Abstract Modular construction offers faster and safer manufacturing, better predictability to completion time, superior quality, less workers on site, less resource wastage, and a more environmentally friendly solution than the conventional construction process. Despite having several advantages of modular construction, the private sector still relies heavily on the traditional on-site construction method. To understand the scientific reason behind this situation, this paper critically reviews the recent developments, performances, challenges and future opportunities of modular buildings. Modular constructions are extensively used for low-rise buildings and further attracts strong interest for multi-storey building structures. Prefabricated modules demonstrated satisfactory performance under static, dynamic impact, cyclic, seismic, blast, fire and long-term sustained loading, and offer environmental, economic and social benefits. The acceptance and application of modular construction will further spread with the development of design guidelines, more skilled workers, addressing handing and transportation difficulties, and the development of novel interlocking connections between modules. Recently, composite materials demonstrated high potential to manufacture prefabricated building modules. In Australia, it is expected that modular construction will increase from the current stage of 3% to 5–10% by year 2030.
Anna Carolina Menezes, A. Cripps, D. Bouchlaghem
et al.
With the increasing demand for more energy efficient buildings, the construction industry is faced with the challenge to ensure that the energy performance predicted during the design stage is achieved once a building is in use. There is, however, significant evidence to suggest that buildings are not performing as well as expected and initiatives such as PROBE and CarbonBuzz aim to illustrate the extent of this so called ‘performance gap’. This paper discusses the underlying causes of discrepancies between energy modelling predictions and in-use performance of occupied buildings (after the twelve month liability period). Many of the causal factors relate to the use of unrealistic input parameters regarding occupancy behaviour and facilities management in building energy models. In turn, this is associated with the lack of feedback to designers once a building has been constructed and occupied.
Prefabricated concrete structures (PCS), while recognized as a greener alternative to conventional cast-in-place methods, still entail significant resource and energy consumption. This study employs a life cycle assessment to quantify the carbon emission intensity and reduction potential of a typical PCS. The results indicate a total lifecycle carbon emission intensity of 1135.22 kgCO2e/m2, with the material production stage being the largest contributor at 419.13 kgCO2e/m2. Scenario analysis reveals that promoting green building materials, such as recycled steel and concrete, can achieve a maximum emission reduction of 11.12 % during the construction process. Under an optimistic scenario, this translates to a cumulative reduction potential of 94.33 million tCO2e in Shenzhen from 2025 to 2035. These findings provide a critical quantitative benchmark and a viable pathway for decarbonizing the building sector, offering valuable insights for policymakers and stakeholders in promoting prefabricated construction.
Loess, predominantly distributed in arid and semi-arid regions of central and western China, exhibits low shear strength and structural instability, rendering it prone to geological hazards such as landslides and collapses, which pose significant threats to local infrastructure and safety. This study evaluated the urease activity of soybean and sword bean at different temperatures to screen the optimal enzyme source for enzyme-induced carbonate precipitation (EICP). Methods including single EICP, EICP combined with nano-SiO<sub>2</sub>, and EICP combined with both nano-SiO<sub>2</sub> and soil stabilizer (SS) were adopted to enhance the surface strength of loess. The results showed that the EICP technique significantly improved the surface strength of loess, especially with the addition of nano-SiO<sub>2</sub> and soil stabilizer. This study confirmed that using sword bean urease treated at −20 °C for 24 h in combination with 1.5% nano-SiO<sub>2</sub> was both cost-effective and efficient in reinforcement. The incorporation of 5% soil stabilizer further enhanced the surface strength, and the accuracy was further verified by combining the results of SEM and XRD. Future research will focus on optimizing the material ratio to maximize the improvement of surface strength, providing an economical and feasible solution for rapid loess solidification, and evaluating the long-term durability under cyclic wet and dry conditions.
With the continual expansion of global urbanization and population growth, urban energy demands have intensified, and anthropogenic activities have precipitated profound shifts in the global climate. These climatic changes directly alter urban environmental conditions, which in turn exert indirect effects on human physiological function. Consequently, the comfort of outdoor community environments has emerged as a critical metric for assessing the quality of human habitation. Although existing studies have focused on improving singular environmental factors—such as wind or thermal comfort—they often lack an integrated, multi-factor coupling mechanism, and adaptive strategy systems tailored to hot-summer, cold-winter regions remain underdeveloped. This study examines the Minhe Community in Qian’an City to develop a performance evaluation framework for outdoor spaces grounded in subjective comfort and to close the loop from theoretical formulation to empirical validation via an interdisciplinary approach. We first synthesized 25 environmental factors across eight categories—including wind, thermal, and lighting parameters—and applied the Analytic Hierarchy Process (AHP) to establish factor weights, thereby constructing a comprehensive model that encompasses both physiological and psychological requirements. Field surveys, meteorological data collection, and ENVI-met (V5.1.1) microclimate simulations revealed pronounced issues in the community’s wind distribution, thermal comfort, and acoustic environment. In response, we proposed adaptive interventions—such as stratified vegetation design and permeable pavement installations—and validated their efficacy through further simulation. Post-optimization, the community’s overall comfort score increased from 4.64 to 5.62, corresponding to an efficiency improvement of 21.3%. The innovative contributions of this research are threefold: (1) transcending the limitations of single-factor analyses by establishing a multi-dimensional, coupled evaluation framework; (2) integrating AHP with ENVI-met simulation to realize a fully quantified “evaluation–simulation–optimization” workflow; and (3) proposing adaptive strategies with broad applicability for the retrofit of communities in hot-summer, cold-winter climates, thereby offering a practical technical pathway for urban microclimate enhancement.
This paper discusses several repair design and maintenance practices to produce durable and sustainable concrete structures. Emphasis is given in the assessment and evaluation of deteriorated concrete structures. The evaluation and repair principles are demonstrated through case studies of deteriorated concrete structures. Concrete preservation is an important consideration to sustain both economic and natural resources. Concrete, like almost any other building material, is susceptible to deterioration during its service life. Repairing and extending the service life of concrete structures contributes to overall sustainability of materials and resources. Assessment and repair decisions should be based on a thorough evaluation consisting of visual inspection, nondestructive Testing (NDT), laboratory testing, and a service life evaluation analysis.
With the rapid development of urban rail transit, the impact of shield tunneling on existing pipelines is increasing. To protect pipeline safety, this research focuses on the complex pipelines in the Shaluo shield tunneling section, utilizing FLAC3D numerical simulation software to investigate the deformation characteristics of cast iron pipelines during shield construction. Additionally, it quantifies the influence of pipeline materials on deformation and establishes the pipeline safety risk grading system. Safety assessment of pipelines based on the research. The research indicates that (1) The deformation difference between the tops of the pressure and pressureless pipeline is less than 1 mm, suggesting that pipeline deformation is minimally influenced by pressure. The deformation is the largest at the entrance and gradually decreases along the direction of excavation, indicating that the deformation has an obvious hysteresis effect. (2) The threefold variation in maximum deformation among pipelines of different materials during shield tunneling indicates the high sensitivity of pipeline material properties to shield construction processes. (3) By analyzing and discussing the literature and local norms, the deformation value of the pipeline is taken as the evaluation index. And the pipeline assessment system is established. (4) Cast iron pipelines at the start of the shield have the highest safety, and concrete pipelines at the beginning of the shield are the lowest.
Decision-making in building energy systems critically depends on the predictive accuracy of relevant time-series models. In scenarios lacking extensive data from a target building, foundation models (FMs) represent a promising technology that can leverage prior knowledge from vast and diverse pre-training datasets to construct accurate probabilistic predictors for use in decision-making tools. This paper investigates the applicability and fine-tuning strategies of time-series foundation models (TSFMs) in building energy forecasting. We analyze both full fine-tuning and parameter-efficient fine-tuning approaches, particularly low-rank adaptation (LoRA), by using real-world data from a commercial net-zero energy building to capture signals such as room occupancy, carbon emissions, plug loads, and HVAC energy consumption. Our analysis reveals that the zero-shot predictive performance of TSFMs is generally suboptimal. To address this shortcoming, we demonstrate that employing either full fine-tuning or parameter-efficient fine-tuning significantly enhances forecasting accuracy, even with limited historical data. Notably, fine-tuning with low-rank adaptation (LoRA) substantially reduces computational costs without sacrificing accuracy. Furthermore, fine-tuned TSFMs consistently outperform state-of-the-art deep forecasting models (e.g., temporal fusion transformers) in accuracy, robustness, and generalization across varying building zones and seasonal conditions. These results underline the efficacy of TSFMs for practical, data-constrained building energy management systems, enabling improved decision-making in pursuit of energy efficiency and sustainability.
We give direct, geometric constructions for nontrivial root elations for rank $2$ residues of higher rank buildings $Δ$ of type $\mathsf{B_n}, \mathsf{C_n}$ and $\mathsf{H_m}$ for $n \in \mathbb{N}$ and $m \in \{3,4\}$. We show that we can extend these to the ambient building in the case that $Δ$ has type $\mathsf{B_n}$ or $\mathsf{C_n}$. With that, we obtain a different proof for the fact that buildings of type $\mathsf{B_n}$ and $\mathsf{C_n}$ are Moufang. This geometric approach enables us to gain more insight into the root groups associated to these buildings and we obtain new results; Namely, that certain root elations generically fix more points than we previously knew and that every root elation in each point residual can be written as an even self-projectivity. Concerning $\mathsf{H_m}$, we will be able to see in a novel way why thick, spherical buildings of type $\mathsf{H_m}$ cannot exist. Altogther, this provides an alternative proof for the fact that all thick, irreducible, spherical buildings $Δ$ of rank 3 have the Moufang property.
Benedikt Kantz, Stefan Lengauer, Peter Waldert
et al.
Knowledge Graphs (KGs) contain vast amounts of linked resources that encode knowledge in various domains, which can be queried and searched for using specialized languages like SPARQL, a query language developed to query KGs. Existing visual query builders enable non-expert users to construct SPARQL queries and utilize the knowledge contained in these graphs. Query building is, however, an iterative and, often, visual process where the question of the user can change and differ throughout the process, especially for explorative search. Our visual querying interface communicates these change between iterative steps in the query building process using graph differences to contrast the changes and the evolution in the graph query. We also enable users to formulate their evolving information needs using a natural language interface directly integrated into the difference query view. We, furthermore, communicate the change in results in the result view by contrasting the differences in both result distribution and individual instances of the prototype graph and demonstrate the system's applicability through case studies on different ontologies and usage scenarios, illustrating how our system fosters, both, data exploration and analysis of domain-specific graphs.