Othman Subhi Alshamrani

Hospital fire safety standards in Saudi Arabia remain primarily prescriptive and do not explicitly account for patient mobility constraints, complex building geometry, and time-dependent fire dynamics. The 2015 Jazan Hospital fire, which claimed 25 lives and injured more than 100 people, demonstrated that code compliance alone cannot guarantee occupant safety. This study presents a four-phase BIM framework integrating Autodesk Revit, PyroSim/FDS fire simulation, and Pathfinder agent-based evacuation simulation, applied to a 250-bed hospital in Qatif, Saudi Arabia. The FDS computational mesh was assessed at D*/δx = 12.2 against NIST NCSTAR 1-5E benchmark data (mean errors: temperature 6.8%, smoke optical density 7.2%), and Available Safe Egress Time (ASET) was determined using the multi-criterion ISO 13571:2012 methodology. Under the examined SBC 2018 baseline (Scenario 1, four corridor-end exits), smoke penetrated the ICU corridor within 60 seconds, yielding ASET = 118 s and a Monte Carlo Required Safe Egress Time (RSET) of 412 ± 35 s (n = 50; approximate 95% CI for the mean: 402–422 s), an ASET–RSET deficit of 294 seconds. Scenario 2, incorporating fire-rated ICU/OR compartmentation and ten distributed emergency exits, extended the reported ASET beyond 185 s and reduced mean RSET to 281 ± 22 s (approximate 95% CI for the mean: 275–287 s), a descriptive reduction of 32%. On the reported ASET range of 185–225 s, however, RSET remains greater than ASET; the residual deficit is 56–96 s. Sensitivity analysis across three ignition locations indicates that the Scenario 1 deficit is not specific to one fire origin. The findings support performance-based BIM simulation as a complement to prescriptive code assessment in hospitals.

Delays in completing the construction of oil and gas projects impact the production, sustainability, reliability, and revenues of the company, which result in market share losses in the long term. This research aimed to determine, evaluate, and rank the root causes of schedule delays in oil and gas pipeline projects in Saudi Arabia. Forty-seven different causes were identified firstly from a wide-ranging literature review and then finalized through conducting interviews with two local experts. These causes were ranked by distributing and analyzing questionnaires on the topic. Client-related materials, delays in materials and equipment delivery, permit approval, delays in subcontractor work, and delays in preparing and approving engineering drawings were found to be the top five major causes affecting oil and gas pipeline construction projects. From the initial analyses, it was observed that an adversarial relationship was apparent as the results indicated that the parties tended to blame each other for the delays. The sub-causes of the initial five causes were identified and root cause analysis was performed. A delay in the material and equipment delivery category had the most weighted sub-causes; hence, it is of high importance to mitigate it. Further recommendations were made for different delay causes.

Introduction: Construction industry is increasingly emphasizing productivity due to its effect on key performance indicators such as schedule, budget, and quality of work. This study aims to identify and rank the factors affecting the productivity of steel rebar work in construction projects in a hot climate. Among the activities involved in structural reinforced concrete work, fabricating and placing reinforced steel on a construction site is considered the most labor-intensive, outdoor, and time-consuming. Methods: In this paper, an intensive qualitative literature review is conducted to identify the factors affecting the productivity of steel rebar work in concrete construction. Initially, forty factors were identified from the literature affecting the productivity of steel rebar work in Saudi Arabia. Final list of thirty-seven factors was used in the questionnaire survey. The identical nature and core content of these factors are clustered and grouped into five categories: technical, labor, management, external, and financial. As part of this study, fifty contractors working in the Saudi Arabian construction industry are recruited to participate and complete a structured pilot study questionnaire. Results: The results of the questionnaire are weighted using the pairwise comparison method and then ranked based on the Analytic Hierarchy Process technique. The analysis of the thirty-seven factors results in a top ten list of the leading factors that directly impact the productivity of steel rebar work in concrete construction projects in Saudi Arabia. These factors are (1) humidity, (2) delay of salary, (3) sandstorms, (4) payment delay by client, (5) labor's low wage, (6) lack of financial incentives, (7) labor work experience and skills, (8) completeness of drawings, (9) poor labor relations, and (10) labor absenteeism. The general trend in these studies is that the factors tend to vary from jurisdiction to jurisdiction, from one construction project to another, and are directly related to the zone or country of construction. Conclusion: These findings benefit stakeholders working in the concrete construction industry in Saudi Arabia, particularly project managers, project planners, cost estimators, and civil design and site engineers working on construction projects.

In the kingdom of Saudi Arabia almost 60% of the construction projects were delayed in the recent decade. Contractor selection is the critical decision for the success of any construction project. The typical method of contractor selection in Saudi Arabian projects is generally based on prioritizing the lowest bid price, irrespective of experience, quality, and other factors without investigating in-depth the pre-qualification of contractors. This often leads to disputes and project delays. In this regard, the main goal of the presented research work is the development of a framework that can help decision-makers in both government and private sector to investigate the pre-qualification, and then to select the most suitable contractors for the proposed projects. The presented framework was developed based on a detailed literature review, market analysis, information collection from stakeholders and decision-makers along with collaboration with industry-academia experts. Forty criterion-based selection framework was developed in the presented research work with each criterion possessing a relative weightage developed in comparison with ones obtained using smart techniques. The main categories of the selection criteria are project value, financial capability, reputation, management structure, technical capability and performance, organizational culture, along with safety and environmental health. Through detailed survey and analysis, the main criterion for contractor selection was identified as quality assurance and control with the least important being the Current/Past Joint Venture(s). The presented framework model was validated using a case study where three construction contractors were evaluated using Multi-Attribute Utility Theory Score (MAUT). The framework was deemed reliable and valuable for contractor selection in construction projects for adding the increased selection criterion and insight into the selection evaluation.

In Saudi Arabia, housing projects account for almost half of the total electricity consumed by the construction industry because of the large number of housing projects compared to other types of buildings. This paper proposes a quantitative approach using a multiple linear regression assessment model to predict the energy cost and environmental cost of housing building in Saudi Arabia. It was developed to assist house owners in Saudi Arabia in estimating the monthly energy cost and associated operational carbon cost according to several predictor parameters. Based on related literature, these parameters were reviewed and discussed by experts from the Ministry of Housing. They included building location, wall type, number of occupants, window type, envelope insulation, building age, building area, number of air-conditioning units and their systems, and lighting system. The model development process included five main stages: collecting the energy and carbon cost data from completed operating housing units, categorizing the collected data based on parameters, diagnosing the quality of gathered data and filtering outlier data if any, building and generating a model, and lastly, testing and validating the model. More than 77 datasets were collected across the country during different times of the year. The findings of this study reveal that the relationship between the number of users and the building area with the energy cost is significant and that the number of users is more correlated to the energy cost than the age of the building or the number of central air conditioners installed. Moreover, the results show that the developed model has the ability to predict energy and carbon costs with high accuracy. The developed model serves as a decision support tool for householders and decision makers in the Ministry of Housing to control the predicted parameters. This would be beneficial for the housing unit owners for allocating constrained budgets.

Greenhouse gases associated with energy extraction, production, and consumption are considered a major source of environmental pollution that has led to global warming and climate change. In Saudi Arabia, the building sector represents the largest domain of total energy consumption (roughly 80%) followed by the industrial and agricultural sectors. This study seeks to assess the environmental impacts and economic viability of various construction systems including prefabricated and conventional ones using models for life cycle cost (LCC) and life cycle assessment (LCA). The LCA used in this study was assigned monetary values according to the market price of CO₂ and then combined with the LCC. The developed LCA-LCC therefore provides information regarding the sustainability of the construction method and may assist decision makers in public sector on the selection of the best possible construction system to minimize energy consumption, greenhouse gas emission, and environmental impact while simultaneously reducing overall life cycle costs. The highest LCC was associated with construction costs, which represented 55% to 58% of the whole LCC. The operation and maintenance costs of the project over a 50-year lifespan ranged between 25% and 27% of the overall LCC, while the environmental impact cost was found to represent approximately 17.0% to 18% of the total LCC.

Green building has witnessed significant growth in the North American market in recent years. Since the construction cost of green office buildings represents a significant impact on the life cycle costs in office buildings in North America, and since green building costs are still not well understood by buildings owners, a linear regression model is developed in this study to enable office building owners to predict the initial cost based on the structural and envelope materials used. A multi-regression model is then developed to forecast the initial construction cost based on the use of different combinations of materials, such as concrete and steel, for the envelope and structural systems. The construction cost data is gathered, categorized based on various parameters, and then adjusted according to the national average cost for 2019 in North America, which is applied to develop the predictive model. This model estimates the cost per square foot of mid-rise office buildings according to specified predictor parameters such as building structural system, number of floors, total floor area, and floor height. The process followed modal development consists of three main phases: preliminary quality diagnostics of gathered data, model development, and model testing and validation. This model can assist office building owners in estimating the initial cost of new buildings using green structural and envelope systems, and to provide decision support in the selection among alternative systems and materials from the economic point of view.