Building Design Optimization Research Articles

A state-of-the-art-review on grey water management: a survey from 2000 to 2020s.

Water reuse can contribute to reducing pressures on water resources, as an important approach and practice, reducing the demand for potable water for purposes not requiring high quality water. With water resources being depleted and the demand for water increased, grey water reuse becomes more popular in order to preserve water worldwide. This paper presents a comprehensive review of all significant research and reviews existing case studies to review the present knowledge with respect to the characteristics of grey water. The main summary table covers 63 works that focus on the application of these methods to different fields of sustainable building design. Key fields are reviewed in detail: grey water, including water reuse; grey water recycling; water sustainability; building design optimization; and wastewater of several areas simultaneously, with particular focus on buildings. This research aims to introduce the review of the research that covered the grey water management. Various engineering databases, international journals, and conference proceedings were searched. International journals were searched for relevant research papers. This paper provides perspectives on grey water context in order to frame the breadth and multiple dimensions it encompasses, to summarize recent activities on selected relevant topics, and to highlight possible future directions in research and implementations.

Modeling the similarity and the potential of toluene and moisture buffering capacities of hemp concrete on IAQ and thermal comfort

Controlling and understanding indoor humidity and pollutants can help reduce the risk of health concerns. The experimental results suggested that there is a similarity relationship between water vapor and Volatile Organic Compounds (VOC) in diffusion through porous media. In this paper, the similarity between the moisture and pollutant transport and storage coefficients of porous building materials has been clearly established and explained. In addition, two similarity coefficients have been defined for VOC storage and diffusion to estimate the VOC properties from the moisture properties of the same material. A coupled hygric-pollutant (VOC) model which can be used to simulate VOC and hygric behavior of building materials under dynamic conditions is presented. The model which is implemented in the environment SPARK (Simulation Problem Analysis and Research Kernel) suited to complex problems using finite difference technique with an implicit scheme, has been validated with the experimental data. It is then applied to study the effect of toluene and moisture buffering capacities of a hemp concrete wall on indoor toluene concentration and relative humidity (RH). Hemp concrete was chosen in this study because it is an environmentally-friendly material that is used more and more in building construction. The toluene (TOL, selected VOC for this study) transport and storage properties obtained from hygrique properties of hemp concrete based on the assumption of the similarity between toluene and moisture transport have been modelled and investigated. At the room level, the results obtained show that taking into account the sorption capacity toward moisture and toluene has a significant effect on indoor RH and IAQ because hemp concrete contributes to dampen indoor RH and toluene variations. The numerical model presented is very useful for the building design optimization and can be used for a fast estimation of indoor pollution and hygrothermal conditions in building.

Future energy-optimised buildings — Addressing the impact of climate change on buildings

Building energy optimisation is generally performed under present climate conditions with fixed simulation parameters (e.g. internal loads). However, climate change and variations in simulation parameters over the building’s life span may impact the optimised design. A key question is whether a particular energy-optimised design under present climate conditions would remain energy-optimised in the future. Accordingly, in this paper, a new simulation-based optimisation method is developed, which uses climate models and Ant Colony Optimisation to compare the energy-optimised designs under present and future climates. To demonstrate its potential, this method is applied to a typical office building in two Australian cities, Brisbane and Canberra.The results show that optimising under future climate conditions can lead to different optimal building designs. For Brisbane, the energy difference between optimising under present and future climate conditions is small, but in Canberra the cooling load is increased by up to 6%. This suggests that optimising the studied office building under present climate conditions is acceptable for Brisbane, while considering future climate may yield some savings in Canberra. Results also show that the energy-optimised building configuration for both future and present climates in Brisbane is less sensitive to changes in the load scenario than in Canberra.

Exploring the impact of problem formulation in numerical optimization: A case study of the design of PV integrated shading systems

Optimization in buildings has been increasingly popular due to its growing availability and documented ability to improve the performance of building designs following specified targets. However, the quality and robustness of optimized solutions may be dependent on how the optimization problem is formulated, and few studies have investigated the impact of modelling choices or optimization strategies. This study presents a simulation-based investigation of the impact of problem formulation in building design optimization using the case study of a PV integrated shading device (PVSD) and an evolutionary algorithm. For this, we modify both the size of the solution space and how it is searched using three different approaches to define the objective function(s): single-objective optimization, bi-objective optimization, and tri-objective optimization. The results show that increasing the size of the solution space provided better designs compared to both a full factorial parametric analysis and an optimized but more rigid model, regardless of the nature and number of objectives. The findings support the idea that exploring the impact of problem formulation may be an important part of the process of optimization in buildings and allows obtaining more insight into the tradeoffs at play and the workings of a selected optimization study.

Reduction of the Energy Demand With Passive Approaches in Multifamily Nearly Zero-Energy Buildings Under Different Climate Conditions

Nearly zero-energy buildings (nZEBs) will be the standard in Europe in the future. How nZEBs are defined and therefore designed varies amongst Europe due to different national definitions/ legislations. Furthermore, finding the optimal building design and technology sets for nZEBs under different boundary conditions (climate, availability of renewable energy sources on-site etc.) and for different building types (residential, non-residential) is still a challenge. Many studies in the field focus on active technologies and renewable energies in buildings. However, the effects of passive approaches on energy consumption are not quantified. This paper therefore focuses on the quantification of the effects of passive design approaches/ technologies to improve the energy performance of buildings. Passive approaches are the basis for finding optimal nZEB technology sets. Technology sets are combinations of different types of technologies in nZEBs for both the satisfaction of energy needs and thermal comfort requirements. In this paper different passive approaches for already realized buildings in different European countries with different climate conditions (Stuttgart (Germany), Kiruna (Sweden) and Palermo (Italy)) are demonstrated. Even though several technologies are available to achieve nZEBs, applying and combining these technologies in an optimal way is still a challenge. Furthermore, higher initial investment costs for nZEBs are an obstacle for the market acceleration of nZEBs. Hence finding the best trade-off amongst the different goals, optimizing the most promising passive approaches that can be applied is a central part of the solution.

ОПТИМІЗАЦІЯ РОЗТАШУВАННЯ ДЕМПФЕРІВ СУХОГО ТЕРТЯ ДЛЯ СЕЙСМІЧНОГО ЗАХИСТУ КАРКАСНИХ БУДІВЕЛЬ ЗА ДОПОМОГОЮ МЕТОДУ РОЮ ЧАСТИНОК

Abstract. A challenging problem of Civil Engineering is the protection of buildings against dynamic loads and earthquake impacts. The advanced solutions employ lightweight structures equipped with special damping devices. These devices can be active or passive and their application depends on the investments for the project. The active devices change their properties depending on the structural response and they are the most expensive ones. On the other hand, passive devices are essentially cheaper and, in many cases, require minimal costs of installation and maintenance. Last decades, passive friction dampers are widely used for the earthquake protection of multi-storey buildings. The friction dampers make use of the effect of solid friction to dissipate the mechanical energy and to reduce the amplitude of the vibration of the structure. The friction is developed between two solid bodies sliding in relation to one another. As usual, pairs of metal, polymer or concrete components can be utilized. Determination of the optimal location of the friction dampers inside the building presents a complicated task for the practical design. In this paper, a new approach is developed basing on the method of particle swarm optimization (PSO). The PSO method presents an artificial simulation of the phenomenon of collective intelligence, which is observed in many decentralized biological systems like ant colonies, bee swarms, flocks of birds and even social groups of human individuals. As an illustrative example, the 2D model of a ten-storey concrete frame building is considered. The purpose of the analysis is to minimize the objective function, which is the amplitude of the displacements of the top of the structure in a case of the resonance dynamic load with a frequency of the first normal mode. Non-stationary dynamic analysis is performed by the finite elements method using the program package «LIRA-SAPR» and its module «Dynamic-plus». The software implementation of the PSO procedure is developed using the open-source computer algebra system «Maxima». The optimal placement of friction dampers is determined providing the minimal displacements of the frame. The developed approach can be further extended to various problems of the optimal design of buildings and structures.

Wind-resistant optimal design of tall buildings based on improved genetic algorithm

Modern tall buildings are likely sensitive to wind excitations due to their increasing height and structural flexibility. Proper or optimal wind-resistant structural design of such high-rise buildings is required or sometimes necessary to meet the requirement of safety and serviceability. Combining a genetic algorithm (GA) with improved penalty function and calculation method for equivalent static wind loads (ESWLs), this paper presents an optimal procedure for the wind-resistant design of tall buildings, which aims to minimize the total weight of the designed building subject to the constraints of top acceleration and lateral drifts. A penalty function is utilized to deal with the implicit expressed constraints of optimization. The ESWLs can be instantaneously updated due to the change of structural dynamic properties during the optimal design process. A 60-story rectangular reinforced concrete frame structure with the same geometric shape of the CAARC standard tall building is adopted to verify the feasibility of the presented method. The example demonstrates that the proposed optimal design procedure is an effective tool for the wind-resistant optimal design of tall buildings.

A statistical-based optimization method to integrate thermal comfort in the design of low energy consumption building

It is necessary to design energy-efficient buildings so that a trade-off between energy-savings and occupants’ thermal comfort is fulfilled. Advanced thermal comfort-based control strategies have been proposed for this purpose. However, such an approach could consume energy as the conventional one if the building is poorly designed. The aim of this study is to propose a method that integrates thermal comfort in the design of energy-efficient buildings. The use of sensitivity analysis and an optimization approach to identify the values of design parameters represent its core steps. The meta-modeling approach based on the design of experiments technique is adopted to perform the sensitivity analysis. Then, the obtained meta-models are used to optimize building design for the intended objectives. A case study is selected to test the proposed method. The results indicated that implementing the suggested strategy leads to about 20% of heating energy-savings compared to the base case while significantly enhancing occupant thermal comfort. Moreover, the results indicated that a reduction of about 22% of heating energy can be achieved compared to the comfort controlled case while it consumes 4% more if the comfort control is applied to the optimized design while maintaining consistent thermal comfort conditions.

Wind-resistant structural optimization of a supertall building with complex structural system

Wind load is the most critical kind of loads in the structural design of supertall buildings. Performance-based wind-resistant structural optimization can effectively reduce the material cost of supertall buildings in the premise of ensuring their structural safety and serviceability. For modern supertall buildings with complex structural systems, the formulation of its structural optimization problem is highly complicated. Moreover, the optimization problem itself is also nonlinear and extensive in scale. This study first addresses the optimization formulation of complex structure system which includes concrete-filled steel tube (CFST) frame members and shear wall members. These structural members are often used in supertall buildings but are seldom discussed in existing literature of structural optimization. Then, the interior point algorithm, which is propitious for large-scale nonlinear optimization, is used to seek the optimal design solution. A real-life supertall building, the 432 m Guangzhou West Tower, is used as an example to examine the effectiveness of the proposed computer-based optimization method. The proposed method is shown to work effectively in the optimal wind-resistant design of supertall buildings with complex structural systems.

Integrated Structural–Nonstructural Performance-Based Seismic Design and Retrofit Optimization of Buildings

The assessment of anticipated losses due to damage of both structural and nonstructural components is now recognized to be a key component in the performance-based seismic design or retrofit of buildings. Current performance-based seismic loss estimation procedures are building case-specific, and they do not easily allow for the integrated optimization of structural and nonstructural interventions in a particular building. The main objective of this paper is to develop a general optimization procedure within the performance-based earthquake engineering (PBEE) framework developed by the Pacific Earthquake Engineering Research (PEER) Center and implemented through the FEMA P-58 methodology. Available optimization procedures that can be applied to the PEER-PBEE framework are first reviewed, leading to the selection of the genetic algorithm for this purpose. The implementation of the genetic algorithm within the PEER-PBEE framework, considering integrated structural and nonstructural seismic upgrades, is described. The seismic retrofit case study of a 3-story steel moment-resisting frame archetype building is then conducted for the three different target metrics included in the PEER-PBEE framework: (1) an economic target metric, (2) a downtime target metric, and (3) a casualty-reduction target metric. The results of the case study indicate how this optimization process, based on the genetic algorithm, quickly and reliably converges to different allocations of resources for structural and nonstructural components depending on the target metric selected. Finally, a parametric study on the effects of the owner’s expected internal rate of return and building occupancy time on the optimum retrofit solutions illustrates the utility of the optimization process beyond the single case study.

Multi-objective Building Design Optimization under Operational Uncertainties Using the NSGA II Algorithm

Operational uncertainties play a critical role in determining potential pathways to reduce the building energy footprint in the Global South. This paper presents the application of a non-dominated sorting genetic (NSGA II) algorithm for multi-objective building design optimization under operational uncertainties. A residential building situated in a mid-latitude steppe and desert region (Köppen climate classification: BSh) in the Global South has been selected for our investigation. The annual building energy consumption and the total number of cooling setpoint unmet hours (h) were assessed over 13,122 different energy efficiency measures. Six Pareto optimal solutions were identified by the NSGA II algorithm. Robustness of Pareto solutions was evaluated by comparing their performance sensitivity over 162 uncertain operational scenarios. The final selection for the most optimal energy efficiency measure was achieved by formulating a robust multi-criteria decision function by incorporating performance, user preference, and reliability criteria. Results from this robust approach were compared with those obtained using a deterministic approach. The most optimal energy efficiency measure resulted in 9.24% lower annual energy consumption and a 45% lower number of cooling setpoint unmet h as compared to the base case.

Aerodynamic performance of CAARC standard tall building model by various corner chamfers

This paper takes CAARC standard tall building as example to investigate the effects of corner chamfers on the aerodynamic performance of tall buildings. Five rigid tall building models including CAARC standard tall building as benchmark model and four corner chamfered models with different modification rates from 5% to 20% are tested for pressure measurements in a boundary layer wind tunnel. Based on the experimental results, wind pressure coefficients, local wind force coefficients, base moment coefficients and their power spectral densities from the five models are compared and discussed. The results show that the aerodynamic performance of the tall building models can be effectively improved as the corner chamfer rate increases. The correlation factors for base moment coefficients and power spectral densities are proposed to assess the aerodynamic performance improvement. This paper aims to provide useful information for the wind-resistant optimal design of rectangular tall buildings.

Single Objective Optimization of Net Zero Energy Residential Building in Tropical Climate

The Building sector is the largest consumer of energy worldwide. Net Zero Energy Residential Building (NZERB) is one of the prudent approaches to reduce pressure on primary sources of energy. The main objective of this study is to use Taguchi simulation based on orthogonal arrays approach to optimize thermal envelope of a building, SEER value of HVAC system, lighting power density, and ventilation level to reduce the Building Energy Intensity (BEI) 50% lower than the base case building according to International Energy Conservation Codes 2015. In this study whole building energy simulation was performed by Hourly Analysis Energy Program and PVWatts calculator was used to estimate the size of the PV system for balancing the energy demand of the house. The results of Taguchi simulation approach show that by decreasing the U value of wall, windows, roof, floor to 0.1, 0.8, 0.1, 0.2 W/m2. °K respectively and ventilation rate 0.15 l/s-m2, lights of 110 lm/W and SEER of the HVAC system 4 (W/W option) reduce BEI from 147.78 kWh/m2/year for base case building to 67.085 kWh/m2/year for optimal design case. PV system size estimation was performed with PVWatts calculator. PV Watts recommended the size of 13kW DC rating system (open rack type) of 15% efficiency for the weather of Johor Bahru to meet the annual energy demand of the proposed optimal building design.

Predicting Crowd Egress and Environment Relationships to Support Building Design Optimization

Evaluating and optimizing the design of built and yet-to-be-built environments, with respect to human occupancy and behavior is both greatly beneficial and challenging. Crowd simulation can provide the computational means to analyze a design through the movement of virtual occupants (agents). A range of analytic information (metrics) can be computed from the simulated movement of the agents that offer insights on the design. Crowd simulation and the related analysis can be part of interactive or offline design optimization pipelines. Unfortunately, large scale crowd simulations are prohibitively expensive, especially when used within iterative design and optimization loops, where hundreds of simulations often need to be computed at interactive rates. We propose a machine learning framework that aims to solve this problem by learning the relationship between a building design and the evaluation metrics extracted from expensive simulations. We train an offline regression neural network using a synthetic training set that we generate for this purpose. Once the network is trained it can evaluate new designs efficiently, and approximate the corresponding analytic information with high accuracy. The proposed framework can also be used to find an optimized layout. We demonstrate the effectiveness of the framework on a variety of real world case studies.

Particle swarm method for solving the problems of nonlinear optimization

Purpose. The optimal design of buildings and structures requires solving a number of important tasks related to determining the best topology and geometric shape of structures, physical properties of elements, connections of elements among themselves, etc. In this case, it is necessary to take into account the influence of many factors: the distribution of static and dynamic loads, corrosive effects, the nature of the operating conditions, the requirements for the reliability and durability of the unit. The complexity of solving such problems is connected with the fact that, as a rule, the objective functions of such problems are nonlinear.Methods. Various approaches are used to solve nonlinear optimization problems: stochastic search (Monte Carlo method); search methods in which the step is successively reduced, following to the given relation (halving, golden ratio, inverse Fibonacci numbers); gradient descent method; evolutionary algorithms; penalty function method and others. In recent years, a new class of methods of numerical optimization has been intensively developed, in various works it is called social-behavioral, population, or swarm. For practical verification of the particle swarm method, the finding of the extrema of the test functions of Rosenbrock and Rastrigin is considered. Results. A new software implementation of one of the methods of artificial collective intelligence, the particle swarm method, is proposed for solving nonlinear optimization problems in the Maxima open-source computer algebra system. The high computational efficiency of this method for finding global extrema of “ravine” and multimodal functions in those cases where the application of many classical algorithms can be difficult is shown. Scientific novelty. Compared to classical methods, swarm intelligence methods are especially effective for finding extrema of nonlinear multimodal functions, as well as for solving high-dimensional problems. Practical significance. The effect of the method parameters (particle number and weight coefficients) on the rate of practical convergence is investigated. The developed method can be used, inter alia, to solve the problems of optimal design of building structures, buildings and structures.

BIM assisted Building Automation System information exchange using BACnet and IFC

Smart buildings are the trend of the next generation's commercial buildings that link different building systems together with the Building Automation System (BAS). Building information modeling (BIM) assists in data exchange and information flow. Previous research has explored BAS and BIM integration for energy management, building design optimization and operation, and building fault detection and diagnostics. However, it is rarely seen to design BAS or exchange BAS information in different project stages using BIM tools. The current design of the BAS system is either using 2D drawings based on AutoCAD or vendor customized tools. Unlike the other building systems, BAS seldom participates in design-build BIM cycle but blends into facility management in the later stage. To tackle this issue, this research aims to set a fundamental step to facilitate information exchange for BIM assisted BAS design and operation using one of the BAS open communication protocol named Building Automation and Control Networks (BACnet) and open BIM standard Industry Foundation Class (IFC). This paper leverages Information Delivery Manual (IDM) and Model View Definition (MVD) methodologies to define an IFC subset schema (a BACnet MVD) so that BAS information conforming to the BACnet protocol can be represented in IFC data model for information exchange throughout various project stages with BIM tools. Revit and a web browser were used to demonstrate the implementation of the BACnet MVD for BAS information exchange. In this way, BAS information represented in the open BIM standard can unlock the potential of future smart building information exchange and integration.

Bringing Energy Efficiency for Hospital Building through the Conservative and Preventive Measures

The energy consumption of hospital buildings, have increased due to embedment of sophisticated equipment pertaining to advent of technology. Factors affecting energy consumptions are air quality monitoring, high maintenance of sophisticated machineries, accurate sanitization of premises, high load of patients to doctor ratio in India which is 1596:1 as compared to regulation of 1000:1 prescribed by World Health Organization (WHO). Confederation of Indian Industry (CII) reported that nearly 60% of health care services and hospitals do not meet the minimum of Energy Performance Index (EPI) criteria. Energy Conservation Building Code (ECBC) of India shows that hospitals in India have a potential to achieve 42% energy saving by implementing energy efficient measures. Hence, there is a dire need to assess the parameters contributing to heavy energy consumption and the conservative and preventive measures need to be addressed. Literature indicates incorporation of efficient domestic water heating techniques, boilers, usage of renewable energies, thermal insulation improvement, optimal building design, improvement of air conditioning and heating systems, optimizing electric energy installations etc as possible techniques for achieving energy efficiency. A compile of best practices proposed from literature as compared to the regulations made by ECBC, CII, MEDA, and GBC (Green building council) is made in this paper. HVAC being the highest contributing system for energy consumption, IoT based working models are prepared and proposed for application; suitability of adoption of the system is discussed.

Metamodeling of mean radiant temperature to optimize glass facade design in PMV-based comfort controlled space

In recent years, glass facades and extensive glassing areas have gained popularity in the built environment. However, thermal comfort and energy-savings in such buildings are still questionable. Advanced comfort-based control strategies have been proposed in order to fulfill a tradeoff between energy-saving and occupants’ thermal comfort. Yet, they could consume energy as the conventional control approach if the building is poorly designed. Thus, an adequate design of building envelope, namely glass facades, is essential to achieve the desired trade-off. The objective of this study is to understand and formulate the relationship between the mean radiant temperature (MRT) and glass facades design parameters in a comfort-controlled space in order to optimize building design for a trade-off between energy savings and thermal comfort. The combined use of numerical simulations, the design of experiments (DoE) technique and an optimization approach is adopted. For the investigations, a previously developed and validated dynamic simulation model is used. The combined use of numerical simulation and DoE aims to identify the significant parameters affecting the MRT, as well as to develop a metamodeling relationship between the considered design factors and MRT. Lastly, the developed meta-models are validated and used to determine a set of optimal solutions using the desirability function approach. The results indicate that the optimized design case allowed about 26% reduction of heating energy consumption compared to the base case design. Finally, the results show that an adequate design of the glazed envelope leads to improved thermal comfort conditions and reduce heating energy consumption.

A Two-Stage Building Information Modeling Based Building Design Method to Improve Lighting Environment and Increase Energy Efficiency

Buildings are one of the largest energy consumers in the world, and have great energy saving potential. Thermal systems and lighting systems take most of the energy in a building. Comparing with the optimization solutions developed for a thermal system, the research of improving the lighting system is insufficient. This study aims to improve the lighting environment and reduce the energy by optimizing the building design, which has the largest potential for cutting energy economically compared with the other stages in the life cycle of a building. Although many approaches have been developed for building design optimization, there is still one big problem obstructing their successful practices, in that the designers who take the responsibility of making building designs are not experts in building physics, thus they are not capable of calculating the most appropriate parameters and operating the professional software to optimize their designs. Therefore, this study proposes a user-friendly method for designers to improve building designs. Firstly, Building Information Modeling (BIM) and particle swarm optimization algorithm are applied to build an intelligent optimal design search system. The optimized design from this system can largely use daylighting for internal illumination and save energy. Secondly, different types of lighting control systems are compared and the one which can save maximal energy is added to the selected optimal design. A case study demonstrates that optimized designs generated by the proposed design method can save large amounts of life cycle energy and costs, and is effective and efficient.

A parametric approach for performance optimization of residential building design in Beijing

During the early design stage of green residential buildings, there are tremendous potential of using parametric optimization to achieve preferable green performance, such as building energy consumption efficiency, daylighting, ventilation and thermal comfort. Taking residential design features into consideration, this paper presents an optimization workflow and effects based on a case study of a residential building project in Beijing. Firstly, 27 design parameters related to residential spatial form and building envelope were selected for the optimization. The simulation results of the cooling and heating load were taken as the optimization objects. Secondly, optimized schemes were obtained from 6246 simulation results, with 1925 verified simulation results proving that the optimized result is reliable. Finally, analysis was performed to establish the correlations between design parameters and performance in order to create the easy access for architects to determine design parameters depending on the performance sensitivity of each parameter. Analysis results showed that parametric optimization of spatial form and building envelope at the design stage is a feasible approach to reducing energy consumption in residential building design.