Building Systems Research Articles

Seismic performance assessment of structural systems in the aftermath of the 2023 Kahramanmaraş earthquakes: Observations and fragility analyses

This article evaluates how different reinforced concrete (RC) building systems in Türkiye behaved during the extreme 2023 Kahramanmaraş earthquakes. The analysis relies on a comprehensive field survey covering 242 RC buildings across various heavily affected locations. Most surveyed buildings were low- and mid-rise RC moment frames and frame-wall (hybrid) systems, with RC wall construction being less commonly observed. Both RC frame and hybrid buildings exhibited several common deficiencies, resulting in significant structural and non-structural damage due to high drift demands. The performance of RC wall construction varied, with some buildings sustaining severe damage while others remained largely unaffected. An analysis of structural plans revealed that RC wall buildings with adequate wall amounts demonstrated exceptional performance, while those with inadequate amounts of walls experienced severe damage. In addition, fragility analyses using simplified models based on surveyed buildings reinforced these findings. The analyses suggested that RC frame and hybrid systems were insufficient in ensuring life safety during the earthquakes. Conversely, properly designed RC wall buildings are expected to perform well. This alignment between field observations and fragility analyses underscores the reliability of the study’s findings and emphasizes the effectiveness of RC wall construction in mitigating seismic risks and protecting life and property.

Cooling peak load reduction potential of ventilated slabs: a numerical study

Thermally activated building systems provide an effective method to combine thermal inertia and HVAC systems, and can be used to promote comfortable indoor conditions in summer. Ventilated slabs (VS) use supply air flow directly for heating or cooling, without the need for separate auxiliary systems. This paper proposes a detailed model of an office building equipped with VS under three different climatic conditions during one month in the summer. A Model Predictive Controller and a Genetic Algorithm, developed in MATLAB, are subsequently implemented to reduce energy consumption of the system while maintaining the room temperature set point. The outcomes of both short and extended sequences are presented after conducting modelling considerations. The dynamic behaviour of the room is highlighted, while the cooling demand is further evaluated using statistical indexes. The reduction in peak cooling load was noted in all instances, including during outdoor conditions that are unfavourable to free cooling strategies.

Traditional Building Knowledge in Indian Lime and Earthen Plasters

India's traditional building systems and knowledge involving natural materials provide fine examples of low-carbon, place-adaptive architectural solutions as well as embodying simplicity and holistic sustainability. They utilize locally available materials prepared and applied so as to build structures and dwellings that are resilient to climate conditions and able to provide comfort and livability. Culturally, this knowledge is transferred orally from generation to generation and continuously recreated. Unfortunately these knowledge systems and practices have become endangered owing to a rupture in their continuity for reasons such as a preference for and incentivization of easier conventional solutions like cement and steel. With a focus on natural plasters used traditionally, this paper highlights some of these diverse plasters along with their natural additives.

Multi-Objective Optimization of Insulation Thickness with Respect to On-Site RES Generation in Residential Buildings

This paper investigates the optimization of insulation thickness with respect to the integration of renewable energy systems in residential buildings in order to improve energy efficiency, maximize the contribution of renewables and reduce life cycle costs. Using the DesignBuilder and EnergyPlus software, this study models a representative two-story residential building located in Athens, Greece. The building envelope features extruded polystyrene thermal insulation and windows with unplasticized polyvinyl chloride frames and low-e glazing. Six scenarios with hybrid renewable energy systems are analyzed, including air- and ground-source heat pumps, solar thermal systems and a biomass fired boiler, so as to assess energy consumption, economic feasibility and internal air temperature conditions. A Pareto-fronts-based optimization algorithm is applied to determine the optimal combination of insulation thicknesses for the walls, the roof and the floor, focusing on minimizing the life cycle cost and maximizing the percentage of renewable energy utilized. The results demonstrate that scenarios involving biomass boilers and solar thermal systems, both for heating and cooling, when combined with reasonable thermal protection, can effectively meet the recent European Union’s directive’s goal, with renewable energy systems contributing more than 50% of the total energy requirements, whilst maintaining acceptable internal air temperature conditions and having a life cycle cost lower than contemporary conventional buildings.

Under the Perspective of Seeing Party Self-governance Exercised Fully and with Rigor: Research on High-quality Party Building Leading and Guaranteeing High-quality Cadre Team Construction

Abstract: The Third Plenary Session of the 20th CPC (the Communist Party of China is referred to as CPC in this paper) Central Committee stressed that the focus is on improving the Party's leadership and long-term governance capacity, innovate and improve the mode of leadership and governance, deepen reform of the system for Party building, and optimize the system for seeing party self-governance exercised fully and with rigor. This is a strong response to Xi Jinping's speech on July 1st that "it takes a good blacksmith to make good steel" and the report of The 20th CPC National Congress emphasized "the Party's self-revolution." It highlights the significance of full and rigorous Party self-governance and the value and orientation of building the ranks of party cadres. In the new era, to carry out the Party building in government organs and ensure the construction of cadres, this study focus on the "high-quality" under the "full and rigorous Party self-governance". That is, the historical starting point and the theoretical quality of the guiding ideology of Party building is "high-quality", and the "evaluation criteria" of Party building promotes the responsibility of The Times, the quality and ability.

ABSORPTION REFRIGERATION SYSTEMS FOR WASTE HEAT RECOVERY AT THE SILICATE INDUSTRY

The glass, ceramic and cement plants are energy intensive industrial systems, releasing high amounts of greenhouse gases. The dissipation of the waste heat reduces their profitability, energy and ecological efficiency. The absorption refrigeration systems are successful solutions for the recovery of thermal energy at different temperature levels to obtain useful cooling and heating powers for technological needs, and for air conditioning of administrative and industrial buildings. Although the absorption units in a heat pump and refrigeration cycle are currently used in building and industrial systems, they have not yet penetrated widely into the silicate factories. This paper discusses possibilities for the applications of basic types of absorption cycles at heat pump and refrigeration modes to utilize waste energy at different temperature levels in glass, ceramic and cement plants. The examined variants are demonstrated via examples, diagrams and analyses of the possible energy saving.

On the Stresses in Thin-Walled Channels Under Torsion

Thin-walled channel beams such as cold-formed steel purlins are primarily used to withstand wind forces in the roofing and walling systems of buildings. Traditionally, these types of members are usually designed for bending moments, with the effects of torsion ignored. However, the loading on thin-walled channels can be much more complicated than simple bending actions. Because of the position of the shear centre outside the section, channels can undergo bending and torsion when subjected to vertical load on the top flange. The applied torsion may cause significant stresses in the channel, which may need to be accounted for in design. There appears to be no research on quantifying the effects of torsion on thin-walled channels subjected to a uniformly distributed load acting on the top flange. In this paper, a theoretical solution is derived for calculating the longitudinal stresses in thin-walled channels subjected to torsion caused by a uniformly distributed load acting on the top flange. The theory is validated by modelling the channels in a finite-element analysis. The theoretical results include calculations of the twist rotation, bimoment, sectorial coordinate and longitudinal stresses, while the results from the finite-element analysis include the twist rotation and longitudinal stresses. The results show that the longitudinal stresses caused by torsion can significantly exceed those caused by the bending moment. Practical advice is also given for engineers on how to minimize torsion in cold-formed steel purlins.

Commentary: Strengthening System Readiness for Health Interventions: Lessons for Implementing Interventions and Implementation Support in Low-And Middle-Income Countries.

In low- and middle-income countries (LMICs), barriers such as low system readiness, contextual mismatches, and resource limitations impede effective implementation of evidence-based interventions. This commentary offers insights into overcoming these challenges with a case study of the PRISM project, designed to reduce behavioral and psychological symptoms of dementia in older adults living in Thailand. The case highlights how combining two evidence-based models - the Reducing Disability in Alzheimer's Disease clinical intervention and the Getting To Outcomes implementation science process enhances program success. Using interviews with stakeholders across various health system levels, we identify factors critical to successful program implementation: (1) integrating interventions into policy frameworks, (2) empowering local implementers, (3) fostering collaborative learning, and (4) adapting interventions to local contexts. The case demonstrates that building system readiness through local engagement and ownership is central to scaling up health programs in LMICs. This commentary's contribution lies in its emphasis on the role of implementation science as a vehicle for translating research into practice. It presents a practical, adaptive model for embedding interventions into routine health systems, thereby offering a pathway for successfully scaling up evidence-based programs in LMICs. Such findings provide lessons for overcoming barriers to implementation in resource-limited environments.

Cost-Effectiveness Analysis of Nearly Zero-Carbon Office Buildings in Taiwan

The formulation of an affordable and economically-feasible policy for nearly zero-carbon building design is a challenge that countries encounter in promoting net-zero building. In 2022, Taiwan promulgated Building Energy Rating System (BERS), the world's first building energy efficiency assessment system tailored for subtropical climates, as a basis for evaluating its goal of achieving nearly zero-carbon buildings by 2050. However, whether this nearly zero-carbon building policy is financially feasible has remained unknown to the government and the industry. To address the issue, the objective of the paper is to conduct a cost-benefit and payback period analysis of newly constructed nearly zero-carbon office buildings in accordance with the Building Energy-efficiency Rating System for New Buildings (BERSn) assessment framework, and thereby examines the financial affordability and feasibility of Taiwan's net-zero building policies.Firstly, this study introduces existing building energy performance evaluation methods in Europe, America, and Japan, and explains the methodology of Taiwan's Building Energy Rating System (BERS). The paper then reviews international Cost-Benefit Analyses of Nearly Zero Energy Office Buildings and parallelly conducts a Cost-Benefit Analysis of Nearly Zero-Carbon Office Buildings in Taiwan. Following the BERS methodology, this paper identifies the baseline efficiency level and the Nearly Zero-Carbon Building (NZCB) efficiency level, along with their associated solutions and investment costs, for air conditioning and lighting systems. In this study, a questionnaire survey of 28 experts identifies the air conditioning unit costs of Basic Mechanical Equipment Efficiency (BME) and energy-saving control technologies (R) for energy-efficient design of Fan Coil Unit (FCU), Air Handling Unit (AHU), and Variable Refrigerant Flow (VRF) system. Accordingly, 33 air conditioning design solutions and their corresponding construction costs complying with the BERSn requirements of EAC≦0.5 for nearly-zero carbon office buildings are identified. Regarding the nearly zero-carbon lighting design, the simulations reveal that the use of LED panel luminaires or T8 LED luminaires (including those with energy-saving labels) can achieve an average operational lighting illuminance of 500 LUX and the BERSn requirements of EL ≤ 0.5 for lighting. Finally, the study further analyzes the payback period and premium cost ratio of NZCB by employing the budget data of seven building projects. The analysis shows that the premium cost ratio and the payback period of NZCB range from 1.33%-1.50% and 6.4-7.7 years, respectively. The results demonstrate that while a higher budget is commonly associated with NZCB by the public, it is in fact economically and technologically feasible to realize NZCB with prevailing energy-efficient measures.

Thermal performance analysis of a domestic-size absorption cooling system incorporating nanofluid with thermal insulation in hot climate of Algeria

The increased demand for energy consumption for air conditioning, due to rising temperatures, has created challenges related to thermal comfort in residential environments .In the present study, a simulation of an air conditioning system for a small building was conducted, considering various absorption cooling scenarios to assess system performance through dynamic and economic analysis. The proposed system employs a parabolic trough collector in conjunction with a storage tank, designed to cool a 12 m² room in Adrar, Algeria. The study aims to identify the optimal scenario based on temperature, heat, and system coefficient of performance indicators. A computer program was developed using characteristic equations and finite difference methods to analyze the system's behavior with different nanofluid concentrations and thermal insulation. Simulation results show that scenario with nanofluid and insulation the best performance is achieved with a 4% nanofluid concentration, a 9 m² solar collector, a 0.3 m³ storage tank, and 0.05 m thick polystyrene insulation. The system can operate for 9 h, maintaining an indoor temperature of 27°C with a peak cooling load of 3 kW. The economic analysis estimates an investment cost of 4535.4$ and Net Present Value 3,370.40$ with a payback period of 12 years and 3 months.

Performance analysis of air conditioner system integrated with thermal energy storage using enhanced machine learning modelling coupled with fire hawk optimizer

Integrating air conditioning (AC) systems with thermal energy storage (TES) offers a promising solution for managing large buildings' peak load demands and energy efficiency. Predicting the performance of the AC-TES is a significant index in ensuring optimal cooling load and energy consumption. However, conventional approaches encounter challenges in achieving high levels of accuracy, reliability, and scalability. Therefore, this study introduces leveraging machine learning techniques and in-situ measurements for precise predicting the energy performance of AC-TES system in a semi-arid climate building. The study proposes a hybrid prediction strategy leveraging the benefits of machine learning and meta-heuristic optimization algorithms. The proposed approach integrates a Radial Basis Function Neural Network (RBFNN) with the Fire Hawk Optimizer (FHO) for predicting the performance parameters of the AC-TES system; including, energy consumption, cooling load, air room temperature and performance coefficient (COP). The RBFNN framework in the developed strategy is trained to identify intricate patterns and correlations within the data, while the FHO is utilized to explore the optimal hyperparameters of the RBFNN for maximizing the prediction accuracy. The proposed strategy was modelled in MATLAB software and validated using a publicly available measurements for the AC-TES system. The system maintained improved cooling performance in which the average daily values of energy consumption, cooling load, air room temperature and COP are 1100 kWh/hr, 1.30 kW, 23.97 oC, and 3.12, respectively. The statistical outcomes depict that the developed RBFNN-FHO strategy achieved an impressive prediction accuracy of 95.81% accuracy, a 0.94 correlation coefficient, a 0.4193 mean absolute error (MAE), and a 0.5200 root mean square error (RMSE), respectively. Furthermore, the performance of the proposed RBFNN-FHO is model, is compared with the existing machine-learning approaches utilized for predicting the dynamic performances of HVAC systems. The comparative analysis with existing techniques highlights the robustness and effectiveness of the proposed RBFNN-FHO strategy in predicting AC-TES performances.

Design, Optimization, and Autonomous Construction of Martian Infrastructure including Slabs Using In-situ CO2-Based Polyethylene

A crucial development in 21st-century space exploration is the establishment of human settlements on Mars. In recent years, Mars exploration rovers have been deployed, and studies investigating human journeys to Mars have been conducted, with the objective of a human-crewed mission to Mars before 2050. This study presents an innovative approach to designing and optimizing Martian habitats by using in-situ CO2-based polyethylene (PE) as a construction material for Martian buildings and greenhouses. It seeks to develop sustainable and resilient habitats on Mars, leveraging local resources to address the environmental challenges specific to the Martian environment. The research targets several key areas: realistic construction techniques, effective utilization of in-situ materials, and building resilience under the harsh Martian conditions. These conditions include radiation, micrometeoroid impacts, low atmospheric pressure, low gravity, wind storms, temperature extremes, Paschen discharge, and marsquakes. Finite element analysis (FEA) of several pressurized spherical structures is used to design and optimize for minimum material usage, inspired by soap bubbles that naturally stick together with separating walls. The proposed habitat design features a central spherical structure surrounded by nine smaller spheres, optimized for material efficiency. It is demonstrated that utilizing two layers of 0.1 m thick PE and a 0.5 m thick CO2 layer in between them offers significant protection against Martian environmental loads such as radiation shielding and thermal insulation. It facilitates light transmission into the building. This study offers a realistic structural system for buildings and greenhouses that can be constructed using in-situ materials and is suitable for an optimal 539-day stay on Mars. The proposed autonomous robotic arm technology can perform all necessary tasks, from producing PE to automatically assembling the Mars Spherical Building (MSB), including in-place slab printing.

Redefining realistic and stochastic occupancy schedules and patterns for residential buildings in Jordan

Occupant behavior significantly influences building energy consumption, underscoring the importance of understanding the interplay between energy usage and occupant behavior. This integration is vital for evaluating how occupants and their interactions impact building energy consumption patterns. Despite widespread recognition of the importance of behavior-centric approaches in achieving sustainable architecture, there remains a gap in understanding human behavior, particularly in performance-based design. This study presents realistic and stochastic occupancy schedules for residential buildings in Jordan. This was achieved using a mixed-method approach involving a survey, data classification, clustering processes, and a co-simulation approach combining Rhino Grasshopper and Python. The results contributed to refining the general characteristics of each cluster within different age groups, encompassing various patterns of interaction, tolerance levels or levels of sensing, energy conservation consciousness, and occupancy patterns. A significant correlation was also observed between age groups, occupancy schedules, and energy consumption behaviors. The simulation also evaluated the effects of stochastic behavior patterns on the prediction of the energy performance of residential buildings. The results confirm the significant variation in energy use intensity levels between realistic occupancy schedules and fixed schedules for residential buildings. The results also prove that using realistic occupancy schedules for each age group significantly affects energy consumption behavior through occupant-based behaviors. This confirms the pivotal role of dynamic schedules and occupant behaviors in understanding and shaping energy consumption patterns and realistically determining the efficiency of building systems.

Metadata schema for virtual building models in digital twins: VB schema implemented in GPT-based applications

A virtual building model (VBM) is a virtual entity that represents the physical behavior of a target building mathematically within a digital twin environment. The creation and synchronization of a VBM are achieved by utilizing various interrelated virtual sub-models, including behavior, correction, and distance models. To achieve continuous digital twinning, it is essential to manage the VBM with virtual sub-models. However, these metadata schemas have limitations in describing VBMs representing operational building behaviors within the concept of building digital twins (DTs). Therefore, this study proposes a novel metadata schema, termed the virtual building model metadata schema (VB schema), to represent and manage VBMs in DT-built environments. The VB schema is established according to the mathematical and semantic ontology of the in-situ modeling and calibration approach for constructing and correcting virtual models during building operations, and it is linked to physical entities, data, and applications within DTs. Specifically, it involves: (1) determining classes for operational data and virtual models; (2) establishing relationships for interactions between model and data entities, between model classes, between model and physical entities, and between model and applications; (3) defining properties for each class of models; and (4) extending into the exiting metadata schema of Brick. To demonstrate the proposed VB schema, a virtual model describing supply pressure behaviors in a central heating system was developed and represented using the VB schema for DT-enabled building operations. Additionally, the VB schema was utilized for implementing generative pre-trained transformer (GPT)-based DT applications, which highlights its benefits in enhancing ontology comprehension of DTs in the context of VBMs, improving autonomous problem-solving capabilities in real building systems, and providing better interpretation of application results compared to cases where only the Brick schema was used. The VB schema is expected to enable continuous and autonomous in-situ management of VBMs for intelligent building services within the DT.

Implementing Integrated Holistic Education System (IHES) for Character Building at Seven Skies International School in Selangor, Malaysia

The modern educational system emphasizes not only the intellectual development of students but also the formation of moral and social character. Traditional educational systems are often perceived as inadequate in meeting the demands of globalization, technological advancement, and social change. Seven Skies International School adopts the Integrated Holistic Education System (IHES) to address these needs by incorporating intellectual, emotional, spiritual, and physical aspects into student learning. The primary challenge in implementing IHES is maintaining a balance between academic achievement and the development of students' character, as well as ensuring that educators are capable of effectively guiding emotional and spiritual growth. Common obstacles include the lack of understanding and skills among teachers in comprehensively applying IHES. This study aims to analyze the implementation of IHES at Seven Skies International School, evaluate character-building strategies, and measure their impact on students' moral and social development. The methodology employed is a qualitative approach through observation, interviews, and document analysis. The research findings indicate that IHES positively influences students' moral and social development. However, several challenges were identified in its implementation, particularly concerning teacher training and the methods used for character evaluation, which require improvement. The study's recommendations include enhancing training programs for educators and developing more comprehensive methods for character assessment.

Design, optimization, and performance analysis of a solar-wind powered compression chiller with built-in energy storage system for sustainable cooling in remote areas

This study aims to develop a sustainable cooling solution for refrigeration in remote areas, utilizing solely wind and solar power. Ensuring that the power generated aligns with consumption throughout the day is a critical challenge. The investigation centers on the integration of an energy storage and a compression cooling cycle to attain the desired objective. This system integrates refrigerant storage on both the evaporator and condenser sides. The storage tanks' volume is variable by time and should be adjusted automatically. The sustainability of the cooling capacity depends on the amount of input power and the type of refrigerant. Moreover, additional heat is extracted to produce hot water. The analysis includes the coefficient of performance, exergy efficiency, cooling capacity, total heating capacity, and environmental impacts for six refrigerants R134a, R22, R717, R125, R500, and R407c. The system is configured to offer a cooling capacity of 15 kW while maintaining a temperature difference of 38K. The best performance is achieved using R717 as the refrigerant with a coefficient of performance of 5.26, an exergy efficiency of 36 %, and a payback period of 2.267 in Sabzevar. Furthermore, R717 does not contribute to ozone depletion or global warming.

Simulation of PSDF (Photovoltaic, Storage, Direct Current and Flexibility) Energy System for Rural Buildings

The PSDF (photovoltaic, storage, direct current, and flexibility) energy system represents an innovative approach aimed at achieving carbon neutrality. This study focused on rural buildings and utilized Modelica to develop a dynamic simulation model of the PSDF system. The research introduced a framework for direct current distribution microgrid systems with flexible regulatory mechanisms, employing a virtual inertia control strategy to provide stable adjustments for flexible operations and support integration with local grids. Case simulation results indicated that the system equipped with a water tank saved 3.15 kWh compared to the system without a water tank, resulting in an energy savings rate of 22.14%. Compared to traditional photovoltaic systems, the PSDF system significantly enhanced energy management flexibility and system reliability through the integration of thermal storage and battery management. This research made significant contributions to the fields of renewable energy and building energy systems by offering a scalable and practical solution suitable for rural contexts.

Towards a Rust-Like Borrow Checker for C

Memory safety issues in C are the origin of various vulnerabilities that can compromise a program’s correctness or safety from attacks. We propose an approach to tackle memory safety by replicating Rust’s Mid-level Intermediate Representation (MIR) Borrow Checker. Our solution uses static analysis and successive source-to-source code transformations to be composed upstream of the compiler, ensuring maximal compatibility with existing build systems. This allows us to apply the memory safety guarantees of the rustc compiler to C code with fewer changes than a rewrite in Rust. In this work, we present a comprehensive study of Rust’s efforts towards ensuring memory safety, and describe the theoretical basis for a C borrow checker, alongside a proof-of-concept that was developed to demonstrate its potential. We have evaluated the prototype on the CHStone and bzip2 benchmarks. This prototype correctly identified violations of the ownership and aliasing rules, and exposed incompatibilities between such rules and common C patterns, which can be addressed in future work.

IoT—A Promising Solution to Energy Management in Smart Buildings: A Systematic Review, Applications, Barriers, and Future Scope

The use of Internet of Things (IoT) technology is crucial for improving energy efficiency in smart buildings, which could minimize global energy consumption and greenhouse gas emissions. IoT applications use numerous sensors to integrate diverse building systems, facilitating intelligent operations, real-time monitoring, and data-informed decision-making. This critical analysis of the features and adoption frameworks of IoT in smart buildings carefully investigates various applications that enhance energy management, operational efficiency, and occupant comfort. Research indicates that IoT technology may decrease energy consumption by as much as 30% and operating expenses by 20%. This paper provides a comprehensive review of significant obstacles to the use of IoT in smart buildings, including substantial initial expenditures (averaging 15% of project budgets), data security issues, and the complexity of system integration. Recommendations are offered to tackle these difficulties, emphasizing the need for established processes and improved coordination across stakeholders. The insights provided seek to influence future research initiatives and direct the academic community in construction engineering and management about the appropriate use of IoT technology in smart buildings. This study is a significant resource for academics and practitioners aiming to enhance the development and implementation of IoT solutions in the construction sector.

Application of a decision tree approach to predict energy consumption in lightweight buildings under subtropical climate

PurposeLightweight building systems have emerged as alternatives to reduce the high environmental impact of conventional masonry. However, in subtropical climates, the low thermal inertia of lightweight envelopes negatively affects energy performance. The purpose of this paper is to investigate the thermophysical parameters that influence heating and cooling energy consumption in lightweight residential buildings under subtropical climates and develop a model to predict these parameters using statistical and machine learning tools.Design/methodology/approachA database was created with computer simulation data on the energy performance of 2048 building conditions generated by factorial combination of 10 parameters. Sensitivity analysis was performed to identify which parameters contribute most to energy performance indicators. Subsequently, decision trees were created using a classification and regression tree (CART) algorithm to visualize parameters and improve energy performance indicators, particularly cooling energy consumption.FindingsLow thermal transmittance and ground contact are interesting strategies for low thermal capacity buildings. Furthermore, the findings showed that relying only on the most influential properties does not ensure good energy performance; rather, it is the adequate combination of envelope properties that leads to good energy efficiency. The tree developed by CART can be used as a guide to assist designers and researchers in the initial selection of building envelopes, demonstrating the impact of each choice on electrical energy consumption for indoor climate control.Originality/valueBy adopting a global approach to assess the thermal performance of lightweight buildings, this study makes a significant contribution to synthesizing the results of a complex and time-consuming methodology into a guide for optimizing envelope design decisions and directing efforts and resources toward efficient strategies.