Efficient Building Design Research Articles

New Fuzzy-Heuristic Methodology for Analyzing Compression Load Capacity of Composite Columns

Predicting the mechanical strength of structural elements is a crucial task for the efficient design of buildings. Considering the shortcomings of experimental and empirical approaches, there is growing interest in using artificial intelligence techniques to develop data-driven tools for this purpose. In this research, empowered machine learning was employed to analyze the axial compression capacity (CC) of circular concrete-filled steel tube (CCFST) composite columns. Accordingly, the adaptive neuro-fuzzy inference system (ANFIS) was trained using four metaheuristic techniques, namely earthworm algorithm (EWA), particle swarm optimization (PSO), salp swarm algorithm (SSA), and teaching learning-based optimization (TLBO). The models were first applied to capture the relationship between the CC and column characteristics. Subsequently, they were requested to predict the CC for new column conditions. According to the results of both phases, all four models could achieve dependable accuracy. However, the PSO-ANFIS was tangibly more efficient than the other models in terms of computational time and accuracy and could attain more accurate predictions for extreme conditions. This model could predict the CC with a relative error below 2% and a correlation exceeding 99%. The PSO-ANFIS is therefore recommended as an effective tool for practical applications in analyzing the behavior of the CCFST columns.

Determination of criteria weights of energy efficient building design parameters by SWARA method

Determination of criteria weights of energy efficient building design parameters by SWARA method

Determination of criteria weights of energy efficient building design parameters by SWARA method

Determination of criteria weights of energy efficient building design parameters by SWARA method

Prediction of Thermal Energy Demand Using Fuzzy-Based Models Synthesized with Metaheuristic Algorithms

Increasing consumption of energy calls for proper approximation of demand towards a sustainable and cost-effective development. In this work, novel hybrid methodologies aim to predict the annual thermal energy demand (ATED) by analyzing the characteristics of the building, such as transmission coefficients of the elements, glazing, and air-change conditions. For this objective, an adaptive neuro-fuzzy-inference system (ANFIS) was optimized with equilibrium optimization (EO) and Harris hawks optimization (HHO) to provide a globally optimum training. Moreover, these algorithms were compared to two benchmark techniques, namely grey wolf optimizer (GWO) and slap swarm algorithm (SSA). The performance of the designed hybrids was evaluated using different accuracy indicators, and based on the results, ANFIS-EO and ANFIS-HHO (with respective RMSEs equal to 6.43 and 6.90 kWh·m−2·year−1 versus 9.01 kWh·m−2·year−1 for ANFIS-GWO and 11.80 kWh·m−2·year−1 for ANFIS-SSA) presented the most accurate analysis of the ATED. Hence, these models are recommended for practical usages, i.e., the early estimations of ATED, leading to a more efficient design of buildings.

Prediction of Ecofriendly Concrete Compressive Strength Using Gradient Boosting Regression Tree Combined with GridSearchCV Hyperparameter-Optimization Techniques.

A crucial factor in the efficient design of concrete sustainable buildings is the compressive strength (Cs) of eco-friendly concrete. In this work, a hybrid model of Gradient Boosting Regression Tree (GBRT) with grid search cross-validation (GridSearchCV) optimization technique was used to predict the compressive strength, which allowed us to increase the precision of the prediction models. In addition, to build the proposed models, 164 experiments on eco-friendly concrete compressive strength were gathered for previous researches. The dataset included the water/binder ratio (W/B), curing time (age), the recycled aggregate percentage from the total aggregate in the mixture (RA%), ground granulated blast-furnace slag (GGBFS) material percentage from the total binder used in the mixture (GGBFS%), and superplasticizer (kg). The root mean square error (RMSE) and coefficient of determination (R2) between the observed and forecast strengths were used to evaluate the accuracy of the predictive models. The obtained results indicated that-when compared to the default GBRT model-the GridSearchCV approach can capture more hyperparameters for the GBRT prediction model. Furthermore, the robustness and generalization of the GSC-GBRT model produced notable results, with RMSE and R2 values (for the testing phase) of 2.3214 and 0.9612, respectively. The outcomes proved that the suggested GSC-GBRT model is advantageous. Additionally, the significance and contribution of the input factors that affect the compressive strength were explained using the Shapley additive explanation (SHAP) approach.

Selection of a Transparent Meta-Model Algorithm for Feasibility Analysis Stage of Energy Efficient Building Design: Clustering vs. Tree

Energy Efficient Building (EEB) design decisions that have traditionally been made in the later stages of the design process now often need to be made as early as the feasibility analysis stage. However, at this very early stage, the design frame does not yet provide sufficient details for accurate simulations to be run. In addition, even if the decision-makers consider an exhaustive list of options, the selected design may not be optimal, or carefully considered decisions may later need to be rolled back. At this stage, design exploration is much more important than evaluating the performance of alternatives, thus a more transparent and interpretable design support model is more advantageous for design decision-making. In the present study, we develop an EEB design decision-support model constructed by a transparent meta-model algorithm of simulations that provides reasonable accuracy, whereas most of the literature used opaque algorithms. The conditional inference tree (CIT) algorithm exhibits superior interpretability and reasonable classification accuracy in estimating performance, when compared to other decision trees (classification and regression tree, random forest, and conditional inference forest) and clustering (hierarchical clustering, k-means, self-organizing map, and Gaussian mixture model) algorithms.

Systems of social practice and automation in an energy efficient home

The development of residential automation and energy management systems have aimed to achieve energy reduction within the home. These systems have been developed to compliment human behaviour and potentially impart change in the way people consume energy. The development of energy efficient buildings has been considered a sustainable approach to better manage or optimise energy consumption and generation within a building however, multiple studies have demonstrated some limitations to these buildings and systems. The advancement of the home system of practice using the basis of Social Practice Theory has demonstrated a new focus for the design methodology of these systems. The home system of practice outlines the routines and repetitive nature of individual lifestyles, and these routines result in the temporal characteristic of energy consumption. This study monitored an Australian home that consisted of renewable energy systems, smart technology and automated systems designed to reduce the use of grid electricity. The aim was to understand the performance of the automation systems and interaction with the occupants and their routines. The paper discusses the effectiveness of incorporating social theories and the home system of practice into the design of energy efficient buildings and energy management systems. The methodology utilised machine learning techniques to identify patterns in energy consumption data and related these patterns to the routines and lifestyles of the home occupants. These patterns aimed to describe why the automation system incorporated into the study home did not operate as intended and how design changes can increase effectiveness and performance.

STRATEGIES IN IMPROVING THE BUILDING EFFICIENCY AND DAYLIGHTING: A CASE STUDY OF GREEN BUILDING

Malaysia is one of the rising countries with the highest energy consumption rate, which is attributable to strong economic development in the residential and commercial sectors that consume approximately half of the total electricity generated. Several criteria have been implemented in Malaysia to develop efficient building design, such as the Green Building Index (GBI) and Passive Daylighting Strategies. The study aims to investigate passive daylighting solutions for different building orientations and facade materials to measure energy efficiency through building designs. Buildings are a variable that contributes to growing energy consumption resulting from population increase and climate change. The building facade is a factor that could control the indoor environment, which affects the energy consumption in buildings. A case study determined the elements that maintain building efficiency and electric savings by examining two buildings certified by the Green Building Platinum and the Ministry of Finance (MoF). Low consideration of Passive Daylighting Strategies in building designs allows direct sunshine and increases the use of air conditioning to maintain the room at a comfortable temperature.

A framework approach to the design of energy efficient residential buildings in Nigeria

The main objective of the Nigerian building sector working on achieving energy efficiency is to decrease energy demand of buildings and thereby reduce the negative implications of urban development and poor energy infrastructure on people's wellbeing. One of the key strategies being adopted for substantial reduction of energy demand in the Building Energy Efficiency Guide for Nigeria is the bioclimatic architectural design approach. Hence, intelligent design of buildings, especially the building envelope, can considerably improve energy efficiency and help to realize heating and cooling targets. The aim of this paper is to promote and encourage sustainable building development in Nigeria by developing a systematic and context-based framework for the design of energy efficient residential buildings. This study adopted a mixed method approach of interviews with 12 architects and 22 householders. Moreover, measurements and observational surveys of 22 existing buildings that fit into three distinct building typologies were conducted. Three existing buildings were investigated using a building simulation approach to compare their performances, especially in terms of thermal comfort. The data collected was analysed using content analysis, descriptive statistics analysis, and simulations. The interviews with architects and householders showed enormous potential to reduce residential buildings’ energy demand. To achieve this, the interviewees emphasized the need for strong collaboration between all stakeholders in the building sector. Measurements, observational surveys, and case studies of existing buildings confirmed that thermal discomfort in residential buildings and challenges with building design, have a significant effect on the building occupants’ wellbeing. The research developed a framework for the design of energy-efficient residential building, which is expected to enhance sustainability, particularly in the building sector. The framework was produced based on the findings from the research data and the review of relevant literature. It involves an integrated process focused on bridging the gap between building stakeholders achieving sustainability in buildings. Ultimately, the framework is hoped to guide professionals in the design of energy-efficient buildings and assist institutions on policy guidelines.

Developing a Method to Connect Thermal Physiology in Animals and Plants to the Design of Energy Efficient Buildings.

The literature shows that translating the thermal adaptation mechanisms of biological organisms to building design solutions can improve energy performance. In the context of bio-inspired thermoregulation several worthwhile attempts have been made to develop a framework for finding relevant thermal adaptation mechanisms in nature as inspiration for architectural design. However, almost all of these have followed a solution-based approach despite the problem-solving nature of architectural design. Given this, this research set out to take a problem-based approach to biomimetic design. The aim was to investigate the most effective way of accessing biological thermoregulatory solutions to assist architects in finding relevant biological inspirations for the thermal design of buildings. This required the development of an optimal structure for categorizing thermoregulatory mechanisms that could then be used as part of a framework for finding appropriate mechanisms for a particular architectural design problem. This development began with a three-step literature review to find, study, generalize and categorize a comprehensive list of thermal adaptation mechanisms used by animals and plants. This article describes how this literature review was carried out leading to the identification of nine main themes which were analysed for their practicality in informing the structure of the proposed framework. The selected themes were built around the common aspects of biology and architecture, and hence facilitated the categorization of biological thermoregulation mechanisms. This article thus explains the steps taken to develop a structure for generalizing and categorizing thermal adaptation strategies in nature. This article does not report on the list of thermal adaptation mechanisms identified in step 2 of the literature review. Instead, it presents the literature review workflow with a focus on step 3. Given that, discussion of the thermal adaptation mechanisms falls outside the scope of this article.

Correction: Kara et al. MgO-Based Cementitious Composites for Sustainable and Energy Efficient Building Design. Sustainability 2021, 13, 9188

The authors would like to make the following corrections about the published paper [...]

Lessons from traditional architecture in energy efficient building design: the case of traditional Tabriz houses

ABSTRACT In discussions on energy consumption in buildings, it is frequently argued that the climate-oriented approaches of traditional architecture are a suitable model. Climate-oriented solutions in traditional buildings are rooted in the lessons from several generations of experience, using local material, technology and labour, without sacrificing comfort. They are also responsive to their natural environment and energy-efficient. This study identifies climate-responsive design approaches in the traditional Tabriz houses, located in the cold-arid climatic zone. For this purpose, 10 traditional houses identified in various studies were examined and compared.

Parametric optimization procedure for efficient window design of educational buildings in the Pearl River Delta of China

Abstract Windows are responsible for the largest amount of energy loss related to building envelope. Past studies on the energy consumption of windows have mainly focused on residential and commercial buildings, while few studies have explored the energy consumption of windows in educational buildings. The sizes and locations of classroom windows affect not only the building energy consumption but also the indoor environment quality, which is an issue that needs to be balanced. This paper takes a classroom in Guangzhou as the object. Under the premise of meeting the lighting standards of the classroom, two parameters—window height and sill height —were simulated in different corridors of north–south and east–west classrooms to analyse the impact of their changes on the indoor environment as well as energy consumption based on the parametric platform Grasshopper and its plug-ins Ladybug and Honeybee. The energy consumption of a number of fenestration combinations on both sides of the classroom was optimized automatically by genetic algorithm, and the sizes and positions of windows that benefitted energy savings were obtained. In the best case ~16.6% of energy consumed in a whole year can be saved compared with the worst case. This conclusion can provide a quick decision-making process for the design of window shapes for the purpose of energy savings in the early design stage of educational buildings in the Pearl River Delta such that energy savings can be quickly and clearly guaranteed in the subsequent window configuration.

Significance of Energy Efficient Component in the Buildings Design Towards the Green Footprint

The energy efficient building or green building design and certifications was started in the starting of twenty-first century because of whole world's people wants warmth, peace and prosperous house. Low energy consumption or energy efficiency is the main component of the green building. In this communication the author's communicating the significance of the possible methods of energy saving in building design by these methods peoples can improve the 'aura' of the building. By the application of these methods’ human can save lot of conventional energy and it say that it is sustainable approach for the building.

Comparative Evaluation of Solar Houses Applied in Turkey

The construction sector consumes a significant portion of the energy resources irreversibly and harms the environment. Limited resources and emerging environmental problems have made it necessary to search for new energy resources in the world and in our country, and to use renewable energy sources, environmentally friendly and energy efficient building designs in the building sector. In this context, the issues of solar energy, which is one of the clean and renewable sources and the use of solar energy in buildings, have gained importance. Although Turkey is in advantageous position compared to European countries in terms of potential solar energy, solar energy is not sufficiently utilized in buildings and studies are limited to academic studies. Solar houses, which are built in Turkey in order to benefit from solar energy with active and passive methods in heating, cooling, lighting and ventilation of buildings, consist of single examples designed with different functions. The aim of this study is to emphasize the importance of the use of solar energy in buildings within the scope of renewable energy sources, to examine the solar houses applied in Turkey comparatively and to make suggestions for solar house design.

An analytical optimization study on the core-outrigger system for efficient design of tall buildings under static lateral loads

The location and number of outriggers in a core-outrigger lateral resisting system have a major influence on the tall buildings' performance and the design's cost efficiency. In this study, an analytical procedure was performed to produce a general equation of the top lateral displacement of a core-outrigger system (up to four outriggers) due to various static lateral loading distribution forms (uniform, triangular and parabolic). Moreover, the optimal positions of outriggers that produce the maximum top displacement reduction are determined in this research. On the other hand, this work proposes the maximum height of a tall building corresponding to displacement limit criteria, number of the outrigger and outrigger positions. For practical use, this study offers curves for use at the preliminary design stage to allocate the top displacement and the number of the required outriggers in terms of the building height and a proposed rigidity factor which shows to have a great influence on a core-outrigger system in a tall building.

A simulation-based multi-objective genetic optimization framework for efficient building design in early stages: application for Vietnam's hot and humid climates

PurposeIn many countries, innovation in building design for improving energy performance, reducing CO2 emissions and minimizing life cycle cost has received much attention for sustainable development. This paper investigates the importance of optimization tools for enhancing the design performance in the early stages of Vietnam's cooling-dominated buildings in hot and humid climates using an integrated building design approach.Design/methodology/approachThe methodology of this study exploits the non-dominated sorting genetic algorithm (NSGA-II) optimization algorithm coupled with building simulation to research a trade-off between the optimization of investment cost and energy consumption. Our approach focuses on the whole optimization problem of thermal envelope, glazing and energy systems from preliminary design phases. The methodology is then tested for a case study of a non-residential building located in Hanoi.FindingsThe results show a considerable improvement in design performance by our method compared to current building design. The optimal solutions present the trade-off between energy consumption and capital cost in the form of a Pareto front. This helps architects, engineers and investors make important decisions in the early design stages with a large view of impacts of all factors on energy performance and cost.Originality/valueThis is one of the original research to study integrated building design applying the simulation-based genetic optimization algorithm for cooling-dominated buildings in Vietnam. The case study in this article is for a non-residential building in the north of Vietnam but the methodology can also be applied to residential buildings and other regions.

A review of approaches to generate equivalent static and synthetic wind loads on tall buildings for the preliminary stage of design

The extraordinary urbanisation of cities in recent decades urges us to consider the efficient design of tall buildings. Because of the increased flexibility of slender buildings, wind loads are expected to dominate the design loads. Although there are widely accepted wind tunnel techniques for obtaining wind loads on tall buildings, they are time-consuming and may be inconvenient in the pre-concept design process, when structural engineers would like fast and low-priced methods to predict the wind loads over the height of tall buildings. This paper mainly reviews the gust loading factor including other semi-empirical approaches and mathematical approaches for generating equivalent static and synthetic wind loads on tall buildings. Although stochastic simulations and time series analysis methods have limited use in generating wind loads on tall buildings, they are also briefly examined. Based on the findings of this review the paper concludes that it is definitely viable for synthetic wind approaches to be used to speed up the preliminary design process when large numbers of structural systems need to be assessed rapidly.

Identifying Retrofitting Strategies for Access to Energy Efficient Building Design in Existing Buildings

Reducing the energy needs of existing buildings has a significant place in reducing global energy demands. High energy savings can be achieved with passive renovation suggestions in existing buildings. In this study, the effect of the proposed renovation suggestions for an educational structure in Safranbolu on the heating and cooling demands of the building was determined with a simulation program. Energy improvements of up to 70 percent have been achieved through passive improvement designs in orientation and insulation material. The highest energy saving (69.31%) was realized in the scenario of rearranging spaces from the north side to the south side where the number of users is relatively high, and selecting a 20 cm aerogel thermal insulation material. While, the fact that the heating and cooling load in accordance with the definition of a zero-energy building could not be reached in this scenario, the study however showed the importance of holistic decisions taken in the design phase of the building with respect to energy efficient building design.

A cost effective approach to design of energy efficient residential buildings

The objective of this study is to identify cost-optimal efficiency packages at several levels of building energy savings. A two-story residential building located in Jordan is selected as a case study. DesignBuilder software is used to predict the annual energy usage of a two-story residence in Irbid, Jordan. Real-time experimental data from a single isolated controlled room was used to verify the proposed model. In addition to energy analysis, the economic, environmental, and social benefits of the proposed design have been investigated. The sequential search optimization approach is used to estimate the minimum cost of the building while considering various design scenarios. In addition, the impact of various energy conservation techniques on residential buildings is assessed, and the payback period for each program is calculated. Ultimately, the optimal combination of design to achieve energy efficiency measures has been identified in several climate regions. The simulations results predict that the annual electricity consumption can be reduced up to 50% if the proper combinations of energy conservation measures are selected at the lowest cost. The payback period is 9.3 years. Finally, energy efficiency measures can lead to a total of 9470 jobs/year job opportunities.The study provide practical framework to link between energy performance criteria and economic goals of building. Linking the energy performance requirements to economic targets provides guidelines for homeowners, contractors, and policymakers for making a suitable decision regarding the retrofitting of existing residential buildings. The study focuses on developing new methodologies that support minimizing costs during a building's lifecycle while maximizing environmental benefits which can not be identified by a series of parametric analyses using individual energy-efficient measures.