOCKER simulations within the CHARMM force field to elucidate the structural and functional features of the M. ruminantium Mcr/ligand complexes. We characterized two distinct states: the reduced Mcr_oxi-silent state bound to HS-CoM and CoB-SH, and the oxidized Mcr_silent state bound to the heterodisulfide CoM-S-S-CoB. Alanine-scanning mutagenesis identified 71 and 62 key residues per active site for each state, respectively, revealing the fundamental determinants of structural stability and substrate selectivity on the Ni-F₄₃₀ cofactor. Furthermore, structure-based pharmacophore modeling defined essential features (AAADDNNN and AAADDNN) that drive ligand binding. These findings provide a high-resolution molecular framework for the rational design of specific Mcr inhibitors, offering a robust starting point for developing broad-spectrum strategies to suppress enteric methane emissions. Full article