Search Results (12,064)

Geothermal energy extraction using existing wellbore systems provides a promising approach for sustainable heat utilization; however, the long-term thermo-hydro-mechanical (THM) responses associated with different working fluids remain insufficiently understood. In this study, a three-dimensional coupled THM model was developed to compare geothermal heat extraction using water and pressurized CO₂ under identical geological and operational conditions. The model integrates Darcy flow, heat transfer, and linear elastic deformation to investigate the evolution of hydraulic, thermal, and mechanical fields over a 100-year operation period. The results show that the hydraulic fields rapidly reach quasi-steady states, whereas thermal responses continuously evolve due to cold-front propagation from the injection well. Compared with water, pressurized CO₂ exhibits stronger fluid mobility and produces a larger thermal influence region, resulting in different heat extraction characteristics under the same mass-flow-rate condition. Thermal cooling induces reservoir contraction and stress redistribution; however, the calculated stress and displacement variations remain within a stable range throughout the simulation period. The comparison demonstrates that pressurized CO₂ can enhance long-term thermal utilization while maintaining acceptable geomechanical stability under the investigated conditions. These findings provide insights into the selection of working fluids for wellbore-based geothermal systems and highlight the importance of coupled THM evaluation for long-term reservoir performance assessment. Full article

3D-printed geopolymer mortars (3DPGPMs) are emerging as low-carbon construction materials that combine digital fabrication with alkali-activated binder technology. However, their hardened performance remains difficult to assess because it is controlled not only by geopolymer chemistry but also by printing parameters, rheological evolution, curing conditions, interlayer bonding, pore structure, and loading direction. This review critically examines the current literature on extrusion-based 3DPGPMs, with emphasis on mechanical properties, durability, sustainability, standardization, and practical implementation. The reviewed studies show that precursor type, activator system, aggregate/binder ratio, additives, printing conditions, and curing regime strongly influence compressive, tensile, flexural, interlayer bond, and anisotropic mechanical responses. Durability performance is also governed by the coupled effects of matrix chemistry and printing-induced features, including interlayer voids, directional pore networks, weak interfaces, and transport pathways that may affect shrinkage, water absorption, chloride penetration, carbonation, acid and sulphate resistance, freeze–thaw response, and elevated-temperature behavior. From a sustainability perspective, the environmental benefits of 3DPGPMs are conditional and depend on activator production, precursor availability, curing demand, transport distance, life-cycle assessment boundaries, and field-scale implementation conditions. The review identifies that the main knowledge gap is the limited availability of integrated datasets linking fresh-state rheology, interlayer quality, multi-scale porosity, mechanical anisotropy, durability indicators, and structural-scale validation. Future research should therefore prioritize standardized reporting, performance-based acceptance criteria, long-term exposure testing, field-scale validation, and predictive material–process–durability models. Overall, this review provides a hardened-performance-oriented synthesis to support the development of reliable, durable, and sustainable 3DPGPMs for construction applications. Full article

Driven by the increasing demand for renewable energy integration and low-carbon transformation in the chemical industry, the production of green hydrogen from renewable electricity for subsequent ammonia synthesis has emerged as an important route for green ammonia production. However, the process still relies on the high-pressure Haber–Bosch synthesis loop, typically operating at 200–300 bar, where multi-stage compression, recycle gas treatment, and low-temperature condensation separation strongly influence energy consumption and feedstock utilization. In this study, a steady-state Aspen Plus (V15) model integrating an Alkaline Water Electrolysis Unit (AWE), cryogenic air separation for nitrogen production, and an ammonia synthesis loop was established for a liquid ammonia plant with an annual capacity of approximately 600,000 t. Under base-case conditions, the specific energy consumption of liquid ammonia production was 10.28 kWh/kg-NH₃, while the hydrogen and nitrogen elemental utilization rates reached 87.73% and 88.92%, respectively, both higher than those of conventional coal- and natural gas-based ammonia routes. Increasing the compression stages from 2 to 5 reduced the fresh syngas compression work by 6.69%, although the energy-saving benefit became marginal beyond four stages. A purge ratio of 1–2% achieved a reasonable balance between recycle compression work and hydrogen/nitrogen purge loss, while the preferred condensation temperature range for improved NH₃ recovery was −20 °C to −25 °C. Full article

Accelerating the renovation of existing residential buildings is essential for achieving European climate targets, but aggregate renovation rates do not show whether interventions are sufficiently deep, well targeted, or cost-effective. This paper develops a transparent scenario framework for prioritising renovation strategies at local building stock scale. The workflow combines a literature-based screening of renovation indicators and implementation conditions, semi-structured expert interviews used for qualitative triangulation, and a typology-based bottom-up model of the South Tyrolean residential stock. The stock model uses census and provincial floor-area data, representative space heating and domestic hot water demand values from SINFONIA and previous South Tyrolean studies, and static end-state renovation assumptions. Three scenarios are compared: deep renovation of priority high-demand clusters, medium renovation of the same clusters, and light renovation of the whole stock. The baseline model estimates residential heating and domestic hot water demand at approximately 1990 GWh/year. The selected priority clusters account for about 56% of floor area and nearly 59% of baseline demand. Under the central assumptions, targeted deep renovation would reduce demand by approximately 704 GWh/year (35%), targeted medium renovation by 352 GWh/year (18%), and whole-stock light renovation by 299 GWh/year (15%). Indicative CO₂ reductions are reported separately and are proportional to the same final energy reduction assumptions because carrier switching is not modelled. A static cost-effectiveness screening using Italy-level energy-related renovation cost data is reported as an order-of-magnitude range rather than a local investment forecast. The results show that renovation depth and target selection should be considered jointly, and that the framework is transferable where typological stock data and representative energy demand values are available. Full article

Inorganic scale deposition in crude oil–water transport trunklines is a formidable flow assurance challenge, uniquely exacerbated in extensive gathering networks where multiple production flowlines commingle multiphase fluids. As some fields experience progressively higher water cuts, the mixing of incompatible waters, characterized by diverse thermodynamic profiles and varying concentrations of scaling ions (Ca²⁺, Ba²⁺, Sr²⁺, ${\mathrm{SO}}_4^{2-}$, ${\mathrm{CO}}_3^{2-}$, etc.) triggers severe precipitation. This comprehensive literature review synthesizes seminal and contemporary studies to critically evaluate the state-of-the-art methodologies for assessing scaling risks in these intricate systems. Progressing chronologically and thematically, the analysis details the transition from static, bulk-fluid thermodynamic equilibrium calculations to dynamic, high-fidelity deterministic and probabilistic approaches. These advanced frameworks include Reactive Transport Modeling (RTM), Computational Fluid Dynamics (CFD), and Machine Learning (ML) architectures. Special emphasis is placed on the mathematical governing equations that dictate trunkline-specific phenomena: multi-stream commingling, non-isothermal gradients, probabilistic kinetic induction, and the profound impact of turbulent transport (turbophoresis) on crystal attachment and wall shear detachment. Finally, an integrated, multi-tier flow assurance workflow is proposed to guide future field-scale risk management and digital twin deployment. Full article

Efficient irrigation management requires complementary information on atmospheric demand, soil conditions, and crop water stress. This study presents a low-power Internet of Things (IoT)-based irrigation system that integrates these components within a unified monitoring and control framework. The system combines LoRa communication, ESP32-based sensor nodes, soil and meteorological sensing, FAO-56 reference evapotranspiration ($E{T}_0$), and canopy-temperature-based Crop Water Stress Index (CWSI). Irrigation decisions rely on the complementary use of $E{T}_0$, in situ soil measurements, and CWSI rather than on a single indicator. A hybrid time-, event-, and query-driven acquisition strategy was implemented to adapt node activity and limit communication overhead. The system was deployed under outdoor conditions in Oujda, Morocco, demonstrating integrated sensing, wireless data transmission, crop-stress monitoring, and automated irrigation control. Energy characterization further showed distinct consumption profiles across sensing, communication, actuation, and low-power operating states, supporting the use of duty cycling to limit active node operation. The results demonstrate the feasibility of integrating environmental, soil, and crop-level information within a low-power IoT framework for adaptive irrigation management. Full article

An excavation-induced clayey landslide in Jianshui County, Yunnan Province, China, threatens a national refined oil pipeline near the rear slope. Field investigation, borehole logging, laboratory testing, and three-dimensional finite-element analyses were integrated to investigate the excavation–rainstorm instability mechanism and evaluate circular anti-slide piles with toe backfilling. Under natural excavation, the reported factor of safety was 1.39, and the maximum displacement was 2.35 mm. Under a 60 mm/day rainstorm, increased pore-water pressure and saturation in the shallow sliding mass and strongly weathered claystone, together with saturated-state strength parameters, reduced the shear-strength reserve. The deformation and stability analyses yielded a maximum computed displacement of 1.36 m and a factor of safety of 0.95, respectively, indicating pronounced pre-failure deformation and loss of stability. After mitigation, the factor of safety increased to 1.41, while the maximum slope and pile-head displacements were both approximately 6.90 mm. The pile row redistributed nonuniform landslide thrust and reduced deformation transfer toward the pipeline. The results are site-specific engineering estimates for the investigated rainfall and parameter conditions. Full article

Voltage-sensitive ion channels are glycoprotein macromolecules that carry ion currents across membranes of nerve and muscle fibers. The hypothesis presented helps explain the changes that convert an insulating ion channel into an ion conductor, stating that it undergoes a structural transformation on threshold reduction in the voltage across the membrane. Experimental data show that the excitable membrane is a ferroelectric liquid crystal. The Channel Activation by Electrostatic Repulsion hypothesis proposes the following: electrical attractions between boundary surface charges compress the polar channel into a compact smectic phase with induced dipoles. Critical depolarization eliminates surface charges and dipoles, decreasing the dielectric permittivity of the ion channel. This increases the repulsive electrostatic forces between positively charged residues in the four S4 segments. These forces form a selectivity filter dome and cause a proteinquake to a chiral nematic phase. The selectivity filter allows ions to enter as it strips their hydration waters. The permeant ions occupy hydrogen bonds of ion-conducting helices, displacing protons. Disordered regions between adjacent helices form liquid line defects. In the thermal chaos of physiological temperature, a line defect occasionally connects the inner and outer surfaces, forming a transient ion pathway that carries unpredictable surges of permeant ion currents, as observed in experiments. Tests for this hypothesis are proposed. Full article

Detection of nanoplastics in drinking-water systems is only the first analytical step toward exposure interpretation; the next challenge is source attribution. This review examines molecular fingerprinting and transformation pathways that can link nanoscale polymer signals to source waters, drinking-water treatment, distribution infrastructure, packaging materials, laboratory background, or aging processes across the potable-water chain. Nanoplastics are treated here as operationally defined particles below 1 µm, including intentionally manufactured primary nanoplastics and secondary nanoplastics generated by fragmentation, abrasion, weathering, treatment, storage, or packaging stress. The synthesis evaluates how polymer identity, particle morphology, surface oxidation, additive and oligomer profiles, thermal degradation markers, matrix context, and quality assurance/quality control (QA/QC) can be combined into defensible source assignments. Analytical platforms considered include surface-enhanced Raman spectroscopy (SERS), atomic force microscopy–infrared spectroscopy (AFM-IR), optical photothermal infrared spectroscopy (O-PTIR), stimulated Raman scattering microscopy (SRS), pyrolysis–gas chromatography–mass spectrometry (Py-GC/MS), asymmetric flow field-flow fractionation coupled to Py-GC/MS (AF4-Py-GC/MS), matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), and chemometric workflows. The central conclusion is that source attribution cannot be inferred from polymer identity alone; robust interpretation requires convergent evidence from particle-level chemistry, polymer-specific mass, additive or marker-ion signatures, aging state, blanks, recovery, and contextual sampling design. Full article

The Lower Ganjiang River is a multi-branch delta with highly uneven spatial and temporal flow distribution, and conventional static diversion or threshold-based operation fails to stabilise the water level or optimise flow allocation under varying inflows. This study develops a hydrodynamic regulation framework that couples an improved integral time-delay model and model predictive control (MPC). A nonlinear state-space equation is constructed using a quadratic storage–water level relationship and rolling optimisation is solved with CasADi-IPOPT to minimise water-level tracking error, discharge deviation and control effort. The framework is validated offline against MIKE21 simulations for three historical flow scenarios (September 2016, February 2017 and March 2018). Under these scenarios, the Waizhou water level is maintained at 15.5 ± 0.2 m, daily water level variation is limited to ≤0.5 m/d, and the diversion ratio deviation is ≤5%. Compared with the natural state, water level fluctuation is reduced by 21.3% (September 2016 storage scenario). The proposed MPC framework effectively alleviates the spatiotemporal hydrodynamic imbalance of the Lower Ganjiang River, showing satisfactory model accuracy, constraint compliance, and engineering applicability, and offers a promising approach for advanced regulation of complex multi-branch river networks. Full article

Photosynthetic water oxidation is catalyzed by the Mn₄CaO₅ oxygen-evolving complex (OEC) of photosystem II (PSII), where hydrogen-bonding and ion-binding networks regulate proton transfer, substrate-water delivery, and S-state advancement. Acetate binding inhibits oxygen evolution, competes with chloride, and stabilizes the $S=5/2$ spin isomer of the S₂ state, but its donor-side binding site remains unresolved. Here, we combine EPR spectroscopy, pH-dependent oxygen-evolution measurements, mutagenesis, and QM/MM calculations to support a donor-side acetate-binding model and determine how acetate perturbs the OEC environment. Acetate increases the ratio of the $g=4.1$ to $g=2$ S₂-state EPR signals in spinach PSII membranes and cyanobacterial PSII core complexes, with stronger stabilization persisting to higher pH in spinach PSII. The D1-N87A Synechocystis PSII variant exhibits spinach-like acetate sensitivity and pH-dependent oxygen-evolution behavior, with an effective acidic $p{K}_a$ of approximately 5.3, versus 4.2 for wild-type cyanobacterial PSII, implicating long-range perturbations of the narrow-channel hydrogen-bonding network. QM/MM calculations support acetate binding near the D1-D61/W1 region, where the acetate-bound $S=5/2$ isomer is only 1.0 kcal mol⁻¹ higher in free energy than the $S=1/2$ isomer, consistent with the observed spin-isomer equilibrium shift. These results reveal how acetate perturbs proton-transfer and chloride-binding processes in PSII. Full article

After offshore sandstone reservoirs enter the high-water-cut development stage, remaining oil gradually changes from a continuously movable state to a dispersed, isolated, and locally trapped state. Therefore, pore-scale dynamic characterization of remaining oil is important for clarifying its occurrence state and identifying potential targets for further recovery. In this study, natural cores from a typical offshore continental sandstone reservoir were used to conduct micro-computed tomography (micro-CT) scanning experiments at different waterflooding stages. Fine identification of the rock skeleton, water phase, and remaining oil, as well as segmentation of remaining-oil units, was achieved using U-Net semantic segmentation and three-dimensional digital image reconstruction. Multiple parameters were extracted, including volume, surface area, equivalent diameter, major-axis length, intermediate-axis width, minor-axis thickness, shape factor, and Euler number. Combined with manually labeled results of typical remaining-oil unit, a decision-tree method was used to establish classification criteria for remaining-oil occurrence states. The results showed that, with increasing pore volumes injected (PV), remaining oil gradually evolved from an initially large-scale and continuously connected state to a small-scale dispersed trapping. The surface area and volume of remaining oil continuously decreased. Meanwhile, the shape factor decreased, and the Euler number increased, indicating that the continuous oil phase was continuously cut and stripped into remaining-oil units with lower topological connectivity during waterflooding. At the early stage of waterflooding, clustered flow dominated in cores with different permeabilities, accounting for 96–99% of the remaining-oil volume percentage. Under high pore volumes injected (PV), the remaining oil volume percentage decreased to 30–65%, whereas the remaining oil volume percentage of columnar flow and droplet flow increased to 16–37% and 5–13%, respectively. These results indicated that waterflooding promoted the transformation of remaining oil from large-scale connected occurrence to locally trapped states under pore–throat constraint. Further comparison of cores with similar permeability but different pore structures showed that differences in pore–throat geometry, local connectivity, and pore–throat matching still significantly affected the fragmentation degree and spatial trapping mode of remaining oil. This study established a pore-scale method for dynamic identification, quantitative characterization, and type classification of microscopic remaining oil during long-term waterflooding in offshore sandstone reservoirs. The results provide a pore-scale basis for fine remaining-oil potential tapping in the high-water-cut stage. Full article

This paper presents a novel approach for estimating 3D human pose from monocular video sequences in underwater scenarios, tackling the unique challenges posed by water refraction, body occlusion, low image quality and illumination distortion in underwater environments. Leveraging both 2D keypoint extraction and parametric model estimation, our method operates in a two-stage framework including preprocessing and optimization. In the preprocessing stage, a Part Attention Regressor (PARE) is adopted to dynamically estimate SMPL human body parameters, particularly adept at handling occlusions common in underwater scenarios. Additionally, a 2D keypoint detector, employing YOLO for bounding box detection and HRNet for keypoint regression, enhances feature extraction despite underwater image challenges. In the optimization stage, we propose an underwater variational autoencoder (UW-VAE), which adopts a data-driven strategy to learn the biomechanical prior distribution of underwater human poses and implicitly correct unreasonable pose parameters caused by refraction and occlusion. The optimization process incorporates constraints aligning final SMPL models with detected 2D keypoints, minimizing disparity between adjusted and original SMPL models, and ensuring temporal consistency. Furthermore, to address the scarcity of annotated underwater datasets, we build a full pipeline to generate synthetic underwater datasets with complete annotations based on UW-VAE. Experimental results on the SwimXYZ synthetic dataset show that our method achieves 51.60% PCK@0.2 and 80.13% PCK@0.5, outperforming state-of-the-art land-based methods across most stroke categories. Validation on real-world underwater swimming datasets demonstrates improved 2D keypoint accuracy after synthetic-data fine-tuning, which provides a new solution for 3D human motion analysis in underwater sports, biomechanical research and swimming training. Full article

This study investigates the interrelationships between soil organic matter (SOM) quality characteristics and key mercury species in two sites in Czech Republic under historical Hg contamination. SOM properties derived from DRIFT spectral analysis including the aromaticity index (iAR), potential wettability index (PWI), decomposability index (DI), and organic matter quality index (OMQ) along with additional SOM quantity and quality indicators were evaluated against several key Hg fractions (Total Hg (HgT), potentially mobilizable Hg (HgPM), potentially mobilizable Hg ions (Hg²⁺), methylmercury (MeHg), and water-soluble Hg (HgWS)). Neural network analysis revealed that type of horizon (organic or mineral) as well as SOM quality characteristics play an important role in Hg mobility and methylation processes. The results show the difference in relevant SOM quality properties that affect Hg mobility and methylation that can also be opposite based on the soil horizon type for the same soil, potentially forcing different pathways for the mobilization and methylation, and indicating that the state of transformation of organic matter and its quality characteristics along with the environmental conditions are some of the key attributes influencing mobility and methylation processes of Hg in the soil. Full article

To ensure the safety and stability of single point mooring (SPM) systems operating in shallow waters, this paper investigates the influences of shallow-water effects on mooring systems under different water depth-to-draft ratios. For the pile-founded column single point mooring system in shallow sea areas, based on the numerical calculation method verified by model tests, frequency domain and time domain calculations are carried out to study the specific impact of shallow water effects on the hydrodynamic parameters of the hull, and the critical water depth-to-draft ratios applicable to the two second-order wave load calculation methods (Newman approximation and Pinkster approximation) are analyzed. At the same time, the specific impact of shallow water effects on the dynamic response of the mooring system under three different hull loading conditions at the same and different water depth-to-draft ratios is studied, and the critical water depth conditions for bottom contact in each loading condition are summarized. The results show that the shallow water effect has a significant impact on the hydrodynamic parameters such as RAO of the hull response, especially in the low-frequency response region. There are obvious differences between the Newman approximation and the Pinkster approximation methods. In shallow water conditions, the Pinkster approximation method has a more accurate calculation effect, and when the water depth-to-draft ratio reaches a certain critical value, the calculation results of the two approximation methods are basically consistent. For the same and different water depth-to-draft ratio conditions, the amplitude of the hull motion in the full-load draft state is greater than the other two loading conditions, but the response results of the cable tension are opposite. The research results reveal the specific influences of shallow-water effects on pile-supported single-point mooring (SPM) systems, which can provide references for the safety and stability design of mooring systems and bear great engineering significance for advancing the deployment of single-point mooring systems in shallow water regions. Full article