Search Results (3,376)

With the accelerated low-carbon transition of the global energy mix, offshore wind power (OWP) is one of the fastest-growing renewable resources and is often integrated with conventional thermal units into a bundled export transmission system. Under sudden large disturbances, the lack of inertia support makes rotor-angle instability prone to occur, which undermines sustainable operation. Battery energy storage systems (BESS) provide fast emergency power support, and an effective control strategy can enhance transient rotor-angle stability while improving operational sustainability. Accordingly, equivalent-circuit models of the regional export system are established for the before-fault, during-fault, and after-fault stages. Building on the extended equal area criterion (EEAC) and the low-voltage ride-through (LVRT) capability of OWP, the stabilizing mechanism of BESS participation is examined from the perspectives of optimal power and timing, thereby yielding an optimal BESS control strategy for improving transient rotor-angle stability in regional renewable export systems. Finally, a regional renewable export system is implemented in MATLAB/Simulink R2022b, where severe contingencies are imposed to validate the effectiveness of the proposed BESS control strategy. Full article

In the context of global climate change and rapid urbanization, integrating urban blue-green infrastructure into the built environment is essential for mitigating the urban heat island effect and enhancing climate resilience. Focusing on urban riparian corridors as vital natural cooling systems, this study aims to: (1) quantify their cooling performance in terms of intensity and distance; (2) identify the key landscape drivers and their relative importance; (3) uncover nonlinear relationships and determine ecological thresholds for optimal thermal regulation; and (4) translate these findings into science-based guidelines for climate-adaptive design and sustainable management. Taking 27 representative riparian green spaces in Zhengzhou, China (average area: 17,539 m², range: 10,027–42,690 m²) as a case study, nine key factors characterizing vegetation structure and composition, corridor morphology, and blue-green spatial pattern were used as predictors in a Boosted Regression Tree (BRT) model to analyze their contributions and marginal-effect thresholds. Results show that these corridors provide substantial cooling, with an average intensity of 5.43 °C extending over 215.56 m. Canopy Density, 3D Green Volume per Unit Area, and Green Cover Ratio emerged as the three core drivers, jointly explaining >86% of the cooling performance. The key innovation lies in identifying explicit, design-oriented ecological thresholds—for example, cooling efficacy stabilizes when Green Cover Ratio reaches ~77%, Canopy Density attains 0.7, and the Blue-Green Space Width Ratio approaches 1:1. These thresholds can be directly translated into performance benchmarks for sustainable urban planning and landscape engineering, providing evidence-based parameters for optimizing vegetation structure and spatial configuration. This study demonstrates that applying quantified ecological thresholds can transform riparian corridors into efficient climate-resilient infrastructure, thereby synergistically improving thermal comfort, enhancing ecosystem services, and promoting sustainable land use in urban environments. Full article

Understanding the coupling mechanisms between vegetation phenology and carbon productivity is essential for assessing ecosystem responses to climate change and guiding sustainable grassland management. This study focuses on stable alpine grasslands on the southern slope of the Qilian Mountains from 2001 to 2020, a climatically sensitive but relatively under-investigated transition zone on the northeastern Tibetan Plateau. We utilized MODIS NDVI time-series (MOD13Q1) and the latest PML V2 gross primary productivity (GPP) product at 500 m resolution to quantify changes in the start (SOS), end (EOS), and length (LOS) of the growing season. A pixel-wise linear regression approach was applied to evaluate the sensitivity of GPP to phenological metrics, explicitly characterizing how much GPP changes in response to unit shifts in SOS, EOS and LOS. Compared with previous studies that mainly described large-scale correlations between phenology and GPP or relied on coarser GPP products, this study provides a pixel-level, sensitivity-based assessment of phenology–carbon coupling in alpine grasslands using a long-term, phenology–GPP dataset tailored to the Qilian alpine region. The results revealed trends of earlier SOS, delayed EOS, and extended LOS, accompanied by a gradual increase in GPP. However, phenology–GPP coupling exhibited notable spatial heterogeneity. In mid- and low-altitude areas, extended growing seasons enhanced GPP, whereas high-altitude zones showed limited or even negative responses, likely due to climatic constraints such as cold stress and thermal–moisture mismatches. To better understand these spatial differences, we constructed a three-dimensional phenology–GPP sensitivity space and applied k-means clustering to delineate three ecological functional zones: (1) high carbon sink potential, (2) ecologically fragile regions, and (3) neutral buffers. This sensitivity-based functional zonation moves beyond traditional correlation analyses and provides a process-oriented and spatially explicit framework for ecosystem service assessment, carbon sink enhancement and adaptive land-use strategies in sensitive mountain environments. Full article

The liquid oxygen subcooler is a key unit for the deep cooling, storage, and transportation of liquid oxygen. Its frequent start–stop operation under liquid nitrogen bath conditions introduces potential risks to service reliability. This study employs a thermo-structural sequential coupling approach to evaluate the stress behavior of ABS components in a flat plate-fin heat exchanger during the pre-cooling, heat-exchange, and recovery stages. Based on the maximum shear stress (Tresca) criterion, the evolution of principal stresses in the brazed layer under liquid nitrogen bath conditions was analyzed, and a conservative assessment of the material’s fatigue behavior was conducted. The results indicate that the equivalent stress is governed by the third principal stress, originating from the thermal compression effect induced by low-temperature constraint shrinkage. During the heat exchange phase (2700 s), the inlet equivalent stress reached 93.49 MPa, which is below the 258 MPa limit, falling within Region 1. Local stress concentration is primarily driven by thermal loading, with brazing layer thickness, curvature radius, and liquid oxygen pressure serving as key control variables. Under a safety factor of 1.15 (107 MPa), fatigue testing exceeding 1.5 million cycles has confirmed the static safety and operational reliability of the ABS. Full article

Community energy systems are expected to play an increasingly important role in the decarbonization of the residential sector, but their operation depends on how different electricity and heat storage technologies are configured and used. Existing studies typically examine storage options in isolation, limiting the comparability of their operational roles. This study addresses this gap by developing a decision-support framework that enables a consistent, operation-focused comparison of battery energy storage, hydrogen storage, and electric-vehicle-based storage within a unified community-scale hybrid energy system. The model represents electricity and heat balances in a hub formulation that couples photovoltaic and wind generation, a gas engine, an electric boiler, thermal and electrical storage units, hydrogen conversion and storage, and an aggregated fleet of electric vehicles. It is applied to a stylized Polish residential community using local demand, generation potential, and electricity price data. A set of single-technology and multi-technology scenarios is analyzed to compare how storage portfolios affect self-sufficiency, self-consumption, grid exchanges, and operating costs under current electricity market conditions. The results show that battery and electric vehicle storage primarily provide short-term flexibility and enable price-driven arbitrage, as reflected in the highest contribution of battery discharge to the electricity supply structure (5.6%) and systematic charging of BES and EVs during low-price hours, while hydrogen storage supports intertemporal shifting by charging in multi-hour surplus periods, reaching a supply share of 1.4% at the expense of substantial conversion losses. Moreover, the findings highlight fundamental trade-offs between cost-optimal, price-responsive operation and autonomy-oriented indicators such as self-sufficiency and self-consumption, showing how these depend on the composition of storage portfolios. The proposed framework, therefore, provides decision support for both technology selection and the planning and regulatory assessment of community energy systems under contemporary electricity market conditions. Full article

Quartz Crystal Microbalance with Dissipation monitoring (QCM-D) systems are widely used for the real-time analysis of mass changes and viscoelastic properties in biological samples, enabling applications such as biomolecular interaction studies, biosensing, and fluid characterization. However, their accessibility has been limited by high acquisition costs. To address this limitation, a low-cost, open-source QCM-D system was developed. Unlike other affordable, open-hardware alternatives, this system is specifically optimized for potential biomedical applications by integrating active thermal control to preserve the physical properties of the samples and dissipation monitoring to characterize their viscoelastic behavior. A 10 MHz quartz crystal with a sensor module and a control and acquisition unit were integrated. The full system was built at a total cost below USD 500. Performance validation showed a temperature stability of ±0.13 °C, a frequency stability of ±2 Hz in air, and a limit of detection (LOD) of 0.46% polyethylene glycol (PEG), thereby enabling stable, reproducible measurements and the sensitive detection of small mass and interfacial changes in low-concentration samples. These results demonstrate that key QCM-D sensing capabilities can be achieved at a fraction of the cost, providing an accessible and reliable platform for potential biomedical research. Full article

Second-generation bioethanol from food industry lignocellulosic residues offers a promising route toward low-carbon, circular bioenergy systems. However, the reported environmental impacts differ markedly across studies, challenging efforts to assess the true sustainability of these waste-derived bioethanol routes. This review synthesizes current knowledge on the production of bioethanol from key agro-industrial wastes including oil palm empty fruit bunches, sugarcane bagasse, brewers’ spent grain, spent coffee grounds, tea waste, citrus residues, and potato peel waste. We outline feedstock characteristics, availability, and prevailing management practices, and map the principal biochemical conversion routes to identify process steps that drive environmental performance. A systematic comparison of life cycle assessments reveals substantial methodological heterogeneity across functional units, system boundaries, allocation procedures, and impact assessment methods. Nonetheless, consistent hotspots emerge, particularly associated with pretreatment severity, enzyme production, thermal energy demand, and co-product handling. The review highlights robust cross-study trends, pinpoints methodological gaps, and proposes recommendations for harmonized LCA practice. By integrating technological and methodological perspectives, this work aims to support the development and policy uptake of sustainable, waste-based bioethanol within circular bioeconomies. Full article

Integrating renewable energy into power grids is critical for advancing low-carbon transitions. However, the inherent variability of renewables requires flexible generation resources—predominantly thermal power units—to maintain real-time grid balancing. Although these flexible generators earn revenue from electricity production, they often incur significant deficits in recovering their upfront investment and retrofitting costs. While existing research has largely focused on short-term balancing expenses, this persistent investment gap remains underexplored. This article analyzes the causes of the investment deficit in the flexible generation assets needed to support renewable integration. To more comprehensively assess system integration costs, we propose a modeling framework that quantifies the investment and construction costs incurred due to renewable volatility. Through simulation, we estimate the required flexible capacity, associated costs, and operational revenues, thereby calculating the investment gap directly attributable to renewable integration. The model feasibility is further verified via sensitivity analysis. Additionally, the study outlines a conceptual cost allocation mechanism and demonstrates how the proposed method can be extended to assess other types of grid-supporting resources. These insights contribute to improved electricity market design, support evidence-based energy policymaking, and facilitate the market-oriented reform of the power sector. Full article

Wire-directed energy deposition (W-DED) produces steep thermal gradients and rapid heating-cooling cycles due to the moving heat source, where modest variations in process parameters significantly alter heat input per unit length and therefore the full thermal history. This sensitivity makes process tuning by trial-and-error or repeated FE sweeps expensive, motivating inverse analysis. This work proposes an inverse thermal process design framework that couples single-track experiments, a calibrated finite element (FE) thermal model, and a parametric physics-informed neural network (PINN) surrogate. By using experimentally calibrated heat-loss physics to define the training constraints, the PINN learns a parameterized thermal response from physics alone (no temperature data in the PINN loss), enabling inverse design without repeated FE runs. Thermocouple measurements are used to calibrate the convection film coefficient and emissivity in the FE model, and those parameters are used to train a parametric PINN over continuous ranges of arc power (1.5–3.0 kW) and travel speed (0.005–0.015 m/s) without using temperature data in the loss function. The trained PINN model was validated against the calibrated FE model at 3 probe locations with different power and travel speed combinations. Across these benchmark conditions, the mean absolute errors are between 6.5–17.4 °C, with cooling-tail errors ranging from 1.8–12.1 °C. The trained surrogate is then embedded in a sampling-based inverse optimization loop to identify power-speed combinations that achieve prescribed interlayer temperatures at a fixed dwell time. For target interlayer temperatures of 100, 130, and 160 °C with a 10 s dwell time, the optimized solutions remain within 3.3–5.6 °C of the target according to the PINN, while FE verification is within 4.0–6.6 °C. The results demonstrate that a physics-only parametric PINN surrogate enables inverse thermal process design without repeated FE runs while establishing a single-track baseline for extension to multi-track and multi-layer builds. Full article

To address the increasing demands for faster response and higher control accuracy in the braking systems of electric and intelligent vehicles, a novel brake-by-wire actuation unit and its braking force control methods are proposed. The braking unit employs a permanent-magnet linear motor as the driving actuator and utilizes the lever-based force-amplification mechanism to directly generate the caliper force. Compared with the “rotary motor and motion conversion mechanism” configuration in other electromechanical braking systems, the proposed scheme significantly simplifies the force-transmission path, reduces friction and structural complexity, thereby enhancing the overall dynamic response and control accuracy. Due to the strong nonlinearity, time-varying parameters, and significant thermal effects of the linear motor, the braking force is prone to drift. As a result, achieving accurate force control becomes challenging. This paper proposes a model-free adaptive control method based on compact-form dynamic linearization. This method does not require an accurate mathematical model. It achieves dynamic linearization and direct control of complex nonlinear systems by online estimation of pseudo partial derivatives. Finally, the proposed control method is validated through comparative simulations and experiments against the fuzzy PID controller. The results show that the model-free adaptive control method exhibits significantly faster braking force response, smaller steady-state error, and stronger robustness against external disturbances. It enables faster dynamic response and higher braking force tracking accuracy. The study demonstrates that the proposed brake-by-wire scheme and its control method provide a potentially new approach for next-generation high-performance brake-by-wire systems. Full article

An analysis is presented for the steady thermophoresis and photophoresis of a homogeneous dispersion of identical aerosol spheres of typical physical properties and surface characteristics. The analysis assumes a moderately small Knudsen number (less than about 0.1), such that the gas motion lies within the slip-flow regime, including thermal creep, temperature jump, thermal stress slip, and frictional slip at the particle surfaces. Under conditions of low Peclet and Reynolds numbers, the coupled momentum and energy equations are analytically solved using a unit cell approach that explicitly incorporates interparticle interactions. Closed-form expressions are derived for the mean particle migration velocities in both thermophoresis driven by a uniform temperature gradient and photophoresis induced by an incident radiation field. The results reveal that the normalized particle velocities, referenced to those of an isolated particle, generally decrease with increasing particle volume fraction, though exceptions occur for thermophoresis. While thermal stress slip and thermal creep exert no influence on the normalized thermophoretic velocity, they markedly affect the normalized photophoretic velocity, which rises with the thermal stress slip to the thermal creep coefficient ratio. For both phenomena, the normalized migration velocities increase monotonically with the particle-to-fluid thermal conductivity ratio. Full article

The global energy transition to renewable energy sources requires a rigorous assessment of the environmental impacts of all system components, including power electronics converters (PECs), which play a critical role in adapting generated energy to grid and load requirements. This paper presents a comprehensive comparative assessment of conventional PECs used in renewable energy systems, with a focus on DC-AC, DC-DC, and AC-DC converters. The study combines life cycle assessment (LCA) with the Circular Energy Sustainability Index (CESI) to evaluate both environmental performance and material circularity. The LCA is conducted using a functional unit defined as a representative converter, within consistent system boundaries that encompass material extraction, manufacturing, and end-of-life stages. This approach enables comparability among converter topologies but introduces limitations related to the exclusion of application-specific design optimizations, such as maximum efficiency, spatial constraints, and thermal management. CESI is subsequently applied as a decision-support tool to rank converter technologies according to sustainability and circularity criteria. The results reveal substantial differences among converter types: the controlled rectifier exhibits the lowest environmental impact and the highest circularity score (95.3%), followed by the uncontrolled rectifier (69.3%), whereas the inverter shows the highest environmental burden and the lowest circularity performance (38.6%), primarily due to its higher structural complexity and the material and manufacturing intensity associated with its switching architecture. Full article

The evolution of next-generation urban infrastructure necessitates the deployment of intelligent pavement systems capable of real-time data acquisition, adaptive response, and predictive analytics. This article presents the design, implementation, and performance evaluation of the smart pavement system incorporating multimodal embedded sensors for traffic density analysis, structural health monitoring, and environmental surveillance. SPS integrates piezoelectric transducers, micro-electro-mechanical system accelerometers, inductive loop coils, fiber Bragg grating (FBG) sensors, and capacitive moisture and temperature sensors within the asphalt and sub-base layers, forming a distributed sensor network that interfaces with an edge-AI-enabled data acquisition and control module. Each sensor node performs localized pre-processing using low-power microcontrollers and transmits spatiotemporal data to a centralized IoT gateway over an adaptive mesh topology via long-range wide-area network or 5G-Vehicle-to-Everything protocols. Data fusion algorithms employing Kalman filters, sensor drift compensation models, and deep convolutional recurrent neural networks enable accurate classification of vehicular loads, traffic, and anomaly detection. Additionally, the system supports real-time air pollutant detection (e.g., NO₂, CO, and PM2.5) using embedded electrochemical and optical gas sensors linked to mobile roadside units. Field deployments on a 1.2 km highway testbed demonstrate the system’s capability to achieve 95.7% classification accuracy for vehicle type recognition, ±1.5 mm resolution in rut depth measurement, and ±0.2 °C thermal sensitivity across dynamic weather conditions. Predictive analytics driven by long short-term memory networks yield a 21.4% improvement in maintenance planning accuracy, significantly reducing unplanned downtimes and repair costs. The architecture also supports vehicle-to-infrastructure feedback loops for adaptive traffic signal control and incident response. The proposed SPS architecture demonstrates a scalable and resilient framework for cyber-physical infrastructure, paving the way for smart cities that are responsive, efficient, and sustainable. Full article

A novel ternary transition metal chalcogenide Ba₂Re₆Se₁₁, which crystallizes in the R−3c space group, was synthesized using a high-pressure and high-temperature technique. The lattice is constituted by Re₆Se₈ cube-octahedral clusters connected by additional apical Se anions via the Re-Se-Re pathway, while the Ba atoms reside in the cavities among the Re₆Se₈ units. High-pressure synchrotron X-ray diffraction measurements showed that Ba₂Re₆Se₁₁ maintains a trigonal structure up to a pressure of 60 GPa, with a bulk modulus of 193 GPa. The lattice stability is ascribed to the fully occupied valence bands of the molecular orbital of the Re₆Se₈ cluster with trivalent Re. This fully occupied orbital configuration also gives rise to the diamagnetic state of Ba₂Re₆Se₁₁, which was validated through magnetic measurements. The resistivity of Ba₂Re₆Se₁₁ is as low as several milliohm centimeters, and it follows the thermal activation mechanism at elevated temperatures and the three-dimensional variable-range hopping model at low temperatures, indicating that Ba₂Re₆Se₁₁ is a semiconductor or insulator in close vicinity to a metal–insulator transition. Full article

This study provides a detailed technical and sustainability comparison of the conventional CNC machining and additive manufacturing routes for an aerospace bearing bracket. The work integrates material selection, process parameterization, build simulation, and environmental–economic assessment within a single framework. For the CNC route, machining of Al 7175-T7351 is characterized through process sequencing, tooling requirements, and waste generation. For the Laser Powder Bed Fusion (LPBF) route, two build strategies, single-part distortion-minimized and multi-part volume-optimized, are developed using Siemens NX for orientation optimization and Atlas3D for thermal and recoater collision simulations. The mechanical properties of Al 7175-T7351 and Scalmalloy^® are compared to justify material selection for aerospace applications. Both the experimental and simulation-derived process metrics are reported, including the build time, support mass, energy consumption, distortion tolerances, and buy-to-fly (B2F) ratio. CNC machining exhibited a B2F ratio of 1:7, with cradle-to-gate CO₂ emissions of ~11,000 g and an energy consumption exceeding 100 kWh per component. In contrast, both LPBF strategies achieved a B2F ratio of 1:1.2, reducing CO₂ emissions by over 90% and energy consumption by up to 63%. Build volume optimization further reduced the LPBF unit cost by over 50% relative to the CNC machining. Use-phase analysis in an aviation context indicated estimated lifetime fuel savings of 776,640 L and the avoidance of 2328 tons of CO₂ emissions. The study demonstrates how simulation-guided build preparation enables informed sustainability-driven decision-making for manufacturing route selection in aerospace applications. Full article