Concrete is a fundamental material in the construction industry, with formwork playing a crucial role in shaping and strengthening concrete elements. It also represents a significant cost in building projects. The history of formwork is extensive, and diverse systems have been employed across various projects. When selecting a formwork system, considerations such as safety, cost, structural requirements, construction duration, and environmental impact must be carefully weighed. This project provides a comprehensive review of different formwork systems used in concrete construction, encompassing their materials, flexibility, fabrication methods, application in structures, and environmental implications. The advantages and limitations of these systems are analysed and compared, culminating in practical recommendations. Formwork systems are pivotal in determining the success of construction projects in terms of efficiency, quality, cost-effectiveness, and safety. Recent innovations, particularly modular formwork systems, have revolutionized the construction industry in countries like Japan, Singapore, Malaysia, and the Middle East. These systems have proven to be cost- effective, enhance construction quality, and accelerate project timelines. Their adaptability makes them particularly suitable for mass construction projects in India, where achieving high-quality, rapid construction is crucial. By leveraging modern formwork technologies, construction practices can achieve safer, faster, and more sustainable outcomes, aligning with advancements
The hydration of calcium silicate hydrate (CSH) is crucial in determining the mechanical properties and durability of cement-based materials. In this study, we investigate the impact of graphene oxide (GO) on the hydration process of CSH using molecular dynamics simulations. The primary focus is on how GO influences the nucleation, ion distribution, and structural evolution of CSH gels during cement hydration. The results reveal that GO significantly accelerates the nucleation process, especially in the formation of short-chain and long-chain CSH structures, through its oxidized functional groups, which interact with calcium ions (Ca2+) and promote their aggregation. GO’s presence alters the distribution of Ca2+ and silicon atoms, with a more pronounced effect on Ca2+ ions, leading to localized high-concentration regions and enhancing the nucleation process. In contrast, Si atoms exhibit a more uniform distribution in the system, indicating a weaker adsorption effect. Additionally, GO improves the structural ordering of Si-O bonds in CSH, which accelerates the formation of CSH gels, although it has minimal impact on the bond angle distribution. Overall, GO acts as a heterogeneous nucleation agent, increasing the number and density of nucleation sites, thus improving the early-stage hydration process, microstructure, and potentially the mechanical properties and durability of cement-based materials. The findings provide valuable insights into the role of GO in enhancing cement hydration, offering a promising approach to improving the performance of cement-based materials in construction.
Materials of engineering and construction. Mechanics of materials
With the expansion of high-rise building construction in China, tower cranes have become indispensable key equipment in the construction industry. To ensure the safety and structural reliability of tower cranes under complex working conditions, this paper takes a typical 40 m-high flat-arm tower crane as the research object. For the first time, the orthogonal test method was used to monitor the stress of key components (the root of the tower body and the root of the boom). The stress distribution characteristics of the tower crane structure under different working conditions were systematically analyzed. Then, based on the power spectral density analysis method, the natural frequency of the tower crane structure was identified. The influence of key structural parameters, such as lifting position, rope length, and lifting weight, on the stress of the tower crane was quantitatively studied through orthogonal experiments, revealing the multi-parameter coupling effect. The results show that the stress at the measuring point at the root of the tower body is significantly higher than that at the root of the boom. This indicates that the root of the tower body is the primary stress-bearing part of the tower crane structure, highlighting the need to focus on its fatigue performance and safety assessment. Based on the power spectral density analysis of the root stress of the tower crane, the natural frequencies of the tower crane structure were accurately identified. The first-order frequency was 0.10 Hz, and the second-order frequency was 0.20 Hz, providing data support for the study of the tower crane’s dynamic characteristics. The orthogonal test analysis shows that the influences of lifting position, rope length, and lifting weight on the stress of the tower crane are consistent, with no significant differences. The effects of lifting position and rope length on stress are dominant, while the influence of lifting weight is relatively small. These research findings provide an important basis for the lightweight design and safety assessment of tower cranes.
In the construction industry, efforts are continually being made to replace natural resources with recycled or artificial materials to promote sustainable development worldwide. This article explores the use of recycled plastic waste (expanded polystyrene and polyester fibers) combined with lightweight expanded clay aggregate (Liapor) to produce a mixture that could potentially be used as a structural layer in sub-ballast layers. Prior to testing this recycled material, it was hypothesized that the layer would serve a thermal insulation function and potentially provide partial reinforcement within the structural composition of the sub-ballast layers. The article outlines the procedure for manufacturing samples of the mixture made from plastic and Liapor, which was subjected to a compressive strength test. The results of the compressive strength test revealed that the sample’s strength was insufficient for its intended use in the structural composition of the sub-ballast layers as the achieved maximum compressive strength was only approx. 0.40 MPa. However, its favorable thermal insulation properties remain promising and should be verified in future laboratory investigations after adjusting the ratio of material components and possibly the manufacturing process.
Abstract Iron is a critical yet limited nutrient for microbial growth. To scavenge iron, most microbes produce siderophores—diverse small molecules with high iron affinities. Different siderophores are specifically recognized and uptaken by corresponding recognizers, enabling targeted interventions and intriguing cheater‐producer dynamics. We propose constructing a comprehensive iron interaction network, or “iron‐net”, across the microbial world. Such a network offers the potential for precise manipulation of the microbiota, with conceivable applications in medicine, agriculture, and industry as well as advancing microbial ecology and evolution theories. Previously, our successful construction of an iron‐net in the Pseudomonas genus demonstrated the feasibility of coevolution‐inspired digital siderophore‐typing. Enhanced by machine learning techniques and expanding sequencing data, forging such an iron‐net calls for multidisciplinary collaborations and holds significant promise in addressing critical challenges in microbial communities.
This paper analyzes environmental performance indicators (PIs) in the construction and building industry using bibliometric and content analysis, particularly in the fields of architecture and civil engineering. The paper aims to present a framework for environmental performance in the construction industry, focusing on projects and their impacts. It addresses which research fields are most focused on this area, whether the topic is currently relevant, whether it shows a positive or negative trend, what related topics exist, and what general overlaps or gaps are present. It also examines which PIs are most frequently mentioned and whether the topics and indicators align with the United Nations Sustainable Development Goals (UN SDGs). The results reveal a fragmented research area, with both complex PIs and very narrow PI applications, highlighting the need to bridge these gaps and address the challenge of insufficient data. The research uses QtoQ Target Mapping to map the PIs to the UN SDGs and provide an overview of coverage. The findings indicate that this topic is highly important and researched across various disciplines, and that the PIs and their analysis further contribute to the Sustainable Development Goals.
Abstract A novel Corrax (CX) stainless steel was fabricated using the Selective Laser Melting (SLM) process. This study examined the influence of heat treatment processes on the microstructure and mechanical properties of CX stainless steel. Results indicate that SLM-fabricated CX samples mainly consist of martensite and residual austenite, with tensile strength and hardness of 1124 MPa and 337.4 HV, respectively. After solution treatment at 850 °C for 0.5 h (ST), the sample exhibited the highest martensite content, with nearly all residual austenite eliminated. Nickel and aluminum are fully dissolved within the matrix, leading to a supersaturated solid solution. This martensitic structure with a high dislocation density lays an important foundation for the subsequent aging treatment. Subsequent aging treatments at various temperatures demonstrate that when CX samples are subjected to solution aging at 850 °C for 0.5 h followed by aging at 525 °C for 4 h (ST + AT), all residual austenite is fully converted to martensite. The elements dissolved during the solution treatment precipitate, forming NiAl intermetallic compounds. This process leads to a substantial increase in tensile strength and surface hardness, achieving values of 1743 MPa and 526.8 HV, respectively. These results indicate that the solution and aging heat treatment significantly enhances the overall performance of CX samples.
We propose an approach to generate synthetic data to train computer vision (CV) models for industrial wear and tear detection. Wear and tear detection is an important CV problem for predictive maintenance tasks in any industry. However, data curation for training such models is expensive and time-consuming due to the unavailability of datasets for different wear and tear scenarios. Our approach employs a vision language model along with a 3D simulation and rendering engine to generate synthetic data for varying rust conditions. We evaluate our approach by training a CV model for rust detection using the generated dataset and tested the trained model on real images of rusted industrial objects. The model trained with the synthetic data generated by our approach, outperforms the other approaches with a mAP50 score of 0.87. The approach is customizable and can be easily extended to other industrial wear and tear detection scenarios
The convergence of Information Technology (IT) and Operational Technology (OT) in Industry 4.0 exposes the limitations of traditional, hierarchical architectures like ISA-95 and RAMI 4.0. Their inherent rigidity, data silos, and lack of support for cloud-native technologies impair the development of scalable and interoperable industrial systems. This paper addresses this issue by introducing CRACI, a Cloud-native Reference Architecture for the Industrial Compute Continuum. Among other features, CRACI promotes a decoupled and event-driven model to enable flexible, non-hierarchical data flows across the continuum. It embeds cross-cutting concerns as foundational pillars: Trust, Governance & Policy, Observability, and Lifecycle Management, ensuring quality attributes are core to the design. The proposed architecture is validated through a two-fold approach: (1) a comparative theoretical analysis against established standards, operational models, and academic proposals; and (2) a quantitative evaluation based on performance data from previously published real-world smart manufacturing implementations. The results demonstrate that CRACI provides a viable, state-of-the-art architecture that utilizes the compute continuum to overcome the structural limitations of legacy models and enable scalable, modern industrial systems.