Adrian Chong

Adrian Chong
National University of Singapore | NUS · Department of the Built Environment

PhD

About

54
Publications
37,122
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1,036
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Introduction
specializes in building performance modelling and simulation, uncertainty quantification and building data analytics.

Publications

Publications (54)
Article
Full-text available
Model predictive control (MPC) has shown potential in improving building performance but is bottlenecked by the difficulty in constructing control-oriented models. The challenge lies in evaluating the sufficiency of the model and the data usage beforehand. This paper bridges the knowledge gaps in the interactions between data requirements, model qu...
Article
Full-text available
Reinforcement learning (RL) has been shown to have the potential for optimal control of heating, ventilation, and air conditioning (HVAC) systems. Although research on RL-based building control has received extensive attention in recent years, there is limited real-world implementation to evaluate its performance while keeping occupants in the loop...
Article
Full-text available
The paper presents a review on major contributions in infrared thermography to study the built environment at multiple scales. To elaborate the review, hundreds of studies conducted between the 1980s and 2020s were first selected based on their relevance to the scope. Afterward, the most relevant contributions were classified and chronologically so...
Article
Renewable energy usage is continuing to increase as many countries worldwide are aiming to reach peak carbon emission and achieve carbon neutrality in the near future. One inherent problem with renewable energy is that its generation profile does not often fit well with the electricity usage profile. Therefore, it is of utmost importance that termi...
Article
The availability of the building’s operation data and occupancy information has been crucial to support the evaluation of existing models and development of new data-driven approaches. This paper describes a comprehensive dataset consisting of indoor environmental conditions, Wi-Fi connected devices, energy consumption of end uses (i.e., HVAC, ligh...
Article
Reliable building simulation models are key to optimizing building performance and reducing greenhouse gas emissions. Informed decision making requires simulation models to be accurate, extrapolatable, and interpretable, all of which require calibrating model simulations to ground truth. Complicated building dynamics and highly uncertain exogenous...
Article
Full-text available
Incorporating data-driven thermal comfort models into occupant-centric HVAC controls is crucial to meet occupants’ preferences in thermal comfort. Although HVAC controls and thermal comfort modeling are highly inter-related, the interactions between their various resolutions require further study for a better understanding. This study aims to estab...
Article
Full-text available
Conventional thermal preference prediction in buildings has limitations due to the difficulty in capturing all environmental and personal factors. New model features can improve the ability of a machine learning model to classify a person’s thermal preference. The spatial context of a building can provide information to models about the windows, wa...
Preprint
Full-text available
Conventional thermal preference prediction in buildings has limitations due to the difficulty in capturing all environmental and personal factors. New model features can improve the ability of a machine learning model to classify a person's thermal preference. The spatial context of a building can provide information to models about the windows, wa...
Article
The utilization of physical dividers has been recommended as a practical approach to reducing the droplet and aerosol transmissions of the COVID‐19 virus (SARS‐CoV‐2). This study conducted a series of experiments using video recording with a high‐speed camera, particle image velocimetry (PIV) technique, and concentration measurements. The effective...
Article
Full-text available
Building energy simulation (BES) plays a significant role in buildings with applications such as architectural design, retrofit analysis, and optimizing building operation and controls. There is a recognized need for model calibration to improve the simulations’ credibility, especially with building data becoming increasingly available and the prom...
Article
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Internet-of-Things (IoT) devices in buildings and wearable technologies for occupants are quickly becoming widespread. These technologies provide copious amounts of high-quality temporal data pertaining to indoor and outdoor environmental quality, comfort, and energy consumption. However, a barrier to their use in many applications is the lack of s...
Article
Full-text available
Building occupancy is the basis for building energy simulations, operations, and management. With the increasing need for energy conservation and the occupant-centric service of building energy systems, occupancy forecasting has become an essential input for simulations. These applications include model predictive control and demand response, with...
Article
Full-text available
Indoor environment construction for occupants has high energy consumption; as such, occupancy plays a noteworthy role in the complete life cycle phase of buildings, including design, operation, and retrofitting. In the past few years, building occupancy, which is considered the basis of occupant behavior, has attracted increasing attention from res...
Preprint
Full-text available
Internet-of-Things (IoT) devices in buildings and wearable technologies for occupants are quickly becoming widespread. These technologies provide copious amounts of high-quality temporal data pertaining to indoor and outdoor environmental quality, comfort, and energy consumption. However, a barrier to their use in many applications is the lack of s...
Article
Traditional occupant behavior modeling has been studied at the building level, and it has become an important factor in the investigation of building energy consumption. However, studies modeling occupant behaviors at the urban scale are still limited. Recent work has revealed that urban big data can enable occupant behavior modeling at the urban s...
Article
Indoor airborne transmission largely depends on air distribution and ventilation. This study experimentally and numerically investigates steady-state aerosol transmission characteristics in a full-size room using a dedicated outdoor air system coupled with ceiling fans. Tracer gas was used to simulate the exhaled droplet nuclei from the infector, a...
Article
The ever-changing data science landscape is fueling innovation in the built environment context by providing new and more effective means of converting large raw data sets into value for professionals in the design, construction and operations of buildings. The literature developed due to this convergence has rapidly increased in recent years, maki...
Article
Full-text available
Model predictive control (MPC) has shown great potential in improving building performance and saving energy. However, after over 20 years of research, it is yet to be adopted by the industry. The difficulty of obtaining a sufficient control-oriented model is one major factor that hinders the application. In particular, what data is required to bui...
Article
Significant reduction in energy demand from non-domestic buildings is required if greenhouse emission reduction targets are to be met worldwide. Increasing monitoring of electricity consumption generates a real opportunity for gaining an in-depth understanding of the nature of occupant-related internal loads and the connection between activity and...
Article
Full-text available
Occupancy is a significant area of interest within the field of building performance simulation. Through Bayesian calibration, the present study investigates the impact of the availability of different spatial resolution of occupancy data on the gap between predicted and measured energy use in buildings. The study also examines the effect of occupa...
Article
Building energy simulation (BES) has been widely adopted for the investigation of building environmental and energy performance for different design and retrofit alternatives. Data-driven analytics is vital for interpreting and analyzing BES results to reveal trends and provide useful insights. However, seamless integration between BES and data-dri...
Conference Paper
Full-text available
Parametric analysis using EnergyPlus has been a powerful approach to enable investigation of environmental and energy performance for different design and retrofit design alternatives. However, the absence of streamlined workflow integrating model editing , simulation and output extracting raises problems in the productivity of parametric analysis....
Preprint
Occupancy is a significant area of interest within the field of building performance simulation (BPS). Through Bayesian calibration, the present study investigates the impact of the availability of different spatial resolution of occupancy data on the gap between predicted and measured energy use in buildings. The study also examines the effect of...
Article
Full-text available
Past research has shown that occupancy information can be used to reduce building energy consumption through occupant-based controls and by mitigating wasteful occupant behavior. In this study, we investigate the dynamic relationship between WiFi connection counts (as a proxy to occupancy) and building electricity consumption across four building t...
Preprint
Full-text available
Building energy simulation (BES) has been widely adopted for the investigation of building environmental and energy performance for different design and retrofit alternatives. Data-driven analytics is vital for interpreting and analyzing BES results to reveal trends and provide useful insights. However, seamless integration between BES and data-dri...
Preprint
In this paper, we represent a methodology of a graph embeddings algorithm that is used to transform labeled property graphs obtained from a Building Information Model (BIM). Industrial Foundation Classes (IFC) is a standard schema for BIM, which is utilized to convert the building data into a graph representation. We used node2Vec with biased rando...
Preprint
Full-text available
In this paper, we present a platform that integrates three main aspects in the building industry: 1) Building data from both IoT devices and Building Management System (BMS), 2) Building Energy modeling and simulation engine, and 3)Data analysis and optimization libraries. All of which are combined in a three-tier architecture cloud platform. The p...
Conference Paper
Full-text available
In this paper, we represent a methodology of a graph em-beddings algorithm that is used to transform labeled property graphs obtained from a Building Information Model (BIM). Industrial Foundation Classes (IFC) is a standard schema for BIM, which is utilized to convert the building data into a graph representation. We used node2Vec with biased rand...
Article
Full-text available
Automatic fault detection and diagnosis (AFDD) for chillers has significant impacts on energy saving, indoor environment comfort and systematic building management. Recent works show that the artificial intelligence (AI) enhanced techniques outperform most of the traditional fault detection and diagnosis methods. However, one serious issue has been...
Article
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Current building energy benchmarking systems categorize buildings into peer groups by static characteristics such as climate zones and building types, which cannot account for the huge variation in building operations. Grouping buildings with diverse operations for benchmarking could result in misleading results. The smart meters provide an opportu...
Article
Full-text available
With the advance of the internet of things and building management system (BMS) in modern buildings, there is an opportunity of using the data to extend the use of building energy modeling (BEM) beyond the design phase. Potential applications include retrofit analysis, measurement and verification, and operations and controls. However, while BMS is...
Conference Paper
Full-text available
Unsupervised learning methods have been widely used for building energy consumption profiling, but the currently used methods usually gave undesirable results and could hardly tolerate the highly diversified building cases. A scalable automatic framework is accordingly proposed in this study to achieve accurate load profiling. The framework consist...
Conference Paper
Full-text available
gbXML is an open schema that supports data inter-operability between BIM applications and different building design software tools (gbXML, 2018). Its capability to bring in geometric and construction information can help reduce the time and uncertainty of the energy modeling process (Ham and Golparvar-Fard, 2015). However, during the design cycle,...
Conference Paper
Full-text available
With the emergence of the Internet of Things (IoT), there is an opportunity to create a digital twin of a building that continuously learns and updates itself using real-time observations. Model calibration is an essential aspect of the overall process to ensure its reliability. However, the calibration of building energy models (BEM) is typically...
Article
Whole building energy model (BEM) is a physics-based modeling method for building energy simulation. It has been widely used in the building industry for code compliance, building design optimization, retrofit analysis, and other uses. Recent research also indicates its strong potential for the control of heating, ventilation and air-conditioning (...
Article
The present study proposes a framework for the continuous Bayesian calibration of whole building energy simulation (BES) models utilizing data from building information models (BIM) and building energy management systems (BEMS). The ability to import data from BIM and BEMS provides the potential to significantly reduce the time and effort needed fo...
Conference Paper
Full-text available
Whole building energy model (BEM) is difficult to be used in the classical model-based optimal control (MOC) because of its high-dimension nature and intensive computational speed. This study proposes a novel deep reinforcement learning framework to use BEM for MOC of HVAC systems. A case study based on a real office building in Pennsylvania is pre...
Article
Urban heat island (UHI) can significantly affect building’s thermal-energy performance. Urban materials absorb solar and infrared radiation and the accumulated heat is dissipated in the atmosphere increasing further the air temperature. Roofs are envelope components which with advanced solutions such as cool roofs or green roofs can provide signifi...
Article
This paper provides practical guidelines to the Bayesian calibration of building energy models using the probabilistic programming language Stan. While previous studies showed the applicability of the calibration method to building simulation, its practicality is still impeded by its complexity and the need to specify a whole range of information d...
Conference Paper
Full-text available
Random walk Metropolis and Gibbs sampling are Markov Chain Monte Carlo (MCMC) algorithms that are typically used for the Bayesian calibration of building energy models. However, these algorithms can be challenging to tune and achieve convergence when there is a large number of parameters. An alternative sampling method is Hamiltonian Monte Carlo (H...
Article
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Retrofitting is widely explored as one of the energy conserving opportunities for existing buildings, in which both passive and active solutions are carefully evaluated. However, when different retrofitting solutions are combined and applied to a building, the total energy savings potential, which is less than the sum of the savings from applying t...
Conference Paper
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This paper proposes a computational building design support framework. The framework evaluates and optimizes building envelope systems, electrical systems and HVAC systems simultaneously with the assistance of a newly developed EnergyPlus component cost database. The integrated building system evaluation could potentially reveal the trade-offs amon...
Conference Paper
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In this paper, we present a comparative study of five methods for the estimation of missing values in building sensor data. The methods that were implemented and evaluated include linear regression, weighted K-nearest neighbors (kNN), support vector machines (SVM), mean im-putation and replacing missing entries with zero. Using data collected from...
Article
Building system design optimization is becoming popular for design decision making. State-of-the-art technique that couples evolutionary algorithms with a building simulation engine, which is time consuming and often cannot reach the “true” optimal solutions. Studies addressing these issues focus on implementing strategies such as fine tuning optim...
Conference Paper
Full-text available
Building performance simulation has the potential toquantitatively evaluate design alternatives and various energy conservation measures for retrofit projects.However before design strategies can be evaluated, accurate modeling of existing conditions is crucial. Thispaper extends current model calibration practice bypresenting a probabilistic metho...
Conference Paper
Full-text available
Uncertainty analysis in building energy simulation is often carried out with Monte Carlo Analysis. However , there is currently no standard framework for uncertainty modeling in building energy models. In particular , uncertainty quantification is often based on literature and expert judgment with limited attention on the use of measured data. The...
Article
Full-text available
With increasing urbanization today, the negative impact it has on its surroundings is prevalent in many cities and urban areas. Coupled with the need to create and develop sustainable urban developments, it is essential to understand how much the environment as well as its surrounding morphology affects the built environment. Greater emphasis shoul...
Article
Full-text available
Singapore experiences a hot and humid climate throughout the year. This in turn results in heavy reliance on mechanical systems especially air-conditioning to achieve thermal comfort. An alternative would be the use of evaporative cooling which is less energy intensive. Objective and subjective measurements were conducted at an experimental setup a...

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Projects

Projects (5)
Project
To achieve effective mixed-mode ventilation in the tropics using a combination of natural ventilation from operable windows, elevated air movement from ceiling fans, and cooling from the air-conditioning and mechanical ventilation (ACMV) system. The aim is to maximize conditions when natural ventilation is desirable and reduce reliance on energy-intensive air-conditioning, thereby contributing to urban sustainability and significantly reducing cooling energy consumption.
Project
Through a combination of experiments and CFD simulations, investigate the relative influence of building operation and indoor environmental conditions on the dispersion of bio-aerosols
Project
Parameter uncertainty quantification and to construct posterior prediction intervals to better understand the calibration efficacy