Search Results (21,737)

This study proposes a real-time chiller capacity control strategy based on marginal Coefficient of Performance (COP) analysis to improve the energy efficiency of air-conditioning systems. The research focuses on the air-conditioning system (ACS) of an office building. Operational data, including chiller capacity and the corresponding COP, were collected to derive the chiller’s operating characteristic curve. The Optimal Capacity Control (OCC) strategy aims to maximize the total COP of all chillers, and the initial capacity allocation is determined using the Lagrange multiplier method. To further refine performance, a fine-tuning mechanism is introduced, calculating the ratio of COP variation to capacity variation (RC ratio) for each chiller to identify which unit should be loaded or unloaded. Based on the fine-tuning mechanism, a comprehensive OCC model is established to ensure that the chiller’s cooling output precisely matches the load demand, thereby maximizing system efficiency and reducing energy consumption. To validate the effectiveness of the proposed OCC strategy, a numerical analysis was implemented using real operational data from the existing ACS. Comparative simulations between the OCC and a Traditional Capacity Control (TCC) strategy were conducted. On a representative summer day, total power consumption decreased from 1534.0 kWh (TCC) to 1527.2 kWh (OCC), while total system COP increased from 113.9 to 114.8. Seasonal analysis further confirms consistent energy savings under varying load conditions. The results indicate that the OCC strategy significantly enhances system performance and reduces energy consumption under varying load conditions. Overall, the proposed method achieves a higher system COP, leading to notable electricity savings and improved operational efficiency of the air-conditioning system. Full article

This paper investigates the fundamental mechanisms of technological change in complex systems by analyzing how the evolution of embedded subsystems dictates the trajectory and sets the tempo of a host technology. Building on the theoretical framework of technological parasitism, the study conceptualizes host systems having a modular architecture—such as smartphones—as evolving through dynamic, coevolutionary interactions with their constituent subsystems. These relations gradually shift from parasitic reliance to mutualistic and ultimately symbiotic interactions. Central to this research is the concept of subsystems as pacemakers. Methodologically, this research employs a longitudinal, mixed-methods approach, combining an 18-year case study of the iPhone (2007–2025) with time-series regression and log–log hedonic pricing models. Key findings are: (a) Temporal precedence: Advances in subsystems (e.g., Bluetooth protocols) consistently precede host releases. The integration lag has contracted from three years to one, signaling an acceleration in symbiotic coupling and highlighting Bluetooth as a systemic pacemaker whose evolutionary tempo anticipates shifts in the wider smartphone architecture. (b) Differential evolutionary pressure in technological host systems: While camera resolution exhibited the highest exponential growth (+16.73%), it remained a secondary driver of systemic evolution. (c) Economic pacemakers: Hedonic analysis identifies battery life as the dominant evolutionary predictor (standardized beta = 0.77). With an elasticity of approximately 0.30, a 1% gain in battery performance correlates to a 0.3% increase in nominal price, whereas display and camera resolution exert significantly less influence on the system’s valuation and trajectory. These findings reveal that subsystems evolve—and exert influence—at different speeds and with different degrees of systemic leverage. Overall, the proposed theory shows that subsystem evolution functions as a leading indicator of forthcoming host–system transitions. By identifying which subsystems act as temporal pacemakers, this research contributes new design rules for forecasting technological generations and optimizing R&D strategies in complex, multi-component innovations. Hence, the study demonstrates that mastering complex innovation requires a granular understanding of the asynchronous rhythms between a host technology and its constitutive parts. Full article

Extensive glazing is a common feature of modern buildings, intended to maximize daylight and strengthen visual connections with the outdoors. While this strategy can enhance energy performance, its effectiveness strongly depends on climate, orientation, and seasonal variations, and it often introduces challenges related to visual comfort, particularly glare. This paper proposes a refurbishment methodology that systematically integrates the view out, often neglected in current practice, into the decision-making framework, focusing on its relationship with daylight. The methodology follows a stepwise process encompassing the identification of discomfort conditions, evaluation of intervention feasibility, and design of targeted refurbishment strategies. Its main innovation lies in integrating and verifying a balance between view quality and daylight within a unified analytical framework. Validation through a university building in València confirmed that optimizing these parameters represents a significant design challenge, as enhancing one may compromise the other. The analysis also revealed limitations of current standards, such as EN 17037, whose static approach fails to capture the dynamic interactions among daylight, shading operation, and user perception. Furthermore, the proposed methodology introduces a scalable level of analytical granularity, enabling the assessment depth to be adapted to economic resources and time constraints, thereby supporting informed and sustainable decisions in building refurbishment. Full article

Operable windows are critical for indoor environmental quality (IEQ) and occupant agency, yet their usability is increasingly compromised by conflicts between regulatory compliance and building performance. This study investigates the gap between geometrically compliant provisions and effectively operable windows through a comparative policy analysis of mandatory codes (Level 1), green rating systems (Level 2), and regenerative frameworks (Level 3). The findings identify a structural discrepancy termed the Geometric Trap: while minimum opening areas are legally required, mechanical ventilation often substitutes for natural access. In the United States, Japan, and Republic of Korea, explicit waivers permit full substitution, while in the United Kingdom, conditional constraints such as environmental noise limit practical operability. Germany, by contrast, maintains operable windows as an independent mandate, restricting substitution to defined environmental conditions. Although emerging green rating systems increasingly recognize resilience and adaptive comfort, operability remains optional. Regenerative standards, however, treat it as a prerequisite for occupant health. This study proposes a shift from static geometric compliance toward an Effective Opening Area framework that evaluates actual accessibility and usability, advancing a performance-based and occupant-centered regulatory perspective. Full article

Ventilation systems in agricultural settings are designed to deliver specific air exchange rates, which are often not achievable using natural ventilation. In this study, we analyzed 105 agricultural ventilation fans tested between 2015 and 2025 at the Bioenvironmental and Structural Systems (BESS) Laboratory, including 0.6, 0.9, 1.2, and 1.5 m diameter fans operating at static pressures ranging from 0 to 75 Pa. The main objective of the study is to develop and introduce guidelines to help select the most suitable ventilation fans to improve the sustainability of agricultural operations. Two web-based interactive calculators were developed to visualize fan performance relative to low- and high-performing fans of the same diameter. Our findings indicated that the ventilation efficiency ratio (VER) of the fans ranged from 2 to 50 m³ h⁻¹ W⁻¹, and larger fans consistently showed higher efficiency at typical operating pressures of 12.5 to 37.5 Pa. In general, variable-speed fans operated at 85%, rather than full capacity, achieved higher efficiency. Two cost comparison scenarios were examined. In the first scenario, the fan with a higher purchasing cost but also 35% higher efficiency resulted in a payback period of 4.1 years. In the second scenario, the difference in fan efficiencies was less than 3.5%, which did not help with recovering higher purchase costs during the 10-year analysis period. It was concluded that selecting fans solely based on purchase price can lead to higher long-term costs. To improve the sustainability of agricultural fans, VER and operating conditions need to be evaluated together and integrated into automated control strategies. Future studies can focus on integrating fans with high efficiencies into sensor-based automated ventilation control systems to quantify long-term energy savings in livestock buildings and other agricultural operations. Full article

The Panoma Field in the Hugoton Embayment, Kansas, has produced significant gas resources from thousands of wells perforating the Permian Chase and Council Grove Groups. Variability in gas production from these formations is controlled by facies-influenced petrophysical properties. The use of geological facies data in numerical modeling is often limited to delineating regions of interest without intrinsic use in estimating petrophysical properties. Machine learning provides opportunities to integrate facies data into the numerical model-building process. In this study, we employ facies data in optimizing a numerical model permeability matrix scaling parameter using Monte Carlo Simulation of Markov Switching Dynamic Regression and machine learning. Realizations of the scaling parameter are included in a machine learning facies prediction workflow to identify the parameter that maximizes facies prediction accuracy, with test accuracy as high as 83%. A 3D numerical model was constructed to represent the interlayered carbonate, shale, and non-marine sandstones facies typical of the Council Grove intervals. Multiple field development and completion scenarios were evaluated to maximize cumulative gas recovery and assess the role of facies distribution on reservoir performance. History matching results of historical gas production demonstrate strong coupling between facies distribution and the optimized permeability, emphasizing the importance of facies data integration in reservoir property modeling and gas production estimation in Permian reservoirs. This implies that probabilistically constrained permeability scaling using the Monte Carlo and machine learning workflow produces more realistic modeling compared to traditional approaches. Full article

The fire performance of ventilated facade systems incorporating combustible insulation remains a critical issue in contemporary building design. This study presents a full-scale natural-fire test of a ventilated, rendered facade system containing 150 mm expanded polystyrene (EPS) insulation, conducted in accordance with the DIN 4102-20 methodology. Temperature measurements were recorded at key facade locations via K-type thermocouples, and flame spread, materials melting, and degradation were documented through visual observations. The combustion chamber reached a peak temperature of 912 °C, while the thermocouple located above the opening recorded a maximum temperature of 786 °C. No sustained flaming or debris above the 3.5 m height limit was observed, yet significant internal EPS melting occurred throughout the cavity. These findings underscore the potency of the “chimney effect” in ventilated cavities, highlight the limitations of the current acceptance criteria, and provide evidence relevant to ongoing efforts to develop more coherent approaches to facade fire-safety assessment. Full article

Quantum reinforcement learning (QRL) is often evaluated under idealized, noiseless assumptions, yet realistic quantum devices inevitably introduce noise that can severely degrade performance. This paper improves the robustness of quantum deep Q-learning (QDQN) by redesigning the variational quantum circuit (VQC) used in its value-function approximator. Motivated by recent advances in quantum convolutional neural networks (QCNNs), we construct four QCNN-inspired VQC variants (Models A–D) by combining representative QCNN two-qubit building blocks with an explicit fully connected (all-to-all) layer. Using a 10-fold evaluation protocol at a fixed noise level p = 0.005, Model D achieves the best robustness, reducing the mean number of episodes required to reach a target reward from 1981 (baseline) to 1243. Under a stricter success criterion, Model D also doubles the empirically observed noise-tolerance boundary from 0.002 to 0.004. These results indicate that carefully chosen QCNN-style circuit components and connectivity can significantly improve the noise robustness of QDQN-like QRL agents. Full article

This study explores the passive separation of solid particles from liquid suspensions in spiral separators fabricated using fused filament fabrication (FFF) and stereolithography (SLA). Building on prior work, we investigate the effect of microchannel geometry, circular vs. square cross-sections of equal area, and printing method on separation performance. Devices were tested across a wider range of flow rates (150 mL min⁻¹–350 mL min⁻¹), extending into transitional regimes, to examine geometry-induced inertial effects. Separation performance was quantified using the normalized outlet mass difference (Δ) for talc, precipitated calcium carbonate, and quartz. Maximum separation was obtained for quartz sand in the SLA separator at 250 mL min⁻¹ (Δ = 0.2175 g per 100 mL), while talc showed the highest mass difference in the square FFF separator at 300 mL min⁻¹ (Δ = 0.1196 g per 100 mL). For calcium carbonate, the highest separation occurred in the SLA device at 250 mL min⁻¹ (Δ = 0.1721 g per 100 mL), though performance was limited by agglomeration and clogging in FFF devices. Overall, separation was predominantly mass-based rather than strictly size-selective, with channel geometry, flow regime, and fabrication method jointly governing performance. Full article

Background/Objectives: Nutritional medicine remains underrepresented in medical education despite its relevance across specialties. Online learning offers a resource-efficient option to address this gap, yet evidence on the effectiveness and acceptability of online learning modules (OLMs) is limited. Methods: In this exploratory randomized controlled single post-test trial, medical students were assigned to either an OLM or an in-person lecture (IPL) on nutritional medicine (n = 91, no a priori sample size calculation performed). After course completion, students took a knowledge test and completed a questionnaire on their learning experience. Group differences were analyzed using permutation Welch t-tests, Wilcoxon–Mann–Whitney tests, or Fisher’s exact tests, depending on variable characteristics, with α = 0.05. Results: OLM students achieved significantly higher test scores than IPL students (mean difference: 2.4 points on a 0–40 scale), resulting in differences in grade classification (p < 0.05). OLM was further rated more favorably regarding content delivery, overall course evaluation, and exam preparation (all p < 0.05), while self-reported attention, concentration, and involvement did not differ between groups. Flexibility, time savings, and convenience were the most frequently reported advantages of OLM over IPL. Conclusions: This study suggests that OLM in nutritional medicine may be associated with higher test performance and more favorable student evaluations compared to IPL. These findings highlight the potential of online learning as a scalable, resource-efficient approach that may help address persistent gaps in nutritional medicine education. Building on this evidence, future work should examine how such modules can be optimally integrated into medical curricula to complement existing teaching structures. Full article

Rapid urbanization has significantly increased energy demand in buildings, which now represent nearly 30% of global energy use. In India, buildings are built across highly varied climatic conditions, from hot-dry and warm-humid to cold, high-altitude areas, making climate-responsive envelope design essential to enhance thermal performance. Among envelope components, roofs are the most exposed to solar and outdoor thermal loads, playing a key role in managing indoor heat transfer. This study offers a parametric analysis of climate-responsive roof design strategies for India’s five main climatic zones, using transient simulations and statistical evaluation. The effectiveness of insulation placement, insulation material and thickness, and external surface absorptivity was systematically assessed based on roof heat gain and heat loss. Results indicate that over-slab insulation can lower roof heat gain by approximately 15–35% compared to under-slab insulation in warm-humid, hot-dry, composite, and temperate zones. In comparison, under-slab insulation decreases heat loss by about 10% in colder areas. Among insulation materials, 50 mm polyurethane foam (U = 0.433 W/m²·K) consistently outperformed extruded polystyrene and expanded polystyrene, achieving 82–83% reductions in maximum heat gain in cooling-dominated climates and 89% reductions in heat loss in cold regions relative to uninsulated roofs. When combined with a white reflective surface finish (α = 0.26), the total heat transfer reduction increased further to 89–92%. Surface treatments alone cut heat gain by 37–51% in non-cold climates, highlighting their potential as cost-effective retrofit options. Statistical analysis confirmed that dry-bulb temperature is the primary climatic factor influencing roof heat transfer (R² = 0.86–0.98, p < 0.0001), while solar radiation had a weaker effect, especially in optimized roof systems. The findings emphasize the importance of climate-specific roof design and demonstrate that insulation U-value has a greater impact on thermal performance than surface absorptivity, although both are significant. This research offers practical, climate-adjusted guidance for architects, engineers, and policymakers to enhance the thermal performance of roofs in Indian buildings. It supports the development of more resilient, energy-efficient building envelopes. Full article

The emergency evacuation of visually impaired individuals during fire incidents presents critical challenges that require innovative technological solutions. While existing evacuation systems provide static route guidance, they fail to adapt dynamically to evolving fire conditions, blocked passages, or dangerous zones in buildings with multiple routes and exits. This paper presents a comprehensive implementation of a mobile application built with Flutter/Dart that addresses these limitations by enabling real-time, dynamic route computation based on live sensor data. The presented system operates in a decentralized manner, performing all critical computations on-device to ensure its functionality even when some parts of the building infrastructure fail. A dynamic route calculation modified Dijkstra’s algorithm was implemented on each user’s phone for guidance. If initial path adjustments are needed, they are computed from sensor data to evaluate fire evolution and other relevant factors, including the user’s current position and crowd congestion. An audio–visual interface was designed to provide navigation instructions and to help users follow safety routes efficiently. Field testing with visually impaired participants demonstrated significant improvements in evacuation efficiency, with shorter evacuation times than traditional static guidance approaches. The system architecture complies with international fire safety standards while maintaining user privacy through a no-tracking design philosophy. This work contributes to both theoretical advances in adaptive evacuation algorithms and practical insights for deploying assistive technologies in emergency scenarios. Full article

Wire–Laser Additive Manufacturing (WLAM) is a promising directed energy deposition technique for producing and repairing high-performance components with high material efficiency and strong metallurgical bonding. This study optimizes single-track Inconel 718 claddings deposited by WLAM on AISI 304L stainless steel and S355 structural steel substrates, focusing on the relationships between processing parameters, microstructure, post-deposition heat treatment, and mechanical performance. A systematic parametric assessment evaluated the influence of laser power, laser speed, wire feed rate, and shielding gas pressure on key quality metrics, including dilution, wettability, porosity, and cracking. Distinct optimal processing windows were identified for each substrate, reflecting their different thermal responses: for 304L, 8.5 kW laser power, 0.55 m/min laser speed, 5 m/min wire feed rate, and 2 bar argon; for S355, 9.6 kW laser power, 0.6 m/min laser speed, 4.9 m/min wire feed rate, and 4 bar argon. Post-deposition heat treatment markedly enhanced performance by dissolving Nb-rich interdendritic Laves phase and promoting γ′/γ″ precipitation. As a result, clad hardness increased from ≈225 HV 0.3 (as-built) to ≈412 H V0.3 after heat treatment (+84%). Tensile testing confirmed substantial strengthening, with yield strength increasing from 447 to 853 MPa (horizontal build) and from 488 to 960 MPa (vertical), while ultimate tensile strength rose from 824 to 1057 MPa (horizontal) and from 836 to 1090 MPa (vertical). Mechanical anisotropy remained significant, linked to columnar grain morphology and build orientation. Overall, the results provide practical process window and heat treatment guidelines for reliable industrial implementation of high-quality Inconel 718 claddings on steel substrates for demanding applications. Full article

Accelerating decarbonization in hot-climate buildings requires integrated retrofit strategies that address energy performance, environmental impact, thermal comfort, and economic feasibility within a unified decision framework. This study develops and validates a simulation-driven multi-criteria approach to evaluate retrofit packages across three representative ASHRAE hot sub-climates (1B, 2B, 2A). An academic building was modeled using DesignBuilder (Stroud, UK) and validated in accordance with ASHRAE Guidelines. The retrofit analysis integrates envelope enhancements (insulation and reflective coatings), glazing-integrated photovoltaics (GIPV), rooftop photovoltaics (RTPV), and a Dedicated Outdoor Air System (DOAS). The performance evaluation incorporates dynamically simulated energy consumption, operational CO₂ emissions, thermal comfort indicators (PMV and DCH), and techno-economic metrics (IRR, ROI, PBP). Weighting factors were derived from a structured stakeholder consultation to reflect context-sensitive sustainability priorities. The results indicate energy reductions of approximately 51–57% and carbon emission reductions of 40–53% across the examined zones, while discomfort hours decreased by roughly 42–46%. This demonstrates significant improvements in thermal comfort under integrated retrofit strategies, particularly with DOAS integration, highlighting the importance of ventilation-driven comfort enhancement. Economic feasibility was climate-dependent; envelope-focused solutions yielded high returns, while integrated strategies delivered balanced environmental and economic performance. The proposed framework enables systematic, climate-specific prioritization of retrofit alternatives and supports scalable, economically viable NZEB transitions in rapidly expanding hot-climate educational infrastructure. Full article