Search Results (193)

Energy used in residential buildings accounts for more than 22% of total global energy consumption. Therefore, energy efficiency has become a crucial factor in design and planning processes. A courtyard can be considered one of the most important passive design strategies that contribute to reducing energy consumption. However, due to the spread of multi-story buildings all over the world, this significant strategy has been ignored, hence the emergence of the skycourt. Limited studies have investigated the influence of morphological indicators of skycourts on energy consumption and carbon emissions regarding a hot–humid climate, which presents a research gap. Thus, this research examines the effect of skycourts in reducing energy consumption through an applied study using the Design Builder simulation program for multi-story residential buildings in a hot–humid climate such as Port Said city. The results indicate that skycourt spaces contribute significantly to reducing air temperature by up to 3 °C in the hottest summers and contribute to reducing energy consumption by rates ranging between 8 and 10% annually and reducing carbon emissions. This reflects the role of the skycourt as one of the most important passive design strategies in the current era that can contribute to saving energy consumption in the building sector. Finally, a matrix is conducted to help select the appropriate replacement for the skycourt of multi-story residential buildings in hot–humid climates, which reflects the novelty of the research. The proposed investigations and matrix can contribute to providing well-being, sustainable communities, and overcoming climate change effects, hence reflecting sustainability and the Sustainable Development Goals (SDGs), especially goals three, eleven, and thirteen. Full article

Rectangular aqueducts are critical building structures in large-scale water conveyance systems used worldwide. Liquid sloshing can produce hydrodynamic forces that threaten structural safety and long-term performance. This study analytically investigates the vibration characteristics of two-dimensional rectangular cantilever aqueduct systems while accounting for soil–structure interaction (SSI). To reduce sloshing and enhance the performance of the mechanical system, a bottom-mounted vertical baffle is proposed as a hydrodynamic damping solution. Through subdomain analysis, mathematical expressions for liquid potential fields are derived. The continuous liquid is represented through discrete mass–spring elements for dynamic analysis. Horizontal soil impedance is characterized by using Chebyshev orthogonal polynomial approximations with optimized least squares fitting techniques. A dynamic mechanical model for the soil–aqueduct–liquid–baffle coupling system is developed by using the substructure method. Convergence and comparative studies are conducted to validate the reliability of the proposed method. Between the current results and those reported previously, the variation in the first-order sloshing frequency is less than 1.10%. Parametric analyses evaluate how baffle size, baffle position, and soil properties influence sloshing behavior. The presentation of an equivalent analytical model is the novelty of this research. The results can provide the theoretical basis for optimizing anti-sloshing designs in hydraulic building structures, thereby supporting safer and more sustainable engineering practices. Full article

Exchangeability is a foundational concept in Bayesian statistics, crucial for ensuring the validity and generalizability of inferences from experimental data. This paper presents a theoretical and computational framework for understanding the role of exchangeability in the reliability of scientific conclusions, with specific reference to psychology, neuroimaging, and clinical trials. We build on de Finetti’s representation theorem to show how exchangeability enables using hierarchical Bayesian models, and we analyze how its violation can lead to interpretative errors and paradoxes, such as Simpson’s Paradox. In addition to theoretical discussion, we present practical strategies to evaluate and enforce exchangeability, including randomization, matching, stratification, and hierarchical modeling. We also introduce computational tools—such as the Shuffle Test and Stratified Bootstrap—to empirically test for exchangeability and detect latent structures in the data. The novelty of this work lies in unifying theoretical reasoning and empirical testing within a single framework that bridges de Finetti’s representation theorem and resampling-based diagnostics. By providing concrete tools to evaluate exchangeability prior to model fitting, the proposed approach introduces a pre-analysis verification step that strengthens the reliability and transparency of Bayesian inference. Our results emphasize that exchangeability is not merely a technical assumption, but a structural property that governs the coherence and informational integrity of the data. This framework provides both conceptual clarity and operational tools for researchers aiming to perform robust Bayesian inference in complex and heterogeneous datasets. Full article

Aligned with China’s “Dual Carbon” goals, this study addresses carbon emissions in the building sector. Existing research predominantly focuses on single-stage carbon emission assessment or separately examines the benefits of BIM applications and photovoltaic (PV) technology. There is a notable lack of studies that deeply integrate the BIM platform with dynamic assessment of building life cycle carbon emissions and PV carbon reduction strategies, particularly under the specific context of the hot-summer/cold-winter climate in Central China and a regional grid primarily reliant on thermal power. Moreover, localized and in-depth analyses targeting residential buildings in this region remain scarce. To address this gap, this study takes a residential building in Central China as a case study and establishes a BIM-based life cycle carbon emission assessment model to systematically quantify the carbon footprint across all stages. Results show total life cycle carbon emissions of 12600 tCO₂, with embodied carbon (4590 tCO₂, 36.6%) and the operational phase identified as the main emission sources. Through PV system integration and multi-scenario simulations, the study demonstrates significant carbon reduction potential: systems with 40–80 kW capacity can achieve annual carbon reductions ranging from 26 to 52 tCO₂. The 60 kW system shows the optimal balance with an annual reduction of 38.7 tCO₂ and a payback period of 3.53 years. The primary novelty of this work lies in its development of a dynamic BIM-LCA framework that enables real-time carbon footprint tracking, and the establishment of a first-of-its-kind quantitative model for PV strategy optimization under the specific climatic and grid conditions of Central China, providing a replicable pathway for region-specific decarbonization. Full article

Composite membranes are a hot topic in the field of membrane research. With the continuous progress of technology, its development has advanced from the application of simple copolymers to diversified material combinations. This Perspective examines why many composite membranes that excel in the lab struggle to deliver credible, durable performance at scale. Our aim is to connect four issues that are often treated in isolation—interfacial stability, manufacturability, data quality, and circular design—and to translate them into practical reporting and testing habits for the community. The novelty lies in treating “credibility” as the target function: we propose discipline-first guidelines that couple dynamic interfacial measurements with standardized long-run fouling and cleaning protocols, techno-economic and life-cycle reporting, and process-aware chemistry that fits existing hardware. We outline near-term applications in water treatment and resource recovery where drop-in formats and safer solvents already enable pilot-level operation. The future scope includes round-robin builds, FAIR data deposits, and durability metrics aligned with widely used standards for fouling potential and system benchmarking. Progress, we argue, will be measured less by first-day flux and more by what survives months of operation with uncertainty and costs on the page. Full article

This paper addresses the challenge of improving the thermal performance of building envelopes in hot arid climates by identifying optimal configurations for biomimetic opaque ventilated façade (OVF) designs. To overcome the complexity of parameter interactions in such systems, a multi-objective optimization framework is developed using computational fluid dynamics (CFD) simulations integrated with parametric modeling and machine learning surrogate models. A central contribution of this research is the application of machine learning-based surrogate models to predict CFD simulation outcomes with high accuracy. This predictive capability enables the rapid generation and evaluation of thousands of façade design alternatives without the need for full-scale CFD runs, significantly reducing computational effort and time. The proposed workflow establishes a direct connection between parameterized biomimetic geometries and thermal performance indicators, allowing for a comprehensive exploration of the design space through automated optimization. The optimization process relies on response surface modeling to approximate system behavior and evaluate design performance across multiple objectives. The final results reveal that the computationally optimized biomimetic façades achieved superior thermal performance compared to the initial bio-inspired design. To validate and extend the findings, additional simulations were carried out to evaluate the performance of selected designs under varying wind conditions and solar exposures. The larger wide mound configuration consistently performed best, offering a strong balance across the defined objectives. This solution was then applied to three-floor and five-floor commercial buildings in Riyadh, Saudi Arabia, where it showed a clear reduction in the average inner skin surface temperature of the OVF. The design proved suitable for construction with conventional methods and could be integrated into a range of architectural styles without major changes to the façade. These results reinforce the potential of combining biomimetic design strategies with computational optimization to develop high-performance façade systems for hot desert climates. The novelty of this work lies in combining biomimetic design principles with machine learning-driven optimization to systematically explore the design space and identify configurations that balance thermal efficiency with material economy. Full article

Post-industrial cities across Europe are undergoing profound transformation, where sustainable building design plays an increasingly strategic role in redefining urban identity and function. The transition toward sustainable urban environments requires innovative construction technologies and performance-driven standards. This study examines the role of sustainable building design in post-industrial urban regeneration, focusing on Katowice, Poland—a city undergoing significant socio-spatial and economic transformation. Through descriptive case studies of selected buildings, the research highlights how high-performance construction techniques, including advanced insulation, energy-efficient ventilation, and integrated daylighting, contribute to prestigious certifications while reducing energy demand for heating, cooling, and lighting. Beyond technical performance, the analyzed projects demonstrate how sustainable buildings can act as catalysts for post-industrial urban renewal, fostering social engagement, environmental responsibility, and architectural innovation. The novelty of this work lies in linking building-scale sustainability interventions with city-scale urban transformation dynamics, offering practical insights for similar post-industrial contexts in Central and Eastern Europe. This research provides the first comparative analysis of certified and non-certified sustainable buildings in the context of post-industrial regeneration in this region. The post-industrial revitalization of Katowice is largely driven by advancements in building energy systems, such as high-efficiency HVAC technologies and other sustainable solutions. The findings demonstrate that sustainable architecture can act as a tangible driver of social, economic, and spatial renewal, providing practical insights for post-industrial regeneration strategies across similar urban contexts. Full article

This study investigates the thermal resilience of naturally ventilated Lebanese residential buildings in the context of future climates, based on four climate zones: coastal (moderate and humid), low mountain (cool and seasonally variable), inland plateau (semi-arid with high summer heat), and high mountain (cold, with significant winter conditions). The aim of the study is to evaluate how passive envelope interventions can enhance indoor thermal resilience under five present and future work scenarios: TMY, SSP1-2.6 (2050 and 2080), and SSP5-8.5 (2050 and 2080). A baseline model was developed for typical building stock in each climate using EnergyPlus-23.2.0. The passive design parameters of window type, shading depth, and building orientation were systematically altered to analyze their effect on thermal comfort and building thermal resilience. Unlike previous studies that assessed either individual passive strategies or a single climate condition, this research combines multi-objective optimizations with overheating resilience metrics, by optimizing passive interventions using the GenOpt-3.1.0 and BESOS (Python-3.7.3 packages to minimize indoor overheating degree (IOD) and maximize climate change overheating resistivity (CCOR) index. Our findings indicate that optimized passive interventions, such as deep shading (0.6–1.0 m), low-e or bronze glazing, and southern orientations, can reduce overheating in all climate zones, reflecting a substantial improvement in thermal resilience. The novelty of this work lies in combining passive envelope optimization with future climate situations and a long-term overheating resilience index (CCOR) in the Mediterranean region. The results provide actionable suggestions for enhancing buildings’ resilience to climate change in Lebanon, thus informing sustainable design practice within the Eastern Mediterranean climate. Full article

This paper explores the application of the generalized beam theory (GBT) in analyzing the buckling behavior of isotropic and composite thin-walled beams with open cross-sections, both with and without branching. The composite beams are composed of orthotropic laminate layers arranged in arbitrary symmetrical orientations. By integrating GBT with the Ritz method and solving the associated generalized eigenvalue problem (GEP), an efficient and robust semi-analytical framework is developed to assess the stability of such isotropic and orthotropic members. The novelty of this work is not the GBT cross-sectional formulation itself, but its implementation at the beam level using a Ritz formulation leading to a generalized eigenvalue problem for the critical buckling loads and mode shapes that capture coupled global, local, and distortional modes in isotropic and orthotropic composite members. This makes the method suitable for early-stage design studies and parametric investigations, where many design variants (geometry, laminate lay-up, and aspect ratios) must be screened quickly without building large-scale high-fidelity finite element (FE) models for each case. The preliminary outcomes, when compared with those obtained using FE, confirm the approach’s effectiveness in evaluating buckling responses, particularly for open-section composite beams. Ultimately, the combined use of GBT and the Ritz method delivers both physical insight and computational efficiency, allowing engineers and researchers to address complex stability issues that were previously difficult to solve. In summary, the methodology can be correctly used for stability assessment of thin-walled composite members prone to interacting global–local–distortional buckling, especially when rapid, mechanistically transparent predictions are required rather than purely numerical FE output. Full article

The sustainable integration of Artificial Intelligence in Education (AIEd) in higher education hinges on students’ prolonged and meaningful adoption. Grounded in the Acceptance of AI Device Usage (AIDUA) framework, this study extends the model by incorporating novelty value and trust to investigate the determinants of students’ willingness to use AIEd Tools sustainably. Data from 400 university students in China were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that novelty value acts as a powerful catalyst, substantially boosting performance expectancy and diminishing effort expectancy. Furthermore, this study delineates a dual-pathway mechanism where performance and effort expectancies shape both emotions and trust, which in turn directly determine adoption intention—with emotion exhibiting the stronger influence. Theoretically, this research validates an extended AIDUA model, highlighting the critical roles of sustained innovation perception and cognitive-affective dual pathways. Practically, it advises higher education institutions to prioritize building robust trust through transparent practices and to design AIEd Tools that deliver lasting innovative value and positive learning experiences to foster sustainable adoption. Full article

As the core space for students’ daily living and learning, the quality of the indoor wind environment and air quality in dormitory buildings is particularly critical. However, existing studies often neglect natural ventilation optimization under local climatic conditions and the multidimensional evaluation of health benefits, leaving notable gaps in dormitory design. Under the Healthy China Initiative, the indoor wind environment in university dormitories directly impacts students’ health and learning efficiency. This study selects dormitory buildings in Xuzhou as the research object and employs ANSYS FLUENT 2020 software for computational fluid dynamics (CFD) simulations, combined with orthogonal experimental design methods, to systematically investigate and optimize the indoor wind environment with a focus on healthy ventilation standards. The evaluation focused on three key metrics—comfortable wind speed ratio, air age, and CO₂ concentration—considering the effects of building orientation, corridor width, and window geometry, and identifying the optimal parameter combination. After optimization based on the orthogonal experimental design, the proportion of comfortable wind speed zones increased to 44.6%, the mean air age decreased to 258 s, and CO₂ concentration stabilized at 613 ppm. These results demonstrate that the proposed optimization framework can effectively enhance indoor air renewal and pollutant removal, thereby improving both air quality and the health-related performance of dormitory spaces. The novelty of this study lies in integrating regional climate conditions with a coordinated CFD–orthogonal design approach. This enables precise optimization of dormitory ventilation performance and provides locally tailored, actionable evidence for advancing healthy campus design. Full article

Digital Twin (DT) technology is increasingly recognized as a key enabler for optimizing design, operation, and management across the built environment. While several reviews have addressed DTs in either building- or city-scale contexts, a comprehensive integration of these two perspectives remains limited. This paper provides an updated overview of DT developments from Building Digital Twins (BDTs) to Urban Digital Twins (UDTs), aiming to identify convergences, divergences, and future directions. The analysis is conducted through a review of recent literature and selected case studies, considering technical, environmental, economic, and social dimensions. Findings reveal that although BDTs and UDTs share common conceptual and technological foundations, scaling from single assets to complex urban systems introduces new challenges in terms of interoperability, governance, and data management. Furthermore, while environmental and economic benefits are relatively well-documented, social implications, such as citizen engagement, inclusivity, and behavioral modeling, remain underexplored. This review highlights the novelty of adopting a cross-scale perspective, emphasizing the importance of integrating technical and social aspects to fully exploit the potential of DTs for sustainable and resilient transitions. The study concludes by outlining research gaps and recommending strategies for developing more integrated, socially aware DT frameworks in both building and urban contexts. Full article

Rainfalls are the result of complex cloud microphysical processes. Trying to estimate their intensity and duration is a key task necessary for assessing precipitation magnitude. Across mountains, extreme rainfalls may cause several side effects on the ground, triggering severe geo-hydrological issues (floods and landslides) which impact people, human activities, buildings, and infrastructure. Therefore, having a tool able to reconstruct rainfall processes easily and understandably is advisable for non-expert stakeholders and researchers who deal with rainfall management. In this work, an evolution of the LUME (Linear Upslope Model Experiment), designed to simplify the study of the rainfall process, is presented. The main novelties of the new version, called LUME 2D, regard (1) the 2D domain extension, (2) the inclusion of warm-rain and cold-rain bulk-microphysical schemes (with snow and hail categories), and (3) the simulation of convective precipitations. The model was completely rewritten using Python (version 3.11) and was tested on a heavy rainfall event that occurred in Piedmont in April 2025. Using a 2D spatial and temporal interpolation of the radiosonde data, the model was able to reconstruct a realistic rainfall field of the event, reproducing rather accurately the rainfall intensity pattern. Applying the cold microphysics schemes, the snow and hail amounts were evaluated, while the rainfall intensity amplification due to the moist convection activation was detected within the results. The LUME 2D model has revealed itself to be an easy tool for carrying out further studies on intense rainfall events, improving understanding and highlighting their peculiarity in a straightforward way suitable for non-expert users. Full article

This paper presents a comprehensive sensitivity analysis of the pioneering real-world deployment of computer vision-enabled construction waste sorting in Finland, implemented by a leading provider of robotic recycling solutions. Building upon and extending the findings of prior field research, the study analyzes an industry flagship case to examine the financial feasibility of computer vision-enabled robotic sorting compared to conventional sorting. The sensitivity analysis covers cost parameters related to labor, wages, personnel training, machinery (including AI software, hardware, and associated components), and maintenance operations, as well as capital expenses. We further expand the existing cost model by integrating the net present value (NPV) of investments. The results indicate that the computer vision-enabled automated system (CVAS) achieves cost competitiveness over conventional sorting (CS) under conditions of higher labor-related costs, such as increased headcount, wages, and training expenses. For instance, when annual wages exceed EUR 20,980, CVAS becomes more cost-effective. Conversely, CS retains cost advantages in scenarios dominated by higher machinery and maintenance costs or extremely elevated discount rates. For example, when the average machinery cost surpasses EUR 512,000 per unit, CS demonstrates greater economic viability. The novelty of this work arises from the use of a pioneering real-world case study and the improvements offered to a comprehensive comparative cost model for CVAS and CS, and furthermore from clarification of the impact of key cost variables on solution (CVAS or CS) selection. Full article

With growing urban populations and rapid technological advancement, major cities worldwide are facing pressing challenges from surging energy demands. Interestingly, substantial unused space within residential buildings offers potential for installing renewable energy systems coupled with energy storage. This study innovatively proposes a grid-connected photovoltaic (PV) system integrated with pumped hydro storage (PHS) and battery storage for residential applications. A novel optimization algorithm is employed to achieve techno-economic optimization of the hybrid system. The results indicate a remarkably short payback period of about 5 years, significantly outperforming previous studies. Additionally, a threshold is introduced to activate pumping and water storage during off-peak nighttime electricity hours, strategically directing surplus power to either the pump or battery according to system operation principles. This nighttime water storage strategy not only promises considerable cost savings for residents, but also helps to mitigate grid stress under time-of-use pricing schemes. Overall, this study demonstrates that, through optimized system sizing, costs can be substantially reduced. Importantly, with the nighttime storage strategy, the payback period can be shortened even further, underscoring the novelty and practical relevance of this research. Full article