Developments in the Built Environment最新文献

Calcium silicate cement (CSC) is a non-hydraulic cement that solidifies in moist conditions with CO₂ curing. To contribute to the standardization of CSC, the material has been produced locally, and the microstructural characterization of the carbonation products of CSC samples with water-to-cement (W/C) ratios of 0.35, 0.4 and 0.45 at 10% CO₂ concentration using XRD, ²⁹Si MAS NMR, ¹H NMR and compressive strength tests. CSC primarily consists of Q⁰, Q¹ and Q² silica species, among which β-C₂S and β-CS exhibit higher reactivity to CO₂ curing. The obtained results confirm the presence of calcite and amorphous phases as the main carbonation products, which become more prominent with an elapse in CO₂ curing. The CO₂ uptake of CSC samples with a W/C ratio of 0.45 was 8 g per 100 g binder, although a higher W/C ratio induced a relatively larger capillary and gel pore width, consequently reducing the strength of CSC.

Due to infrastructural development activities, the need for the construction materials increases, because of which most of the naturally available natural resources are over exploited and the cost of construction materials are increased. Therefore, the present study focuses on the use of industrial by-products for the development of concrete and examines the physical, mechanical, durability and sustainable performances. Fly ash (FA) and ground granulated blast furnace slag (GGBS) were employed as binder medium and the industrial effluent sodium silicate waste was used to replace the conventional river sand in the geopolymer concrete (GPC). GGBS was employed as source material for the production of concrete to increase the polymerization reaction process and further, the developed concrete was cured in the ambient condition of temperature range 27 ± 2 °C, in the laboratory. The concentration of the sodium hydroxide (NaOH) in the present study was 12M, and the alkaline solution ratio was 1:1.5. During the production process of sodium silicate solution in the factory, the residue left at the bottom of the boiling hopper were dumped as waste in the open land. GPC gains its strength based on the alumina and silica in the source material and alkaline activator solution, therefore, this industrial waste residue was identified as potential alternative to conventional river sand. The concrete with and without effluent was subjected to two types of acid (Sulfuric acid (H₂SO₄) and Hydrochloric acid (HCl)) and further to examine the performance of concrete under marine condition, two types of salt solutions, namely, magnesium sulfate (MgSO₄) and Sodium Chloride (NaCl) were used, the concentration of acids employed in the present study is 2% and the marine solution is 3.5%. Increase in the proportion of effluent from 0% to 100% decreases the slump value of the concrete. Contrastingly, increasing the proportion of effluent increases the strength of GPC after 28-d of room temperature curing. To examine the performance of the concrete under acidic and marine conditions, average of three concrete specimens were employed and the duration of exposure was considered in the present study starts from 28-d and continues till 360-d. After exposing to acidic environment, mass loss, strength loss and surface modification were examined; the loss in mass was found to be 1.5–3% and the strength loss was found to be 35%–45%. In the case of salt solution exposure, the loss in mass was seen to be 1–2% and whereas in the case of strength, the loss was found to be 30%–42%, respectively. Further, the sustainability aspects of the concrete with industrial effluents were examined in detail; focusing on economic value of the concrete, carbon emission and energy demand during the production of concrete.

The most widely used design approaches today for improving the robustness of buildings rely on improving continuity within the structural system to ensure that loads supported by failed components can be redistributed to the rest of the system. Although this is effective for small initial failures, it can increase the risk of disproportionate collapse after larger initial failures due to collapsing elements pulling down parts of the structure that would otherwise be unaffected. This form of continuity-enabled collapse propagation can be avoided by dividing a structure into different segments. However, completely separating parts of a building results in lower performance under operational conditions, against lateral loads, and after small initial failures. In fact, the advantages of both continuity and segmentation can be combined through a fuse-based segmentation approach in which predefined segment borders ensure connectivity after small initial failures but separate to isolate collapse after larger initial failures. To ensure that this approach is used effectively to improve the robustness of building structures, a design framework is proposed in this article to systematically consider relevant structural and geometric criteria in order to define suitable segmentation configurations for reinforced concrete and steel framed building structures. An application to a realistic case study is also presented to demonstrate the effectiveness of the proposed framework in enhancing structural robustness.

The majority of bridges and quay walls in the centre of Amsterdam are supported by 100–300 years-old wooden foundation piles subjected to bacterial decay. Bacterial degradation proceeds at a slow rate, allowing the piles to perform their function for many years, although causing a reduction of their load-carrying capacity over time. In this study, micro-drilling measurements were employed to capture the amount of decay and remaining short-term compressive strength of the historic wooden piles. The applicability of micro-drilling was studied on 60 wooden piles with various decay levels, retrieved after 100–295 years of service life. An algorithm was developed for analysing the micro-drilling signals, aimed at determining the decayed outer layer of the piles’ cross section, and validated with the results of mechanical testing on the piles. The micro-drilling technique is now used on a large scale in Amsterdam, supporting the assessment of the wooden foundation piles in the city.

Working at height in construction sites is universal but dangerous, which can directly or indirectly lead to numerous injuries and fatalities. Meanwhile, workers' adverse mental state exerts a significant influence on the occurrence of safety accidents. Recent attempts have been made to precisely detect workers' unsafe psychology using electroencephalogram (EEG) technology. Unfortunately, unidimensional psychological factors considered in previous studies cannot represent complicated mental state. To fill this major knowledge gap, this study proposed a framework for comprehensively considering the effects of multi-dimensional critical unsafe psychology (i.e., fear of height, distraction, and mental fatigue) on workers’ adverse mental state at height. Results show that the four support vector machines (SVMs) achieved excellent performance with 96.33%, 96.75%, 95.50%, and 96.50% accuracy, respectively, when inputting the critical EEG features for adverse mental state assessment, verifying the effectiveness of the proposed framework. In addition, the Gaussian kernel SVM achieved 96.50% accuracy and balanced classification performance, making it most applicable to the development of adverse mental state assessment approach. The framework proposed reveals the complex interactions between unsafe psychology and adverse mental states, enriching the theoretical models of occupational safety and mental health. It provides a more comprehensive perspective on the factors influencing unsafe environments at high altitudes. This offers the possibility for the automatic detection of adverse mental states, contributing to a more proactive approach to safety management in high-altitude operations.

Building materials that are reused in a circular economy context are often non-standard because previous usage has altered their original properties. Material matching algorithms aid design and construction by matching components in stock with those needed in a design. The efficiency of these matches is assessed based on factors such as waste, logistics, and structural applicability. In this paper, we evaluate the efficacy and practicality for design evolution of construction-relevant optimisation goals. We evaluate goals based on their construction-time and design time results, using a software pipeline optimising both the mapping and design. One design was also constructed based on the optimised matching, to assess additional considerations when working component-specific designs. Based on difficulties and inefficiencies observed during fabrication, we propose two alternate matching strategies and compare their effects on the chosen factors. The study reveals that component allocation systems frequently overlook the need for both contingency planning and redundancy in the construction process. Additionally, inaccuracies in inventory tracking can significantly compromise the feasibility of the planned design. The stability of these design assistive techniques strongly affects their ability to be applied in large-volume projects. This implies the need for a new set of objective factors to be incorporated into existing methods of design optimisation.

Information and automation technologies play a pivotal role in achieving cyber-physical integration within Construction 4.0. In this transformed landscape, the evolution of the construction management paradigm carefully considers the enhancement of business models and organizational structures to prioritize stakeholders’ well-being, environmental sustainability, and heightened resilience. A significant challenge lies in effectively managing and coordinating a myriad of multi-source and heterogeneous entities using information and automation technologies. The key obstacle is synchronizing these elements based on cyber-physical interoperation to optimize multiple objectives seamlessly. Hence synchronization emerges as a crucial factor for orchestrating and sustaining harmonious relationships among multiple entities or activities within a delimited spatial-temporal framework. This ensures seamless and aligned coordination throughout dynamic processes. Therefore, this paper presents a strategic roadmap for the synchronized construction management, derived from a thorough analysis of fundamental elements in Construction 4.0, aimed at advancing the current construction management practices. Moreover, to articulate this synchronization approach systematically, an Orthogonally Synchronized Digital Twin (SDT) model with regular expression is formulated, built upon the proposed roadmap for reshaped construction management. This study provides valuable insights for stakeholders in the construction industry, including architects, engineers, project managers, and policymakers. The findings guide decision-making on digital twin adoption in construction, supporting practitioners to enhance efficiency and improve outcomes, offering a roadmap for industry advancement towards human-centrality, sustainability, and resilience. Future research should focus on validating the proposed roadmap and SDT model in real-world scenarios, exploring synergies between AI and digital twins, and investigating advanced technologies for holistic smart cities management.

A holistic understanding and careful balancing of different quality aspects can support sustainable, evidence-based decisions during the planning and realisation phases of a building. To this end, it is important to consider, whether and to what extent different quality aspects are interrelated in order to assess potential consequences of decisions. For this purpose, the Holistic Quality Model 2.0 is introduced, representing a second iteration of the Holistic Quality Model developed in recent studies. It incorporates two improvements. First, the integration of the economic quality aspect in addition to the technical, environmental and social quality aspects. Second, the development of an extended interrelations methodology to facilitate better identification and quantitative analysis of interrelations. These improvements and a corresponding case study emphasise the shift from the conventional practice of evaluating quality aspects in isolation towards a holistic approach enabling informed decision-making by considering and balancing different quality aspects.

Repointing is a prevalent maintenance practice in Northern Europe aimed at mitigating moisture-related damage in brick masonry buildings. Although commonly used, evidence of its effectiveness is limited. This study assesses repointing's role in reducing damage risks by conducting a probabilistic hygrothermal analysis of two wall types: timber frame walls and masonry cavity walls. Results indicate that repointing could reduce the mold index in timber frame walls and moisture content in the autoclaved aerated concrete (AAC) layer of masonry cavity walls, particularly in walls with visible defects. However, its impact is minimal on walls without significant deficiencies. Moreover, the study suggests that repointing, given its labor-intensive and costly nature, may not always be the most judicious maintenance strategy. It recommends a selective repointing approach, suiting the specific conditions and needs of the wall based on its location, orientation, and existing state, rather than a blanket application across all façade sections.

Fiber-reinforced polymer (FRP) is widely used for retrofitting structural elements due to its easy application. However, establishing a retrofit strategy is challenging due to conflicting objectives, such as cost and performance level, requiring optimization for effective decision-making. This study proposes a many-objective optimization model for seismic retrofitting using FRP and the Non-dominated Sorting Genetic Algorithm (NSGA)-III. The model's efficacy was demonstrated through two numerical examples: a reinforced concrete building retrofitted with FRP jackets and a masonry-infilled reinforced concrete building retrofitted with FRP bracings. Each example included three objective functions and multiple constraints. Nonlinear static pushover analysis provided optimal strategies to enhance base shear and energy dissipation while minimizing costs and retrofitting locations. Among the Pareto-optimal solutions, the optimal solution with the minimum Euclidean distance was selected. NSGA-III offered a wider distribution and more Pareto-optimal solutions compared to NSGA-II, demonstrating its potential in addressing many-objective problems related to retrofit decision-making.