The structural design process is iterative and involves many design parameters. Thus, this paper presents a controlled framework for selecting the adequate structural floor system for reinforced concrete buildings and efficiently utilizing the corresponding construction materials. Optimization was performed using an evolutionary algorithm to minimize the total construction cost, considering the costs of concrete, steel reinforcement, formwork, and labor. In the problem formulation, the characteristic compressive strength of concrete was treated as a design variable because it affects the mechanical performance of concrete. The design variables included the column spacings, concrete dimensions, and steel reinforcement of different structural components. The constraints reflected the Egyptian code of practice provisions. Because the choice of the structural floor system affects the design details, three systems were considered: solid slabs, flat slabs with drop panels, and flat slabs without drop panels. Two benchmark examples were presented, and the optimal design results of the structural floor systems were compared. The solid slab system had the lowest construction cost among the three structural floor systems. Comparative diagrams were developed to investigate the distribution of construction costs of each floor system. The results revealed that an adequate choice of design variables could save up to 17% of the building’s total construction cost.
In this paper a structural optimization technique based on a modified genetic algorithm (GA) is presented. The technique is developed to deal with discrete design optimization of structural steelwork. Also, the paper discusses the effect of different approaches, employed for the determination of the effective buckling length of a column, on the optimum design. In order to consider realistic steelwork design problems, a modified GA has been linked to a system of structural design rules (British Standards BS 5950 and BS 6399), interacting with a finite element package. In the formulation of the optimization problem, the objective function is the total weight of the structural members, as it gives a reasonably accurate estimation of the cost. The cross-sectional properties of the structural members, which form the set of design variables, are chosen from two separate catalogues (universal beams and columns) covered by the British Standard BS 4. The minimum weight designs of two plane steel frame structures subjected to realistic multiple loading cases are obtained. These examples show that the modified GA in combination with structural design rules and more accurate analysis provides an efficient tool for practicing designers of steel frame structures. Finally, it is shown that the resulting design optimization is considerably influenced by a specific choice of a technique employed for the evaluation of the effective buckling length of structural members.
This paper investigates the effects of concrete grades and column spacings on the optimal design of reinforced concrete (RC) buildings. To this end, cost design optimization was performed for buildings with three different floor systems: flat plates (FS), flat slabs with drop panels (FSDP), and solid slabs (SS). The evolutionary method provided by the Excel solver was used as the optimization algorithm because it can deal with the complex nature of structural design problems. The objective function was the total construction cost of the building, including the costs of concrete, reinforcement bars, labor, and formwork, while still fulfilling the constraints of the Egyptian code of practice (ECP-18). The applicability of the presented algorithm was investigated in a design example, where the tuning of the evolutionary algorithm control parameters was sought, and the best parameters were investigated. Two case studies were employed to study the impacts of changing the column spacing and concrete grades on the optimal cost for each floor system. The results showed that low concrete grades, (i.e., characteristic strength up to 40 MPa) and column spacings up to 5 m are preferred in terms of direct construction costs for low-rise RC residential buildings.
The construction costs of hospital buildings are relatively high due to the need to fulfill their complex functions and avoid mishaps. In this context, this study aims to minimize the total construction costs of hospitals while still satisfying the special architectural, practical, and structural requirements specified by design codes. To this end, 48 design alternatives with two floor systems (flat slabs with and without drop panels), three column spacings, and eight concrete grades were optimized using genetic algorithms provided by Palisade Evolver. The objective function included the materials and labor costs per square meter of the floor plan. The decision variables involved the concrete dimensions and steel bars of floors and columns. The hospital buildings were subjected to gravity, earthquake, and wind loads to thoroughly examine the realistic loading conditions. The design was performed in accordance with the Egyptian code for the design and construction of concrete structures and the Egyptian guidelines for hospitals and healthcare facilities. The results revealed that using low-strength concrete, and flat slabs without drop panels could achieve the best design. The slab thickness had a governing impact on the total cost of both floor systems.
Project schedule monitoring and controlling are critical challenges of construction project management that are not adequately implemented, likely due to the predominance of earned value management and the lack of utilizing technology, such as BIM tools. Unlike earned value, earned duration management (EDM) was developed, which includes several indices to track schedule progress and measure the performance of a schedule. The goal of this research was to establish a decision support system to track and monitor construction project activities during construction, with better performance and accuracy. A survey was conducted and distributed among ten site engineers, selected from different construction sites. The survey asked the site engineers about the possible durations of certain activities; based on their answers, the authors started the proposed system. In this study, we aimed to develop a decision support system (DSS), which combines BIM with EDM to help calculate probabilistic total project duration, visually detecting critical activities, monitoring visually risky activities subjected to delay and visually categorizing the accuracy of estimated duration for delayed activities.
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