Building Construction Costs Research Articles

Advances in Highly Ductile Concrete Research.

In recent years, high-ductility concrete (HDC) has gradually become popular in the construction industry because of its excellent ductility and crack resistance. Concrete itself is a kind of building material with poor tensile properties, and it is necessary to add a large number of steel bars to improve its tensile properties, which increases the construction cost of buildings. However, most of the research studies on high-ductility concrete are scattered. In this paper, the basic mechanical properties of high-ductility concrete and the effects of dry and wet cycles, freeze-thaw cycles, and salt erosion on the durability of high-ductility concrete are obtained by comprehensive analysis. The results show that the tensile properties of HDC can be significantly improved by adding appropriate fiber. When the volume fraction of steel fiber is 2.0%, the splitting tensile strength of concrete is increased by 98.3%. The crack width threshold of concrete chloride erosion is 55-80 μm, and when the crack width threshold is exceeded, the diffusion of CL-1 will be accelerated, and the HDC can control the crack within the threshold, thereby improving the durability of the concrete. Finally, the current research status of high-ductility concrete is analyzed, and the future development of high-ductility concrete is proposed.

Intelligent building construction cost optimization and prediction by integrating BIM and elman neural network

This study aims to address the challenges of capturing design changes, supply chain fluctuations, and labor cost variations to improve the accuracy and real-time nature of intelligent building construction cost predictions. It seeks to accurately forecast and optimize project costs. The study innovatively constructs an intelligent building construction cost prediction model based on Building Information Modeling (BIM) and Elman neural networks (ENNs), denoted as the BIM-ENN model. The BIM-ENN model first introduces BIM technology to digitize and visualize information related to building structures, electromechanical systems, and pipelines. The digitized data obtained through BIM technology is then used as input data for the ENN, which optimizes the neural network parameters to predict and optimize intelligent building construction costs. Finally, the BIM-ENN model is experimentally evaluated. The results demonstrate that the prediction value of the construction cost of the intelligent building by this model closely matches the original information price, with a prediction accuracy of 95.83 %. Compared with the single ENN, the root mean squared error of the BIM-ENN model is less than 75, and the determination coefficient is above 0.95. This indicates that this model can explain more than 95 % of the construction cost prediction results, making it a feasible solution for actual prediction problems and achieving satisfactory results. The intelligent building construction cost prediction model reported here exhibits high accuracy and reliability. It can successfully forecast construction costs, providing robust decision support for the digitalization and intelligent development of construction enterprises. The practical significance of this study lies in providing the construction industry with an accurate cost management tool that helps enterprises optimize budget control and resource allocation, enhancing risk assessment and management capabilities. Moreover, the potential impact of the BIM-ENN model is its ability to elevate prediction standards within the construction industry, promote technological integration and innovation, enhance enterprise competitiveness, and drive the industry's transition towards digitalization and intelligent sustainable development.

Simplification of Concrete Construction Processes and Rational Use of Eco-friendly Building Materials of BIM Technology in the Perspective of Renewable Energy

As the economy and society continue to grow quickly and as the people's living standards gradually rise, the share of building energy consumption in overall societal energy consumption will continue to rise. Sustainable standards need to be assigned top priority in the building business considering limited resources, impact on the environment, and socioeconomic limits. Additional materials are used to make concrete more sustainable. Several environmental, technological, and financial limitations make the selection of supplemental materials difficult. Building construction costs are capable of being decreased and global emissions of carbon can be reduced through the design optimization of concrete reinforced structures. Based on the above limitations, this paper proposes a new framework in BIM technology. This paper presents an approach for support of decisions that take criteria for sustainability related to social, technical, environmental, and economic aspects when ranking concrete supplemental content. The decision framework comprises the short listing of supplemental materials with technological and cost features based on the OSM, and the following use of ANP to prioritize the materials based on sustainable possibility order. By using the technical properties of every technically sound material utilized as concrete, the current study provides a decision support framework. Based on this, proposing a novel optimization strategy that considers both the structural topology and the optimization of specific components to build high-rise reinforced concrete buildings in a low-carbon and cost-effective manner. This technique first involves determining the optimal structural typology and afterwards optimizes the individual member sizes by using the OCLO algorithm. The suggested method is able to be expanded to optimize different building kinds with comparable issues, increasing the built environment's sustainable development and cost-effectiveness.

Risk-based life cycle cost–benefit analysis for progressive collapse design of RC frame structures

Progressive structural collapse is a typical low-probability high-consequence event. Progressive collapse design can effectively improve the robustness of structures against accidental local damage and reduce the probability of collapse. However, progressive collapse design also increases the construction cost of buildings. Hence, it is necessary to conduct cost-benefit analyses for the progressive collapse design of building structures. This study first designs a reinforced concrete (RC) frame based on a progressive collapse design program that simultaneously optimizes material consumption and structural resistance. Then, the structural failure probability is quantified using an alternative path (AP) method-based fragility analysis that considers the structural uncertainties. Based on this, the life cycle costs and benefits of the structure designed with different design load factors are investigated. A four-story RC frame is used as an example. By considering the time value of money and threat probability, the break-even points and optimized design load factors for the progressive collapse design of the RC frame are analyzed. These research outcomes can help promote progressive collapse design in engineering practice and provide references for proposing scientific and reasonable design load factors.

Comparison of thermal hydraulic performance between horizontal and vertical steam generators in nuclear power plants

Abstract Steam generators (SG) for Nuclear Power Plants (NPPs) are important large-sized metal consuming equipment of nuclear power installations. Efficiency of steam generator operation determines the overall service life of the whole nuclear facility. Vertical steam generators are used normally in North America, Europe and South East Asia, but horizontal steam generators are currently of great importance to reduce building heights and construction costs that govern the overall cost of new nuclear power plants. The objective of the current study is to measure the performance of nuclear steam generators in NPPs through comparative assessments of vertical and horizontal configurations. For this purpose, the vertical U-tube steam generators of a typical 4-loop Pressurized Water Reactor (PWR) was replaced by a VVER-1000 horizontal steam generators to evaluate the horizontal SG performance, at the same plant conditions and characteristics, in comparison with the vertical SG. The thermal hydraulic system code RELAP5 was used in the current work to perform the required analysis, during steady and transient scenarios.

Avaliação probabilística da carga variável de projeto para garagens brasileiras de veículos leves

Abstract Design loads for parking garages should be reviewed every few years due to changes in fleet characteristics and the impact of design loads on carbon emissions by the built environment. Specifically for Brazil, the authors are unaware of existing studies to justify the design values and corresponding exceedance probabilities stated in NBR 6120:2019 - Design Loads for Structures. In this paper, a simplified probabilistic model for live loads in parking garages is presented. A set of updated statistics characterizing the gross curb weight of the fleet in circulation was obtained based on technical specifications and sales reports between 2003 and 2022. These statistics and the probabilistic load model are employed to derive the equivalent uniform design load corresponding to a 30% probability of being exceeded in 50 years, according to the definition stated in NBR 6120:2019 and NBR 8681:2003. The results provide support for a significant reduction of the current design load for light-duty vehicle parking garages, from the current 3.0 kN/m2 to at least 2.5 kN/m2. Such a reduction has a significant impact on new building construction costs and carbon emissions and would not compromise the structural safety of parking garages built in Brazil.

Accurate estimation of prefabricated building construction cost based on support vector machine regression

Accurate estimation of prefabricated building construction cost based on support vector machine regression

Accurate estimation of prefabricated building construction cost based on support vector machine regression

Accurate estimation of prefabricated building construction cost based on support vector machine regression

The Prediction of Low-Rise Building Construction Cost Estimation Using Extreme Learning Machine

This study aims to predict the possibility of low-rise building construction costs by applying machine learning models, and the performance of each model is evaluated and compared with ensemble methods. The artificial neural network (ANN) emerges as the top-performing individual model, attaining an accuracy of 0.891, while multiple linear regression and decision trees follow closely with accuracies of 0.884 and 0.864 respectively. Ensemble methods like maximum voting ensemble (MVE) improve the accuracy beyond individual models with an impressive accuracy rate of 0.924. Meanwhile, the stacking ensemble and averaging ensemble also demonstrate competitive performance with accuracies of 0.883 and 0.871, respectively. These findings can result in more informed decision-making, which is valuable for the real estate industry.

Prefab Facades – From Prototype to Product?

Building envelopes are not only the prime element of the exterior aesthetic quality of buildings; they have also become a major driver both for building construction cost and operational performance. The importance of prefabrication is growing in the building industry as it allows faster, high-quality, and cost-effective construction while reducing risks associated with onsite labour. Although prefabrication for structural components is a relatively recent development, it has been widely used in the manufacturing of building envelopes for many years, particularly in the case of unitized curtain wall systems. However, whether using prefabricated components or not, façade design development remains a challenge due to the need for façade engineers to rapidly develop technically viable and financially feasible solutions that achieve the desired architectural design intent. Particularly at the early stages of the design process, the turnaround for multiple iterations is often fast-paced, and abortive work is, therefore, not uncommon. This paper outlines an approach to addressing this challenge, attempting to bridge the gap between façade design, fabrication, and installation. A new design approach and tools are presented that allow designers to iteratively validate concepts based on a pre-engineered system that is optimized for performance and take fabrication, transport, installation costs, maintenance, and circularity into account. As a result, the tool/design workflow will ensure consistent quality, meeting budgets and timelines while enhancing material efficiency and fostering energy-conscious and circular envelope design approaches.

친환경 건축물의 가치 및 향후 과제

As environmental pollution and climate change intensify, many buildings are increasingly adopting equipment and materials that affect their energy efficiency. However, there are insufficient tools, guidance materials, and studies for determining the value of green buildings. When comparing the cost of green buildings and eco-friendly certification systems, we must consider whether the certification system is viewed from a regulatory or a benefit perspective. This study is a foundational study for the appraisal of eco-friendly buildings. It focused on building energy efficiency certification among eco-friendly certification systems and the construction cost factors that affect the cost method from a regulatory standpoint. Accordingly, we conducted a theoretical review focusing on research data pertaining to the domestic and international construction costs of eco-friendly buildings, as well as appraisal standards and guidelines. Additionally, examples of construction costs were applied and compared to reflect the value of eco-friendly buildings from the perspective of cost method. It is necessary to differentiate between use value and capital premium when calculating reconstruction costs and facility prices. In addition, an expert council must discuss cases in which the certification validity period has expired.

DETERMINING THE OPTIMUM LOCATION OF TWO-FLEXIBLE OUTRIGGER SYSTEMS IN TALL BUILDINGS USING ENERGY METHOD

Construction of tall buildings has been rapidly increasing worldwide, introducing new challenges that demand rigorous engineering. Structural and nonstructural damage to tall buildings can be minimized by implementing appropriate lateral resisting systems, such as the outrigger and belt-truss system. The location of outrigger and belt-truss systems plays a critical role in the behavior, structural integrity, safety, and overall construction cost of tall buildings subjected to lateral loads; thus, they should be selected carefully. This research develops a framework that can determine the optimum location of two flexible outrigger and belt-truss systems in skyscrapers subjected to uniform lateral loading. To achieve this goal, an energy method is applied to maximize the outrigger and belt-truss system’s strain energy. In this approach, the framed tube and effect of outrigger and belt-truss systems on shear core are modeled as a cantilevered hollow section beam with orthotropic plates and rotational springs placed at outrigger and belt-truss location respectively. The optimal location is determined where the rotational spring absorbs the most amount of energy; and this is accomplished by setting the first derivative of the energy equation with respect to the spring’s location, as measured from the structure’s base, to zero. The practical graph developed in this research can aid engineers during the preliminary design of tall buildings for quick calculation of the optimum locations of outrigger and belt-truss systems.

Application of machine learning techniques in estimating the construction cost of residential buildings in the Middle East region

The recent global economic crisis resulted in a crash in the real estate market. This has underscored the significance of accurately predicting construction costs for real estate units in the near-term economy. Over the past few decades, there has been limited research conducted on forecasting the construction costs of housing units. Effective cost forecasting, particularly during the early stages, can play a crucial role in minimizing expenses and ensuring the viability of a project. In recent years, the utilization of machine learning techniques has witnessed a significant surge. These techniques offer generalized solutions and demonstrate favorable performance in terms of effort, time, and cost. Therefore, the objective of this paper is to compare the capabilities of different machine learning methods in estimating real estate construction costs. As part of the study, multiple economic variables and indices will be used as inputs for the machine learning models. The paper will also assess and discuss the performance of each technique by comparing it against actual measurements. Ultimately, the aim is to identify the most suitable approach for such cost estimation tasks.

Effects of Slab Types on the Seismic Behavior and Construction Cost of RC Buildings

Reinforced concrete-framed buildings are commonly preferred to other types of buildings in Turkey. In these types of buildings, a two-way slab with beams, flat, waffle, and ribbed slab types are widely used. In building design, determining the best slab type that will perform well under gravity and lateral loads, with the least cost, is required. However, the proper selection of slab type has generally been overlooked by designers due to the emphasis on other structural members, such as beams, columns and structural walls. For this reason, the structural contribution of floors to building design has not been adequately examined. This shortcoming must be inspected in detail starting from the very first step of the design stage of a building. This study assesses the effects of different slab types on multi-story reinforced concrete buildings by investigating their structural behaviors while trying to optimize their overall cost. For this purpose, a total of 36 structural models were constructed, analyzed, and designed according to the current Turkish Building Codes and Standards. The type of slab system (a two-way slab with beams, flat, waffle and ribbed), the number of floors (10, 20 and 30), and span length (6, 7.5, and 9 m) were selected as the key parameters in these analyses. The buildings were assumed to be office buildings located in a seismically-active zone in Istanbul. The results indicated that a two-way slab with beams was the most economical slab type for 6-meter spans, while the waffle slab was the most economical for spans larger than 7.5 meters. Based on these results, the flat slab was found to be the most expensive slab type in all cases. Out of all slab types, the two-way slab with beams exhibited better earthquake performance, while the waffle and flat slabs provided relatively poor earthquake performances.

Comparison of construction cost of residential buildings in Sri Lanka: offsite vs onsite

Offsite construction (OSC) entails the planning, designing, manufacturing, transportation, and assembly of prefabricated building components at the construction site. As recommended in previous studies, the offsite construction technique can be considered a high-quality and cost-effective construction method that consumes less time and labour while delivering higher productivity. Consequently, it is recognized as a sustainable solution compared to existing onsite structures in countries like Sri Lanka, given the restriction on the availability of resources and high constructional cost. However, this technique is underutilized in the Sri Lankan construction industry, creating a significant void that must be addressed with sufficient cost data and broader access to knowledge regarding the positive impacts of the technique. This research seeks to evaluate current OSC practices together with a comparison of the cost of two similar-natured onsite and offsite residential projects to determine the economic feasibility of OSC in Sri Lanka. The required cost data were extracted through semi-structured interviews with the professionals who engaged in building projects and document reviews. The comparative analysis indicated that beams, columns, masonry walls, and wall finishes (plastering) are contributing to 100% cost-saving in offsite projects compared to onsite projects due to the offsite concrete wall. Further, concrete walls, stairs and ramps, roofs, and floor slab shows 25%, 16%, 12%, and 8% cost saving for the off-site project compared to an onsite project, respectively. Hence, the adoption of off-site elements would enable construction clients and investors to achieve substantial savings in the construction cost of buildings.

Material quantities and estimated construction costs for new elevated IRC 2015-compliant single-family home foundations

Residential foundation selection is critical for the lifetime performance of the project, but the type of foundation selected can depend on cost. This study aims to compare the new construction costs of residential slab-on-fill and four types of crawl space foundations for residential projects by quantifying the material quantities for each and exploring the effect of building characteristics on material quantities and total costs. The building characteristics selected are size (139 m2, 186 m2, and 232 m2), footprint aspect ratio (1:1, 1:2.5, and 1:5) and first floor elevation (0 m–1.2 m in 0.3 m increments). We find that material quantities and total costs change not only with building size and elevation, but also with footprint aspect ratio. Applying 2022 RSMeans Building Construction Cost data, the results show that for any building size, aspect ratio, or elevation, raised wood flooring on pier foundations ($118–$180 per m2) and slab on fill ($103–$211 per m2) are the least expensive, while crawl space foundations with stemwalls are the most expensive ($147–$280 per m2). The results of this study can be used by residential builders, developers and designers in evaluating foundation costs and design alternatives. The methodology may also be adapted for use in other applications such as flood mitigation or energy efficiency projects or environmental sustainability assessments.

Utilizing the Monte Carlo Simulation for Estimating Construction Costs of Residential Buildings

Utilizing the Monte Carlo Simulation for Estimating Construction Costs of Residential Buildings

Costs of Implementing Design for Adaptability Strategies in Wood-Framed Multifamily Housing

Owners, occupants, and society are constantly changing the demands and expectations placed on buildings. Design for adaptability (DfA) provides one approach for delivering buildings that serve current needs and that can be readily adapted to meet future demands. The benefits and strategies of DfA have been widely reported; however, there is a dearth of information on the costs of implementing DfA. This paper presents a case study evaluating the economic costs of applying select DfA strategies to a wood-framed multifamily residential building in Atlanta. Comparisons are made between the construction costs of a baseline non-DfA building and a series of adaptable buildings. DfA strategies in the adaptable buildings include increased floor live load, increased floor-to-floor height, and the use of post-and-beam framing instead of interior structural walls. When all three of these strategies were implemented in the same design, the estimated building construction cost increased by 14%. The cost increase ranged from 1% to 7% when only one of the DfA strategies was implemented in a design. These comparisons are intended to facilitate cost–benefit analyses by designers, owners, and contractors interested in intentionally designed adaptable buildings.

Scaling of the simulated pass-by measurement based on the vehicle's acoustic centre

Preliminary work by the IPEK - Institute of Product Engineering at KIT has shown that the simulated pass-by measurement for exterior noise homologation of vehicles has relevant optimization potential: the measurement can be carried out in smaller halls and with a smaller measurement setup than required by the standard and thus with less building construction cost and measurement effort. A prerequisite for this, however, is the scaling of the entire setup. For the scaling to work correctly, the sound sources of the vehicle must be combined to a single point sound source - the acoustic centre. Therefore, in a preliminary work, the IPEK developed a method, with the help of which the dominant sound sources of a vehicle can be localized and combined to an acoustic centre. In this work, the method is applied exemplarily on two test vehicles and their acoustic centres are determined. Afterwards, the measurement setups for both vehicles are scaled based on the acoustic centres, Finally, the simulated pass-by measurement with the scaled measurement setup is performed on an acoustic roller test bench and the scaled sound pressure levels are determined. To verify the overall method, the results of the scaled pass-by measurements are compared with the unscaled one and with measurements on the test track.

Time series analysis of building construction cost index in Türkiye

Time series analysis of building construction cost index in Türkiye