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This research proposes a viable method of slab and shore load computation for the partial striking technique utilized in high-rise construction projects to optimize the use of horizontal formwork. The proposed Partial Striking Simplified Method (PSSM) is designed to be utilized by industry practitioners to schedule the construction operations of casting floors in order to control the formwork costs incurred throughout the completion of a project.

The article presents the PSSM for calculating slab and shore loads in multi-story building construction. It introduces the concept of “clearing before striking,” where shore supports are partially removed after a few days of pouring fresh concrete. The PSSM procedure is validated through numerical analysis and compared to other simplified approaches. Additionally, a user-friendly Python program based on the PSSM procedure is developed to explore the capability of the PSSM procedure and is used to study the variations in slab load, shoring level, concrete grade and cycle time.

The study successfully developed a more efficient and reliable method for estimating the loads on shores and slabs using partial striking techniques for multi-story building construction. Compared to other simplified approaches, the PSSM procedure is simpler and more precise, as demonstrated through numerical analysis. The mean of shore and slab load ratios are 1.08 and 1.07, respectively, which seems to have a slight standard deviation of 0.29 and 0.21 with 3D numerical analysis. The Python program developed for load estimation is effective in exploring the capability of the proposed PSSM procedure. The Python program's ability to identify the floor under maximum load and determine the specific construction stage provides valuable insights for multi-story construction, enabling informed decision-making and optimization of construction methods.

High-rise construction in Indian cities is booming, though this trend is not shared by all the country's major metropolitan areas. The growing construction sector in urban cities demands rapid construction for efficient utilization of formwork to control the construction costs of project. The proposed procedure is the best option to optimize the formwork construction cost, construction cycle time, the suitable formwork system with optimum cost, concrete grade for the adopted level of shoring in partaking and many more.

The proposed PSSM reduces the calculation complexity of the existing simplified method. This is done by considering the identical slab stiffness and identical shore layout for uniform load distribution throughout the structure. This procedure utilizes a two-step load distribution calculation for clearing phase. Initially, the 66% prop load of highest floor level is distributed uniformly over the lower interconnected slabs. In the second step, the total prop load is removed equally from all slabs below it. This makes the load distribution user-friendly for the industry expert.

The fundamental aim of the study is to investigate the implications of labor housing designs in Dubai, with a focus on courtyards and the governing building regulations, on daylight performance as an underlying factor impacting laborers’ indoor environmental quality. Several studies shed light on the subject of labor camps and labor migration in Dubai, but few have focused on the subject from the perspective of the environmental performance of these camps. A model that represents one of the labor camps was built using Rhinoceros 7.0 and Grasshopper software packages. Annual daylighting and glare simulations were carried out using the lighting modeling engine RADIANCE 5.0 in conjunction with the “ClimateStudio”.

The construction sector has emerged as a significant economic development driver, attracting a diverse labor force from a variety of countries to Dubai. As a result, Dubai authorities have implemented several measures to ensure the provision of suitable housing facilities for its labor force. These measures contribute to the reduction of energy costs in labor housing by encouraging the use of renewable energy. While several studies shed light on the subject of labor camps and labor migration in Dubai, few have focused on the subject from the perspective of the environmental performance of these camps.

The study provided statistical evidence that the current regulations governing courtyards in labor housing resulted in significant changes in daylight levels across different floor levels of the labor housing units. It is suggested that both 2:3 and 3:4 Court Width-to-Height ratios would further contribute to a more consistent daylight Illuminance with marginal statistical differences between floor levels (p > 0.05). The 3:4 ratio, on the other hand, offers a consistent distribution across all floor levels in the North and South with negligible variances, although weakly significant differences can be yet expected between the first and fourth floors in the East and West orientations (p < 0.05). The results of Annual Sunlight Exposure (ASE) suggest excessive solar incidence and a high probability of glare, which remains a problem that must be addressed under the governing building regulations.

This study could serve as a framework for analyzing and contrasting the findings of other studies on labor accommodation, notably in the Gulf Cooperation Council (GCC) countries. Such an approach has the potential to enhance living conditions in labor accommodations in Dubai and other areas. It is necessary to meet people' physical and psychological well-being while also addressing sustainability and regulatory compliance.

Maintaining the safety of the human is a major concern in factories where humans co-exist with robots and other physical tools. Typically, the area around the robots is monitored using lasers. However, lasers cannot distinguish between human and non-human objects in the robot’s path. Stopping or slowing down the robot when non-human objects approach is unproductive. This research contribution addresses that inefficiency by showing how computer-vision techniques can be used instead of lasers which improve up-time of the robot.

A computer-vision safety system is presented. Image segmentation, 3D point clouds, face recognition, hand gesture recognition, speed and trajectory tracking and a digital twin are used. Using speed and separation, the robot’s speed is controlled based on the nearest location of humans accurate to their body shape. The computer-vision safety system is compared to a traditional laser measure. The system is evaluated in a controlled test, and in the field.

Computer-vision and lasers are shown to be equivalent by a measure of relationship and measure of agreement. R² is given as 0.999983. The two methods are systematically producing similar results, as the bias is close to zero, at 0.060 mm. Using Bland–Altman analysis, 95% of the differences lie within the limits of maximum acceptable differences.

In this paper an original model for future computer-vision safety systems is described which is equivalent to existing laser systems, identifies and adapts to particular humans and reduces the need to slow and stop systems thereby improving efficiency. The implication is that computer-vision can be used to substitute lasers and permit adaptive robotic control in human–robot collaboration systems.

The purpose of this paper is to scrutinise the effectiveness of four derivative exchanges’ enforcement efforts since 2007. These exchanges include the Commodity Exchange Inc. and ICE Futures US from the United States and ICE Futures Europe and the London Metal Exchange from the UK.

The paper examines 799 enforcement notices published by four exchanges through a behavioural science lens: HUMANS conceived by Hunt (2023) in Humanizing Rules: Bringing Behavioural Science to Ethics and Compliance.

The paper finds the effectiveness of the exchanges’ enforcement efforts to be a mixed picture as financial markets transition from the digital to artificial intelligence era. Humans remain a key cog in the wheel of market participants’ trading operations, albeit their roles have changed. Despite this, some elements of exchanges’ enforcement regimes have not kept pace with the move from floor to remote trading. However, in other respects, their efforts are or should be, effective, at least in behavioural terms.

The paper’s findings are arguably limited to exchanges based in Anglophone jurisdictions. The information published by the exchanges is variable, making “like-for-like” comparisons difficult in some areas.

The paper makes several recommendations that, if adopted, could help exchanges to increase the potency of their enforcement programmes.

A key aim of the paper is to shift the lens through which the debate concerning the efficacy of exchange-level oversight is conducted. Hitherto, a legal lens has been used, whereas this paper uses a behavioural lens.

In this study, a novel framework based on deep learning models is presented to assess energy and environmental performance of a given building space layout, facilitating the decision-making process at the early-stage design.

A methodology using an image-based deep learning model called pix2pix is proposed to predict the overall daylight, energy and ventilation performance of a given residential building space layout. The proposed methodology is then evaluated by being applied to 300 sample apartment units in Tehran, Iran. Four pix2pix models were trained to predict illuminance, spatial daylight autonomy (sDA), primary energy intensity and ventilation maps. The simulation results were considered ground truth.

The results showed an average structural similarity index measure (SSIM) of 0.86 and 0.81 for the predicted illuminance and sDA maps, respectively, and an average score of 88% for the predicted primary energy intensity and ventilation representative maps, each of which is outputted within three seconds.

The proposed framework in this study helps upskilling the design professionals involved with the architecture, engineering and construction (AEC) industry through engaging artificial intelligence in human–computer interactions. The specific novelties of this research are: first, evaluating indoor environmental metrics (daylight and ventilation) alongside the energy performance of space layouts using pix2pix model, second, widening the assessment scope to a group of spaces forming an apartment layout at five different floors and third, incorporating the impact of building context on the intended objectives.

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.

Several studies were made on paired site and soil–structure interaction (SSI) effects, but most of them were site specific. This paper aims to investigate the impact of SSI effects in conjunction with local soil condition effects on the seismic response of typical multistory low- to mid-rise–reinforced concrete (RC) buildings resting on Algerian regulatory design sites through a global explicit transfer function (TF).

A preliminary quantification of SSI effects associated with site effects is carried out through a frequency-domain solution based on the concept of rock-to-soil surface displacement TF performed for each design site category. It results from the combination of the TFs of structure, foundation and soil and reflects how seismic waves are amplified due to changes in the geological contrast between the rock and overlying soil deposits. As well, response modification factors, denoting displacement ratios of the building responses within the flexible and site-structure conditions with respect to the fixed-base one, are carried out.

In the context of Algerian seismic regulation, the study provides a clear vision of how and when site or SSI effects are expected to be influential, as opposed to the fixed-base hypothesis still retained by the current regulation. This helps engineers to be aware of the extent of the expected seismic damage.

The research applies to low- to mid-rise RC buildings within the Algerian seismic regulation, but it may also be expanded to other examples that fall under other seismic regulations.

The response modification ratio is a quantitative approach to assessing response fluctuations. It draws attention to how the roof level drift varies depending on the condition. These results can be used as numerical parameters in structural seismic design when the structure is comparable because they provide useful information about how the two phenomena interact with the structure.

The study goes beyond particular situations dealing with site specific and offers effective indicators and quantitative evaluation of combined site and SSI effects according to the current national seismic provisions, where no indication about site or SSI effects exists.

The provision of an accessible and inclusive built environment is both a common regulatory requirement for architects and facilities managers, and a critical issue of equitable access for people with disability. Post Occupancy Evaluation (POE) is key to ensuring appropriate building accessibility is provided and maintained. Improved Building Information Modelling (BIM) integration with Facilities Management (FM) will enable more effective POE over time. This study aims to define and demonstrate the practicability and utility of a particular configuration of emerging BIM and related digital technologies, applied in the field.

A field study approach is applied to investigate the practicability and utility of the technology configuration and POE procedures. A proposed technology configuration is applied to evaluate 21 accessible bathrooms across three university buildings in Sydney, Australia. First, a checklist of technical functionality for a POE of accessible bathrooms particular to the field study FM context is established. The checklist is based on a review of recent literature, relevant standards, best practice guidelines, expert opinions, and the organisational requirements. Then, a technical and procedural approach to POE and BIM integration with FM is defined and applied in the field. Finally, a quantitative analysis of the results is presented and discussed relative to both the particular and general FM contexts.

The use of low-cost BIM and related technologies can usefully be applied in the field to promote a more progressive integration of BIM with FM and provide enhanced baseline models for ongoing POE. A rudimentary risk assessment of key accessible bathroom features (in the context of this field study) identified that the Toilet: toilet rolls location is unsatisfactory across all bathrooms surveyed and represents an immediate and high-risk failing. Other high-risk issues highlighted in this study included: Approach: access; Entrance: door fittings and security; and Layout: hazards.

This study offers a blue-print for building practitioners to adopt and progressively integrate low-cost BIM and related technologies with extant FM systems. The study also promotes an improved approach to effective POE practice in general, and to the assessment of accessible bathrooms in particular.

Recent reviews highlight key barriers to BIM integration with FM and significant limitations to current POE practice. Proposals for BIM integration with FM tend to focus on the comprehensive use of BIM. This study demonstrates the practicability and utility of a more progressive approach to BIM adoption and integration with FM in general. The study is also novel in that it shows how low-cost BIM and related technologies can be used as a baseline reference for ongoing POE. Building practitioners can adopt and adapt the technology configuration and approach to support a range of POE applications. This field study has identified immediate and high-risk potential failings of the accessible bathrooms provided on one university campus in Sydney, Australia.

Several factors influence the costs of buildings. Thus, identifying the cost significant factors can assist to improve the accuracy of project cost forecasts during the planning phase. This paper aims to identify the cost significant parameters and explore the potential for improving the accuracy of cost forecasts for buildings using machine learning techniques and large data sets.

The Australian State of Victoria Building Authority data sets, which comprise various parameters such as cost of the buildings, materials used, gross floor areas (GFA) and type of buildings, have been used. Five different machine learning regression models, such as decision tree, linear regression, random forest, gradient boosting and k-nearest neighbor were used.

The findings of the study showed that among the chosen models, linear regression provided the worst outcome (r² = 0.38) while decision tree (r² = 0.66) and gradient boosting (r² = 0.62) provided the best outcome. Among the analyzed features, the class of buildings explained about 34% of the variations, followed by GFA and walls, which both accounted for 26% of the variations.

The output of this research can provide important information regarding the factors that have major impacts on the costs of buildings in the Australian construction industry. The study revealed that the cost of buildings is highly influenced by their classes.

The lightweight design of aircraft seats can significantly improve fuel efficiency and reduce greenhouse gas emissions. Metal additive manufacturing (MAM) can produce lightweight topology-optimized designs with improved performance, but limited build volume restricts the printing of large components. The purpose of this paper is to design a lightweight aircraft seat leg structure using topology optimization (TO) and MAM with build volume restrictions, while satisfying structural airworthiness certification requirements.

TO was used to determine a lightweight conceptual design for the seat leg structure. The conceptual design was decomposed to meet the machine build volume, a detailed CAD assembly was designed and print orientation was selected for each component. Static and dynamic verification was performed, the design was updated to meet the structural requirements and a prototype was manufactured.

The final topology-optimized seat leg structure was decomposed into three parts, yielding a 57% reduction in the number of parts compared to a reference design. In addition, the design achieved an 8.5% mass reduction while satisfying structural requirements for airworthiness certification.

To the best of the authors’ knowledge, this study is the first paper to design an aircraft seat leg structure manufactured with MAM using a rigorous TO approach. The resultant design reduces mass and part count compared to a reference design and is verified with respect to real-world aircraft certification requirements.