Thermal Comfort Of Occupants Research Articles

A novel occupant-centric stratum ventilation system using computer vision: Occupant detection, thermal comfort, air quality, and energy savings

Traditional ventilation and air conditioning systems typically operate on a predetermined schedule with fixed operating parameters. Occupant-centric control (OCC) strategies have been proposed to reduce system operation energy consumption without sacrificing thermal comfort. Indoor occupancy detection in real time is a critical step in successfully implementing the OCC strategy. Thus, the deep learning-based computer vision method was adopted in the first step of the study, and the detection performance and camera position were analyzed in an office scenario. Next, the proposed OCC strategy was used to regulate the supply air parameters and outdoor air volume in stratum ventilation based on the monitored occupant number. The traditional static control strategy was then compared to two control strategies: constant air volume and variable air volume. Occupant detection performance results showed the mean NRMSD for the five most common relative positions of the occupants and camera was 0.1109, with sitting back to camera having the lowest accuracy. Subjective response results demonstrated that, when compared to the traditional control strategy, thermal comfort was improved by 43%–73%, perceived air quality was maintained at an acceptable level, CO2 concentration was less than 700 ppm, and energy could be saved by 2.3%–8.1%. Furthermore, the lower the occupancy, the greater the improvement in comfort and the greater the energy savings. This research focused on how the stratum ventilation system responds to dynamic changes in occupancy and provided insights into reducing unnecessary energy waste while maintaining comfort.

Dual-objective building retrofit optimization under competing priorities using Artificial Neural Network

Building retrofit has received renewed interests in recent years, driven by energy-savings and indoor environmental quality goals. Digital technologies such as building performance simulation and optimization algorithms have been used to identify optimal retrofit schemes, yet the existing approaches are limited by the slow running speed of physics-based models and sub-optimal results. This study describes a novel framework, the Building Performance Optimization using Artificial Neural Network (BPO-ANN), which can automatically identify optimal building retrofit schemes. A robust Artificial Neural Network model was developed and validated as a surrogate to rapidly assess building performances, which was then connected to a genetic algorithm in search of Pareto optimal. The impact of key design attributes on building performances have been assessed using sensitivity analysis. The BPO-ANN framework has been tested in a high-performing campus building in Northern China under two competing objectives: building energy demand and occupant thermal comfort. It can automatically identify optimal design schemes, which were expected to achieve an energy-savings of 4% and reduce the annual thermal discomfort percentage by 4%. Sensitivity analysis suggested that window-to-wall ratio and HVAC setpoint have contributed the most to the performances of the campus building, followed by the roof U-value and wall U-value. The study has contributed methodologically to simulation-based optimization method, with novelties in the use of neural network algorithms to accelerate the otherwise time-consuming physics-based simulation models. It has also contributed a robust procedure in the tuning of hyperparameters in neural network models, with marked improvements in model prediction and computational efficiency.

Modeling and simulation of vehicle integrated thermal management system for a fuel cell hybrid vehicle

The high-efficiency thermal management is one of the major challenges for fuel cell vehicles due to the diversity and complexity of the components and systems. Thermal management systems and corresponding control strategies can affect the components’ performance, durability and reliability, the vehicle’s driving performance, fuel economy and occupant thermal comfort. The main objective of this study is to perform multi-case simulation analysis of the fuel cell vehicle thermal management system through modeling to derive the operating mechanism and thermal performance analysis of each subsystem and integrated system. To achieve this purpose, an integrated thermal management system model with different control strategies was proposed based on a fuel cell vehicle prototype, powered by a 65 kW proton exchange membrane fuel cell stack and a Li-ion battery with a capacity of 15 kWh, which considers the cooling of the driving system, fuel cell stack, battery and cabin. The results showed that the critical temperature of each subsystem could be controlled within a reasonable range even in the battery charging mode, where the fuel cell generated about 136.6 % more thermal power than the discharging mode to charge the battery. Moreover, in the series structure of the radiators and condenser, the average temperatures of the inlet air of the motor and the subsequent fuel cell radiator were respectively 3.9 °C and 7 °C higher than the ambient temperature (35 °C), thus reducing the impact of the radiator fan. The proposed model may provide the contribution in the design of integrated solutions for thermal management systems for fuel cell hybrid vehicles under high temperature scenarios, including control strategies development and system-level coupling analysis.

Domestic overheating risks and mitigation strategies: The state-of-the-art and directions for future research

Anthropogenic climate change will likely put dwellings at risk of overheating and potentially increase cooling demand in the decades ahead, leading to higher greenhouse gas (GHG) emissions due to the energy consumed for mechanical cooling. Contemporary constructions with highly insulated fabric have been found to suffer from periodic overheating in today’s climate, the occurrence of which is projected to increase in frequency as the temperature rises. This critical review investigates the factors affecting overheating risks in dwellings and passive cooling strategies to mitigate overheating impacts on occupant thermal comfort and wellbeing. The cooling efficiency of passive strategies is affected by the design, construction and operation of buildings, as well as climate and occupancy. A framework has been developed to illustrate the effect of overheating factors on the cooling efficacy of passive strategies. Findings suggest that a combination of passive strategies is required to minimise overheating risks by the 2080s. External solar shading is the most effective method for retrofitting insulated dwellings. On the other hand, cool paint is ideal for uninsulated dwellings. In addition, thermal mass and natural ventilation require occupant interaction for optimal air circulation and cooling performance.

A two-phase online air balancing method for multi-zone ventilation systems based on distributed finite-time control

Air balancing (AB) is a commonly used technique to control and balance the air flow of multi-zone ventilation systems. The performance of air balancing is associated with occupant thermal comfort, indoor air quality (IAQ) and system energy consumption, which is critical to the ventilation system. However, the existing air balancing methods suffer low convergence and some even require shutdown period of the ventilation system for offline operation, causing big inconvenience and degraded ventilation performance. To fix the above issues, this paper proposes a novel air balancing method based on distributed finite-time control (DFTC). The proposed DFTC-AB method is an online method which can be performed during system operation without interrupting the ventilation service. It achieves the balance of air flow by two phases, i.e. to first proportion the ventilation system and then finely regulate the absolute quantity of each terminal flow. A revised DFTC control protocol is proposed to accelerate the convergence of terminal flow given any initial state, which significantly improves the efficiency of the air balancing process. To validate the proposed DFTC-AB method, a 5-terminal duct system is fabricated in the lab. The experimental results demonstrate that the proposed DFTC-AB method can balance the 5-termial ventilation system under various cases with satisfactory dynamic performance. The whole process of air balancing can be fulfilled within 20 min, with the highest accuracy achieving 3.2% among the tested cases.

Numerical simulation of heat and mass transfer of a wall containing micro-encapsulated phase change concrete (PCC)

Before planning to equip buildings with energy systems, it is essential to first understand and control the behavior of the premises (via control of heat and water transfer phenomena) (air conditioners, heat pumps, heat exchangers, etc.). Given the amount of solar radiation to which it is exposed in summer and its significant contribution to energy loss in winter, the thermal insulation of the ceiling appears effective. The objective of this work is to study the heat and mass transfer through a ceiling wall containing micro-encapsulated phase change materials under realistic climatic conditions based on meteorological data in Tunisia. This article is about a numerical study that uses software (DIGITAL Visual FORTRAN 95) to predict the effect of incorporating a layer of PCM on thermal behavior, mass, and occupant thermal comfort, as well as energy consumption for summer and winter periods.

Holistic Approach towards a Sustainable Urban Renewal: Thermal Comfort Perspective of Urban Housing in Kigali, Rwanda

Urban upgrading programs are implemented to enhance the living conditions in a city. However, the concept of to what extent the life of the targeted communities is improved remains contested and fluid. The purpose of this study was two-fold. First, it evaluated for the first time the indoor thermal conditions in the three main urban housing types in Kigali and analyzed whether the ongoing urban renewal takes into consideration occupant thermal comfort. Second, alternatives to improve thermal performance of urban housing were investigated and recommendations were given. Results indicate that modern urban housing performed significantly greater compared to other housing types, especially during daytime. Indoor thermal conditions in the planned low-income housing were no better—and, in fact, were slightly poorer—than in the informal settlement from which households were to be relocated. Through design parameter optimization, the indoor thermal conditions in the planned low-income housing were improved by 85.5% in the daytime hours and 71.2% in the nighttime hours. These findings are valuable to officials in resettlement programs by providing insights to improve urban dwellers’ living conditions from a wholistic prospective. This can assist related parties in mitigating project failure often caused by local resistance to resettlement.

Improving Occupant Thermal Comfort through Personalized Space Recommendation

Improving Occupant Thermal Comfort through Personalized Space Recommendation

Simulation of performance of five types of external windows: a case study in Chongqing, China

The efficiency of transparent envelopes must be improved in purpose of saving energy. The EnergyPlus software was used to examine the inside glass surface temperature and annual energy performance (AEP) of five different types of external windows, including built-in louvre ventilation windows (BLVW), built-in louvre hollow windows (BLHW), interior side louvre ventilation windows (ILVW), ventilation windows (VW), and regular hollow windows (HW), using office buildings in Chongqing as the target. The results demonstrate that the design of ventilation and louvres can reduce energy consumption of buildings, lower the room's radiant asymmetry, and raise occupant thermal comfort. During the cooling season, built-in louvre ventilation windows and hollow windows for rooms facing south are the best window operation options. During the heating season, ventilation windows are the best option. In four orientations of north, east, south, and west, respectively, the overall building energy efficiency rate of the optimal operation mode compared to typical hollow windows is 5.87%, 5.70%, 2.80%, and 5.74%. This will serve as a guide for the building design of energy-efficient windows and the mode of the windows' year-round functioning in Chongqing.

Assessment of Occupants Thermal Comfort in University Classrooms on the basis of gender preferences

In the present research work, the thermal comfort of an educational building in a semi-arid climate of Lahore, Pakistan has been analyzed based on the PMV-PPD method using a subjective scale in terms of acceptability, neutrality, and preference, considering the impact of gender. Firstly, this study examine how the temperature affects occupants\' (male and female) comfort levels in current university classrooms during the winter and summer. Secondly, how occupant behavior affects thermal comfort, productivity, and health well-being to determine how future buildings should be designed to accommodate gender preferences. Thirdly, the study improve retrofitting approaches for building systems that make it satisfies inhabitants\' thermal requirements, and is cost and energy effective. This study revealed that females were more affected by winter conditions while males were more affected by higher temperatures in summers. In both seasons, males found a frequent impact of thermal comfort, due to which more productivity loss was observed in them in comparison to females. In winter, females were more affected form SBS, and in summer, males showed more symptoms of getting affected by SBS. The overall percentage saving in energy consumption was found 27 % for considered Building compared with retrofitted simulated model of building systems. It is suggested that a well-insulated indoor thermal environment is the need of the hour for classrooms in university buildings to improve the thermal comfort conditions, productivity and health conditions of the occupants for both seasons.

Design of an EnergyPlus Model-Based Smart Controller for Maintaining Thermal Comfortable Environment in Non-Domestic Building

Heating, Ventilation and Air Conditioning (HVAC) systems account for 59% of energy consumption in domestic buildings and 36% in non-domestic buildings. According to a study, around 39% of occupants are dissatisfied with indoor temperature in non-domestic buildings. To maintain thermal comfort and indoor air quality, HVAC systems are widely used in non-domestic buildings. This research aims to develop energy-efficient control techniques for HVAC systems while ensuring indoor thermal comfort. Three control strategies, namely EnergyPlus model-based Model Predictive Control (MPC), Sliding Mode Control (SMC), and simple ON/OFF control, are employed and compared at the Department of Electrical and Computer Engineering, COMSATS University Islamabad, Lahore Campus. Furthermore, a machine learning-based Predicted Mean Vote (PMV)-based temperature setpoint estimator is designed to ensure occupant thermal comfort. The control techniques estimate the temperature setpoints and supply air temperature of the Variable Air Volume (VAV) system to control indoor room temperature. The energy consumption and indoor thermal comfort of the building are compared under different control techniques. The results show that MPC with PMV-based setpoints consumes 17.20% less energy during winters and 14.67% less energy during summers than a simple ON/OFF controller.

Thermal Management System of the UNICARagil Vehicles—A Comprehensive Overview

The collaboration project UNICARagil aiming to develop new autonomous battery electric vehicle concepts has progressed and the four vehicle prototypes have been built up. All seven universities and six industrial partners have worked towards this milestone. At the time of writing the four vehicles are operational and can be driven by a safety driver using a sidestick. The automated driving functions are being applied on the test track and first demonstrations are carried out. This paper gives an overview of the results, which have been achieved within the work package of the thermal onboard network. The thermal management system including the heating, ventilation and air conditioning system and its development process is explained in detail. Furthermore, climate chamber measurements with prototype hardware of a sensor data processing computer and the integration of the air conditioning control unit into the vehicle’s automotive service-oriented architecture framework are described. A coupled simulation approach to predict occupant thermal comfort in one vehicle variant is presented. Simulation results using environmental conditions typical for a European summer show a comfortable environment for all six occupants. In addition, the simulation and development process of a thermoelectric heat pump is shown. First measurement results with the heat pump on a test bench are highlighted which show an achievable coefficient of performance greater than two.

Wireless, AI-enabled wearable thermal comfort sensor for energy-efficient, human-in-the-loop control of indoor temperature

The conventional heating, ventilation, and air conditioning (HVAC) systems are based on a set-point control approach that only considers the temperature of the environment without reflecting the thermophysiological status of the occupant. This approach not only fails to fully satisfy individual thermal preferences, but it also makes an HVAC operation energy-inefficient. One possible solution is to control the indoor thermal condition based on an accurate prediction of the occupant's thermal comfort to prevent any unnecessary energy consumption. Here, we present an artificial intelligence (AI) wearable sensor-based human-in-the-loop HVAC control system that is operated on a real-time basis reflecting the thermophysiological condition of the occupant to automatically improve their thermal comfort while reducing the energy consumption of the building. The wristband-type, AI-based, three-point wearable temperature sensor offers excellent thermal comfort prediction accuracy (93.9%), enabling a human-centric HVAC control operation. A proof-of-concept demonstration of closed human-in-the-loop HVAC control using the AI-enabled wearable sensor system confirms both the accuracy of the thermal comfort prediction and the energy-efficiency of this approach, demonstrating its potential as a new solution that improves the occupant's thermal comfort and provides building energy savings.

A year-long field investigation on the spatio-temporal variations of occupant's thermal comfort in Chinese traditional courtyard dwellings

Multiple researchers have proven the different thermal perceptions of occupants living in naturally ventilated dwellings. As one of the representatives of Chinese traditional dwellings, courtyard-style vernacular residence is the result of human wisdom in adapting to the natural thermal environment through architectural forms. Exploring whether such classical building form still meets the thermal comfort needs of contemporary residents can help architects generate relevant design concepts when dealing with energy-saving-oriented projects in the context of carbon neutralization and rural revitalization. A year-long follow-up investigation is conducted on a typical courtyard dwelling in Wufu Town, Fujian Province. Based on the built digital twin platform, relevant parameters were monitored by various sensors from different investigation points throughout the year. Additionally, year-round monthly thermally neutral temperatures are obtained from over 1000 Thermal Sensation Vote questionnaires. By applying the adaptive thermal comfort theoretical model, which is widely recognized in the field of thermal assessment on naturally ventilated buildings, the linear relationship between indoor neutral temperature and outdoor air temperature can be generated. According to ASHRAE Standard 55, the time-series predicted acceptable thermal comfort ranges are then calculated to evaluate the measured operative temperature. Results show no large gap between the actual temperature and the predicted acceptable range in semi-open spaces and interior spaces. With suitable optimized renovations and the application of several low-power conditioning equipment, such courtyard dwellings are still capable of providing occupants comfortable thermal environment throughout the year.

Deciphering optimal mixed-mode ventilation in the tropics using reinforcement learning with explainable artificial intelligence

The application of mixed-mode ventilation (MMV) in the tropics is challenging, given its hot and humid climate. Consequently, there are limited periods when operating in natural ventilation (NV) is desirable. Furthermore, the potential to use NV diminishes at locations characterized by generally light winds. Given the complex interactions in MMV, this study aims to use reinforcement learning (RL) to identify relationships that can further reduce cooling energy use while maintaining occupant thermal comfort. The control variable variables considered include the percentage of window opening area and dynamic cooling setpoint temperature. Results show that RL can achieve a 52% reduction in cooling energy while maintaining good thermal comfort and indoor air quality compared to the existing baselines that typically involve switching between NV and air-conditioning based on outdoor conditions. We then developed an Explainable AI (XAI) framework to prompt building scientists toward new insights into MMV control in the tropics, which consists of shapley additive explanations (SHAP) and decision tree. The SHAP is able to improve the transparency of RL strategy by revealing the impact of each input on the final decision and the decision tree can extract the key control rules from RL. Using the XAI framework, this study also identified that the RL algorithm was taking advantage of the internal thermal mass to increase cooling efficiency. The extracted rules are further applied to the actual testbed, showing the feasibility of the rules extracted by XAI approach.

Comparison of simulation methods for dynamic internal air distribution in naturally ventilated livestock buildings

Accurate internal air distribution prediction facilitates the analysis of occupant thermal comfort and the control of gaseous contaminants within naturally ventilated livestock buildings (NVLB). However, the dynamic and random change in external wind conditions makes it difficult to predict the air distribution. This study compares three scenarios based on real-time monitored external wind conditions: the quasi-static simulation method with moving average data, the transient simulation method with raw data, the transient simulation method with Kalman filtering, and the continuous fast Fourier transform. The quasi-static simulation was verified for computational efficiency and reliability within different time spans. The simulation results were validated with measurement data in a low-rise stand-alone NVLB surrounding a low-density building complex. The quasi-static simulation results of internal air distribution in oblique wind directions partially agreed with the hourly averaged wind speed measurements and turbulent kinetic energy. Additionally, the quasi-static simulation agrees with the direct transient method for predicting the air distribution within a long-time span. The quasi-static simulation shows promise for the future simulation of internal air distribution in naturally ventilated livestock buildings under dynamic boundary conditions.

Cooling access and energy requirements for adaptation to heat stress in megacities

As urban areas are increasingly exposed to high temperatures, lack of access to residential thermal comfort is a challenge with dramatic consequences for human health and well-being. Air-conditioning (AC) can provide relief against heat stress, but a massive AC uptake could entail stark energy demand growth and mitigation challenges. Slums pose additional risks due to poor building quality, failing to provide adequate shelter from severe climatic conditions. Thus, it is unclear how many people in the Global South will still lack access to basic cooling under different future climate and socioeconomic developments. We assess the impact of different shared socioeconomic pathways (SSPs) and climate futures on the extent of population lacking access to cooling where needed—the cooling gap—and energy requirements for basic comfort for a set of 22 megacities in the Global South. We find that different SSPs greatly influence the extent of future cooling gaps, generally larger in SSP3 due low income levels, and consequent limited access to AC and durable housing. Megacities in Sub-Saharan Africa and South Asia have the largest share of population affected, ranging from 33% (SSP1) to 86% (SSP3) by mid-century. Energy requirements to provide basic cooling for all are higher in SSP1 for most megacities, driven by urbanization, and can increase by 7 to 23% moving from 2.0 to 3.0 °C temperature rise levels. Strategies combining improved building design and efficient cooling systems can improve adaptation to heat stress in cities while reducing energy and emission requirements to reach climate and sustainability goals.

Evaluation of the Influence of Natural Ventilation Variables on Indoor Thermal Comfort of Occupants of Secondary School Classrooms During Hot Season in Enugu Metropolis, Nigeria

Evaluation of the Influence of Natural Ventilation Variables on Indoor Thermal Comfort of Occupants of Secondary School Classrooms During Hot Season in Enugu Metropolis, Nigeria

Optimizing the Passive House Planning Package simulation tool: A bottom-up dynamic approach to reduce building performance gap

The Passive House Planning Package (PHPP) simulation tool is the only authorized software in Australia for the Passivhaus (PH) certification. Despite its key role in this certification scheme, previous studies have reported significant gaps between the simulated and actual performance. To address this limitation, this study introduces a bottom-up approach to building performance simulation based on a dynamic method combined with advanced appliance profiles. This study uses two-year monitored data in a PH-certified student accommodation building in Australia and validates the proposed bottom-up approach in both annual and monthly granularity. The results show that the level of reliability and robustness of the PHPP tool is substantially improved for three PH criteria (i.e., overheating frequency, space heating energy demand, and primary energy renewable) and three operational variables (i.e., indoor temperature, plug load, and lighting power density), all within the ranges of error allowed by ASHRAE’s Guideline 14–2014. Based on the proposed approach, a set of stepwise retrofit actions was put in place to further improve the energy efficiency and occupant thermal comfort in the case study building.

NUMERICAL STUDY OF THE EFFECTS OF EVAPORATIVE COOLER SUPPLY AIR OUTLET HEIGHT ON THERMAL COMFORT

Thermal comfort in a space equipped with a direct evaporative cooler is a function of the height of the cooler's supply air outlet. This article attempts to numerically investigate the impact of hybrid downdraft evaporative cooler (HDEC) supply outlet height on occupant thermal comfort in an office building. DesignBuilder CFD parametric simulations was carried out by varying the height of the HDEC supply outlet from 0.1m to 2.4 m, step 0.1 m above ground level, using Predictive Mean Vote (PMV) as an objective function. The results show that the best PMV of -0.27 was obtained at 0.4m above the floor level.