From Transitions to Transformation: A Brief Review of the Potential Impacts of COVID-19 on Boosting Digitization, Digitalization, and Systems Thinking in the Built Environment

In a short time, during the early phases of the COVID-19 pandemic outbreak, we managed to shift rapidly to use digital technologies and replace some of our daily operations with virtual modes. This shift happened so instantly and widely that it enables us to argue that the COVID-19 became a valid reason to boost some of the gradual and ongoing transitions towards faster transformations. In this study, we use gray literature to delve into arguments around the boost for digitization, digitalization, and systems thinking in the development of the built environment. This is mostly discussed from the influence of COVID-19 on some of the existing practices or the business-as-usual of the built environment sector. From technological advancement to technology use, these arguments are put forward to discuss what is likely to be the major driver of technological adoption and the shifting paradigms that are yet to be revealed. The study concludes that the current push towards new directions and development pathways are likely to be widely accepted in a shorter time. The findings of this brief study feed into existing arguments on transformative pathways due to the COVID-19 pandemic.

Evaluating the Nexus between Housing and Energy Sectors: The Comparison of Urban, Peri-Urban and Rural Housing Areas in Zhuhai, China

China has developed several housing policy reforms and has, in recent years, progressed further on developing policies to promote green strategies and energy-saving plans. The urban housing has much benefited from such reforms and plans, while rural housing has experienced minimal change in the past few decades. As a result, this study aims to identify and explore these differences, challenges, and implications that exist between three areas of urban, peri-urban, and rural in a particular case study in China. For this study, selected residential areas in the City of Zhuhai and its peri-urban and rural areas are selected as case studies. A questionnaire survey is conducted to analyze energy and housing conditions across the more prosperous urban, the dynamic and transitory peri-urban, and the less prosperous rural areas. The case studies are analyzed as comparative examples in a hot and humid sub-tropical area of Southern China. The study compares energy and housing conditions and argues potential possibilities and challenges for the future development of housing policy reforms that are the result of current housing development patterns and green strategy situation in China.

Mental Health Impacts of the COVID-19 Pandemic: Reflecting on Lockdowns and Social Isolations

This brief study explores the diverse and long-term mental impacts of the COVID-19 pandemic on societies worldwide. Based on the recent existing literature, six primary categories of mental effects are identified to verify how people are affected by reoccurring lockdowns and social isolations. The study urges holistic research in this field, suggesting that researchers must not neglect the diversity of mental health impacts and context-specific factors. While long-term mental and psychological impacts are mostly hidden for now, we anticipate them to fuel other health issues already experienced by the vulnerable groups, healthcare units, and those fighting the pandemic at the front line. The paper aims to highlight primary mental health impacts of the COVID-19 pandemic due to reoccurring lockdowns and social isolations. This is an opinion paper reflecting on ongoing research related to mental health issues of the ongoing pandemic, some of that could be looked at through case study research or extended research and comparative studies. This brief study suggests further case study-based analysis to evaluate the impacts of lockdowns and social isolations on societal wellbeing and mental health. Globally, the ongoing pandemic has made public health unstable and is expected to continue with its long-term consequences on societies. Research studies should help make governments and policymakers more aware of such long-term consequences to ensure they can respond more effectively to foreseeing public health issues.

Analysis of the Impact Resistance of Photovoltaic Panels Based on the Effective Thickness Method

Based on the recent development of renewable energy utilization technology,in addition to centralized photovol-taic power plants,distributed photovoltaic power generation systems represented by building-integrated photo-voltaic systems are frequently employed for power supply.Therefore,in the architectural design,the double-glass photovoltaic module used in the integrated photovoltaic building system puts forward a higher load-bearing capa-city requirement and the corresponding simplified method of carrying capacity check.This article focuses on the simplified method of checking the bearing capacity of the four-sided simply supported double-glass photovoltaic module.First,the principle of equivalent stiffness is used to calculate the effective thickness.Then,the rationality of this approach is verified by comparing the bending states of sandwich panels under different shear moduli.The double-glass photovoltaic module is equivalent to a single-layer board,and its effectiveness is verified by compar-ing the impact test results of the double-glass photovoltaic module with the results of the single-layer board.But the comparison with the test results shows that,from the perspective of architectural design,the effective thick-ness results in this paper can ensure that the building structure has sufficient bearing capacity,but the four-side simply supported boundary theory cannot fully reflect the calculation of the bearing capacity of the four-side clamped double-glass photovoltaic module.

Reflection on Early Lessons for Urban Resilience and Public Health Enhancement during the COVID-19

With growing impacts on public health systems and economies across the world, as a result of the COVID-19 pandemic outbreak, we need to reflect on some of the early lessons for urban resilience enhancement. In this paper, a brief discussion is made through several recommendations that could make our cities more prepared specially in the probable future waves of this current outbreak or potential spikes in infections or clustered cases. The experiences from global examples highlighted in this study address what has worked in the past few months at the spatial levels of communities and cities. The COVID-19 outbreak highlighted the deficiencies and shortfall across multiple sectors of the urban systems and enabled us to identify risks, challenges, and pathways to better city management. With regard to urban resilience enhancement, the negative impacts of the COVID-19 outbreak are assessed to suggest a checklist of what could be done through early preparedness. The findings are novel in ongoing research related to urban resilience and public health during the COVID-19 pandemic. The early lessons here reflect on the ongoing situation of this pandemic outbreak, but could effectually help to enhance the resilience of our cities and communities, and especially addressing the protection of public health and societal well-being. The findings contribute to major sectors of urban resilience, city management, and public health. The recommendations from this study could be utilised and adapted in any context, allowing for the consideration of all-inclusive decision-making and much-enhanced planning processes.

Optimisation of Direct Expansion (DX) Cooling Coils Aiming to Building Energy Efficiency

Efficient Air Conditioning (A/C) system is the key to reducing energy consumption in building operation. In order to decrease the energy consumption in an A/C system, a method to calculate the optimal tube row number of a direct expansion (DX) cooling coil for minimizing the entropy generation in the DX cooling which functioned as evaporator in the A/C system was developed. The optimal tube row numbers were determined based on the entropy generation minimization (EGM) approach. Parametric studies were conducted to demonstrate the application of the analytical calculation method. Optimal tube row number for different air mass flow rates, inlet air temperatures and sensible cooling loads were investigated. It was found that the optimal tube row number of a DX cooling coil was in the range of 5 - 9 under normal operating conditions. The optimal tube row number was less when the mass flow rate and inlet air temperature were increased. The tube row number increased when the sensible cooling load was increased. The exergy loss when using a non-optimal and optimal tube row numbers was compared to show the advantage of using the optimal tube row number. The decrease of exery loss ranged from around 24% to 70%. Therefore the new analytical method developed in this paper offers a good practice guide for the design of DX cooling coils for energy conservation.

The Analysis of Global Warming Patterns from 1970s to 2010s

While global warming is only one part of climate change effects, it poses the highest risk to our habitats and ecologies. It is alarming that global warming has heightened in multiple locations and is intensified since the early 1970s. Since then, there are certain global warming patterns that could guide us with an overview of what mitigation and adaptation strategies should be developed in the future decades. There are certain regions affected more than another, and there are certain patterns with adverse effects on regions, sub-regions, and even continents. This study provides an insightful analysis of recent global warming patterns, those that are affecting us the most with regional climate change of different types, upsurge in frequency and intensity of natural disasters, and drastic impacts on our ecosystems around the world. By analysing the global warming patterns of these last four decades, this research study sheds light on where these patterns are coming from, how they are developing, and what are their impacts. This study is conducted through grey literature and analysis of the recorded global warming data publicly available by the NASA-GISS data centre for global temperature. This brief—but comprehensive—analysis helps us to have a better understanding of what comes next for global warming impacts, and how we should ultimately react. The study contributes to the field by discovering three key points analysed based on available data and literature on recorded global temperature, including: differences between north and south hemispheres, specific patterns due to ocean surface temperature increase, and recent impacts on particular regions. The study concludes with the importance of global scale analysis to have a more realistic understanding of the global warming patterns and their impacts on all living habitats.

Development of an Enhanced Self-Tuning RBF-PID Controller for Achieving Higher Energy-Efficient Process Control

Proportional, integral and derivative (PID) control strategy has been widely applied in heating systems in decades. To improve the accuracy and the robustness of PID control, self-tuning radial-basis-function neural network PID (RBF-PID) is developed and used. Even though being popular, during the control process both of PID and RBF-PID control strategy are inadequate in achieving simultaneous high energy-efficiency and good control accuracy. To address this problem, in this paper we develop and report an enhanced self-tuning radial-basis-function neural network PID (e-RBF-PID) controller. To identify the superiority of e-RBF-PID, following works are conducted and reported in this paper. Firstly, four controllers, i.e., on-off, PID, RBF-PID and e-RBF-PID are designed. Secondly, in order to test the performance of the e-RBF-PID controller, an experimental water heating system is constructed for being controlled. Finally, the energy consumption for the four controllers under the three control scenarios is investigated through experiments. The experimental results indicate that in the three scenarios, the developed e-RBF-PID controller outperforms on-off controller as having higher accuracy. Compared to the PID controller, the e-RBF-PID controller has higher speed in control, and the experimental results show that settling time savings is between 12.6% - 49.0%. Most importantly, less control energy consumption is obtained if using the e-RBF-PID controller. It is found that up to 28.5% energy consumption can be saved. Therefore, it is concluded that the proposed e-RBF-PID is capable of enhancing energy efficiency during control process.

Exploration on Research Methods for Exploring Human Response to Luminous Environment with Chromogenic Windows Applied

Chromogenic windows enable both energy-saving and daylighting regulation.However,the human response to the luminous environment affected by them is difficult to test,since their features of dynamic change and tinting automatically.This study explores the research methods,including experimental design and statistical analysis,by literature review and an experiment demonstration.The results show that a proper size of the test room is significant to obtain desired data,and the advanced VR technologies have the potential to be applied for testing these dynamic variables.Bayesian approaches are recommended to be tried and get more accurate interference about the experimental results.

A geopolitics of mud construction:Self-help and the CINVA-Ram machine in Ghana and South Vietnam during the Cold War

In 1951,the Organization of American States established the Centro Interamericano de Vivienda y Planeamiento(CINVA)to provide specialized training to tackle the housing problem.Based on archival documentation examined at the Rockefeller Archive Center and the Central and Historical Archive of the National University of Colombia,this article explores two significant episodes in which the story of one of the Center’s most successful outputs connects to the history of the ColdWar.It thus contributes to the literature investigating the architecture and related technologies of development aid in the historical context of the Cold War with a precise focus on the role of non-governmental actors.After detailing the history of the CINVA-Rammachine,the pressingmachine to producerammed-earth blocks developed at theCenter andlater exportedtoAmerica,Europe,Africa,and Asia,the article explores its deployment in two different fronts of the Cold War:Ghana and South Vietnam.As highlighted in the conclusions,the significance of CINVA-Ram use in these contexts is manyfold.Firstly,its diffusion,although appearing as a successful case of south-to-south cooperation,was in fact possible because of the Rockefeller family-controlled IBEC’s involvement.Secondly,it shows the global outreach of the intertwined action of governmental agencies,private companies,and NGOs,when fighting poverty and housing shortage via aided self-help initiatives were complementary strategies to the armed containment of Communism.Finally,it discusses the role played by US governmental and non-governmental actors in advancing US interests through technoscience,highlighting how the battle against poverty in the so-called“ThirdWorld”was in this case fought with one of the oldest andsimplest construction techniques in the ideological framework of self-help.

Numerical evaluation of the use of vegetation as a shelterbelt for enhancing the wind and thermal comfort in peripheral and lateral-type skygardens in highrise buildings

Skygardens or skycourts are a unique architectural intervention in the built environment,enhancing the social,economic,and environmental values of the building.It allows occupants to connect and experience outdoor freshness within a semi-enclosed environment.However,skygardens located on a highrise building may generate intense wind gusts,endangering the safety of occupants.Using a validated computational fluid dynamics model,this study investigates the potential of various vegetative barriers or shelterbelts in attenuating the high wind speeds encountered in such spaces and the impact on wind and thermal comfort.Three skygarden configurations were investigated with and without vegetative barriers,simplified and modelled as porous zones,and their effect was studied on the velocity and temperature profile at the occupants’level.The results indicate that while hedges and trees can offer resistance to airflow,trees provide higher temperature reduction.However,a combination of vegetative and geometrical barriers provides the most optimal condition in the skygarden.The study has identified the importance of assessing wind attenuation characteristics of tree plantations on highrise skygarden,and the results can be used in designing intervention strategies.Moreover,vegetation can attenuate pollutants and mitigate poor air quality by surface deposition,and future studies should investigate in that direction.

Machine Learning and Deep Learning Methods for Enhancing Building Energy Efficiency and Indoor Environmental Quality – A Review

The built environment sector is responsible for almost one-third of the world’s final energy consumption. Hence, seeking plausible solutions to minimise building energy demands and mitigate adverse environmental impacts is necessary. Artificial intelligence (AI) techniques such as machine and deep learning have been increasingly and successfully applied to develop solutions for the built environment. This review provided a critical summary of the existing literature on the machine and deep learning methods for the built environment over the past decade, with special reference to holistic approaches. Different AI-based techniques employed to resolve interconnected problems related to heating, ventilation and air conditioning (HVAC) systems and enhance building performances were reviewed, including energy forecasting and management, indoor air quality and occupancy comfort/satisfaction prediction, occupancy detection and recognition, and fault detection and diagnosis. The present study explored existing AI-based techniques focusing on the framework, methodology, and performance. The literature highlighted that selecting the most suitable machine learning and deep learning model for solving a problem could be challenging. The recent explosive growth experienced by the research area has led to hundreds of machine learning algorithms being applied to building performance-related studies. The literature showed that existing research studies considered a wide range of scope/scales (from an HVAC component to urban areas) and time scales (minute to year). This makes it difficult to find an optimal algorithm for a specific task or case. The studies also employed a wide range of evaluation metrics, adding to the challenge. Further developments and more specific guidelines are required for the built environment field to encourage best practices in evaluating and selecting models. The literature also showed that while machine and deep learning had been successfully applied in building energy efficiency research, most of the studies are still at the experimental or testing stage, and there are limited studies which implemented machine and deep learning strategies in actual buildings and conducted the post-occupancy evaluation.

Technical Design for Holistic Wireless Communication in Smart Buildings

This paper presents the design of a wireless building monitoring network implemented at the University of Nottingham's Creative Energy Homes test site.The network is installed in seven smart buildings with the aim of holistically collecting energy data.Data will be used to inform a central control algorithm to optimise the energy flows between buildings,in turn promoting the smart cities concept.Sensors and meters measuring temperature,humidity,CO_2,heat energy,power,and stratified tank temperature are described.Furthermore,the communication protocols utilised are also discussed,which include wireless MBus and EnOcean.This paper also covers the methods used for ensuring the reliability of data signals and the system controls.

Evaluation tool for the thermal performance of retrofitted buildings using an integrated approach of deep learning artificial neural networks and infrared thermography

In most countries,buildings are responsible for significant energy consumption where space heating and air conditioning is responsible for the majority of this energy use.To reduce this massive consumption and decrease carbon emission,thermal insulation of buildings can play an important role.The estimation of energy savings following the improvement of a building’s insulation remains a key area of research in order to calculate the cost savings and the payback period.In this paper,a case study has been presented where deep retrofitting has been introduced to an existing building to bring it closer to a Passivhaus standard with the introduction of insulation and solar photovoltaic panels.The thermal performance of the building with its improved insulation has been evaluated using infrared thermography.Artificial intelligence using deep learning neural networks is implemented to predict the thermal performance of the building and the expected energy savings.The prediction of neural networks is compared with the actual savings calculated using historical weather data.The results of the neural network show high accuracy of predicting the actual energy savings with success rate of about 82%when compared with the calculated values.The results show that this suggested approach can be used to rapidly predict energy savings from retrofitting of buildings with reasonable accuracy,hence providing a practical rapid tool for the building industry and communities to estimate energy savings.A mathematical model has been also developed which has indicated a life-long monitoring will be needed to precisely estimate the benefits of energy savings in retrofitting due to the change in weather conditions and people’s behaviour.

Effect of the spectrally selective features of the cover and emitter combination on radiative cooling performance

Radiative cooling(RC)shows good potential for building energy saving by throwing waste heat to the cosmos in a passive and sustainable manner.However,most available radiative coolers suffer from low cooling flux.The situation becomes even deteriorated in the daytime when radiative coolers are exposed to direct sunlight.To tackle this challenge,an idea of employing both a spectrally selective cover and a spectrally selective emitter is proposed in this study as an alternative approach.A comparative study is conducted among four RC modules with different spectral characteristics for the demonstration of how the spectral profiles of the cover and the emitter affects the RC performance.The results under given conditions show that the RC module with a spectrally selective cover and a spectrally selective emitter(SC/SE)reaches a net RC power of 62.4 W/m^(2)when the solar radiation is 800 W/m^(2),which is about 1.8 times that of the typical RC module with a spectrally non-selective cover and a spectrally selective emitter(n-SC/SE).When the ambient temperature is 30°C,the SC/SE based RC module realizes a daytime sub-ambient temperature reduction of 20.0°C,standing for a further temperature decrement of 9.2°C compared to the n-SC/SE based RC module.

Evaluation of model predictive control(MPC)of solar thermal heating system with thermal energy storage for buildings with highly variable occupancy levels

The presence or absence of occupants in a building has a direct effect on its energy use,as it influences the operation of various building energy systems.Buildings with high occupancy variability,such as universities,where fluctuations occur throughout the day and across the year,can pose challenges in developing control strategies that aim to balance comfort and energy efficiency.This situation becomes even more complex when such buildings are integrated with renewable energy technologies,due to the inherently intermittent nature of these energy source.To promote widespread integration of renewable energy sources in such buildings,the adoption of advanced control strategies such as model predictive control(MPC)is imperative.However,the variable nature of occupancy patterns must be considered in its design.In response to this,the present study evaluates a price responsive MPC strategy for a solar thermal heating system integrated with thermal energy storage(TES)for buildings with high occupancy variability.The coupled system supplies the building heating through a low temperature underfloor heating system.A case study University building in Nottingham,UK was employed for evaluating the feasibility of the proposed heating system controlled by MPC strategy.The MPC controller aims to optimize the solar heating system’s operation by dynamically adjusting to forecasted weather,occupancy,and solar availability,balancing indoor comfort with energy efficiency.By effectively integrating with thermal energy storage,it maximizes solar energy utilization,reducing reliance on non-renewable sources and ultimately lowering energy costs.The developed model has undergone verification and validation process,utilizing both numerical simulations and experimental data.The result shows that the solar hot water system provided 63%heating energy in total for the case study classroom and saved more than half of the electricity cost compared with that of the original building heating system.The electricity cost saving has been confirmed resulting from the energy shifting from high price periods to medium to low price periods through both active and passive heating energy storages.

Influence of urban morphological factors on building energy consumption combined with photovoltaic potential: A case study of residential blocks in central China

Studies on urban energy have been growing in interest,and past research has mostly been focused on studies of urban solar potential or urban building energy consumption independently.However,holistic research on the combination of urban building energy consumption and solar potential at the urban block-scale is required in order to minimize energy use and maximize solar power generation simultaneously.The aim of this study is to comprehensively evaluate the impact of urban morphological factors on photovoltaic(PV)potential and building energy consumption.Firstly,58 residential blocks were classified into 6 categories by k-means clustering.Secondly,3 energy performance factors,which include the energy use intensity(EUI),the energy use intensity combined with PV potential(EUI-PV),and photovoltaic substitution rate(PSR)were calculated for these blocks.The study found that the EUI of the Small Length&High Height blocks was the lowest at around 30 kWh/(m^(2)·y),while the EUI-PV of the Small Length&Low Height blocks was the lowest at around 4.45 kWh/(m^(2)·y),and their PSR was the highest at 87%.Regression modelling was carried out,and the study concluded that the EUI of residential blocks was mainly affected by shape factor,building density and floor area ratio,while EUI-PV and PSR were mainly affected by height and sky view factor.In this study,the results and developed methodology are helpful to provide recommendations and strategies for sustainable planning of residential blocks in central China.

Unveiling the potential of space syntax approach for revitalizing historic urban areas:A case study of Yushan Historic District,China

Historic urban areas are a crucial component of urban heritage,embodying the collective memory of urban development and possessing distinctive urban textures and cultural attributes.However,the growing impact of globalization on the urban environment poses challenges to historic urban areas,including diminishing social recognition,aging infrastructure,loss of vitality,and cultural erosion.To address these challenges,this study proposes a novel approach to revitalizing historic urban areas by employing space syntax methodology.The study focuses on Yushan Historic District in China as a case study and uses spatial models within space syntax to describe,analyze,and interpret its urban morphology.The objective is to enhance urban vitality while preserving the heritage fabric of historic urban areas.Additionally,it aims to contribute to the advancement of space syntax research,specifically in the context of urban renewal and revitalization of historic districts.The findings reveal the spatial factors that contribute to the generation of vitality within the district,identify areas requiring intervention,and provide strategies for revitalizing historic urban areas.This study demonstrates the potential of utilizing a space syntax approach in urban revitalization,providing valuable guidance for effectively conserving urban heritage within the context of urban renewal.

Energy flexibility characteristics of centralized hot water system in university dormitories

The large-scale application of renewable energy is an important strategy to achieve the goal of carbon neutrality in the building sector.Energy flexibility is essential for ensuring balance between energy demand and supply when targeting the maximum penetration rate of renewable energy during the operation of regional integrated energy systems.Revealing the energy flexibility characteristics of centralized hot water systems,which are an important source of such flexibility,is of great significance to the optimal operation of regional integrated energy systems.Hence,in this study,based on the annual real-time monitoring data,the energy flexibility of the centralized hot water system in university dormitories is evaluated from the perspective of available storage capacity(C_(ADR)),recovery time(t_(recovery)),and storage efficiency(η_(ADR)),by the data-driven simulation method.The factors influencing the energy flexibility of the centralized hot water system are also analyzed.Available storage capacity has a strong positive correlation with daily water consumption and a strong negative correlation with daily mean outdoor temperature.These associations indicate that increased water use on the energy flexibility of the centralized hot water system is conducive to optimal dispatching.In contrast,higher outdoor temperature is unfavorable.The hourly mean value of the available storage capacity in spring and winter is found to be around 80 kWh in the daytime,and about twice that in summer and autumn.Recovery time is evenly distributed throughout the year,while t_(recovery)/C_(ADR)in spring and winter is about half that in summer.The storage efficiency was significantly higher in spring,summer,and winter than in autumn.The hourly mean storage efficiency was found to be about 40%in the daytime.The benefits of activating energy flexibility in spring and winter are the best,because these two seasons have higher available storage capacity and storage efficiency,while the benefit of activating energy flexibility is the highest at 6:00 a.m.,and very low from midnight to 3:00 a.m.

Repercussions of Singularity of Site Authorities in Making Heritage Conservation Decisions:Evidence from Iraq

Different global assertions have recently been made prohibiting the mono approach of decision-makers in formulating heritage conservation policies,due to many unfavourable touristic and political implications.The mono approach has led to exploitation of some sites’cultural standing as well as condoning a veritable remedy of some of their social and urban aspects,and thus threatening these sites with exclusion from the World Heritage List.This paper investigates the approach of some local Iraqi experiences of conservation,aiming at revealing some of the more painful repercussions of the singularity of site authorities in planning for built heritage future,which may draw a plan for the site away from its heritage potential.Some local cases are reviewed here,such as Erbil Citadel,setting them as examples that may add more facts to the global experience of heritage conservation in this regard.The paper concludes that the site authorities are also liable to drift as a result of some ramifications that impede setting a deep-sighted strategy,and thus may stray far from delivering the far-reaching aims.Accordingly,the monaural authority approach may need to be synthesised with some of the site’s locally-based views through an overlapped integral loop of interactions between them,which may support the conservation policy-formulation with diverse contributions.