Search Results (1,405)

The push for higher energy density in electric vehicles has resulted in large-sized lithium-ion batteries, but their geometric upscaling exacts a heavy thermal price. Under high-rate discharge, these massive cells become heat traps, risking thermal runaway. To tame this instability, this paper engineered a hybrid management strategy fusing liquid cooling, Phase Change Materials (PCMs), and flow deflectors. With a primary focus on the structural optimization of the cooling channel, a three-dimensional numerical model, calibrated using experimentally determined thermophysical properties, was developed to overcome the thermal bottlenecks of conventional cooling architectures. Results indicated that the initial channel optimization effectively reduced the maximum temperature to 327.7 K, but it still remained near the safety threshold. Integrating PCM radically altered the thermal landscape, slashing the outlet temperature differential by 41.67% (from 2.76 K to 1.61 K) compared to pure liquid cooling and blunting peak thermal spikes. Furthermore, to overcome laminar stagnation, strategic deflector baffles were introduced to agitate the coolant, enhancing heat dissipation. Specifically, the optimal half-coverage (L = 1/2) baffle configuration successfully lowered the maximum temperature to 322.42 K while substantially reducing the system pressure drop from 948.16 Pa to 627.57 Pa, achieving a 33.33% reduction compared to the full-coverage scheme. Finally, a multi-variable sensitivity analysis confirmed the extraordinary engineering robustness of the optimized configuration, demonstrating a negligible maximum temperature fluctuation of less than 0.5% despite ±10% operational and material uncertainties. This synergistic system actively stabilizes the thermal envelope, offering a robust engineering blueprint for next-generation high-power battery packs. Full article

The upscaling of turbines in the offshore wind industry has been unprecedented, as compared to 5–6 MW rated turbines 10 years ago. A typical 20–26 MW rated turbine in modern commercial applications (MingYang MySE 18.X-20 MW installed in 2025 and 26 MW prototype by Dongfang Electric tested in 2025) has been demonstrated. This scaling has been made possible by increasing rotor diameters (>250 m) and hub heights (>150–180 m) to achieve capacity factors of up to 55–65%, annual energy generation of more than 80 GWh/turbine, and significant decreases in levelised cost of energy (LCOE) to current values of up to 63–65 USD 2023/MWh globally averaged in 2023 (with minor variability in 2024 due to market changes and new regional areas). The paper analyses turbine upscaling over three levels of hierarchy, including turbine scale—rated capacity and physical aspect, project scale—multi-gigawatts of farms, and market scale—the global pipeline > 1500 GW level, and combines techno-economic evaluation, structural evaluation of loads, and infrastructure needs assessment. The upscaling has the advantage of reducing the number of turbines dramatically (e.g., 500 to 67 turbines in a 1 GW farm, as turbine size is increased to 15 MW) and balancing-of-plant (BoP) CAPEX (turbine-to-turbine foundations and cables) by some 20 to 30 percent per unit of capacity, and serial production learning rates of between 15 and 18% per doubling of capacity. But the problems that come with the increase in ultra-large designs are nonlinear increments in mass and load (i.e., blade-root and tower-bending moments), logistical constraints (blades > 120 m, nacelle up to 800–1000 tonnes demanding special vessels and ports), supply-chain issues (rare-earth materials, vessel shortages increase day rates by 30–50%), and technology limitations (aeroelastic compounded by numerical differences between reference 5 MW, 10 MW, and 15 MW models), it becomes evident that there is a significant increase in deflections of the tower and blades and platform surge/pitch responses with continued increases in power levels, but without a correspondingly mature infrastructure. The regional differences (mature ports of Europe vs. U.S. Jones Act restrictions vs. scale-up of vessels/manufacturing in China) lead to the necessity of optimisation depending on the context. The analysis concludes that, to the extent of mature markets with adapted logistics, continuous upscaling is an effective business strategy and can result in 5 to 12 percent further reductions in LCOE, but beyond that point, gains become marginal or even negative, as risks and costs increase. The competitiveness of the future depends on multi-scale/multi-market-based approaches—modular-based families of turbines, programmatic standardisation, vibration control innovations, and industry coordination towards supply-chain alignment and standards. Its major strength is that it transcends mere size–cost relationships and shows how nonlinear structural processes, aero-hydro-servo-elastic interactions, and bottlenecks in logistical systems are becoming more determinant of the efficiency of ultra-large turbines. The study demonstrates that upscaling turbines has LCOE benefits through the support of associated improvements in installation facility, supply-chain preparedness, and structural vibration control potential, based on the comparisons of quantitative loads, techno-economic scaling trends, and regional market differentiation. Full article

Plasma-facing materials (PFMs) for future fusion reactors require advanced mechanical and thermal properties to withstand the extreme challenges of high heat flux, plasma exposure, and neutron irradiation. Tungsten is one of the most suitable materials for use as a PFM in the divertor region. However, considering the high thermal loading/thermal stress combining plasma exposure and neutron irradiation/embrittlement, one of the major concerns for tungsten in PFMs is its intrinsic brittleness. To avoid cracking and components failure, tungsten toughening has been widely investigated, including the development of tungsten fiber-reinforced tungsten composites (W_f/W) using an extrinsic toughening mechanism, which could provide damage resilience against neutron embrittlement. Recently, a type of aligned long-fiber W_f/W (L-W_f/W) based on a powder metallurgical fabrication process was developed, demonstrating advanced fracture toughness while retaining other application-relevant properties. For L-W_f/W, the relatively easy production process suggests the feasibility and basis of industrialization. This work reports on the initial progress in industrializing L-W_f/W, with a focus on adapting the lab sintering process to a sintering process with industrial partner (Dr. Fritsch Sondermaschinen GmbH) and optimizing the process parameters. To improve the sinterability of tungsten and achieve higher density, various tungsten powders were explored, including commercial W powders, bimodal mixtures of different particle sizes, and granulated W powders. At the dedicated yttria interface, the thickness of yttria coating on the fibers was also optimized to ensure effective separation between the fibers and the matrix. Series of samples were produced with different dimensions up to 100 mm × 100 mm × 4 mm. After optimization, samples with 93% density and desired pseudo-ductility were prepared. Similarly to production in the lab, a major challenge in this work involved balancing the densification of the tungsten matrix with controlling fiber recrystallization and mitigating damage to the yttria interface. Full article

Scalability of the original test design for the box assembly with removable component (BARC) structure is of interest in the field of experimental structural analysis. As complex structures become increasingly difficult to test experimentally the larger they become, it is a common test practice to use a scaled-down representative model to understand the characteristics of these systems. For complex structures with non-rigid boundary conditions, there exists a gap in understanding the effects of scalability and welding. To gain a better understanding of the outcomes of this phenomenon, the dynamical effects of upscaling the dimensions of the BARC structure are analyzed. Three variations of the BARC are investigated experimentally and computationally, namely, the original BARC system, the BARC system upscaled at 1.5 times the size of the original model, and the BARC system upscaled at two times the size of the original model. The original BARC is tested to investigate the properties of the predetermined boundary conditions. Because the upscaled BARC systems are manufactured using welding, an investigation of the variability of results due to welding imperfections is conducted to evaluate its effects on the vibrational properties of the systems. The dominant resonant frequencies of the three systems are identified through an impact hammer test. The results are then compared to those obtained through finite element analysis, in which both datasets show agreement. In general, as the BARC system is upscaled, the resonant frequencies decrease without inducing mode switching for the selected boundary conditions, indicating that the larger systems are less rigid. To understand the trends of nonlinear softening/hardening and nonlinear damping, forced vibration experiments conducted in the form of true random and controlled stepped-sine excitations are performed. The results show that, in general, as the BARC system is upscaled, changes in the nonlinear properties of the system are induced. With regard to the effects of using welding to manufacture BARC systems, the results prove that variations in welding can lead to non-negligible variations in the vibratory responses of the BARC system. Additionally, several types of harmonic vibrational testing are investigated to understand the physics behind their varied responses. Overall, this work shows that upscaling the BARC system can be beneficial to researchers who require a less rigid system for investigations and that manufacturing of BARC systems by welding can be a cost-effective alternative to subtractive manufacturing. Full article

Mechanical pretreatment techniques are essential for overcoming lignocellulosic biomass recalcitrance in emerging biorefineries. This review critically synthesizes advances from 2020 to 2025 across fundamental mechanisms, hybrid technologies, energy efficiency, Life Cycle Assessment, and industrial scalability. The analysis reveals that effective pretreatment targets supramolecular modification—defect generation in cellulose crystallites and the creation of reactive sites—beyond simple particle size reduction. Impact–shear regimes prove most effective for fibrous materials. Hybrid approaches are examined: mechanocatalysis enables solvent-free depolymerization, while mechanoenzymatic technologies achieve hydrolysis without bulk water, though enzyme denaturation under mechanical stress remains unresolved. Energy consumption is the primary upscaling barrier, with Life Cycle Assessment identifying electricity use as the dominant environmental hotspot and emphasizing burden per unit of final product as the critical metric. Technology Readiness Level assessment provides a strategic framework: continuous extruders and mills are industrially mature for bulk applications, while high-intensity batch devices are suited for high-value coproducts. A research agenda prioritizing mechanistic understanding, hybrid process engineering, feedstock diversification, and embedded sustainability assessment is proposed. Full article

The Tianshan–Pamir mountain region, serving as the core “water tower” for countries in Central Asia east of the Aral Sea, is a critical bulwark for sustaining downstream socioeconomic systems. However, constrained by complex topography and harsh climatic conditions, this region suffers from a severe scarcity of long-term, continuous hydrological observation data. This study focuses on a typical data-scarce mountainous area, coupling UAV and satellite imagery-based (e.g., Landsat/Sentinel) flow inversion with a hybrid spatial regionalization method—integrating spatial proximity, basin similarity, and regression-based hydrograph reconstruction—to quantitatively estimate long-term discharge time series. The results indicate that, for the validation of instantaneous discharge inversion, the Nash–Sutcliffe efficiency coefficient (NSE) at 29 river cross-sections was consistently greater than 0.80, with the coefficient of determination (R²) reached 0.94 (p < 0.01). Subsequently, for the long-term discharge series reconstructed using the regionalization method, the NSE values at three representative verification sites—each corresponding to a distinct basin type—were 0.88, 0.84, and 0.86, respectively. These findings exhibit higher precision compared to direct temporal upscaling, confirming the reliability of the regionalization method across varying temporal scales. An analysis of monthly discharge trends from 1989 to 2020 revealed a decreasing trend in the discharge of glacier-dominated rivers, with an average rate of change of −2.89 ± 2.54% (p < 0.05); the Pamir Plateau experienced the largest decline (−4.89 ± 6.58%), which is closely linked to large-scale glacial retreat within the basins. Conversely, the discharge of non-glacier-dominated rivers showed an increasing trend, with a multi-year average rate of change of +0.32 ± 8.43% (n.s.), primarily driven by shifts in precipitation and vegetation cover. This research introduces a new approach for hydrological monitoring in data-scarce regions and provides essential data and methodological support for water resource management decisions in arid zones. Full article

The synergistic impacts of land use/land cover (LULC) transformations and weather pattern variabilities (WPV) represent a primary driver of hydro-geological instability, threatening agricultural productivity, soil conservation, and water quality. Disentangling the discrete contributions of these stressors to runoff and sediment yield (SY) remains a significant challenge, particularly in complex, confluence-proximal watersheds lacking major hydraulic regulations. This study investigates the Tirumakudalu Narasipura watershed in Karnataka, India, an agriculturally intensive system undergoing rapid peri-urbanization. Leveraging the process-based geospatial interface of the Water Erosion Prediction Project (GeoWEPP), we analyzed hydrological responses over a 24-year period (2000–2023) and projected future trajectories through 2030. To overcome the traditional constraints of GeoWEPP, which was developed for small-scale watersheds (<260 ha), we present a novel upscaling framework utilizing a multi-site multivariate temporal calibration of hydrological response variables to exploit its process-based precision in capturing distributed soil erosion and landscape heterogeneity. This approach is further reinforced by an ancillary data validation to minimize error propagation while model-upscaling. Our findings reveal projected increases in runoff and SY of 14.69% and 49.23%, respectively, between 2000 and 2030. Notably, the sub-decadal acceleration from 2023 to 2030 (17.32% for runoff and 18.51% for SY) underscores a shifting dominance where LULC-driven surface modifications now outweigh climatic variance in forcing hydrologic change. Furthermore, the study quantifies how anthropogenic interventions such as strategic crop selection, tillage intensity, and irrigation regimes act as critical determinants of topsoil preservation. These results provide a scalable, economically feasible framework for precision land stewardship and sustainable watershed management in rapidly developing tropical landscapes. Full article

This scoping study assesses practical aspects of electrokinetic (EK) biocementation of clay soil underneath a railway embankment ahead of upscaled testing to include a reduced-scale field pilot as an intermediate step towards subsequent pilot embankment treatment. It considers suitable field setups and performs Life Cycle Analysis (LCA) of biocementation by biostimulation of carbonic anhydrase (CA)-producing bacteria compared to hydrated lime slurry, if both treatments were implemented electrokinetically. LCA analysis was conducted using SimaPro software (version 9.6.0.1) with Ecoinvent database and bench-scale laboratory testing data. Electroosmotic flow modelling was performed to instruct on suitable setups and for estimates of power consumption towards the field application of 30 m of railway embankment and foundation soil. LCA indicated a considerable reduction in global warming if CA biocementation is used (0.00823 kg CO₂ eq for biocement vs. 0.022136 kg CO₂ eq for lime), and resource usage (7.06 × 10⁻⁵ kg Cu eq compared to 8.47 × 10⁻⁵ kg Cu eq for lime). Biocementation was more water-consuming compared to lime, as it involved multiple chemical solutions. Terrestrial acidification, aquatic eutrophication, and ecotoxicity were slightly higher for biocement, possibly due to system boundaries and processes assumed for material production. Further sustainability improvements would be possible if waste materials (e.g., captured industrial CO₂) could be used. Field trials will be essential for validation, system optimisation, and advanced model calibration. Full article

Food waste management represents an important economic and environmental challenge for the hospitality sector on a global level, and especially for markets that are still developing, such as Serbia. This exploratory qualitative pilot study supported by descriptive statistics based on expert interviews investigates management perceptions of food waste in Belgrade’s hotels, analyzing the gap between sustainability food waste awareness and operational implementation within a transitional economy. An exploratory pilot study was conducted using a purposive sample of nine general managers from upscale hotels. Interviews with general managers were conducted in person and data was collected via a structured questionnaire based on a five-point Likert scale. The results suggest that general managers perceive food waste reduction primarily as a cost-saving measure rather than a strategic driver of profitability. Using Upper Echelons Theory (UET), this research provides insights into how management-level cognition shapes sustainability routines. The findings offer a preliminary framework for integrating basic training modules and transparent cost-tracking systems to transition from passive to proactive sustainable operations in the Serbian hospitality sector. This exploratory pilot study advances hospitality sustainability research by offering preliminary insights into managerial cognition concerning food waste within a transitional tourism economy. Full article

Solar-induced chlorophyll fluorescence (SIF) is an emerging predictor in the crop gross primary production (GPP) estimation for its close relationships with vegetation photosynthesis. Conventional crop GPP are estimated by data-driven models upscaled from eddy covariance flux observations, light-use efficiency (LUE) models, and process-based models, which are constrained by the limited availability of in-site experimental and simulated data. By using vegetation remote sensing data and meteorological data to simulate the combined impacts of changes in vegetation physiological factors and environmental factors on GPP estimation, we proposed a new method to estimate GPP for winter wheat over the North China Plain (NCP) based on the SIF-based mechanistic light response (MLR) model with bias correction. Results showed that (1) vegetation and meteorological factors could be used to fit the bias caused by the static input parameters of the MLR model for winter wheat GPP estimation, which solved the unavailability of the input parameters in the MLR models; (2) the MLR model with bias correction could quickly achieve large-scale crop GPP estimation at the regional scale during the vigorous period of winter wheat, whose performance was superior to that of a traditional statistical regression model with an increased R² of 6.4%. Full article

Background: e-Lung (Brainomix) is an artificial intelligence (AI)-driven software that is based on multi-class convolutional neural network (CNN) techniques. The aim of this research was to demonstrate the feasibility of e-Lung to evaluate progression in lung volume reduction in patients with interstitial lung disease (ILD) undergoing lung transplant assessments. Methods: This was a single-center retrospective cohort study of consecutive patients with ILD who received lung transplants between June 2021 and November 2024. Patients who underwent serial prospective conventional evaluations using lung function testing (LFT) and conventional radiological assessments as well as retrospective lung volume measurements using e-Lung were included in this study. Results: An analysis of 20 consecutive patients who met strict inclusion criteria and underwent an additional e-Lung assessment revealed that both the serial physiological actual total lung capacity (aTLC) measurements and e-Lung-derived lung volume measurements were able to provide recipient lung size estimations and detect serial declines in lung volume. A poorer DLCO (2.61 ± 0.77 vs. 3.87 ± 1.59 mmol/min/kPa, p = 0.044) at the time of wait-listing was associated with a significant lung volume reduction. Conclusions: e-Lung may serve as an additional upscale tool for the rapid and objective quantitative evaluation of the actual lung volume and the detection of the extent of parenchymal shrinking in patients with advanced ILD awaiting lung transplantation. Full article

To compete with fossil fuels, biofuels produced from renewable waste biomass must be cost-effective, adaptable to existing heat and power infrastructure, and possess desirable fuel properties and performance metrics matching those of fossil fuels, while having a much lower carbon footprint. However, handling and processing biowastes in thermochemical biorefineries is challenging owing to their high moisture content, low bulk density, poor grindability, low calorific value, and heterogeneous physicochemical properties. Torrefaction has emerged as an effective thermochemical technology for upgrading biowastes into torrefied biomass, which exhibits improved, homogeneous physicochemical properties, including higher calorific value, higher bulk density, better grindability, and hydrophobicity. This review synthesizes the current state of research on torrefaction, with particular emphasis on process parameters, reactor designs, commercial-scale implementations, and an analysis of its strengths, weaknesses, opportunities, and threats. The comparative advantages and limitations of different torrefaction reactors are highlighted, emphasizing how each reactor’s characteristics determine its suitability for specific circumstances and operating conditions. This article also considers the technical and economic challenges associated with scaling up torrefaction. The discussion on specific case studies on techno-economic analysis of torrefaction outlines the key barriers and provides incentives for researchers to consider when upscaling the technology. The strengths, weaknesses, opportunities, and threat analysis offers strategic insights for policymakers and industry stakeholders into possible actions to support torrefaction and its upscaling. Full article

Radiative cooling technology, which leverages the emission of long-wave infrared radiation to deep space, offers a promising passive cooling solution that can reduce the energy consumption associated with conventional air conditioning systems. This technology is particularly relevant in tropical and subtropical regions, where buildings are exposed to high levels of solar radiation and excessive heat. Passive radiative cooling materials, such as petroleum-, inorganic- and cellulose-based materials, have shown significant potential in reducing building temperatures (more than 8 °C at daytime and 10 °C at nighttime) and enhancing energy efficiency by weakening the utilization of air conditioning. This review explores the development of promising radiative cooling materials, focusing on their raw materials, manufacturing, and key distinction (such as high solar reflectivity of >90% and middle-infrared band light emissivity of >0.9) for radiative cooling. Further, the progressive application of radiative cooling material in building and construction is significantly discussed, focusing on the cooling performance, mechanical properties, hydrophobicity and long-term stability. Lastly, future directions for advancing radiative cooling materials for building applications are presented, emphasizing the importance of integrating sustainability, up-scale manufacturing, and low cost with high thermal management performance. Full article

An assessment and prediction system for the quality of public water networks was developed, using Timișoara, Romania, as a case study. This was implemented on a Google Firebase cloud storage system and comprised twelve ML algorithms applied to test samples for drinkability and used in predictions of upcoming samples. The system compares 17 water quality parameters to the World Health Organization and public reports of Timișoara drinking water standards for 804 samples. The system provides real-time data storage, drinkability prediction for the reservoir water system, and rule-based critical water recommendations for elementary treatment in samples. The most accurate and best-calibrated against random forest, gradient boosting, and Logistic Regression algorithms was the decision tree algorithm of the ML models. The experimental findings also determine the regions of the worst and best water quality and propose respective treatment. In contrast to previous research and structures, the paper demonstrates an approved stable solution for smart water monitoring, correlating practical deployment with sophisticated data-based conclusions. The results contribute to enhancing public health, enhancing water management measures, and upscaling the system for larger-scale applications. Full article

Mangrove ecosystems are important blue carbon systems and play a critical role in understanding carbon cycling and responses to climate change. However, accurate regional estimation of Net Ecosystem Exchange (NEE) remains challenging due to the environmental complexity and spatial heterogeneity. This study combined eddy covariance observations from four mangrove sites along China’s southeastern coast (natural and restored mangrove forests) with multi-source remote sensing and environmental reanalysis data to construct three variable schemes (site observations only, with added vegetation indices, and comprehensive multi-source variables). We compared three machine learning models for daily NEE prediction, including eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Support Vector Machine (SVM). The results showed that: (1) Restored and natural mangroves exhibited similar temporal NEE dynamics and consistently functioned as carbon sinks, restored mangrove sites showed greater cross-site variability. Among the study sites, CN-LZR exhibited the strongest cumulative carbon uptake. (2) Scheme 3 combined with the XGBoost algorithm achieved the highest predictive accuracy, reaching an R² of 0.73 across sites. Differences among machine learning models were primarily associated with their ability to capture nonlinear interactions between atmospheric and hydrological variables, with tree-based models outperforming SVM. (3) SHAP analysis indicated that radiation-related variables were the dominant drivers of NEE, while hydrological influences were site-dependent; and (4) Regional upscaling indicated that all sites consistently functioned as long-term carbon sinks, with CN-LZR exhibiting slightly higher daily mean carbon uptake than the other sites. This study presented the first machine learning framework for estimating daily-scale NEE in mangroves, providing methodological and data support for regional carbon flux assessment and blue carbon management. Full article