Building Cost Research Articles

Road Tolling and Domestic Revenue Mobilisation in Zimbabwe

The study analyses the effectiveness of road tolling-systems as an instrument for mobilising domestic revenue in Zimbabwe. The study assessed the effectiveness of road-tolling systems in mobilising revenue to recoup the costs of building, operating and maintaining road infrastructure. Revenue performance was rated using the internal and external dimensions of toll revenue, which revolve around activities such as toll revenue collection, administration (remittance) as well as the Zimbabwe National Road Administration’s (ZINARA’s) distribution and usage of the toll revenue. By way of mixed methods research design, the study conceptualised and contextualised the theory, models, technologies and practices of toll revenue collection in Zimbabwe. The study found that the Zimbabwean road tolling model as a hybrid conventional tolling model is a progressive, effective and reliable tool to raise revenue for constructing road infrastructure and related road-related capital investments in Zimbabwe and that the internal toll revenue performance is up-to-date with reduced toll revenue leakages and increased toll revenue yield. However, the study found that there is no meaningful investment on the road network and related highway infrastructure thus making the performance of external toll revenue questionable. The study recommended the strengthening of toll revenue collection, management, remittance and toll fees usage.

Optimizing Construction Cost Control through BIM5D Digitalization: A Case Study on the Application of Glodon Software in China

Cost managers in China have established cost control information platform for a construction phase, based on BIM5D technology, allowing for the timely and efficient integration of all cost data throughout the construction phase. However, only a small amount of study has examined BIM5D's potential for controlling building costs. Therefore, the Glodon BIM5D software is used in this study to shed some light on the software's benefit, in the construction sector who were directly involved in projects using Glodon identify the factors that influenced the development of BIM5D and propose efficient strategies to improve the software's usage in construction cost control. Key personnel BIM5D were interviewed in semi-structured interviews using a case study approach to gather data for this study. Six informants from two projects were interviewed. Interestingly, Glodon’s high mobility capabilities were found a new finding in relation to the benefit of the application of the software. The most significant obstacles in using the software were cost and usability. Finally implementing effective talent development programs to improve the skills and capabilities of employees, enabling them to leverage BIM5D, was found one of the most effective strategies in this study. This study contributed significantly to introducing Glodon BIM5D software and promoting its adoption within the organization, leading to improved efficiency and effectiveness of cost control in a project environment

Dreaming of efficient markets? Residential construction, competition & affordability in the Swedish housing sector

This paper problematises the perception that enhanced competition within the Swedish residential construction sector offers a panacea to rising building costs and deteriorating housing affordability. The paper investigates the relationships between housing production, exchange, and consumption from three perspectives: (i) an historical analysis of the residential construction industry; (ii) elite semi-structured interviews with stakeholders, and (iii) an exploration of state crisis management. Instead of viewing competition within the construction sector as an isolated sphere, we argue that the inherent unevenness within this sector needs to be grasped in combination with broader political-economic developments. We claim that rising productions costs (particularly in the tenant-owner sector) have been fuelled by soaring land prices, and that this situation has provided fertile terrain for rent-seeking throughout the housing supply chain. We conclude that calls for more competition, both in Sweden and further afield, tend to oversimplify the complex issue of housing provision and shroud more fundamental housing system imbalances.

IS SUSTAINABILITY COSTLY? EMPIRICAL EVIDENCE FROM BUILT PROJECTS

ABSTRACT The affordability of sustainable building remains a significant challenge; developers, building owners, and design teams often point to high construction costs as the primary obstacle hindering the uptake of sustainable building. Because of a lack of clarity, empirical studies and evidence supporting the claim of sustainable building as expensive are inadequate, thus the perceived high cost of sustainable building is still debatable. This study has a three-pronged approach: (1) to collect actual construction costs of certified sustainable buildings, (2) to take a deep dive into construction cost using empirical data and analyze the correlation between the level of sustainability and the construction cost, and (3) to examine the influence of cost components on the total construction cost. Data from 72 LEED buildings was collected and included in the analysis. The findings show the following: (a) the construction costs of the studied sustainable buildings are comparable to those of conventional buildings (even lower); (b) the correlation between the level of sustainability and the construction cost is inconclusive; and (c) soft costs, especially the design cost, have a similar level of influence on the total construction cost as those of hard costs.

Development of a low-cost quad-extrusion 3D bioprinting system for multi-material tissue constructs

This study presents the development and characterization of a low-cost bioprinting system with a compact low-profile quad-extrusion bioprinting head for producing multi-material tissue constructs. The system, created by modifying an off-the-shelf three-dimensional (3D) printer, enables larger print volumes compared to extant systems. Incorporating gelatin methacrylate (GelMA) as a bioink model, the bioprinting system was systematically tested with two different printing techniques, namely the traditional in-air printing (IAP) mode along with an emerging support bath printing (SBP) paradigm. Structural fidelity was assessed by comparing printed structures under different conditions to the computer-aided design (CAD) model. To evaluate biological functionality, a placental model was created using HTR-8 trophoblasts known for their invasive phenotype. Biological assays of cell viability and invasion revealed that the cells achieved high cell proliferation rates and had over 93% cell viability for a 3-day incubation period. The multi-compartmental 3D-bioprinted in vitro placenta model demonstrates the potential for studying native cell phenotypes and specialized functional outcomes enabled by the multi-material capability of the quad-extrusion bioprinter (QEB). This work represents a significant advancement in bioprinting technology, allowing for the printing of complex and highly organized tissue structures at scale. Moreover, the system’s total build cost is only US$ 297, making it an affordable resource for researchers.

High speed calculation method using convolution for calculating normal and disaster costs of buildings with energy generation and storage facilities

AbstractIn recent years, resilience‐enhanced building buildings have been attracting increasing attention, in which photovoltaic (PV) power generation and storage batteries are installed in office buildings to continue operations even during a grid outage. PV power generation and storage batteries can be introduced to office buildings to continue commercial operations in the case of grid outages. When introducing PV power generation and storage batteries into a building, the total cost, which is the sum of the equipment installation cost and the damage cost in the event of a disaster, is crucial. When installing PV power generation and storage batteries in a building and calculating the total cost of using these facilities in the event of a disaster, it is necessary to consider the uncertainty of power demand and the amount of power generated by PV power generation. Monte Carlo Simulation is a method to consider uncertainty. However, it has a problem that the combination of conditions becomes enormous, and the calculation load is high when the total cost is calculated. Therefore, in this study, we propose convolution as a method to reduce the computational load generated when calculating the probability distribution of the total cost generated by strengthening the resilience of the building.

Dissonances in Building Cost: An Analytic Review of the Impact of Design Variables

The cost of building is influenced by a variety of design variables. There would however appear a paucity of readily available cost data on the impact of design variables. This research is set out with a view towards the establishing readily available cost data information as well as relevant cost indices. The research used case study from previous buildings, extensive reviews, the statistical technique of percentile as its computational technique and rates obtained from synthesized bills priced by professional Quantity Surveying firms, as relevant components of its methodology. The location of the research, Port Harcourt metropolis is situated in Niger Delta region of Nigeria. Research findings from the case study buildings as well as extensive literature review established that there exist differentials in the initial and total costs of both building plan Shapes (Square and rectangular), recording a 12.56 percentage differential. The elemental cost derived from both shapes also established differentials between 0.53 to 17.79%. The study also establishes the perimeter wall and gross floor area ratio which is an important index towards the determination of economic building shapes. The research concludes that the results, from the case study building would appear limited and as such should avoid being overgeneralized, nevertheless, it does serves to further reveal in broad terms, that the influence of plan shapes of simple buildings on cost is minimal. It recommends further, exploratory study that focuses on design and their cost implications, using cost models that input a wider range of variables

A Scalable Compact Additively Manufactured Molten Salt to Supercritical Carbon Dioxide Heat Exchanger for Solar Thermal Application

Abstract Design of an additively manufactured molten salt (MS) to supercritical carbon dioxide (sCO2) primary heat exchanger (PHE) for solar thermal power generation is presented. The PHE is designed to handle temperatures up to 720 °C on the MS side and an internal pressure of 200 bar on the sCO2 side. In the core, MS flows through a three-dimensional periodic lattice network, while sCO2 flows within pin arrays. The design includes integrated sCO2 headers located within the MS flow, allowing for a counterflow design of the PHE. The sCO2 headers are configured to enable uniform flow distribution into each sCO2 plate while withstanding an internal pressure of 200 bar and minimizing obstruction to the flow of MS around it. The structural integrity of the design is verified on additively manufactured (AM) 316 stainless steel sub-scale specimens. An experimentally validated, correlation-based sectional PHE core thermofluidic model is developed to study the impact of flow and geometrical parameters on the PHE performance, with varied parameters including the mass flowrate, surface roughness, and PHE dimensions. A process-based cost model is used to determine the impact of parameter variation on build cost. The model results show that a heat exchanger with a power density of 18.6 MW/m3 (including sCO2 header volume) and effectiveness of 0.88 can be achieved at a heat capacity rate ratio of 0.8. The impact of design and AM machine parameters on the cost of the PHE are assessed.

Optimization and dynamic techno-economic assessment of integrated combined ejector cooling, heating, and power system

Solar energy systems have been extensively studied for their potential to reduce greenhouse gas emissions and their economic feasibility in buildings. However, due to the high initial cost, the implementation of these systems has been limited. This study proposes an innovative energy system, incorporating Photovoltaic Thermal (PVT) technology without batteries and heaters, and ejector cooling for smart buildings that can interact with the power grid. The proposed system aims to offset the energy costs of buildings by selling excess electricity to the grid. Both thermodynamic and economic analyses were conducted using TRNSYS software, and optimization was applied to meet maximum exergy efficiency and minimum cost objectives. Results indicate that the maximum annual exergy efficiency of the system can reach 21.98%, while the minimum total production cost unit is $22.48/MWh. Operating conditions yield an annual exergy efficiency of 14.18%, with a total production cost unit of $34.01/MWh. Overall, findings demonstrate that this proposed system can efficiently provide electricity to the building while offering surplus energy for sale to the grid.

Internet of Things (IoT) in Buildings: A Learning Factory

Advances towards smart ecosystems showcase Internet of Things (IoT) as a transversal strategy to improve energy efficiency in buildings, enhance their comfort and environmental conditions, and increase knowledge about building behavior, its relationships with users and the interconnections among themselves and the environmental and ecological context. EU estimates that 75% of the building stock is inefficient and more than 40 years old. Although many buildings have some type of system for regulating the indoor temperature, only a small subset provides integrated heating, ventilation, and air conditioning (HVAC) systems. Within that subset, only a small percentage includes smart sensors, and only a slight portion of that percentage integrates those sensors into IoT ecosystems. This work pursues two objectives. The first is to understand the built environment as a set of interconnected systems constituting a complex framework in which IoT ecosystems are key enabling technologies for improving energy efficiency and indoor air quality (IAQ) by filling the gap between theoretical simulations and real measurements. The second is to understand IoT ecosystems as cost-effective solutions for acquiring data through connected sensors, analyzing information in real time, and building knowledge to make data-driven decisions. The dataset is publicly available for third-party use to assist the scientific community in its research studies. This paper details the functional scheme of the IoT ecosystem following a three-level methodology for (1) identifying buildings (with regard to their use patterns, thermal variation, geographical orientation, etc.) to analyze their performance; (2) selecting representative spaces (according to their location, orientation, use, size, occupancy, etc.) to monitor their behavior; and (3) deploying and configuring an infrastructure with +200 geolocated wireless sensors in +100 representative spaces, collecting a dataset of +10,000 measurements every hour. The results obtained through real installations with IoT as a learning factory include several learned lessons about building complexity, energy consumption, costs, savings, IAQ and health improvement. A proof of concept of building performance prediction based on neural networks (applied to CO2 and temperature) is proposed. This first learning shows that IAQ measurements meet recommended levels around 90% of the time and that an IoT-managed HVAC system can achieve energy-consumption savings of between 10 and 15%. In summary, in a real context involving economic restrictions, complexity, high energy costs, social vulnerability, and climate change, IoT-based strategies, as proposed in this work, offer a modular and interoperable approach, moving towards smart communities (buildings, cities, regions, etc.) by improving energy efficiency and environmental quality (indoor and outdoor) at low cost, with quick implementation, and low impact on users. Great challenges remain for growth and interconnection in IoT use, especially challenges posed by climate change and sustainability.

A technique for modelling networks with junctions and what it tells us about the Roman road network of Gaul

Many different techniques have been applied for the construction of putative networks to model connectivity and communication between ancient settlements. The large majority of these networks consist of edges joining at settlement nodes, without representing the fact that real road systems have junctions and crossroads at locations away from settlements. Here it is shown that the minimum total cost principle of network generation, based on optimising the balance of build and travel cost, can be extended to generate junctions and crossroads. This further improves the cost-benefit ratio by reducing road length for little penalty to the traveller. The resulting junctions divide into two main groups – perpendicular and oblique – with angular separation increasing and relative frequency changing as network complexity increases. Analysis of the population of junction angles in the Roman road network in Gaul suggests strong similarity to theoretical networks with a travel-to-build cost ratio of 7, similar to that found by a different technique in an earlier study, encouraging some credence that the network construction methodology approximates actual practice. The angle distribution further suggests a model based on local networks built around pre-existing through-roads.

Toward Sustainable Manufacturing Facilities: Utilization of Solar Energy for Efficient Scheduling of Manufacturing Processes

Abstract The utilization of solar energy as a renewable energy source has been a subject of interest for researchers in recent years. Despite recent advances in promoting solar energy, its intermittent and unpredictable nature limits its widespread utilization in manufacturing facilities. This research paper focuses on utilizing solar energy for efficient scheduling of manufacturing processes while keeping friendly environmental conditions for the workers. The work proposes an energy-aware dynamic scheduling procedure to minimize production and building costs by optimizing the utilization of an onsite photovoltaic (PV) system energy generation. The proposed method considers various factors such as the availability of solar energy, energy consumption of different manufacturing processes, and thermal requirements of the building. A stochastic energy prediction algorithm is developed to forecast the hourly one-day-ahead solar resources based on year-long solar radiation observations collected from an outdoor solar test facility in Qatar. This study shows that using the forecasted PV output improves the overall efficiency of manufacturing processes and building thermal requirements, thus achieving up to a 20% reduction in energy costs. These findings help the development of sustainable manufacturing systems and decrease the negative environmental impacts from industries.

Methodological aspects of optimization of energy consump-tion costs of low-rise buildings with a built-in air heat pump

Objective. The rational use of fuel and energy resources is one of the urgent problems. One of the promising ways to solve this problem is the use of environmentally friendly energy-saving air source heat pumps based on the use of non-traditional energy sources. The use of such innovative energy-saving technologies requires not only modern architectural and planning, design and engineering solutions, but also sound methodological recommendations for as-sessing their energy efficiency and feasibility. The article presents a methodology for calculating the consumed electrical energy and heat generation, as well as the seasonal indicator of energy efficiency in the operation of an air source heat pump.Method. The technique takes into account, as input data, experimental data from tests of high-voltage heat pumps in terms of heat output depending on the change in the temperature of the source of low-grade heat and the temperature regime of the coolant.Result. The need to develop a methodology is due to the shortcomings in the regulatory documents of the methodological basis for optimizing energy costs and heat generation by heat pumps. The accuracy of calculating the operating costs that will occur during the heating period of the air source heat pump (AHP) depends on the correct accounting of the required heat load of a low-rise building and the consumption of electricity to ensure it.Conclusion. This technique can be applied not only to calculate the annual operating costs of using a heat pump and determine the structure of energy consumption (thermal and electrical), but also to optimize the energy parameters of HHP with an assessment of the energy efficiency of different options for their configurations.

Application of business model canvas to merchandising sterile supplies from a hub hospital to smaller hospitals in India

BackgroundOutsourcing and regionalization of Central Sterile Supply Department (CSSD) could mutually benefit both smaller and bigger hospitals. Larger hospitals with established CSSDs have an opportunity to extend their services to maximize the utilization of their equipment. For outsourcing the sterile supplies department to smaller hospitals, extra capital investment is not required. This study highlights the application of merchandizing sterile supplies from hub hospital with a large CSSD to smaller hospitals. MethodsA prospective observational study is conducted at a hub hospital with return on investment observations as the study tool. Business Model Canvas was used to identify spoke hospitals. Two business options, known as the processing model and the rental model, were proposed to the owners of spoke hospitals. ResultIn both models, the infrastructure of CSSD is owned by the hub hospital. In the processing model, the smaller hospital owns the instruments, and in the rental model, hub hospital supplies instruments, and spoke hospitals pay rent for the instruments. The cost of CSSD building and equipment, sterilizing cost, manpower costs, and transporting costs were considered. In the processing model, the profit to the hub hospital will be 60%, 44%, and 28% annually. In the rental model, we see diminished profit margins of 50%–35%. ConclusionThe smaller hospitals can benefit by avoiding investing in infrastructure, skilled workforce, and space. The bigger hospitals can use their vast existing infrastructure more efficiently and break-even quicker on the initial capital investment.

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.

Enhancing Building Energy Efficiency with Aluminum Composite Material Facade: A Performance Simulation Study using Building Energy Modeling and Building Information Modeling

Building facade is an integral piece to the overall design of a building, which not only ensures adequate interior thermal comfort, minimizing cooling load rate but also lowering overall building energy consumption. In recent years, aluminum composite material wall (ACM) is a new decorative material that is increasingly being used by developers, designers, and architects, which led to many innovative building facade designs. It is a straightforward and versatile product that provides a weather-resistant, sound-insulation, heat-insulation, earthquake-resistant, and shock-resistant façade that is simple to install. As a result, this study proposes a perfomance of energy simulation with ACM material applied in building design using Building Energy Modeling (BEM). Energy simulation in buildings using a Building Information Modeling (BIM) system is proposed to reduce the Energy Use Intensity (EUI) and energy cost of building in its construction process. The results of this study are expected to assist architects and building managers in improving and enhancing the energy efficiency of buildings. These significant findings demonstrate the potential of using ACM wall to improve building energy efficiency.

Sensitivity Analysis of Housing Affordability under Public Private Partnership (PPP) Scheme in Niger State

The provision of affordable housing has been a concern in developed and developing world because of its role in man’s welfare and productivity. This study aimed to carry out a sensitivity analysis of the affordability of a Public Private Partnership (PPP) housing scheme in Niger State. The study set out to establish what can be done to make repayment for such housing affordable for all categories of allotees. Sensitivity analysis was applied to building cost, repayment period and interest rate. Data used for the analysis were sourced through the collection of archival data and carrying out of a questionnaire survey. The random sampling technique was employed in administering the questionnaire to a sample of 187 beneficiaries. Against standard affordability criteria that housing should consume not more than 30 percent of gross household income, the results revealed that only civil servant allotees on Salary Grade Levels 10 - 16 can afford monthly repayments of ₦10, 000.00 for 2-bedroom housing costing ₦1,900,000.00. The application of sensitivity analysis enabled the study to recommend modifications to the PPP housing scheme that will allow all workers on Salary Grade Levels 01 - 16 to afford a 2-bedroom house at a selling price of ₦1,200,000M, mortgage interest of 3 percent and a repayment period of 25 years.

Exploring the Benefits and Limitations of Digital Twin Technology in Building Energy

Buildings consume a significant amount of energy throughout their lifecycle; Thus, sustainable energy management is crucial for all buildings, and controlling energy consumption has become increasingly important for achieving sustainable construction. Digital twin (DT) technology, which lies at the core of Industry 4.0, has gained widespread adoption in various fields, including building energy analysis. With the ability to monitor, optimize, and predict building energy consumption in real time. DT technology has enabled sustainable building energy management and cost reduction. This paper provides a comprehensive review of the development and application of DT technology in building energy. Specifically, it discusses the background of building information modeling (BIM) and DT technology and their application in energy optimization in buildings. Additionally, this article reviews the application of DT technology in building energy management, indoor environmental monitoring, and building energy efficiency evaluation. It also examines the benefits and challenges of implementing DT technology in building energy analysis and highlights recent case studies. Furthermore, this review emphasizes emerging trends and opportunities for future research, including integrating machine learning techniques with DT technology. The use of DT technology in the energy sector is gaining momentum as efforts to optimize energy efficiency and reduce carbon emissions continue. The advancement of building energy analysis and machine learning technologies is expected to enhance prediction accuracy, optimize energy efficiency, and improve management processes. These advancements have become the focal point of current literature and have the potential to facilitate the transition to clean energy, ultimately achieving sustainable development goals.

Life Cycle Cost in Circular Economy of Buildings by Applying Building Information Modeling (BIM): A State of the Art

The building industry is one of the largest consumers of materials resources and significant contributors to global waste. Applying core principles of circular economy (CE) could significantly help the environment by reducing waste and decreasing the life cycle cost of buildings. Several strategies to implement the concept of CE in buildings include design for deconstruction, adaptability, and flexibility. However, implementing these design strategies could face constraints. In this study, we identified 22 barriers related to the adoption of CE in buildings, as reported in the literature. We discussed the role of Building Information Modeling (BIM) in overcoming those barriers. This paper demonstrates how BIM can facilitate the implementation of CE principles while providing critical insights into the life cycle costs of circular buildings. We identified 14 ways to use BIM to foster the implementation of a circular economy approach. To achieve these objectives, we have undertaken a thorough review of recent publications that explore CE design strategies, Life Cycle Costing in the circular construction of buildings, and BIM developments in the building industry. This literature review is based on 88 articles covering BIM’s role in enhancing the management of a building’s end-of-life while reducing the life cycle cost in the circular construction of buildings.

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.