Building Cost Research Articles

Predictive Mutation Analysis via the Natural Language Channel in Source Code

Mutation analysis can provide valuable insights into both the system under test and its test suite. However, it is not scalable due to the cost of building and testing a large number of mutants. Predictive Mutation Testing (PMT) has been proposed to reduce the cost of mutation testing, but it can only provide statistical inference about whether a mutant will be killed or not by the entire test suite. We propose Seshat, a Predictive Mutation Analysis (PMA) technique that can accurately predict the entire kill matrix , not just the Mutation Score (MS) of the given test suite. Seshat exploits the natural language channel in code, and learns the relationship between the syntactic and semantic concepts of each test case and the mutants it can kill, from a given kill matrix. The learnt model can later be used to predict the kill matrices for subsequent versions of the program, even after both the source and test code have changed significantly. Empirical evaluation using the programs in Defects4J shows that Seshat can predict kill matrices with an average F-score of 0.83 for versions that are up to years apart. This is an improvement in F-score by 0.14 and 0.45 points over the state-of-the-art PMT technique and a simple coverage-based heuristic, respectively. Seshat also performs as well as PMT for the prediction of the MS only. When applied to a mutant-based fault localisation technique, the predicted kill matrix by Seshat is successfully used to locate faults within the top 10 position, showing its usefulness beyond prediction of MS. Once Seshat trains its model using a concrete mutation analysis, the subsequent predictions made by Seshat are on average 39 times faster than actual test-based analysis. We also show that Seshat can be successfully applied to automatically generated test cases with an experiment using EvoSuite.

Modelling UK electricity regional costs for commercial buildings

As electricity prices continue to rise, it is essential that UK non-domestic consumers develop smart energy management practices. However, most of these consumers lack awareness of the spatial–temporal dynamics of electricity prices and their tariff components. To help overcome these barriers and contribute to energy price digitalisation, this paper presents a Modelling UK Electricity Regional Costs (MUKERC) framework. A bottom-up methodology that defines all the tariff components and then aggregates them to quantify the cost of a kWh across each half-hour of the day. The framework not only facilitates understanding which tariff components have a higher impact during different time periods, but also depicts how they vary spatially across regions. This model was used to estimate and analyse the evolution of electricity costs from 2017 to 2024. Case studies from buildings in the education sector are showcased depicting their energy costs derived from their load profiles. Results show that the London area has the lowest average prices, while the Northern Wales & Merseyside is the most expensive. From the case studies conducted, peak period charges account for 17% of annual electricity costs (occurring between 4 and 7 p.m.). Winter period charges represented about 53% of the charges. The MUKERC framework showcases the valuable insights data-driven costing models offer as it allows to understand the dynamics of electricity charges and identifies “when” and “where” the cost of electricity is more expensive; thus, supporting the development of bespoke cost-effective energy measures that improve resource efficiency and smart energy management initiatives.

Bacterial Performance in Crack Healing and its Role in Creating Sustainable Construction.

Building practices began with human civilization. Cement is the most commonly used building construction material throughout the world. These traditional building materials have their own environmental impact during production, transportation, and construction, but also have limitations on building quality and cost. Biological construction materials are currently emerging technology to combat emissions from the construction sector. Different civil and biotechnology researchers have turned to microorganisms for the production of bio construction materials that are environmentally friendly, socially acceptable, and economically feasible but can also produce high strength. Scanning electron microscope (SEM) and X-Ray diffraction (XRD) are the most characterization methods used to observe and ensure the production of calcite precipitate as bacterial concrete. As compared to conventional concrete, bacterial concrete was greater by 35.15% in compressive strength, 24.32% in average tensile strength, and 17.24% in average flexural strength, and it was 4 times lower in water absorption and 8 times lower in acid resistivity than conventional concrete. Genetic engineering has great potential to further enhance the mechanical strength of bacterial concrete for use in crack repairs in existing buildings.

The value of energy efficiency in residential buildings – a matter of heterogeneity?!

Energy efficiency ratings of residential buildings are intended to remove assessment errors from real estate markets to increase energy efficiency – the key to fully decarbonizing the building sector. Price premiums of rated buildings should reflect capitalized future energy savings, but instead are nonlinear (1), can exceed savings (2) and are correlated with buyer's characteristics (3). We explore these anomalies with a hedonic model of product differentiation, which is adapted to efficiency valuation in the housing market. The model implies that buyers with high willingness to pay for efficiency “sort” themselves to efficient buildings (and vice versa) and drive their premiums above average discounted energy expenditures - if the market share of the efficient buildings is below average. In this sense a non-linear scarcity premium explains findings (1) and (2). Furthermore, it is revealed that the results from (3) require average buyer's characteristics to vary spatially, but neither their variance nor the variance of buildings stocks efficiency – strong assumptions. The model explains measured premiums of the UK well and shows that as well as buyer heterogeneity and supply structure, the prebound effect - the overestimation of energy costs in inefficient buildings by ratings – also plays an important role in determining efficiency premiums.

An integrated framework for multi-objective optimization of building performance: Carbon emissions, thermal comfort, and global cost

In this paper, we proposed an integrated optimization framework to explore minimum building carbon emissions (BCE), indoor discomfort hours (IDH), and global cost (GC) of building, as well as a new formula for selecting the best scheme in the Pareto front set. Such framework improves the efficiency of the optimization process, the accuracy of the results, and the rationality of the best scheme. The entire optimization process can be divided into four steps. First, the input parameters were randomly generated using three sampling methods and then simulated to build the database. Then, the contribution rates of the selected parameters to the outputs were comprehensively evaluated and combined with multi-sensitivity analysis methods to screen important parameters. Next, we trained and validated the Back Propagation Neural Network (BPNN) model, in which different methods were used for hyperparametric optimization. Third, based on the comparison of various optimization methods, the Non-dominated Sorting Genetic Algorithm-III (NSGA-III) was selected and combined with BPNN to solve the proposed multi-objective optimization problem. Then, finally, we applied the proposed optimal balance formula to select the scheme that considered all aspects of objectives in the Pareto front set. The results demonstrated that the best sampling method and hyperparameter combination can result in an R 2 of BPNN that reaches 0.992. The simulation results are in good agreement with the optimization results. Compared with the case building, the optimal balance schemes of BCE, IDH, and GC were reduced by 53.25%, 42.95%, and 22.33%, respectively. Therefore, we demonstrated that this method is feasible and effective for improving building design in more practical and complex situations and can be widely popularized in the building performance optimization field. • This integration method can predict and optimize complicated solutions efficiently. • Several sampling and sensitivity analysis methods were applied in data evaluation. • BPNN models were trained to replace simulation process. • NSGA-III was the best algorithms in building performance optimization. • A new optimal solution was proposed for the optimal balance scheme.

The Influence of Nanoclay and Powdered Ceramic on the Mechanical Properties of Mortar

The amount of concrete utilized worldwide has lately grown due to rising populations and urbanization. The gas emissions during cement manufacturing and the usage of common resources result in a significant environmental threat. As a result, researchers are attempting to minimize the amount of cement consumed by using waste materials while lowering building costs. This research aims to minimize the amount of cement used in concrete by partially replacing it with ceramic powder waste while also increasing the mechanical qualities of concrete mortar by substituting cement with nanoclay hydrophilic bentonite. Mortar samples were prepared using five different replacement percentages of cement by nanoclay, including 0, 2, 4, 6, and 8%, and two replacement percentages of cement by ceramic powder, including 0% and 20%. Compressive and flexural strength tests were performed on mortar samples for 7, 14, and 28 days of moist curing. The toughness was also measured for all mixes by measuring the area under the load-deflection curve. Also, water absorption and relative densities for all mortar mixes were measured. The results show that replacing cement with 2% nanoclay and 20% ceramic powder increases the flexural strength by 11%. Doi: 10.28991/CEJ-2022-08-07-08 Full Text: PDF

Managing the additional cost of passive buildings from the supply chain perspective: A case of Nanjing, China

The development of passive buildings is of great significance for sustainable development worldwide. However, the features of passive buildings are high capital investment with long payback periods, and complex supply chains involving numerous and disparate enterprises, all of which result in the need for additional cost control measures. This study systematically explores the interaction mechanism among the factors influencing the additional cost of passive buildings from the supply chain perspective. The additional cost components of passive buildings and their influencing factors are first identified in the aspects of design, materials and equipment, and technology, based upon which a system dynamics model of the additional cost of passive buildings is established. By reference to a real-life case study, the model is verified and applied to simulations. The simulation results present the impact of different measures on the additional cost of passive buildings, and further reveal its sensitive factors and mechanism. Based on the above work, four targeted strategies to reduce the additional cost of passive buildings are proposed. This is done with a view to promoting the development of passive buildings, and ultimately reducing the energy consumption and carbon emissions of the construction industry.

Impact of rice husk ash on compressed cement-lateritic brick durability and microstructural characteristics

One of the potential ways to lower building costs and improve the quality of the environment in both urban and rural regions is to use local resources as a substitute for cement in building construction. The purpose of this study was to determine how Rice Husk Ash (RHA) affected the morphology and durability of cement-lateritic bricks. Analytical techniques were utilized in the lab to ascertain the RHA's chemical make-up. Compressed Earth Bricks (CEB) were created by employing water content of 20 to 25 percent and replacing 0 to 5 percent of the cement with 0 to 5 percent of RHA. Response Surface Methodology (RSM) of Design Expert software was used to create seventeen (17) variables for the CEB manufacture.The created CEBs underwent compressive strength and microstructural studies in the lab after being cured for 28, 56, and 108 days. According to the results, RHA is a powerful pozzolan with a high SiO2 concentration that might potentially replace non-renewable silica as one of the primary cement sources of oxide that pozzolans react with. Most samples exhibit an increase in compressive strength with longer curing times and have a minimum strength of 1.65 N/mm2 or higher.The microstructural study of the pozzolan revealed that it contains tiny particles. Consequently, as the curing age increased, the porosities decreased and the compressive strength of the stabilized bricks improved. In conclusion, the finest CEBs for building construction are those produced with 1.25 percent RHA and 23.75 percent water content.

Green Building Project Cost Budgeting and Cost Control Integrating Interactive VR Genetic Algorithm

The development of buildings in the future will tend to the direction of green buildings. At present, most of the calculations of their costs usually use empirical models, which lack the basis for quantitative prediction. For the purpose of improving the accuracy of budget and control of project cost for green buildings, this paper applies interactive virtual reality (VR) genetic algorithm and analyze project budget accordingly. The prediction accuracy is effectively increased based on the mathematical analysis model. Finally, the test results suggest that the proposed algorithm can effectively improve the cost control efficiency and engineering quality of green buildings and reduce the construction cost of buildings.

Methodology to Determine Energy Efficiency Strategies in Buildings Sited in Tropical Climatic Zones; Case Study, Buildings of the Tertiary Sector in the Dominican Republic

The application of energy-efficiency strategies in buildings is a hot topic around the world; in some countries, there are regulations with more or less degree of compliance, but in most countries located in the tropical zone, there are no regulations, and it is not easy to transfer regulations of countries outside of tropical zone. For countries located in tropical zones, the implementation of strategies to reduce the heat flow from outside to inside buildings is a key point. As a case study, the Dominican Republic (DR) was chosen, and during 2020, an analysis focusing on buildings of the tertiary level was carried out with the goal of using scientific methodology focused on tropical climates that allows for a significant reduction in energy consumption by implementing Energy Efficiency Strategies (EESs) that are available, with minimal intrusion into the building and low cost. The study includes, as parts of the proposed methodology, the characterization of building parks, including the climatic zonification of the country, an in-depth study of the building typologies in DR, and a massive survey around the country about the technical characteristics of air conditioning units and their usage; the election and characterization of buildings, including simulation and validation throughout the monitoring of eight different buildings; ananalysis of the measures of energy efficiency and implementation in the models, including the election of a demonstrative building, the election of the most convenient EESs, modeling of EESs, implementing EESs in the building, monitoring, and validation; and ananalysis of the impact of the measures at the region or country level, throughout which important conclusions can be obtained in order to reduce energy consumption in the country. The results show that this methodology is a valid tool for countries situated in tropical areas in order to reduce the energy consumption associated with air conditioning units with low cost, availability, and no intrusive EESs.

Сравнение безредукторного и редукторного гидроприводов машин транспортного строительства

Improving the technical and economic indicators of machine building is possible by increasing their production, reducing their dimensions and masses, reducing energy consumption and reducing their reliability, which ultimately will correspond to the norm for reducing construction time (putting objects into regulatory significant ones), the labor intensity of construction and installation works and increase in capital costs for temporary buildings and structures. A separate and specific type of machines for construction are drilling machines based on industrial tractors of the T10 type. As a rule, this uses a hydraulic volumetric drive of the main working bodies. The traditional design consequence of the drilling string drive of the machine is the use of a low-torque hydraulic motor with a gearbox. At the same time, high-torque hydraulic motors have grown in domestic industrial resistance, making it possible to provide the necessary torque on the drilling rig without using a gearbox. This solution allows you to simplify the light, reduce production costs and increase the reliability of the drive in operation. This article provides a comparative analysis of some of the advantages and disadvantages of the geared and gearless variants of the drilling string drive, in relation to the mass-produced machine BTS-150.

Digital Twin and Cloud BIM-XR Platform Development: From Scan-to-BIM-to-DT Process to a 4D Multi-User Live App to Improve Building Comfort, Efficiency and Costs

Digital twins (DTs) and building information modelling (BIM) are proving to be valuable tools for managing the entire life cycle of a building (LCB), from the early design stages to management and maintenance over time. On the other hand, BIM platforms cannot manage the geometric complexities of existing buildings and the large amount of information that sensors can collect. For this reason, this research proposes a scan-to-BIM process capable of managing high levels of detail (LODs) and information (LOIs) during the design, construction site management, and construction phases. Specific grades of generation (GOGs) were applied to create as-found, as-designed, and as-built models that interact with and support the rehabilitation project of a multi-level residential building. Furthermore, thanks to the sharing of specific APIs (Revit and Autodesk Forge APIs), it was possible to switch from static representations to novel levels of interoperability and interactivity for the user and more advanced forms of building management such as a DT, a BIM cloud, and an extended reality (XR) web platform. Finally, the development of a live app shows how different types of users (professionals and non-expert) can interact with the DT, in order to know the characteristics with which the environments have been designed, as well as the environmental parameters, increasing their degree of control, from the point of view of improving comfort, use, costs, behaviour, and good practices. Finally, the overall approach was verified through a real case study where the BIM-XR platform was built for energy improvements to existing buildings and façade renovations.

Effects of Concrete Grades and Column Spacings on the Optimal Design of Reinforced Concrete Buildings.

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.

Stoichiometry versus ecology: the relationships between genome size and guanine-cytosine content, and tissue nitrogen and phosphorus in grassland herbs.

Plant tissue nitrogen (N) and phosphorus (P) and genome traits, such as genome size and guanine-cytosine (GC) content, scale with growth or metabolic rates and are linked to plant ecological strategy spectra. Tissue NP stoichiometry and genome traits are reported to affect plant growth, metabolic rates or ecological strategies in contrasting ways, although the elemental costs for building and maintaining DNA are typically overlooked. We formulated stoichiometry- and ecology-based predictions on the relationship between genome size and GC content to tissue N, P and N : P and tested them on a set of 130 herbaceous species from a temperate grassland using ordinary, phylogenetic and quantile regression. Genome size was only negatively linked to plant N and N : P in species with very small genomes. We found no link between genome size and plant P. GC content was negatively linked to plant N and P but we found these significant links consistently in both GC-rich and GC-poor species. Finally, GC content correlated positively with plant N : P but only in species with GC-rich genomes. Our results provide stronger support for the ecology-based predictions than the stoichiometry-based predictions, and for the links between GC content and plant N and P stoichiometry than for genome size. We argue that the theories of plant metabolic rates and ecological strategies (resource-acquisitive vs. conservative or ruderal vs. stress-tolerator spectra) better explain interspecific genome-NP stoichiometry relationships at the tissue level (although relatively weakly) than the stoichiometric theory based on the elemental costs for building and maintaining DNA.

MosSkin: A moss-based lightweight building system

A low cost and lightweight moss envelope system for buildings has been developed to address the problem of the lack of greening in densely urbanized areas. Several moss species have been sampled in the wild, selected, based on their ability to tolerate the abiotic stresses of urban environments, cultivated in controlled conditions and tested for their growth capacity on different (building) materials. Five of these showed the most promising results in terms of growth speed and coverage, proving the most suitable for the development of the greening system: Homalothecium sericeum, Barbula unguiculata, Pseudoleskea incurvata, Grimmia pulvinata and Hypnum cupressiforme. An in vitro growing method was also set up for large scale moss cultivation and application.A modular multi-layer panel, with a built-in irrigation system, has been developed, designed and tested. MosSkin is a low-cost low maintenance, versatile and lightweight system, with interesting performances in terms of water management and surface temperature reduction (up to 14 °C).

Impacts of Building Energy Consumption Information on Energy-Saving Intention of College Students

As college students bear little energy cost of public buildings on campus, information intervention is more feasible than economic intervention to augment the energy-saving intention of college students. College students are sensitive to environmental information; thus, building energy consumption information, which reflects the energy consumption levels of the environment where students live, may be effective to promote the energy-saving intention of college students. However, the changeable cognitive structure of college students makes it difficult to predict the cognitive results of building energy consumption information. Based on social cognitive theory and theory of planned behavior, this paper reveals the impacts of building energy consumption information on energy-saving intentions of college students from the perspective of perceived value and personal norms. The conclusions are: (1) The impacts are positive and indirect; (2) the impacts are realized through the path “perceived benefit—perceived value—intention” and “perceived benefit & risk—personal norm—intention”; (3) the perceived value and personal norm independently affect energy-saving intention; and (4) the effect of perceived benefits is the most obvious. Based on the above results, we put forward a series of policy suggestions, with the aim to enhance the positive effect of building energy consumption information on college students.

Comparative Analysis of German Dgnb and Chinese Green Building Evaluation Standards

With the concept of sustainable development being promoted all over the world, green building, as one of the necessary ways to achieve sustainable development, has been carried out by more and more countries, and a series of evaluation standards related to green building have been introduced. This paper makes a brief introduction and comparative analysis of some typical green building evaluation codes in the world. On the basis of the German DGNB algorithm on the full life cycle cost of green buildings, combined with the actual situation of China, this paper puts forward the algorithm of the full life cycle cost of green buildings suitable for China, and carries out analysis and verification, so as to provide reference for improving the evaluation criterion of green buildings in China.

Східноєвропейський досвід застосування багатошарових залізобетонних елементів зовнішнього стінового огородження

The capital building field is constantly updating the tasks: to reduce material consumption, cost and complexity of building, the mass of buildings and structures; significantly improve thermal protection; to increase the level of industrialization of building and factory readiness of prefabricated constructions; to improve the architectural and operational qualities of buildings and structures. Practical realization of the set tasks entails the the necessity to expand the use effective kinds of building materials and constructions, improving their properties. The field of effective three-layer constructions in civil, industrial and agricultural building is wide and multifaceted, as it covers almost all constructive elements of buildings, the solution of which depends on the functional requirements imposed on buildings and structures, local climatic and geological conditions, availability of building materials, level of development industrial base, etc. Already behind the idea itself of layered reinforced concrete constructiones have significant advantages: 1) the ability to select the materials of the layers taking into account the effective use of their main functional qualities; 2) reducing the cost and outlay of cement; 3) weight reduction of separate constructions and buildings and/or structures as a whole; 4) reducing heat consumption and increasing heat transfer resistance without thickening the construction; 5) improving the temperature-humidity regime in the room, etc. The purpose of this article is to perform a brief overview of research, proposals for standardization of design developments conducted during the most active implementation in Eastern European building practice of three-layer reinforced concrete constructions for fencing by the heat, air and waterproofing properties, strength, deformations and crack resistance, as well as their manufacturing technology. The article takes into account the results of research, field observations, materials for the development of new proposals, accumulated in many research and design departments of Eastern Europe in the period from the late 60’s to mid-80’s of the 20th century (Research Institute of Building Constructions, Kyiv Zonal Research Institute of Experimental Design, Ukrainian Research and Design Institute of Civil Rural Construction (Ukraine); Central Research Institute of Building Constructions named after V.A. Kucherenko, All-Union Research Institute of Fire Safety, All-Union Scientific Research Institute of Reinforced Concrete, Central Research and Design Institute of Residential and Public Buildings, Central Research and Design and Experimental Institute of Industrial Buildings and Structures, Central Research Institute of Experimental Design of Commercial and Domestic Buildings and Tourist Complexes (Russia), etc.).

Inland waterway transport and the 2030 agenda: Taxonomy of sustainability issues

Inland Waterway Transport (IWT) is recognized as energy efficient, with lower levels of greenhouse gas emissions and large freight capacity when compared to other modes. Therefore, IWT helps to achieve the Sustainable Development Goals in 2030 Agenda (SDGs) that relate to sustainable transport. Still, transport sustainability assessments must include environmental, social and economic issues. This paper reviews recent research aiming to provide a conceptual definition of sustainable inland waterway transport that relates to the SDGs, and to identify gaps in literature for future research. To accomplish this task, a cluster analysis-based taxonomy was built through the intuitive approach, with peer-reviewed papers published between 2015 and 2020. The sample was classified into twelve clusters of IWT sustainability issues, which were related to SDGs and their targets. Results show increased scientific interest in eco-friendly practices. However, social issues remain underappreciated. We present a definition for sustainable IWT and the pathways for future research to achieve higher sustainability levels, as prescribed by the 2030 Agenda. • In sustainable IWT, freight increase meets lower building and operational costs. • Sustainable IWT is resilient to climate change and promotes social equity. • IWT relates to twelve targets in SGDs 3, 6, 8, 9, 10, 11 and 13 in the 2030 Agenda. • Technical solutions for IWT save time, as well as financial and natural resources. • Technological tools also foster democratic decision-making in IWT.

Optimizing machine learning inference queries with correlative proxy models

We consider accelerating machine learning (ML) inference queries on unstructured datasets. Expensive operators such as feature extractors and classifiers are deployed as user-defined functions (UDFs), which are not penetrable with classic query optimization techniques such as predicate push-down. Recent optimization schemes (e.g., Probabilistic Predicates or PP) assume independence among the query predicates, build a proxy model for each predicate offline, and rewrite a new query by injecting these cheap proxy models in the front of the expensive ML UDFs. In such a manner, unlikely inputs that do not satisfy query predicates are filtered early to bypass the ML UDFs. We show that enforcing the independence assumption in this context may result in sub-optimal plans. In this paper, we propose CORE, a query optimizer that better exploits the predicate correlations and accelerates ML inference queries. Our solution builds the proxy models online for a new query and leverages a branch-and-bound search process to reduce the building costs. Results on three real-world text, image and video datasets show that CORE improves the query throughput by up to 63% compared to PP and up to 80% compared to running the queries as it is.