Building Cost Research Articles

4E analysis and multi-objective optimization of an ejector-expansion cascade refrigeration system for building cold storage using low GWP refrigerants

The need for efficient, eco-friendly refrigeration systems operating at ultra-low temperatures (-50°C to -100°C) has spurred interest in cascade designs. Traditional single-stage cycles are constrained by pressure ratios and temperature range, limiting their effectiveness. This study seeks to improve such systems with an ejector-expansion cascade refrigeration system (EECRS) incorporating low global warming potential (GWP) refrigerants and dual ejectors for both high- and low-temperature cycles. It uses a 4E (Energy, Exergy, Exergoeconomic, Exergoenvironmental) analysis and a three-objective optimization focused on cost rate, exergy efficiency, and Coefficient of performance (COP), utilizing TOPSIS methodology with refrigerants R744, R41, R1234yf, and R1234ze. The findings highlight that an R41-R1234yf refrigerant pair performs best at -55°C evaporator and 50°C condenser temperatures, achieving a COP of 1.44, exergy efficiency of 30.81%, and an operating cost of $0.791/h. It yields 13.07 kW cooling from the evaporator and 22.15 kW heat output from the condenser. Exergy destruction primarily occurs in the evaporator (43.75%), condenser (30.43%), and heat exchanger (19.77%), with lesser losses in other components. Environmental destruction factors are highest for the evaporator, condenser, and heat exchanger, with compressors 1 and 2 showing the highest environmental impact rates, at 7.539 and 3.775 mpts/h, respectively. This study introduces low-GWP refrigerants in an advanced EECRS, promoting high-efficiency, sustainable ultra-low temperature refrigeration ideal for industrial and commercial cold storage within building environments, balancing environmental and cost concerns.

Impact of seismic demand on construction costs for buildings up to 8 storeys high

The legally binding earthquake performance requirements in New Zealand's Building Act and Building Code emphasise building collapse prevention, allowing for a certain degree of damage to resist the seismic load. However, societal expectations demand that buildings remain operational after an earthquake. This research aims to understand the true cost of up to 8 storeys high building structures that remain operational after an earthquake. Our assumptions are: 1) higher seismic demand is expected to have a limited impact in overall construction costs, and quite minimal impact on total development costs, and 2) the influence of seismic resilience on construction costs is different depending on the structural system. An extensive construction costs database was developed including the most typical structural and foundation systems. The main conclusions are that 1) the effect of location and floor type on construction costs is not critical, 2) the impact of a higher seismic demand on construction costs depends on the structural system, and 3) foundation type has a large influence on construction costs but seismic demand does not. Engineers should prioritise stiff lateral systems because the cost implications of having a stiffer structural system are minimal, especially when considering the development costs. The cost implications of having more resilient buildings that can be readily occupied after an earthquake are negligible, and New Zealand should move towards stiff, damage resisting structures using well understood structural systems like RC walls. Society expects this from our buildings, our engineers are trained and capable to design them, and the extra cost is minuscule.

Influence of retrofitting in the seismic behaviour of precast reinforced concrete industrial buildings

Previous destructive earthquakes caused large economic losses as well as human losses. Seismic risk studies are of paramount importance to predict the impact of future earthquakes and support seismic risk mitigation policies. The present study presents a seismic risk assessment based on the cost and direct loss assessment of precast industrial buildings with different retrofitting levels in terms of horizontal strength. In this evaluation, a comparative analysis between the configurations of retrofitted buildings and the original building is performed. The effects of retrofitting solution strategies are first investigated in a single building. Then a study is carried out to assess which retrofit solutions level are most appropriate depending on the exposure and seismic risk. The results showed the use of bracing in the PRC building can improve seismic behaviour, with significant increases in horizontal strength. The cost of intervention is reduced, with a slight increase of less than 1% to almost 2% of the cost of the structure. From the derivation of seismic fragility functions for different retrofitting solutions level, the seismic risk analysis with dozens of existing PRC industrial buildings in Portugal points to a large reduction in economic losses as from retrofitted buildings, like an improvement of the seismic capacity of the buildings attributed to the retrofit systems considered. In general, among the different types of retrofit studied, there is an increase in the reduction of total economic losses, namely 49% when retrofitted with a 50% increase in horizontal strength, 58% when retrofitted with a 75% increase in horizontal strength and 64% for retrofitted with 100%.

A Review on Research of Prefabricated Building Costs: Exploring Collaborations, Intellectual Basis, and Research Trends

This analysis provides a comprehensive overview of current research regarding prefabricated construction costs, explained under three main categories: collaboration, intellectual basis, and research trends. The collaboration network covers country, institution, and journal distribution. Intellectual basis includes a cited journal, cited reference, and cited author, while research trends cover research category, keyword and keyword cluster analysis, and cited reference cluster. Through bibliometric analysis, we find that this field has garnered significant attention in the academic community and has developed rapidly. China dominates the field of prefabricated construction, with Curtin University, Chongqing University, and Deakin University being the leading research institutions, while Automation in Construction is the most cited journal. Although technology integration is widely regarded as a key means of cost optimization, its high implementation costs and complexity have limited its widespread application. The challenges of technology integration lie in the need to address high capital costs, complex management practices, and the demand for advanced technology integration, which have become significant barriers to the promotion of prefabricated construction. Moreover, current research also focuses on how to enhance risk control and management practices in cost management to promote sustainable development. Future research will focus on green and sustainable technologies, multidisciplinary engineering, energy and fuel, construction technologies to optimize prefabricated construction techniques, advance low-carbon building practices, and improve decision analysis and risk management. The key factors influencing costs include technological factor, policy factors, market and environmental factors, and organizational management. By systematically controlling these factors, cost pressures can be effectively alleviated, construction efficiency improved, and the sustainability of prefabricated buildings enhanced. This study not only provides a comprehensive analysis of the current state and trends in research on the costs of prefabricated construction but also highlights the critical role of technological innovation, policy optimization, and interdisciplinary collaboration in promoting the sustainable development of prefabricated construction globally.

Optimizing power system efficiency and costs in smart buildings with renewable resources

The increasing industrial development and energy demand have necessitated the maximization of available energy use and the deployment of renewable resources. Effective energy management, optimal modeling, and efficient planning are essential to transform the power system into a high-efficiency, optimal model. This study focuses on the initial step of modeling smart buildings (SBs) equipped with non-responsive devices and renewable photovoltaic sources. A comprehensive energy management (EM) plan is formulated for these buildings, incorporating the KNX protocol for solar energy system management. Batteries are integrated into the building model to store energy during periods of low consumption and serve as generators during peak load conditions, with the primary goal of minimizing power system losses and related costs. To address the complexity of this model, whale optimization algorithm (WOA) is employed for optimization. Optimal candidate buses are selected for interconnected building management based on a suggested sensitivity analysis to minimize losses. Cost performance is then assessed, considering energy production and sales. The findings indicate that substantial control of operating costs can be achieved through strategic management of battery charging and discharging, as well as the utilization of photovoltaic units. The proposed model is evaluated across various scenarios using a test system comprising 30 modified system, demonstrating its effectiveness in enhancing energy efficiency and management.

A Novel Index to Predict the Cost of Green Resilient Buildings

A Novel Index to Predict the Cost of Green Resilient Buildings

Ray Tracing Animated Displaced Micro‐Meshes

AbstractWe present a new method that allows efficient ray tracing of virtually artefact‐free animated displaced micro‐meshes (DMMs) [MMT23] and preserves their low memory footprint and low BVH build and update cost. DMMs allow for compact representation of micro‐triangle geometry through hierarchical encoding of displacements. Displacements are computed with respect to a coarse base mesh and are used to displace new vertices introduced during 1 : 4 subdivision of the base mesh. Applying non‐rigid transformation to the base mesh can result in silhouette and normal artefacts (see Figure 1) during animation. We propose an approach which prevents these artefacts by interpolating transformation matrices before applying them to the DMM representation. Our interpolation‐based algorithm does not change DMM data structures and it allows for efficient bounding of animated micro‐triangle geometry which is essential for fast tessellation‐free ray tracing of animated DMMs.

Sustainability assessment with the green retrofitting concept for building: A study case in the Gresik regency, Indonesia

In green construction, sustainable resources are essential. One such material is copper, which is widely utilized in electronics, transportation, manufacturing, and residential buildings. As a very useful material, it has many beneficial impacts on human life. Observed from the recent demand spike is in line with the overall trend and the current growing smelter construction in Indonesia. Researchers intend to adapt the existing Copper Smelting Plant Building into an environmentally friendly building as a part of the production chain, in addition to reducing public and environmental concerns about the consequences of this development. We have identified a disparity in cost, where the high cost of green buildings is an obstacle to its implementation to enhance the cost performance with increased renewable energy of the Smelter Construction Building, this study investigates the application of LEED parameters to evaluate green retrofit approaches through system dynamics. The most relevant features of the participant assessments were identified using the SEM-PLS approach, which is used to build and test statistical models of causal models. We have results for this Green Retrofitting study following significant variables according to the following guidelines: innovation, low-emission materials, renewable energy, daylighting, reducing indoor water usage, rainwater management, and access to quality transit.

Rapid remote volcanic ashfall impact assessment for the 2022 eruption of Hunga volcano, Tonga: a bespoke approach and lessons identified

When disasters occur, rapid impact assessments are required to prioritise response actions, support in-country efforts and inform the mobilisation of aid. The 15 January 2022 eruption of Hunga volcano, Tonga, and the resulting atmospheric shockwave, ashfall, underwater mass disturbance and tsunami, caused substantial impacts across the Kingdom of Tonga. Volcanic impacts on the scale observed after the eruption are rare, necessitating a reliance on international advice and assistance. The situation was complicated by the loss of Tonga’s international submarine fibreoptic cable (causing a complete loss of communications for approximately 20 days) along with border closures due to the COVID-19 pandemic. A need emerged for a rapid remote volcanic impact assessment and provision of specialist advice to help inform the response of international partners. Here we present a novel methodology for conducting rapid remote volcanic ashfall impact assessments, conducted over a 10-day period following the eruption. We used three different hazard models for ashfall thickness across the main island of Tongatapu and available asset information and vulnerability functions for buildings, agriculture, electricity networks, water supply and roads, to provide initial estimates of losses due to ashfall from the 15 January eruption. For buildings, we estimated losses both as total losses and as percentages of the total replacement cost of buildings on Tongatapu. For agriculture, we made probabilistic estimates of production losses for three different crop classes. For ashfall clean-up, we estimated ranges of ashfall volumes requiring clean-up from road surfaces and roofs. For water supply, electricity networks and roads, our analysis was limited to assessing the exposure of important assets to ashfall, as we had insufficient information on system configurations to take the analysis further. Key constraints on our analysis were the limited nature of critical infrastructure asset inventories and the lack of volcanic vulnerability models for tropical regions including Pacific Island nations. Key steps towards iteratively improving rapid remote impact assessments will include developing vulnerability functions for tropical environments as well as ground-truthing estimated losses from remote approaches against in-person impact assessment campaigns.

OPTIMIZING HVAC EFFICIENCY AND RELIABILITY: A REVIEW OF MANAGEMENT STRATEGIES FOR COMMERCIAL AND INDUSTRIAL BUILDINGS

This study presents a comprehensive review of strategies to optimize HVAC systems in commercial and industrial buildings, focusing on enhancing energy efficiency, system reliability, and environmental sustainability. HVAC systems are major energy consumers, contributing significantly to operational costs in large buildings. With increasing energy costs, regulatory pressures, and the push for sustainability, technological advancements and management strategies have emerged to improve HVAC performance. Following PRISMA guidelines, this review analyzed 58 high-quality peer-reviewed studies published between 2010 and 2023. Key findings show that energy management systems (EMS) can reduce energy consumption by up to 30%, while Building Management Systems (BMS) enhance system reliability through centralized control and predictive maintenance. The adoption of eco-friendly refrigerants and energy-efficient designs, such as heat recovery and variable refrigerant flow (VRF) technologies, further lowers energy usage and environmental impact. Additionally, integrating renewable energy sources like solar and geothermal into HVAC systems can reduce energy consumption by as much as 40%. Green building certifications, such as LEED and BREEAM, drive the adoption of optimized HVAC technologies, delivering both environmental and financial benefits. This review underscores the crucial role of HVAC optimization in reducing energy consumption, lowering carbon footprints, and improving the operational performance of buildings, offering valuable insights for building managers, engineers, and policymakers.

Cost Contingency Strategies in Building Construction: Evaluating Project Risk Influence

Contingency costs are an important part of construction to achieve successful project management. In determining contingency costs, practitioners have used a very subjective approach. This study discussed the determination of the contingency cost of high-rise buildings in six research object projects, based on the results of risk evaluation. The risk evaluation used in this paper is based on the risks in the construction phase. The method used to know the relationship between risk and contingency costs is simple linear regression with tools. The results of this study indicate that the greater the level of risk, the greater the contingency costs incurred by the project. the risk level contributed 71.6% to the contingency cost, while the rest was influenced by other factors. The equation formed is, that if the risk increases by 1 unit, the total contingency cost will increase by 0.0916 units.

Harvesting fragmented boreal forest: system selection using a simulation-optimization approach

ABSTRACT Nordic forests, such as those found in Canada were known to offer opportunities for large and relatively homogeneous harvesting blocks. Increased fragmentation of forests makes operation planning more difficult and affects costs of road building and machinery relocation. Currently, the diversity of systems used for forest operations in eastern Canada represents only a fraction of existing alternatives. It might be that at least one alternative outperforms the systems currently used in the fragmented boreal forest. Hence, a subset of potential systems was identified in a preliminary evaluation of harvest systems in fragmented operations. From this sample, the objective is to develop a mathematical model to identify the harvest system with the lowest wood procurement cost in fragmented boreal forests. The candidate systems were simulated and optimized using a static deterministic approach. According to our results, the best systems in fragmented forests involve fewer machines, hence a lower relocation cost. Two CTL systems outperformed all others. The system using removable crane self-loading trucks for transport and the one using the forwarder for loading both resulted in 4 $/m3 (USD) advantage over the third least expensive system in the most fragmented harvest sites. The proposed model can be directly applied to assess harvest systems in other parts of the world with similar forest fragmentation challenges.

Competitive Data-Structure Dynamization

Data-structure dynamization is a general approach for making static data structures dynamic. It is used extensively in geometric settings and in the guise of so-called merge (or compaction) policies in big-data databases such as LevelDB and Google Bigtable. Previous theoretical work is based on worst-case analyses for uniform inputs—insertions of one item at a time and non-varying read rate. In practice, merge policies must not only handle batch insertions and varying read/write ratios, they can take advantage of such non-uniformity to reduce cost on a per-input basis. To model this, we initiate the study of data-structure dynamization through the lens of competitive analysis via two new online set-cover problems. For each, the input is a sequence of disjoint sets of weighted items. The sets are revealed one at a time. The algorithm must respond to each with a set cover that covers all items revealed so far. It obtains the cover incrementally from the previous cover by adding one or more sets and optionally removing existing sets. For each new set the algorithm incurs build cost equal to the weight of the items in the set. In the first problem the objective is to minimize total build cost plus total query cost , where the algorithm incurs a query cost at each time \(t\) equal to the current cover size. In the second problem, the objective is to minimize the build cost while keeping the query cost from exceeding \(k\) (a given parameter) at any time. We give deterministic online algorithms for both variants, with competitive ratios of \(\Theta(\log^{*}n)\) and \(k\) , respectively. The latter ratio is optimal for the second variant.

A LSTM algorithm-driven deep learning approach to estimating repair and maintenance costs of apartment buildings

PurposeThis study proposes a deep learning algorithm-based model to predict the repair and maintenance costs of apartment buildings, by collecting repair and maintenance cost data that were incurred in an actual apartment complex. More specifically, a long short-term memory (LSTM) algorithm was adopted to develop the prediction model, while the robustness of the model was verified by recurrent neural networks (RNN) and gated recurrent units (GRU) models.Design/methodology/approachRepair and maintenance cost data incurred in actual apartment complexes is collected, along with various input variables, such as repair and maintenance timing (calendar year), usage types, building ages, temperature, precipitation, wind speed, humidity and solar radiation. Then, the LSTM algorithm is employed to predict the costs, while two other learning models (RNN and GRU) are taught to validate the robustness of the LSTM model based on R-squared values, mean absolute errors and root mean square errors.FindingsThe LSTM model’s learning is more accurate and reliable to predict repair and maintenance costs of apartment complex, compared to the RNN and GRU models’ learning performance. The proposed model provides a valuable tool that can contribute to mitigating financial management risks and reducing losses in forthcoming apartment construction projects.Originality/valueGathering a real-world high-quality data set of apartment’s repair and maintenance costs, this study provides a highly reliable prediction model that can respond to various scenarios to help apartment complex managers plan resources more efficiently, and manage the budget required for repair and maintenance more effectively.

Selecting suitable passive design strategies for residential high-rise buildings in tropical climates to minimize building energy demand

Passive design strategies (PDS) are a fitting solution to reduce the ever-growing energy cost of residential high-rise buildings in tropical regions. However, PDSs’ building energy saving potential significantly varies with local climate conditions, but it has been sparsely investigated. Hence, this study investigated the energy-saving efficiency of eight common PDSs integrated into a typical residential high-rise building in three sub-climates: extremely hot humid (0 A), very hot humid (1 A), and warm humid (3 A) defined by ASHRAE for the tropical climate. This study developed a Building Performance Analysis (BPA) workflow with a BIM-based simulation framework and local and global sensitivity analyses for the building energy analysis. The global sensitivity analysis revealed that low e-coating on glasses is the most influential PDS for 0 A and 1 A climates, but it has a negative effect in the sub-climate zone 3 A. The low-conducting exterior walls are the most effective PDS in the sub-climate zone 3 A, but they are poorly performed in the other two sub-climate zones. Based on the energy calculation and sensitivity analysis, this study proposes the best PDS groups, saving up to 40.1 %, 63.5 %, and 31.7 % of average annual building consumption in the sub-climate zones, 0 A, 1 A, and 3 A climates.

Geographic Information System Using Postgre SQL-QGIS for Slum Squatter Distribnution Mapping in North Jakarta

This research aim to build a geographic information system that displays a mapping of slum building distribution in North Jakarta. One of spatial software was developed using a method is the Rational Unified Process (RUP) method. This research aim to build a geographic information system that displays a mapping of building distribution in North Jakarta. This system was built using Postgre SQL and QGIS to build map. The research finding in the research is that there is a tendency for built-up areas to grow in slum areas due to the absence of rental fees, land and building costs, but the feasibility conditions of these areas are very unsuitable. This research is limited to implementing the use of Postgre SQL and QGIS software. Because the rendering process for the visual display is very difficult. I hope that in the future this research will be developed interesting 3D visualization accompanied by charts. The implication of this research is to make it easier to see the distribution of dense and slum areas and become a step for the government in making policies. The originality of this research is that there is still no one who combines the two software in mapping analysis.

Does distance from government hinder enterprises’ OFDI？Evidence from China

This study analyzes the impact of government–enterprise distance on the probability of outward foreign direct investment (OFDI) with matched data from Chinese prefecture-level municipal governments, the Chinese industrial enterprises database, and the directory of overseas investment enterprises. We determine that increased distance between the government and enterprises has a significant negative impact on the probability of enterprises’ OFDI. Mechanism analysis demonstrates that increased government–enterprise distance, which causes higher information search and relationship building costs, and decreased accessibility of public service, are the main reasons for this decline.

Evaluating conventional and renewable energy systems for green buildings: A case study on energy efficiency and cost optimization

This study explores two primary categories of power generation: conventional methods reliant on fossil fuels and renewable energy methods. Fossil fuel-based approaches, including natural gas and heavy fuel oil, contribute to environmental concerns due to their carbon dioxide (CO2) emissions, which are responsible for the greenhouse effect and global warming. Many nations, particularly in Europe, have implemented stringent measures to restrict CO2 emissions, imposing fines on industries that exceed emission limits. In response to these concerns, this study focuses on a green building project that aims to meet its power requirements through renewable energy sources. Various renewable energy resources will be evaluated, considering the merits and drawbacks of each technology, to identify the most suitable option for the building under investigation. Additionally, a comprehensive thermodynamic analysis will be conducted, including calculations of electrical needs such as cooling load, lighting load, and equipment load. A customized power calculator will also be developed for application in similar projects. The ultimate objective of this study is to achieve complete autonomy from the electric grid by utilizing renewable energy resources, transforming the building into a green building. The results indicate that at an outside temperature of 22 °C, the total heat gain decreases from 157.3 to 39 kW, reducing the total cost of electricity from 20,000 to 5100 AED/year. Conversely, at an outside temperature of 50 °C, the total heat gain increases from 157.3 to 196 kW, raising the total cost of electricity from 20,000 to 26,000 AED/year. These findings demonstrate the significant influence of outside temperature on the building's energy requirements and costs, underscoring the importance of considering temperature variations in energy efficiency and cost optimization strategies.

Cost and Benefit Analysis of Different Buildings Through Reuse of Treated Greywater

The fact that the impacts of climate change cannot be prevented in the short term has increased the importance of climate change adaptation activities, and many national and international studies have been initiated in this regard. Greywater reuse (GWR) activities have become important methods recommended by the Intergovernmental Panel on Climate Change (IPCC) for adaptation to climate change. This study selects GWR from 3 different real typologies, a hotel, a residential building, and an industrial plant planned in Izmir Province of Türkiye, to design greywater systems followed by cost-benefit analyses. The applicability of GWR systems in these typologies has been analyzed, and comparisons have been made. GWR systems at the project design stage eliminate the need for installation modifications. Therefore, it is concluded that new buildings should be designed to integrate these alternative water resource systems. Recovered water through the installation of GWR systems is recommended to be used as flushing water, and the excess for garden irrigation, car washing and cleaning. The payback periods were calculated as 12 years for the hotel and industrial plant and 6 years for the residential building. The water savings were calculated as 46% for the hotel, 44% for the residential building, and 29% for the industrial plant. The results put forth the feasibility of this alternative water resource.

Linking forest carbon opportunity costs and greenhouse gas emission substitution effects of wooden buildings: The climate optimum concept

Forests play a crucial role in achieving net-zero greenhouse gas emission targets in the coming decades, as they can act as natural carbon sinks by removing carbon dioxide from the Earth's atmosphere. The use of wood as a building material leads to lower greenhouse gas (GHG) emissions throughout its life cycle compared to other building materials and is therefore considered a valid climate change mitigation strategy. However, the impact of wood harvesting on the potential carbon storage in forests has largely been ignored. In this study, we investigated whether the use of wood as a building material is beneficial for climate change mitigation when considering carbon opportunity costs, which represent the amount of carbon prevented from accumulating in forests due to wood extraction. We introduce the climate optimum concept, which links both GHG emission substitution and associated carbon opportunity cost of wooden buildings. Application of the concept to a case study building shows that the GHG substitution benefits of wooden buildings for climate change mitigation are overshadowed by carbon opportunity costs in forests. In our analysis, no wooden scenario achieves sufficient life cycle embodied GHG emission substitution in order to compensate for the unrealized carbon storage potential in the forest system due to harvest. Wood-based GHG mitigation strategies in the building sector and beyond need to consider this unrealized carbon storage potential of forests expressed via carbon opportunity costs, in order to obtain a more comprehensive picture of the climate impact of forests and wood-based products.