Search Results (953)

Normal shock pressure ratios in equilibrium air for Mach numbers up to 30 and altitudes to 300,000 feet are shown to be correlated by a simple power law which provides an accuracy of ±2%, thereby permitting direct calculation of corresponding enthalpy ratios accurate to ±1% without iteration; a slight change in power-law coefficients extends this capability to Mach 65. Temperature, density, and compressibility may be then found directly from tables for high temperature air. For Mach numbers up to at least 6, a linear approximation for specific heat provides direct solutions for post-shock state variables, while a complementary logarithmic model of the equation of state enables direct solutions for Mach numbers up to about 12. This approach, which provides accuracy within ±3% for all relevant variables in the practical flight corridor of vehicles at these low to moderate hypersonic Mach numbers, should prove useful in design and analysis because the algebraic solutions obtained need neither iteration or interpolation. Full article

To mitigate the emission of greenhouse gases (GHG) from fossil fuel combustion, biomass-to-power development via biochemical or thermochemical pathways has been recognized as a sustainable route for advancing towards a society based on a circular bioeconomy. The key differences between these pathways lie in operating temperature, process design capacity, feedstock characteristics and primary products. The biochemical route focuses on specific biofuels (e.g., biogas), and the thermochemical route often offers broader energy forms like heat and electricity. This perspective paper updates Taiwan’s achievements of its installed capacity and power (electricity) generation over a period of five years (2020–2024) under regulatory promotion that echoes official policies for sustainable development goals (SDGs) and 2050 carbon neutrality. Furthermore, the challenges of the biomass-to-power development in Taiwan (especially biogas-to-power systems) are addressed in the present study. These key issues include biomass resource, promotion incentives, stationary air pollution, site land use requirements and units for meeting performance durability requirements. Based on installed capacity, the main findings showed that biomass-to-power systems using biochemical routes (i.e., anaerobic digestion) in Taiwan showed an increasing trend, as well as increasing results for those using thermochemical routes (direct combustion, gasification). Furthermore, the data on total power generation indicated an upward trend from 201.7 Gigawatt-hour (GWh) in 2021 to 237.7 GWh in 2024, regardless of the kind of route used, whether biochemical or thermochemical. In conclusion, biomass-to-power systems have provided sustainable waste management and a circular bioeconomy model in Taiwan, which can be linked to the targets of sustainable development goals (SDGs) like SDG-7 (i.e., affordable and clean energy) and SDG-12 (i.e., responsible consumption and production). Full article

Listeria monocytogenes is a persistent foodborne pathogen capable of surviving in food processing environments, often in association with diverse environmental microflora. This study examines genomic determinants of persistence, specifically stress adaptation and biofilm-associated traits, in environmental Listeria species and other environmental microflora from a dairy processing facility by analyzing whole-genome sequences of 6 environmental Listeria isolates, 4 ATCC reference strains, and 22 air and floor swab cultures, annotated using the RAST platform. Subsystem analysis revealed that Listeria isolates carried a defined set of genes linked to biofilm formation, antimicrobial resistance, and stress response, though in lower abundance than environmental cultures. Listeria exhibited fewer flagellar genes but greater consistency in core stress-related genes, including those for disinfectant and osmotic stress resistance, with SigB operon and RpoN genes highlighting strong stress tolerance. In contrast, environmental cultures exhibited broader transcriptional regulators (RpoE, RpoH) and greater diversity in acid and heat shock response genes, indicating distinct survival strategies. All examined Listeria species harbor biofilm and stress-resistance genes enabling independent survival, while environmental microbiota show greater genetic diversity that may promote persistence and multispecies biofilm formation. This study underscores the complex genetic landscape that may contribute to the persistence of Listeria and environmental microbiota in dairy processing environments, providing foundational insights for environmental cross contamination control strategies. Full article

At present, the global shortage of water resources has led to serious challenges, and traditional water production technologies such as seawater desalination and atmospheric water harvesting have certain limitations due to inflexible operation and environmental conditions. This study proposes a novel water production system (called “NeWater” system in this paper), which combines saline water desalination with atmospheric water-harvesting technologies to simultaneously produce freshwater from brackish water or seawater and ambient air. To evaluate its performance, an integrated thermodynamic and mathematical model of the system was developed and validated. The NeWater system consists of a vapor compression refrigeration unit (VRU), a direct evaporation unit (DEU), up to four heat exchangers, some valves, and auxiliary components. The system can be applied to areas and scenarios where traditional desalination technologies, like reverse osmosis and thermal-based desalination, are not feasible. By switching between different operating modes, the system can adapt to varying environmental humidity and temperature conditions to maximize its freshwater productivity. Based on the principles of mass and energy conservation, a performance simulation model of the NeWater system was developed, with which the impacts of some key design and operation parameters on system performance were studied in this paper. The results show that the performances of the VRU and DEU had a significant influence on system performance in terms of freshwater production and specific energy consumption. Under optimal conditions, the total freshwater yield could be increased by up to 1.9 times, while the specific energy consumption was reduced by up to 48%. The proposed system provides a sustainable and scalable water production solution for water-scarce regions. Optimization of the NeWater system and the selection of VRUs are beyond the scope of this paper and will be the focus of future research. Full article

Air conditioners are a critical adaptation measure against heat- and cold-related risks under climate change. However, their electricity use and refrigerant leakage increase greenhouse gas (GHG) emissions. This study developed a data-driven life-cycle assessment (LCA) framework for residential room air conditioners in Japan by integrating large-scale field operation data with life-cycle climate performance (LCCP) modeling. We aggregated 1 min records for approximately 4100 wall-mounted split units and evaluated the 10-year LCCP across nine climate regions. Using the annual operating hours and electricity consumption, we classified the units into four behavioral quadrants and quantified the life-cycle GHG emissions and parameter sensitivities for each. The results show that the use-phase electricity dominated the total emissions, and that even under the same climate and capacity class, the 10-year per-unit emissions differed by roughly a factor of two between the high- and low-load quadrants. The sensitivity analysis identified the heating hours and the setpoint–indoor temperature difference as the most influential drivers, whereas the grid CO₂ intensity, equipment lifetime, and refrigerant assumptions were of secondary importance. By replacing a single assumed use scenario with empirical profiles and behavior-based clusters, the proposed framework improves the representativeness of the LCA for air conditioners. This enabled the design of cluster-specific mitigation strategies. Full article

In regions with hot summers and cold winters, elderly care buildings face the dual challenges of high energy consumption and stringent thermal comfort requirements. Using Nanchang as a case study, this research presents an optimization approach that integrates phase change material (PCM) walls with the window-to-wall ratio (WWR). PCM wall performance was tested experimentally, and EnergyPlus simulations were conducted to assess building energy use for WWR values ranging from 0.25 to 0.50, with and without PCM. The phase change material (PCM) used in this study is paraffin (an organic phase change material), which has a melting point of 26 °C and can store and release heat during temperature fluctuations. The experimental results show that PCM walls effectively reduce heat transfer, lowering the surface temperatures of external, central, and internal walls by 3.9 °C, 3.8 °C, and 3.7 °C, respectively, compared to walls without PCM. The simulation results predict that the PCM wall can reduce air conditioning energy consumption by 8.2% in summer and total annual energy consumption by 14.2%. The impact of WWR is orientation-dependent: east and west façades experience significant cooling penalties as WWR increases and should be maintained at or below 0.30; the south façade achieves optimal performance at a WWR of 0.40, with the lowest total energy load (111.2 kW·h·m-2); and the north façade performs best at the lower bound (WWR = 0.25). Under the combined strategy (south wall with PCM and WWR = 0.40), annual total energy consumption is reduced by 9.8% compared to the baseline (no PCM), with indoor temperatures maintained between 18 and 26 °C. This range is selected based on international thermal comfort standards (e.g., ASHRAE) and comfort research specifically targeting the elderly population, ensuring comfort for elderly occupants. These findings offer valuable guidance for energy-efficient design in similar climates and demonstrate that the synergy between PCM and WWR can reduce energy consumption while maintaining thermal comfort. Full article

The relevance of this study is driven by the increasing requirements for the energy efficiency and indoor comfort of residential and public buildings, particularly in regions with extreme climatic conditions characterized by substantial daily and seasonal temperature fluctuations. Effective management of heat transfer through building envelopes has become a key factor in reducing energy consumption and improving indoor comfort. This paper presents the results of an experimental–numerical investigation of the thermal behavior of an adaptive exterior wall system with a controllable air cavity. Steady-state and transient simulations were performed for three envelope configurations: a baseline design, a design with vertical air channels, and an adaptive configuration equipped with adjustable openings. Quantitative analysis showed that during the winter period, the adaptive configuration increases the interior surface temperature by 1.5–2.3 °C compared to the baseline design, resulting in a 12–18% reduction in the specific heat flux through the wall. In the summer period, the temperature of the exterior cladding decreases by 3–5 °C relative to the baseline, which reduces heat gains by 8–14% and lowers the cooling load. Additional analysis of temperature fields demonstrated that the presence of vertical air channels has a limited effect during winter: temperature differences at the surfaces do not exceed 1 °C. A similar pattern is observed in warm periods; however, due to controlled air circulation, the adaptive configuration provides an improved thermal regime. The results confirm the effectiveness of the adaptive wall system under the climatic conditions of southern Kazakhstan, characterized by high solar radiation and large diurnal temperature variations. The practical significance of the study lies in the potential application of adaptive façades to enhance the energy efficiency of buildings during both winter and summer seasons. Full article

Heating, ventilation, and air conditioning (HVAC) systems account for a significant portion of building energy consumption and play a crucial role in maintaining indoor comfort. However, hidden faults in air-handling units (AHUs) often lead to energy waste and degraded performance, highlighting the importance of reliable fault detection and diagnosis (FDD). This study proposes a simulation-driven FDD framework that integrates a standardized prototype dataset and an independent evaluation dataset generated from a calibrated EnergyPlus model representing a target facility, enabling controlled experimentation and transfer evaluation within simulation environments. Training data were generated from the DOE EnergyPlus Medium Office prototype model, while evaluation data were obtained from a calibrated building-specific EnergyPlus model of a research facility operated by Company H in Korea. Three representative fault scenarios—outdoor air damper stuck closed, cooling coil fouling (65% capacity), and air filter fouling (30% pressure drop)—were systematically implemented. A Deep Belief Network (DBN) classifier was developed and optimized through a two-stage hyperparameter tuning strategy, resulting in a three-layer architecture (256–128–64 nodes) with dropout and regularization for robustness. The optimized DBN achieved diagnostic accuracies of 92.4% for the damper fault, 98.7% for coil fouling, and 95.9% for filter fouling. These results confirm the effectiveness of combining simulation-based dataset generation with advanced deep learning methods for HVAC fault diagnosis. The results indicate that a DBN trained on a standardized EnergyPlus prototype can transfer to a second, independently calibrated EnergyPlus building model when AHU topology, control logic, and monitored variables are aligned. This study should be interpreted as a simulation-based proof-of-concept, motivating future validation with field BMS data and more diverse fault scenarios. Full article

Overhead transmission lines are critical carriers for power delivery, directly influencing the security of the power system. In high-altitude areas, special environmental conditions such as low air pressure and intense solar radiation significantly change the heat absorption and dissipation characteristics of conductors. Therefore, it is necessary to correct the overhead conductors’ ampacity in such areas to ensure safe operation. However, the ampacity calculation method and high-altitude ampacity correction coefficients proposed in existing standards have significant limitations, and there are also large errors in the calculation results. Therefore, based on the system of partial differential equations proposed in the “Guidelines for Calculating the Current-Carrying Capacity of Transmission Conductors at High Altitudes” and the suggestions for high-altitude meteorological parameter modifications from existing standards, this paper establishes a three-dimensional finite element model to study the ampacity calculation method for overhead conductors in high-altitude areas. The results show that a significant thermal shielding effect exists among bundled conductors, and meteorological condition variations significantly influence the temperature distribution of the conductors and their surrounding space. At altitudes of 4000~5000 m, the altitude correction coefficient for both twin-bundle and quad-bundle conductors is −0.06 A∙m⁻¹ under specific conservative conditions. Full article

The conventional reactive cooling strategy, which relies on static thresholds, has become inadequate for managing dynamically changing heat loads, often resulting in energy inefficiency and increased risk of local hot spots. In this study, we develop a data center cooling optimization system that integrates distributed sensor arrays for predictive analysis. By deploying high-density temperature and humidity sensors both inside and outside server racks, a real-time, high-fidelity three-dimensional digital twin of the data center’s thermal environment is constructed. Time-series analysis combined with Long Short-Term Memory algorithms is employed to forecast temperature and humidity based on the extensive environmental data collected, achieving high predictive accuracy with a root mean square error of 0.25 and an R² value of 0.985. Building on these predictions, a proactive cooling control strategy is formulated to dynamically adjust fan speeds and the opening degree of chilled-water valves in computer room air conditioning units, changing the cooling approach from passive to preemptive prevention of overheating. Compared with conventional proportional–integral–differential control, the developed system significantly reduces overall energy consumption and maintains all equipment within safe operating temperatures. Specifically, the framework has reduced the energy consumption of the cooling system by 37.5%, lowered the overall power usage effectiveness of the data center by 12% (1.48 to 1.30), and suppressed the cumulative hotspot duration (temperature 27 °C) by nearly 96% (from 48 to 2 h). Full article

This paper addresses the critical challenge of multi-objective optimization in residential Home Energy Management Systems (HEMS) by proposing a novel framework based on an Improved Multi-Agent Proximal Policy Optimization (MAPPO) algorithm. The study specifically targets the low convergence efficiency of Multi-Agent Deep Reinforcement Learning (MADRL) for coupled Battery Energy Storage System (BESS) and Air Source Heat Pump (ASHP) operation. The framework synergistically integrates an action constraint projection mechanism with an economic-performance-driven dynamic learning rate modulation strategy, thereby significantly enhancing learning stability. Simulation results demonstrate that the algorithm improves training convergence speed by 35–45% compared to standard MAPPO. Economically, it delivers a cumulative cost reduction of 15.77% against rule-based baselines, outperforming both Independent Proximal Policy Optimization (IPPO) and standard MAPPO benchmarks. Furthermore, the method maximizes renewable energy utilization, achieving nearly 100% photovoltaic self-consumption under favorable conditions while ensuring robustness in extreme scenarios. Temporal analysis reveals the agents’ capacity for anticipatory decision-making, effectively learning correlations among generation, pricing, and demand to achieve seamless seasonal adaptability. These findings validate the superior performance of the proposed centralized training architecture, providing a robust solution for complex residential energy management. Full article

Cultural practices such as Catalonia’s correfocs (fire parades) represent a vibrant expression of intangible heritage. Outdoor activities are conditioned by weather and threatened by climate change. This study analyses the long-term evolution of night-time thermal conditions during correfoc festivals performed in six Catalan towns located on the coast and in the pre-coastal region from 1950 to 2023, using reanalysis-based indicators of air temperature, humidity, and perceived heat as a first exploratory step prior to incorporating in situ meteorological records. Specifically, the Heat Index (HI) and the Universal Thermal Climate Index (UTCI) were computed for the typical event window (21:00–23:00 local time) to assess changes in human thermal comfort. Results reveal a clear and statistically significant warming trend in most pre-coastal locations—particularly Reus, El Vendrell, and Vilafranca—while coastal cities such as Barcelona exhibit weaker or non-significant changes, likely due to maritime moderation. The frequency and intensity of positive temperature anomalies have increased since the 1990s, with a growing proportion of events falling into “caution” or “moderate heat stress” categories under HI and UTCI classifications. These findings demonstrate that correfocs are now celebrated under markedly warmer night-time conditions than in the mid-twentieth century, implying a tangible rise in thermal discomfort and potential safety risks for participants. By integrating climatic and cultural perspectives, this research shows that rising night-time heat can constrain attendance, participation conditions, and event scheduling for correfocs, thereby directly exposing weather-sensitive form of intangible cultural heritage to climate risks. It therefore underscores the need for climate adaptation frameworks and to promote context-specific strategies to sustain these community-based traditions under ongoing Mediterranean warming. Full article

Urban areas often suffer from enduring environmental issues, including flooding, biodiversity loss, heat island effects, and air and soil pollution. The Miyawaki method of afforestation, characterized by dense planting of native species on remediated soil, has been proposed as a rapid, nature-based solution for restoring urban ecological function. This study aims to evaluate early-stage changes in soil health following Miyawaki-style microforest establishment in formerly redlined neighborhoods in Elizabeth, New Jersey. Specifically, it investigates whether this method improves soil permeability, carbon content, and microbial activity within the first three years of planting. Three microforests aged one, two, and three years were assessed using a chronosequence approach. At each site, soil samples from within the microforest and adjacent untreated urban soil (control) were compared. Analyses included physical (porosity, dry density, void ratio), chemical (total carbon), and biological (microbial respiration, biomass, metabolic rate, carbon use efficiency) assessments. Soil permeability was estimated via the Kozeny–Carman equation. Microforest soils showed significantly greater porosity (p = 0.015), higher void ratios (p = 0.009), and reduced compaction compared to controls. Soil permeability improved dramatically, with factors ranging from 5.99 to 52.27. Total carbon content increased with forest age, reaching 2.0 mg C/g in the oldest site (p < 0.001). Microbial metabolic rate rose by up to 287.5% (p = 0.009), while carbon use efficiency also improved, particularly in the older microforests. Within just one to three years, Miyawaki microforests significantly enhanced both the physical and biological properties of degraded urban soils, signaling rapid restoration of soil function and the early return of ecosystem services. Full article

Oxygen-reduced air injection technology has demonstrated considerable potential for developing heavy oil reservoirs. However, the low-temperature oxidation (LTO) behavior and non-isothermal heat release of heavy oil under oxygen-reduced conditions remain poorly understood. Accordingly, this study systematically investigated the oxygen consumption characteristics of heavy crude oil under two oxygen concentrations (8% and 10%) through isothermal static oxidation experiments. Additionally, scanning electron microscopy (SEM) and differential scanning calorimetry (DSC) were employed to analyze the microstructural evolution of rock cuttings and the exothermic characteristics of heavy oil before and after oxidation. The results indicated that as the oxygen concentration increased from 8% to 10%, the pressure drop during the LTO process rose from 1.73 to 2.04 MPa, and the oxygen consumption rate increased from 1.47 × 10⁻⁵ to 2.06 × 10⁻⁵ mol/(h·mL). This demonstrated that higher oxygen partial pressure promoted LTO reactions, thereby generating more abundant coke precursors for the subsequent high-temperature oxidation (HTO) stage. SEM analysis revealed that the microstructure of the rock cuttings after oxidation transitioned from an originally smooth, “acicular” morphology to a “flaky” structure characterized by extensive crack development, which significantly improved the connectivity of the pore-fracture system. DSC analysis further demonstrated that the mineral components in the rock cuttings played a dual role during the oxidation process: at the LTO stage, their heat capacity effect suppressed the exothermic behavior during oxidation; whereas at the HTO stage, their larger specific surface area and the catalytic effect of clay minerals enhanced the heat release from coke combustion. This study thus provided a theoretical foundation for developing heavy oil reservoirs through oxygen-reduced air injection. Full article

This study employs CFD simulations carried on ANSYS Fluent 2022 R1 (ANSYS Inc., Canonsburg, PA, USA), to address the design, development, and thermodynamic analysis of a biomass burner, based on mass and energy balances, combustion efficiency, flame temperature, and thermodynamic properties. The prototype incorporates a flow deflector located before the combustion chamber. This component improves the air-fuel mixture to maximise thermal efficiency and minimise pollutant emissions. The burner is specifically designed to use sawdust as fuel and is intended for industrial applications such as heating or drying processes. The integration of the flow deflector results in uniform, complete combustion, achieving 90% thermal efficiency and an adjustable thermal power output of 0–100 kW. Compared to conventional burners, this design reduces CO emissions by 20% and NO_x emissions by 15%, demonstrating significant environmental improvements. The design methodology is based on mass and energy balance equations to evaluate combustion efficiency as a function of the stoichiometric ratio, along with experimental testing. These experimental tests were conducted using an ECOM (America Ltd., Nashua, NH, USA) gas analyser and anemometer. The internal temperature was monitored with a K-type thermocouple (Omega Engineering Inc., Norwalk, CT, USA). The results confirmed the positive influence of the structural design on thermal performance. The proposed burner aims to maximise heat generation in the combustion chamber, offering an innovative alternative for biomass combustion systems. Full article