• A residential photovoltaic energy supply system is modelled and analysed. • Hydrogen and battery storages are used for energy balancing. • Fuel cell waste heat is integrated with a heat pump and thermal energy storage. • Optimal sizing of system components determined by modelling and simulation. • Simple yet effective energy management algorithm is provided. This paper analyses a self-sustained, green electricity supply system for residential buildings based on photovoltaic generation supported by battery and hydrogen energy storage. Photovoltaic power generation depends on season, time of day, and weather, and is inherently out of sync with residential electricity demand. This imbalance can be addressed through short-term storage using batteries and long-term storage using a hydrogen system composed of an electrolyser, hydrogen storage, and a fuel cell. However, the high cost of technological equipment results in high annual costs of electricity and heat supply, making optimal system design and operation essential. To address this challenge, a techno-economic simulation model of the entire system is developed to support optimal component sizing and process control. Compared to related studies, the proposed approach employs simple and transparent techno-economic models, enabling adaptability to specific use cases. A power management algorithm is introduced to prioritise battery-based daily balancing and hydrogen-based seasonal balancing. The simulation study provides full-year energy flow profiles, detailed annual energy balance results, and a breakdown of electricity supply costs. Thermal integration of the fuel cell and heat pump is also considered to improve overall system efficiency. Results indicate that, with appropriate sizing and control, the annual electricity supply cost is approximately 4300 EUR for a state-of-the-art single-family house, which may be competitive in regions with high electricity and transmission costs.

• Fit-for-purpose simulation model developed for PVT-heat pump systems in buildings • Early-stage integration of control strategies leads to different design decisions • Including control strategies shifted radiator, PV, and insulation design decisions • Integrated building-energy system approaches are needed over isolated studies The adoption of renewable energy technologies in buildings is rising. While the performance of such systems heavily depends on the use of suitable control strategies, most design processes tend to treat controls as an afterthought. Especially in parametric studies that compare different system configurations in early design stages, simplified control approaches are used. The separation between design and operation risks discarding promising solutions, as simplified controls used during design often misrepresent how these systems can potentially perform in operation. This study investigates the impact of integrating tailored control strategies in the early design stage of residential energy systems, focusing on a Dutch terraced house and considering the inclusion of photovoltaic-thermal panels, a heat pump, and thermal storage during renovation. Through parametric simulations using TRNSYS and Python, five control strategies are evaluated, that vary in their approach to improving self-consumption of on-site PV electricity. The results demonstrate that control strategies have the ability to shift demand to more favorable periods, thereby influencing operational performance and hence design decisions. Systems with superior controls showed up to 35% reduction in annual operational emissions for heating compared to baseline controls. In some cases, solutions dismissed under simplified control assumptions performed competitively when controls that aligned with the systems’ operational principles were applied. The study shows that a control-aware design process that treats control strategies as integral design parameters, rather than post-design operational measures, reduces the risk of misrepresenting a system’s actual potential, and thereby supports better-informed decisions.

Understanding the nuances of climate change on buildings in desert areas is a timely topic with several socioeconomic implications. This study quantifies the impacts of future climate variability and extreme events on the optimal design of renewable energy systems (RES) for buildings in Saudi Arabia. A comprehensive framework integrating multi-model climate projections, extreme event analysis, and stochastic optimization is developed to evaluate system reliability and economic performance under future climate uncertainty. Hourly downscaled climate data spanning 2025–2099 across multiple Shared Socioeconomic Pathways (SSP) are considered, and stochastic optimization is used to determine RES configurations that minimize life cycle cost (LCC) across all scenarios. Analyses are conducted at hourly resolution over three future 25-year periods: 2025–2049, 2050–2074, and 2075–2099. Results indicate that differences between climate scenarios become more pronounced in the late-century period (2075–2099), leading to increased sensitivity of optimal RES design to climate conditions. The stochastic design ensures higher operational reliability than systems optimized solely for a high-emission scenario, with a 3.1% increase in LCC. Relative to the sustainable scenario, the high-emission scenario requires larger RES capacities, particularly in battery storage, resulting in a 20% higher LCC. Accounting for extreme events from an additional 24 scenarios from multiple climate models increases the LCC by 31.7%, highlighting the cost of resilience in an uncertain future climate. • Climate change affects building energy demand and renewable supply in desert areas. • High-emission pathways increase life cycle costs by 20% compared to sustainable ones. • A stochastic-based design improves system reliability with only a 3.1% cost increase. • Extreme weather events across 24 scenarios increase system costs by 31.7% • The best renewable system design is highly sensitive to late-century climate shifts.

A novel boltless interlocking steel modular building system: Design, construction and mechanical performance

Analysis of the economic viability of photovoltaic self consumption system for a public building in Türkiye

In-depth analysis of next-generation hybrid PV–SOFC power system for nearly-zero energy building using an advanced thermodynamic and multi-objective optimization approach

A self-powered wearable structured foam built-in electrode triboelectric sensor system for fall risk detection and vibration hazard monitoring of construction workers

• Four real-life neighbourhood-scale demonstration projects were analysed. • Extensive monitoring systems were designed and implemented. • Plus energy balances annually and high IEQ were achieved. • Cost comparisons of plus energy to NZEB were between 3.3% to 6.5% cost increase. • The most tenant-focused project also achieved the highest social performance. Urban neighbourhoods play a pivotal role towards achieving climate neutrality. This study presents key findings from the operational phase of four sustainable plus energy neighbourhoods (SPEN). The neighbourhoods are real-life projects located in Spain, the Netherlands, Austria, and Norway. Each demonstration neighbourhood incorporates efficient building systems, renewable energy technologies, and advanced control strategies tailored to local climate and contextual conditions. Three of the neighbourhoods encompass new residential buildings, while one is a combination of renovation and new construction. The operational performance of the neighbourhoods was assessed using monitored data, occupant surveys, and a multi-dimensional evaluation framework covering energy performance, indoor environmental quality (IEQ), economics, and social impacts. The results showed that two of the neighbourhoods achieved positive energy and greenhouse gas emission balances, while the two others showed very high energy performance, although not reaching the overall balance. IEQ assessments revealed satisfactory conditions, albeit with climate-dependent variations. Post-occupancy evaluations showed high energy awareness, alongside positive perceptions of affordability, safety, and health benefits. The economic evaluations highlighted notable differences in financial returns. Aggregated indicators showed that the SPENs achieved energy-environmental scores of 43-88%, consistently high IEQ performance, economic scores of 50-96%, and social scores of 74-95%, while highlighting electricity price volatility and feed-in tariffs as key sources of economic uncertainty. The study draws on a harmonised monitoring evaluation of four neighbourhoods, enabling one of the most comprehensive and detailed cross-comparative evaluations of SPEN performance to date, and underscores the benefits and challenges associated with scaling SPENs across diverse climatic contexts.

Development of an optimal multi-agent reinforcement learning control method for an integrated PVT–heat pump system

• Physiological, behavioral, and perceptual adaptations occur during anomalies • Higher mean and local skin temperatures reveal physiological responses to heat • Clothing adjustments and increased airspeed show behavioral coping strategies • Modelling choices critically shift neutral SET interpretations • Occupant control is key to mixed-mode building climate resilience Climate anomalies linked to a changing climate increasingly challenge buildings to maintain comfortable indoor environments without excessive energy use. This study assessed physiological, behavioral, and perceptual responses of occupants in a mixed-mode office during an anomalous year in a subtropical region, which caused hotter-than-average conditions in typically mild seasons. In a year-long living-lab experiment, indoor environmental variables, HVAC use, clothing insulation, thermal perceptions, and physiological signals of 21 participants (12 females, 9 males) were monitored to examine adaptations to these anomalous conditions. Hotter-than-average days elicited higher mean and localized skin temperatures, particularly during outdoor exposure during lunch breaks. Occupants also adopted behavioral strategies, mainly reducing clothing insulation and adjusting building systems to reach higher air velocity levels. Thermal perceptions varied under hotter outdoor conditions; however, the magnitude of this shift depended on the analytical direction adopted in the regression modeling. When thermal sensation was treated as the response variable to indoor conditions, the analysis indicated a notable reduction in neutral SET (-1.12°C) during hotter days, whereas treating indoor conditions as the response to thermal sensation resulted in a minimal shift (+0.12°C). Overall, the findings suggest that buildings can maintain comfortable conditions under climate anomalies when occupants are provided with meaningful adaptive opportunities. Incorporating building interfaces that enable adaptive opportunities, promoting flexible clothing adjustments, and applying adaptive comfort principles are essential for enhancing both building and human resilience in a warming and increasingly variable climate.

Performance characterization and optimization of thermally activated building systems with hybrid geothermal-solar energy technologies in net/nearly zero energy buildings

The structural design of low- to mid-rise residential buildings in urban areas requires reliable assessment of gravity and lateral load effects, appropriate member sizing, and code-compliant detailing of reinforced concrete elements. This paper presents the analysis and design of a G+4 reinforced concrete residential building modelled in ETABS. The building was idealized as a reinforced concrete framed structure with five storeys, 3.0 m storey height, M30 concrete, Fe500 reinforcement, 150 mm slab thickness, 400 mm x 500 mm beams, and square and rectangular columns of 450 mm x 450 mm and 350 mm x 450 mm, respectively. Loads were assigned in accordance with Indian code provisions for dead, imposed and wind loads, and the frame was analysed for displacement, shear force, bending moment and axial force response. The results indicate that the adopted member sizes are structurally adequate for the considered G+4 residential configuration under the applied load cases, subject to final validation using project-specific soil investigation data, seismic parameters and detailed construction drawings. The study demonstrates the usefulness of ETABS as an integrated modelling, analysis and design environment for reinforced concrete building systems, while emphasizing that software results must be supported by engineering judgement, code checks and quality control during execution.

Multi-element geochemical data derived from systematic surveys from a variety of media within a geospatial continuum contain information that provides insight into processes that reflect mineralogy, paragenesis, alteration and economic mineralization. The relationships of the elements and corresponding attributes using a range of data analytical methods, including univariate and multivariate statistical methods along with machine learning, provide the framework for building knowledge from which extended methods of artificial intelligence can enhance model building and mineral systems discovery. This contribution provides the elements for the design of workflows that meet the requirements of enhancing knowledge from geochemical and mineralogical surveys for the purposes of geologic mapping, mineral resource prediction, or environmental management. Further, it outlines a framework for a systematic evaluation of geochemical data plus attributes that enable the discovery of processes from which models can be constructed and tested using machine learning methods. Methods are described for “process discovery” followed by additional methods for “process validation/prediction”. Six case studies are presented that highlight different approaches to the discovery of processes that assist in mineral exploration and geologic mapping at various scales. The workflow includes caveats and flags potential issues or limitations on what can be discovered and validated.

A metaheuristic–machine learning framework for modeling and improving the thermal behavior of bio-based wall panel systems in residential buildings

Thermally activated building systems offer significant potential for low-carbon building operation and energy flexibility by using building mass as distributed thermal storage. Recent advances in data-driven control, machine learning, and digital building infrastructure have expanded their technical capabilities. However, practical deployment remains limited. This paper addresses that gap through a scoping review of the literature on data-driven thermally activated building systems, with a focus on the conditions required for implementation, integration, and sustained operation in practice. The review examines publication patterns, realization stages, dominant realization pathways, and recurring enablers and barriers across the field. The results show that the literature is concentrated in conceptual, simulation, and pilot-stage studies, while evidence of long-term operation in occupied buildings remains scarce and evidence of scalable or transferable realization in the reviewed TABS literature remains limited. The paper proposes five realization conditions for deployment as an interpretive synthesis of the reviewed literature: operational observability, deployable model architecture, embedded digital integration, operational acceptability, and organizational handover capacity. The review reframes data-driven thermally activated building systems as a realization challenge rather than only a control problem and provides a structured analytical framework to support future research and deployment-oriented evaluation in energy informatics.

Integrating direct air carbon capture (DAC) into buildings offers a promising pathway for reducing atmospheric CO2, yet the role of architectural design in enhancing passive carbon-capture performance remains underexplored. This study presents a computational framework developed to optimize architectural design and enclosure geometry for enhanced passive airflow, using mass-flow rate as a proxy for the comparative assessment of carbon absorption potential. Implemented within Rhino3D and Grasshopper using Ladybug and Eddy3D, the workflow integrates weather data and CFD simulation to compute segmented mass-flow rates through stacked capture trays. The framework simplifies traditionally complex CFD processes by introducing a custom segmented mass-flow calculation approach that enables comparative performance assessment during early-stage design. Results confirm the validity of the proposed workflow, revealing that façade rotation can modify total mass flow by up to 96.5%; seasonal wind variability can cause airflow to range from approximately 8.5 kg/s in January to 169.5 kg/s in May in Seattle. Spatial configuration can alter airflow by up to an order of magnitude and introduce substantial spatial heterogeneity within capture zones. This research establishes a performance-driven design framework that enables architectural geometry to actively enhance passive carbon-capture integration, positioning building design as a measurable contributor to climate mitigation strategies. Ultimately, this work bridges architectural design and carbon-capture engineering, supporting interdisciplinary approaches to scalable, climate-responsive building systems.

The construction sector is showing renewed interest in prefabrication, particularly in modular construction and building systems based on precast walls. This is mainly due to the current lack of workmanship and construction time. Prefabrication allows for faster construction and more efficient on-site assembly without compromising structural performance. In this context, an innovative eco-efficient precast wall system was developed, combining ultra-high durability concrete with low-cement lightweight aggregates concrete. This paper presents a study addressing the development of novel dry-connections, designed to facilitate the assembly and disassembly of the referenced precast walls, promoting this way the potential reuse of structural elements. The connections were designed to avoid on-site casting, thus significantly reducing workmanship needs. Three new bolted connections were tested for vertical joints between precast walls, considering the tolerances required for the assembly process and the stiffness, strength and ductility necessary for the structural performance. Monotonic tensile tests were conducted to evaluate their structural behaviour. Results show that all connections can effectively transfer a concentrated tensile load to the concrete wall, with limited cracking under service conditions. The main conclusions are presented, together with recommendations for quality control during production to ensure reliable system performance.

The integration of ceiling fans with radiant systems remains underexplored despite their potential to address cooling capacity limitations. This study adopts a two-step approach to quantify the impact of elevated air movement on thermally activated building systems (TABS). First, we used OpenFOAM to calculate convective heat transfer coefficients under varying airflows, air-to-surface temperature differences, and zone sizes. These coefficients also apply to ceiling fans in buildings without radiant systems. Second, we implemented these coefficients in EnergyPlus to evaluate key radiant design parameters. Scenario 1 results show median steady-state cooling heat transfer rates increase of up to 47% relative to the no-fan cases when operative temperature is held constant. Scenario 2 demonstrates a median cooling effect of up to 4.8 K under fixed capacity, reflecting both lower zone temperatures and direct air movement on occupants. Overall, TABS-fans systems offer a scalable strategy to enhance comfort, increase capacity, and reduce energy demand. Highlights We use CFD to develop simplified surface convective heat transfer models that account for air movement with ceiling fans on room surfaces. We use simplified surface convective models in EnergyPlus to evaluate radiant system performance with ceiling fans. Ceiling fans increase the zone’s steady-state cooling heat transfer rate by a median of 47% at the highest fan speeds. Ceiling fans have a median cooling effect of up to 4.8 K at the highest fan speeds. A radiant and ceiling fan couple system has the potential to decrease HVAC energy use while maintaining occupant thermal comfort.

Wastewater heat recovery has emerged as a vital strategy for building energy conservation, due to its significant potential and the inherent thermal stability of sewage as a heat source. Enhancing synergy between such waste heat and other clean energy sources is a key research focus. This study developed a solar-assisted sewage-source coupled heating system for a Chinese university dormitory and established a multiobjective optimization framework integrating economic, environmental, and energy efficiency indicators via a combined weighting approach of the Analytic Hierarchy Process and Entropy Weight Method. Optimization was conducted using the Hooke–Jeeves algorithm, Particle Swarm Optimization algorithm, and the Hooke–Jeeves–Particle Swarm Optimization hybrid algorithm (shorten as HJ–PSO), with subsequent comparative performance analysis. The HJ–PSO hybrid performed best: 24% lower operating costs, a 4.8-year shorter dynamic payback period, 26.35% fewer carbon dioxide emissions, 38.65% lower overall energy consumption, and an 11.18% higher system coefficient of performance. Supported by relevant policies, the system is low-carbon and economically viable, enabling grid peak shaving. This research provides theoretical and engineering references for renewable energy heating systems.

Abstract The rapid expansion of urban infrastructure has significantly increased the demand for efficient and reliable water supply systems in multi-storey buildings. This study, titled “Study and Design Analysis of Water Supply System in Multi-Storey Building,” presents a comprehensive evaluation of hydraulic performance and system design to ensure adequate water distribution across all floors. The research focuses on estimating water demand based on occupancy and standard per capita consumption, followed by the systematic design of key components such as overhead storage tanks, pipeline networks, and pumping arrangements. Hydraulic analysis is carried out using fundamental engineering principles, including pressure head evaluation, flow characteristics, and frictional loss assessment through the Darcy–Weisbach approach. A detailed investigation of pressure variation at different elevations is performed to ensure sufficient and uniform water supply without excessive pressure that may lead to system failure. The study also examines the influence of pipe diameter, velocity, and friction losses on overall system efficiency. Results indicate that improper selection of design parameters can lead to significant energy losses and inadequate supply at higher levels. The findings of this study contribute to the development of a safe, cost-effective, and optimized water distribution system for multi-storey buildings. The proposed approach not only enhances hydraulic efficiency but also supports sustainable urban infrastructure development by minimizing water losses and improving system reliability. Keywords: Hydraulic Analysis, Pressure Distribution, Head Loss, Darcy–Weisbach Equation, Pipe Flow, Friction Loss, Water Demand Estimation, Overhead Tank Design, Flow Characteristics, Sustainable Water Management.