Your search

In an increasingly digital world, there are fast-paced developments in fields such as Artificial Intelligence, Machine Learning, Data Mining, Digital Twins, Cyber-Physical Systems and the Internet of Things. This paper reviews and discusses how these new emerging areas relate to the traditional domain of building performance simulation. It explores the boundaries between building simulation and these other fields in order to identify conceptual differences and similarities, strengths and...

Energy studies of buildings are becoming more widespread as stakeholders strive to improve energy efficiency and reduce carbon emissions. As a result, there is an increased need for novel numerical techniques to automatically calibrate building energy models (BEMs) for these energy studies. In this paper, a new automated building calibration methodology was developed, which uses a surrogate (i.e., meta) multilayer perceptron artificial neural network (ANN) to infer unknown building...

This paper investigates the use of dilated causal convolutional neural networks for fine-grained temporal forecasting of building zone states. Specifically, we build and evaluate models using a small set of exogenous features (e.g., external temperature) to autoregressively predict zone airflow setpoints every minute for a 24-h prediction window. We carefully explore the trade-off between generality and specificity in these models, training and evaluating them based on zone, zone type,...

The revolution of the industry 4.0 presents a new era of digital transformation for the construction industry, advancing towards the concept of digital twins, while on the other hand it faces the global challenge of reducing carbon emissions from operational assets. The current research gap in the application of digital twins for achieving net zero were reviewed in this study, highlighting its potentials for enhancement in the built environment, and emphasizing the need for demonstration of...

Environmental degradation and carbon emissions have become a major global concern. This has forced policymakers to consider strategic and long-term contingencies to increase carbon sequestration capacity and mitigate the effects of climate change. Soil organic carbon (SOC) provides a reliable long-lasting mechanism to ameliorate climate change and regulate carbon fluxes. However, unanticipated rates of climate change coupled with the dynamic nature of land-use transformation threatens...

Environmental degradation and carbon emissions have become a major global concern. This has forced policymakers to consider strategic and long-term contingencies to increase carbon sequestration capacity and mitigate the effects of climate change. Soil organic carbon (SOC) provides a reliable long-lasting mechanism to ameliorate climate change and regulate carbon fluxes. However, unanticipated rates of climate change coupled with the dynamic nature of land-use transformation threatens...

The Standardized Precipitation Index (SPI) is used to indicate the meteorological drought situation - a negative (or positive) value of SPI would imply a dry (or wet) condition in a region over a period. The climate system is an excellent example of a complex system since there is an interplay and inter-relation of several climate variables. It is not always easy to identify the factors that may influence the SPI, or their inter-relations (including feedback loops). Here, we aim to study the...

The Standardized Precipitation Index (SPI) is used to indicate the meteorological drought situation - a negative (or positive) value of SPI would imply a dry (or wet) condition in a region over a period. The climate system is an excellent example of a complex system since there is an interplay and inter-relation of several climate variables. It is not always easy to identify the factors that may influence the SPI, or their inter-relations (including feedback loops). Here, we aim to study the...

Recently, Occupant-Centric Control (OCC) strategies have gained mounting interest. Previous studies made use of OCC strategies for adjusting the operation of heating/cooling systems, improving indoor thermal comfort and governing mechanical ventilation systems. However, a very limited number of studies have applied OCC strategies to natural ventilation systems. Further, the feasibility of establishing OCC strategies for controlling indoor thermal comfort, energy use and specifically air...

Recently, Occupant-Centric Control (OCC) strategies have gained mounting interest. Previous studies made use of OCC strategies for adjusting the operation of heating/cooling systems, improving indoor thermal comfort and governing mechanical ventilation systems. However, a very limited number of studies have applied OCC strategies to natural ventilation systems. Further, the feasibility of establishing OCC strategies for controlling indoor thermal comfort, energy use and specifically air...

Cauvery Delta Zone is present in the eastern part of Tamil Nadu, popularly known as ‘rice bowl’ of Tamil Nadu. It constitutes of about 11.1% of total area of the state. It lies between 10.00 and 11.30° N latitude and 78.15°–79.45° E longitude. Cauvery Delta Zone includes the districts of Thanjavur, Thiruvarur, Nagapattinam, Mayiladuthurai, Perambalur and some parts of Pudhukottai and Cuddalore Districts. This zone plays a vital role not only in rice production but also in other varieties of...

We present an approach to generate location-specific forecasts of indoor temperature (Ti) and thermal comfort and issue indoor heat warnings for occupational settings. Indoor forecasts are generated using standard outdoor weather forecasting products and an artificial neural network (ANN) trained on-site using local indoor measurements from a low-cost sensor system measuring Ti and indoor physiologically equivalent temperature (PETi). The outcomes are hourly indoor Ti and PET i forecasts....

One of the most important concerns affecting humanity today is climate change that has led to increased frequency of natural disasters that threaten social and economic stability to populations. Zambia’s vulnerability to the threat of disasters remains high because the country still lacks an effective Early Warning System (EWS). This study recognises the need to evaluate various Machine Learning (ML) algorithms, that have been successfully implemented in disaster prediction, in order to...

Recently, Occupant-Centric Control (OCC) strategies have gained mounting interest. Previous studies made use of OCC strategies for adjusting the operation of heating/cooling systems, improving indoor thermal comfort and governing mechanical ventilation systems. However, a very limited number of studies have applied OCC strategies to natural ventilation systems. Further, the feasibility of establishing OCC strategies for controlling indoor thermal comfort, energy use and specifically air...

Recently, Occupant-Centric Control (OCC) strategies have gained mounting interest. Previous studies made use of OCC strategies for adjusting the operation of heating/cooling systems, improving indoor thermal comfort and governing mechanical ventilation systems. However, a very limited number of studies have applied OCC strategies to natural ventilation systems. Further, the feasibility of establishing OCC strategies for controlling indoor thermal comfort, energy use and specifically air...

Simplification of input variables can increase the applicability of Artificial Intelligence (AI) in building load prediction. The most essential inputs for AI therefore need to be identified via a significance level test. In this study, the significance of the input parameters was evaluated using the standardized regression coefficient (SRC) and Explainable AI methods, i.e., Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP). To consider various...