Passive Design Parameters Research Articles

An integrated approach of BIM-enabled LCA and energy simulation: The optimized solution towards sustainable development

Abstract Passive design strategies such as orientation, shading, sealing, glazing, and insulation can significantly reduce the necessity of an artificial heating-cooling system, accounting for 40% of total energy usage in the residential building. However, none of the previous studies have quantified the energy reduction and their environmental impacts simultaneously for these passive design parameters to achieve the national standard requirements for house rating. Hence, this study focuses on the use of Building Information Modeling (BIM-Autodesk Revit), energy rating tool (FirstRate5), and BIM-enabled life cycle assessment (LCA-Tally) to quantify, compare, and improve the building design options to reduce carbon footprint and energy consumptions in residential dwellings. Sensitivity analysis has been performed with the @Risk Palisade decision tool for optimizing operational energy efficiency. The sensitivity indices show the ceiling (0.84–0.96) and the wall (0.22–0.37) are the most influential predictors for passive design strategies to reduce energy consumption. A moderate correlation exists with windows, floors, and orientations (0.13–0.29), where the relationship with eave projection, air infiltrations is relatively weak. BIM has been used as a platform of interconnectivity between optimized operational energy of @Risk optimizer and consequent embodied phases. A comparative study of insulation performance identifies that 95% of the ceiling’s total operational energy consumption can be minimized using R3 rather than R6 of the national thermal code. For the wall, 90% of energy minimization can occur using R2 rather than R4 of the national thermal code. The study reveals that while insulation is only 1% of the total building mass, and the corresponding carbon footprint and primary energy demand are 4% and 7%, respectively, LCA explains a significant amount of energy, about 76% reduction at its operational stage. In this paper, an evidence-based analytical framework provides a BIM-based optimization platform to validate and justify the impact categories of environment-friendly, energy-efficient design of houses.

Effectiveness of passive design strategies in responding to future climate change for residential buildings in hot and humid Hong Kong

The application of passive design strategies is crucial at the early architectural design stage for building energy use minimization. However, the time-varying effectiveness of passive design strategies in responding to future climate change in hot and humid climates are rather limited in the literature. This paper aims to examine the dynamic effectiveness of passive design strategies for residential buildings in Hong Kong under the context of future climate change. Using the newly developed hourly weather data and adaptive comfort standard model, the dynamic effectiveness of viable passive design strategies for residential buildings are evaluated over time in the 21st century by plotting Givoni building bio-climatic charts (BBCC) and simulation-based sensitivity analyses in a validated EnergyPlus model. Results show that solar protection strategies are still the highly sensitive strategies for building energy performance and the effectiveness of external windows’ airtightness is expected to increase up to 329% by the end of this century, whereas the cooling potential of ventilation utilization will significantly decrease over time. When the different combination of sensitive passive design parameters is implemented onto the baseline residential building model for different climate scenarios, the annual and peak cooling load can be reduced up to 56.7% and 64.5%, respectively.

Influence of Passive Design Parameters on Thermal Comfort of an Office Space in a Building in Delhi

Abstract Energy efficiency measures in buildings, along with maintaining indoor thermal comfort, are increasingly drawing attention. The most widely accepted indices, Predicted Mean Vote (PMV) and ...

Sensitivity Analysis of Passive Design Strategies for Residential Buildings in Cold Semi-Arid Climates

Buildings are significant drivers of greenhouse gas emissions and energy consumption. Improving the thermal comfort of occupants in free-running buildings and avoiding active and fossil fuel-based systems is the main challenge in many cities worldwide. However, the impacts of passive design measures on thermal comfort in cold semi-arid regions are seldom studied. With the rapid urbanization and the widespread use of personalised heating and cooling systems, there is a need to inform building designers and city authorities about passive design measures that can achieve nearly optimal conditions. Therefore, in this study, a global sensitivity analysis of the impact of passive design parameters on adaptive comfort in cold semi-arid climates was conducted. A representative residential building was simulated and calibrated in Quetta, Pakistan, to identify key design parameters for optimal thermal comfort. The results list and rank a set of passive design recommendations that can be used widely in similar climates. The results show that among the investigated 21 design variables, the insulation type of roof is the most influential design variable. Overall, the sensitivity analysis yielded new quantitative and qualitative knowledge about the passive design of buildings with personalised heating systems, but the used sensitivity analysis has some limitations. Finally, this study provides evidence-based and informed design recommendations that can serve architects and homeowners to integrate passive design measures at the earliest conceptual design phases in cold semi-arid climates.

Analysis of the Indoor Thermal Environment and Passive Energy-Saving Optimization Design of Rural Dwellings in Zhalantun, Inner Mongolia, China

Zhalantun city is located in a severely cold region of China. The cold climate and long winter bring challenges to the energy-saving design of rural dwellings in this area, while the poor economic conditions restrict the application of energy-saving technology. This paper aims to propose an optimal combination of passive design parameters by investigating, testing, and analyzing simulations of Zhalantun rural dwellings, which have a particular architectural pattern. Field measurements during winter show that the indoor temperature of a traditional house is low and fluctuates greatly, and the inner surface is prone to easy condensation. Through thermal comfort surveys, neutral and acceptable temperature ranges were obtained to provide indoor calculation parameters for an energy-saving design. Numerical simulations of heating energy consumption were conducted on the typical building models using DesignBuilder. The influence of different design factors on energy consumption was evaluated. Orthogonal experiments were designed to optimize a series of design parameter combinations to reduce the energy consumption of Zhalantun rural houses and to determine the sequence and significance of the effect of these design factors on energy consumption. Results show that the optimal parameter combination based on orthogonal experiments can obviously reduce energy consumption and have better economic benefits without considering mechanical methods. This can provide a basis for improved energy-saving designs and indoor thermal environments in such rural dwellings.

Optimization of passive design features for a naturally ventilated residential building according to the bioclimatic architecture concept and considering the northern Morocco climate

Improving the wellbeing of the occupants is the main challenge in the building design field. This work aims optimizing the design of a free-running residential building located in northern Morocco according to the bioclimatic architecture concept. In the first stage, an analysis of the bioclimatic chart has been done to find the best passive design strategies for the northern Morocco climate. Based on the results of the analysis, a set of passive design parameters has been selected to be considered in a building thermal and lighting energy performance optimization. A case study of a family detached residential building is considered for this purpose. The optimization problem is multi-objective, so the Pareto front approach was used to select the best design solution. Finally, a monthly assessment of the thermal and lighting energy performance of the chosen design solution is presented. The main results show that applying exterior insulation with a thick thermal mass layer is best for thermal performance enhancement. A wider glazed area with small overhang depth is more suitable for the south facade. For the east facade, the best solution is to limit the glazed area and increase the overhang depth. The importance of natural night ventilation for summer cooling has been also confirmed. This study can serve as a reference for building designers in northern Morocco while developing their projects.

Exploring the optimization potential of thermal and power performance for a low-energy high-rise building

In this study, a novel high-efficient energy-saving vacuum BIPV (building integrated photovoltaic) curtain wall, which combines photovoltaic curtain wall and vacuum glazing technologies, was developed and investigated. This vacuum BIPV curtain wall can not only perform on-site power generation, but also significantly reduce the heat transfer through the building envelope with improved thermal insulation. The thermal and power performance of the vacuum PV glazing were investigated by experiments and numerical simulations. A prototype of the vacuum BIPV curtain wall was set up for a short-term outdoor testing to consolidate its thermal and power performance under typical weather conditions of Hong Kong. A comprehensive energy model was then developed to predict the dynamic power and thermal performance of the vacuum BIPV curtain wall to evaluate its annual energy saving potential compared to other advanced window technologies used in buildings in Hong Kong. Based on the simulation model, an optimum design of the vacuum BIPV curtain wall was proposed. In addition, the annual energy-saving potential for a typical high-rise commercial building with the application of miscellaneous BIPV products was estimated using the typical meteorological data. BIPV characteristics were jointly optimized with other passive architectural design parameters and the net building energy demand can be decreased by up to 60% compared with a benchmark office building in Hong Kong. The target of near-zero energy high-rise building can therefore be further approached by this integrated design optimization process.

Energy optimization of high-rise commercial buildings integrated with photovoltaic facades in urban context

This research thoroughly explored the impact of archetypes and confounding factors on a proposed holistic design optimization approach for high-rise office buildings with integrated photovoltaic (PV) facades. The design optimization adopts the hybrid generalized pattern search particle swarm optimization (HGPSPSO) algorithm, which is incorporated with qualitative and quantitative sensitivity analyses for factor prioritizing and fixing. Different archetypes are modelled by changing floor plan sizes and shapes, while diverse urban contexts and internal load (heat gain) levels are investigated as major confounding factors beyond designers' control. Variation of these four simulation scenarios are then used to examine the uncertainty of sensitivity indices and optimization potential for passive architectural design parameters. The window geometry, thermal and optical properties are proved to be most important to the reference PV envelope design. The building plan shape is found to have little impact on the weighting of different design parameters, while the shape coefficient (SC) is determined to be almost linearly correlated with the HVAC (heating, ventilation and air-conditioning) demand. The office design with the highest shape coefficient can therefore achieve a net energy demand reduction up to 48.77%. The floor plan size also has minor impact on the sensitivity index for each design factor, but the energy-saving potential grows with decreasing floor sizes. On the contrary, confounding factors can greatly change the sensitivity analysis (SA) result. The window U-value becomes more important with an increasing internal load level and urban context density whereas the impact of the window light-to-solar gain ratio is reduced by peripheral shading. Furthermore, varying confounding factors can even change the dimension of optimization problems based on different factor fixing results. This research can provide early-stage design guidance for energy efficient buildings with a comprehensive analysis of pragmatic building archetypes, background contexts and operation scenarios.

Passive design optimization of low energy buildings in different climates

Worldwide, the residential buildings are consuming a considerable amount of energy. The high potential of buildings towards energy efficiency has drawn special attention to the passive design parameters. A comprehensive study on optimal passive design for residential buildings is presented in this paper. Twenty-five different climates are simulated with the aim to produce best practices to reduce building energy demands (for cooling and heating) in addition to the life-cycle cost (LCC). The occupants' adaptive thermal comfort is also improved by implementing the appropriate passive cooling strategies such as blinds and natural ventilation. In this respect, the implemented methodology is composed of four phases: building energy simulation, optimization, Multi-criteria Decision Making (MCDM), sensitivity study, and finally an adaptive comfort analysis. An optimal passive solution of the studied building indicates the potential to save up to 54%, 87% and 52% of the cooling demands (Qcool), heating demands (Qheat) and LCC respectively with respect to the initial configuration. The obtained optimal passive parameters are validated with the National Renewable Energy Laboratory NREL benchmark for low energy building's envelope. Additionally, the integrated passive cooling strategies have demonstrated its competency since it leads to a significant overheating decrease.

Evaluation of impact of passive design measures with energy saving potential through estimation of shading control for visual comfort

Residential and commercial buildings together account for one-third of world’s final energy consumption, thus making energy management in buildings of considerable significance. Passive design concept that depends on climate and location can be used as an effective and economical method to reduce the energy consumption in buildings. Seven cities in India, each representative of different geographic and climatic conditions, were selected for analysis. This article studies how the peak cooling and heating load are affected by varying some of the passive design parameters for each of the seven cities. The parameters varied are wall insulation thickness, roof insulation thickness, overhang depth, window orientation, and window-to-wall ratio. Results show that optimized passive design could reduce the peak cooling and heating loads by about 50%. Shading reduces cooling loads but is found to increase heating loads. In some of the locations, both heating in winter and cooling in summer are needed and designers should adopt appropriate passive measures depending on the location. Also for the same building, evaluation of shading is done in the context of lighting energy savings. An algorithm has been developed to iteratively alter and analyze set of roller blind positions to maintain visual comfort; as a result, the corresponding potential annual energy savings due to lighting were estimated. It was also observed that even after providing visual comfort to the occupants, energy savings only reduced by approximately 1% as compared to the case when visual comfort was overlooked.

A multi-stage optimization of passively designed high-rise residential buildings in multiple building operation scenarios

This article proposes a two-stage design optimization approach which is applied to a prototype passively designed high-rise residential building under different ventilation modes and thermal load requirements. Machine learning methods are employed to develop surrogate models for improving the computation efficiency of the multi-objective optimization process. The surrogate model is trained by modeling experiments with EnergyPlus and R, which can provide reliable energy performance indicators of generic building models featuring passive design parameters including the building layout, envelope thermophysics, building geometry and infiltration & air-tightness. The lighting, cooling and heating demands of the generic building model are determined by the hybrid ventilation and light diming control strategies in compliance with local green building assessment criteria in Hong Kong. The multiple linear regression (MLR), multivariate adaptive regression splines (MARS), and support vector machines (SVM) are examined by the statistical modelling. SVM is capable of fitting a surrogate model with the best prediction performance based on the coefficient of determination and root mean square error. In addition, both single-sided ventilation and cross-ventilation models under varied thermal load requirements are investigated to compare the preferable design solutions for each scenario. The multi-stage optimization approach is also applied to a Mediterranean climate to explore optimal design solutions in more diverse external environmental conditions. This research can provide a highly efficient design optimization tool to appropriately deploy passive architectural strategies in a green building project.

Optimization of thermal and daylight performance of school buildings based on a multi-objective genetic algorithm in the cold climate of China

A high demand for heating energy in winter, overheating in summer and visual discomfort are important issues in school buildings in the cold climate of China. This study presents the use of simulation–optimization tools to find the optimal trade-off between minimizing energy use for heating and lighting, reducing summer discomfort time and maximizing the Useful Daylight Illuminance (UDIavg, between 100 and 2000lx). Different spatial configurations were investigated, including a single-sided open corridor type, a single-sided enclosed corridor type and a double-sided corridor type school. The following passive design parameters were considered in the optimization analysis: orientation, room depth and corridor depth, window-to-wall ratio of different interfaces, glazing materials and shading types.The results of the optimization study show that the energy demand for heating and lighting can be reduced by 24–28% and summer thermal discomfort by 9–23% while the UDIavg (100–2000lx) can simultaneously increase by 15–63%. Considering all three aspects, the double-sided enclosed corridor type performs best due to its energy performance while the one-sided enclosed corridor type is the least suitable for the cold climate because of its relatively poor visual comfort quality. In addition, the passive design parameters should be carefully considered as each spatial configuration has its own optimal passive design parameters.

Parametric study of a cost-optimal, energy efficient office building in Serbia

Recent building regulations in Serbia prescribe the design of highly insulated, airtight buildings with low U-value glazing. Serbia has continental climate with hot summers, so that for office buildings, whose internal gains are higher from the presence of people, computer systems and lighting, this means that far more focus has to be put on cooling demands than on heating demands. This shift toward cooling is studied here through exhaustive simulation of combinations of selected passive solar design parameters for a model of an office building in Belgrade. Design parameters include glazing type, window-to-wall ratio of façades, presence of exterior shading and U-value of opaque envelope components. Optimal variants of the model have been determined with respect to construction cost and heating, cooling and lighting energy use. Results reveal that exterior shading, which has to sustain occasional strong winds in Belgrade, is too expensive to appear in cost-optimal solutions. Hot summers of Belgrade climate imply that cost-optimal solutions have close-to-minimal window-to-wall ratio at the southern façade and significantly larger window-to-wall ratio at the northern façade. Results further show that glazing in cost-optimal solutions has to have small U-value and medium solar heat gain coefficient, although specific choices of optimal glazing type, as well as thermal insulation level, depend on future electricity prices. The case study is repeated for climates of Frankfurt and Stockholm as well, which yield similar results with respect to glazing type and the absence of exterior shading, but with different patterns of window-to-wall ratios at the southern and northern façades.

An Exhaustive Parametric Study on Major Passive Design Strategies of a Typical High-rise Residential Building in Hong Kong

This paper presents a comprehensive sensitivity analysis (SA) of the typical High-rise residential building in Hong Kong. A generic building model is constructed with proposed natural ventilation strategies subject to the examination of thermal comfort criteria. The numerical modelling exhaustively investigate the thermal and energy responses based on the variation of different passive design parameters. The parametric studies with respect to multiple output indices are able to prove that the window solar heat gain coefficient is the most influential architectural design factor. Different thermal comfort models including the Adaptive Comfort Standard (ACS) and Predicted Mean Vote (PMV) are compared in estimating the indoor environmental quality (IEQ) for the generic building. It is believed that sensitivity analysis benefit the identification of important inputs to facilitate further optimization of the building performance in initial plan stages.

A comprehensive sensitivity study of major passive design parameters for the public rental housing development in Hong Kong

This paper presents a comprehensive SA (sensitivity analysis) of the typical PRH (public rental housing) development in Hong Kong based on a combined building energy, daylight and AFN (airflow network) simulation. A generic building model is constructed with a proposed MM (mixed-mode) ventilation control strategy to fulfill the thermal comfort requirement in the local green building guidance. The numerical modeling results are used to conduct both local and global sensitivity analyses to determine the relative importance of major passive design parameters, which comprehensively cover design aspects of the building layout, envelop thermophysics, building geometry and infiltration & air-tightness. The calculated global and local sensitivity indices on the cooling energy prove that the window solar heat gain coefficient, window to ground ratio, external obstruction and overhang projection fraction are the four most influential passive design factors. Similar results are also obtained when the lighting energy is specified as the output of the sensitivity analysis. The optimized building model derived from the sensitivity analysis is anticipated to achieve an energy saving of 41.6% compared to the baseline model as stipulated by the local building regulation. It is believed that sensitivity analysis is useful for identifying crucial design parameters to facilitate further optimization of the building performance in early architectural design stages.

Assessing effectiveness of utilization of passive design parameters on active energy consumption in public buildings in warm-humid climate

Energy requirement in buildings for physiological comfort can be in form of active or passive energy. When the buildings are not energy conscious and passive energy is not well utilized to achieve the desired comfort level, the use of active energy becomes necessary. The mean minimum satisfaction rating of 1.13 which was significantly correlated at 0.01 level, and mean maximum satisfaction rating of 3.34 which was significantly correlated at 0.05 level were achieved. Various strategies for energy conscious building design were highlighted. The study revealed in the regression models that the contribution and effectiveness of the sets of explanatory variables varied. The regression equations for each of the subsectors of the public buildings was with 0.610 ≥ R2 ≥ 0.099, 0.520 ≥ AR2 ≥ 0.033 and 0.227 ≥ significant level ≥ 0.000. The effectiveness/contribution of utilization of most effective independent variables of climate responsive design (CRD) parameters on active energy consumption (Ec) are 0.327(32.7%) ≥ SR2 ≥ 0.000(0.0%). Key words: Buildings, physiological comfort, passive energy, active energy, energy conscious building design, climate responsive design (CRD) parameters.

Structural-Acoustic Optimization of Composite Sandwich Structures: A Review

We review recent advances in the area of composite sandwich modeling, sensitivity analyses, optimization techniques and applications, with the focus on structural-acoustic problems. The optimization of sandwich structures is with respect to passive design parameters, such as material constants, geometric parameters, cellular core geometry and boundary conditions.

Impacts of some building passive design parameters on heating demand for a cold region

In this study, the impact of passive design parameters such as building shape and orientation position on heating demand has been theoretically investigated. Therefore, a transient heat transfer problem in the building envelope with insulation and without insulation is solved by using the finite difference method. The considered buildings are placed on the ground with the azimuth angles from 0 ∘ to 90 ∘ . The heat loss per unit area of the buildings is computed by hour–hour and the yearly energy consumption of the buildings is also determined in the simulation model. The climatic data of Elazigˇ ( 38 . 4 ∘ N ) , a city located in a cold region of Turkey, are considered for the analysis. It is shown that buildings with a square shape have more advantages, and the most suitable orientation angles are 0 ∘ and 80 ∘ for buildings having shape factors (the ratio of building length to building depth ) 2/1 and 1/2, respectively.