Article
Thermodynamics
Ziwei Xiao, Cheng Fan, Jiaqi Yuan, Xinhua Xu, Wenjie Gang
Summary: In this study, non-intrusive load monitoring (NILM) methods based on artificial neural network (ANN) and random forest (RF) were proposed and compared for disaggregating cooling loads. Results indicated that both methods could accurately achieve load disaggregation, with the RF-based method outperforming the ANN-based one. The equipment load could be disaggregated with the highest accuracy among the four sub-loads, and the detailed sub-loads obtained can guide building renovation and optimization design of building energy systems.
CASE STUDIES IN THERMAL ENGINEERING
(2021)
Article
Energy & Fuels
Ao Li, Fu Xiao, Chong Zhang, Cheng Fan
Summary: Machine learning is increasingly used in building energy management, with attention mechanisms playing a key role in improving the interpretability of deep learning models. This allows users to understand the reasons behind model predictions and how input sequences influence output sequences.
Article
Construction & Building Technology
Shuqin Chen, Yinyan Lv, Zhichao Wang, Yuhang Ma, Yurui Huang, Yichao Wang, Yuxuan Cai, Zhiqin Rao
Summary: This study collects real-time occupancy data and develops a Monte Carlo-based model to simulate and compare the building heating and cooling load differences caused by fixed occupancy schedules and random occupancy time series. The results show that using random occupancy schedules can accurately predict and assess the building loads.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Construction & Building Technology
Seon Jung Ra, Jin-Hong Kim, Cheol Soo Park
Summary: This paper presents the application results of model predictive control (MPC) using multiple deep neural network (DNN) models in the cooling system of a factory building. The authors developed 10 simulation models to predict the thermal behavior of the HVAC system and indoor environment. The MPC approach successfully reduces the energy consumption of the condensing units while maintaining the cooling set-point temperature.
ENERGY AND BUILDINGS
(2023)
Article
Construction & Building Technology
Yun Mao, Junqi Yu, Na Zhang, Fangnan Dong, Meng Wang, Xiang Li
Summary: In this study, a novel model based on the nonlinear chaotic mapping Harris Hawks Optimization algorithm was proposed for accurate building cooling load prediction. The experimental results show that the model outperforms traditional methods in terms of accuracy and generalization.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Energy & Fuels
Hai-Jun Wang, Tao Jin, Hui Wang, Dan Su
Summary: This paper proposes an improved Elephant Herding Optimization (IEHO) algorithm to address the low optimization accuracy and poor stability of the original EHO algorithm in solving complex multidimensional nonlinear problems. The results of test experiments demonstrate that the introduction of improved strategies effectively enhances the accuracy and stability of the EHO algorithm. Furthermore, the combination of IEHO algorithm with BP neural network results in a more accurate and less oscillating cooling and heating load forecasting model compared to other group intelligence optimization algorithms.
Article
Construction & Building Technology
Jing Zhao, Xiulian Yuan, Yaoqi Duan, Haonan Li, Dehan Liu
Summary: This paper proposes an artificial intelligence-driven method for forecasting building loads by integrating the thermal load characteristics of the building. By establishing independent models for the building envelope and occupant behavior, and coupling the predicted values of these models, the total load forecasting model is created. The results of a case study show that the proposed method achieves excellent predictive performance and can effectively forecast the formation mechanism of thermal loads.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Thermodynamics
Liang-Hui Zhi, Peng Hu, Long-Xiang Chen
Summary: A novel optimization method is proposed to optimize the Organic Rankine cycle system, allowing for fast and accurate optimization of system performance under variable engine loads and cooling water temperature. The method combines artificial neural network and non-dominated sorting genetic algorithm to reduce computing time and improve the accuracy of the optimization.
CASE STUDIES IN THERMAL ENGINEERING
(2023)
Article
Construction & Building Technology
Chujie Lu, Junhua Gu, Weizhuo Lu
Summary: An improved attention-based deep learning approach is proposed for robust ultra-short-term cooling load prediction. It incorporates time representation learning, long short-term memory with an attention mechanism, and extreme gradient boosting. The approach outperforms other models in terms of prediction accuracy and robustness across different building types in Guangzhou.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Construction & Building Technology
Yeobeom Yoon, Byeongmo Seo, Soolyeon Cho
Summary: Heating, ventilation, and air-conditioning (HVAC) systems are responsible for about 50% of building energy consumption. It is crucial to explore energy-saving methods and improve HVAC system efficiency. One solution is the use of economizer controls, which can reduce cooling energy usage. However, the effectiveness of different economizer controls may vary depending on the climate conditions.
Article
Energy & Fuels
Xu Zhang, Yongjun Sun, Dian-ce Gao, Wenke Zou, Jianping Fu, Xiaowen Ma
Summary: Short-term building cooling load prediction is crucial in building energy management. Similar day approach combined with machine learning algorithms is a potential method to improve accuracy. However, the performance of different similar day selection methods integrated with machine learning algorithms has not been comprehensively assessed, especially in the absence of occupancy information in the dataset.
Article
Computer Science, Interdisciplinary Applications
Francisco Macia-Perez, Iren Lorenzo-Fonseca, Jose Vicente Berna-Martinez
Summary: The issue of room ventilation, especially in educational environments, has gained attention due to the COVID-19 pandemic. Smart University platforms serve as a good starting point to offer control services of relevant indicators, and this study introduces a Ventilation Quality Certificate (VQC) for Smart Universities. The VQC informs the university community of the ventilation status and supports decision-making with assessments of preventive measures and actions taken.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Thermodynamics
Yuanjin Xu, Fei Li, Armin Asgari
Summary: This study aims to predict the heating and cooling loads of energy-efficient buildings using optimization methods, with a dataset consisting of eight independent factors. Biogeography-based optimization algorithm shows the highest accuracy in both training and test data, outperforming other models significantly.
Article
Construction & Building Technology
Yuefen Gao, Yang Hang, Mengliang Yang
Summary: This paper introduces the Improved CEEMDAN algorithm and Markov chain correction method to predict air conditioning cooling load more accurately. By decomposing affecting parameters and establishing component prediction model, and using parallel computing to enhance operation speed, the improved model shows improved accuracy and is more suitable for practical applications.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Construction & Building Technology
Byeongmo Seo, Yeobeom Yoon, Kwang Ho Lee, Soolyeon Cho
Summary: This paper proposes an optimal algorithm for controlling the HVAC system in a target building. The study compares the accuracy of cooling load prediction using ANN and LSTM algorithms, and finds that the ANN algorithm has higher accuracy and is more suitable for HVAC control. Implementing the ANN-based approach leads to a significant reduction in cooling energy consumption. This study demonstrates the effectiveness of ML-based HVAC system control for energy conservation and improved system efficiency.
Article
Construction & Building Technology
Xiang Fang, Anthony C. Y. Yuen, Guan H. Yeoh, Eric W. M. Lee, Sherman C. P. Cheung
Summary: This study proposes a novel vortex flow driven smoke exhaust system to delay the smoke filling process during atrium fire accident. Good agreements between numerical predictions and experimental measurements were achieved, and the outcomes revealed the factors influencing the smoke interface height.
INDOOR AND BUILT ENVIRONMENT
(2023)
Article
Construction & Building Technology
Wei Xie, Eric Wai Ming Lee, Yiu Yin Lee
Summary: The study introduces a new method to measure the emergent leader-follower behavior in a crowd, showing that dynamic characteristics of evacuees vary with TE threshold. Results indicate a decrease in overall evacuation time with increasing TE threshold, and the formation of L-F groups is influenced by TE threshold.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Mechanics
Liping Lian, Xu Mai, Weiguo Song, Jun Zhang, Kwok Kit Richard Yuen, Eric Wai Ming Lee
Summary: This paper investigates the merging characteristics of pedestrian flow with controlled experiments under laboratory conditions. The study finds that the space usage in the merging area is most efficient when the width of the two branches is half that of the main corridor. The results can be used as references for the design of public infrastructure and human safety management.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Engineering, Civil
Wei Xie, Dongli Gao, Eric Waiming Lee
Summary: In crowd evacuation, individuals are often influenced by the movements of their neighbors, even without social affiliations. This study developed a force-based model integrated with undeclared leader-follower (ULF) structure and used transfer entropy (TE) to measure the ULF structure in evacuation crowds. The results showed that the proposed model provides more realistic trajectories and the leader-follower structures change over time.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Physics, Multidisciplinary
Dong Li Gao, Wei Xie, Eric Wai Ming Lee
Summary: Understanding human decision making during emergency evacuations is crucial. This study examines exit choice behavior and decision-making attitude in uncertain risk scenarios using virtual evacuation experiments. The results show that the weighted uncertainty risk for individuals is determined by considering smoke height and frequency. Decision makers exhibit a rank-and reference-dependent preference towards uncertain risk in evacuation scenarios.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Engineering, Industrial
Wei Xie, Eric Wai Ming Lee, Yiu Yin Lee
Summary: The study developed a method to realistically simulate pedestrian counter flows using a force-based model, incorporating avoidance and following behaviors. New parameters and methods were introduced to measure and explain the characteristics of pedestrian motion, and compared with other models, this model performed well in replicating experimentally observed pedestrian flow patterns.
Article
Chemistry, Physical
Jingwen Weng, Qiqiu Huang, Xinxi Li, Guoqing Zhang, Dongxu Ouyang, Mingyi Chen, Anthony Chun Yin Yuen, Ao Li, Eric Wai Ming Lee, Wensheng Yang, Jian Wang, Xiaoqing Yang
Summary: Although lithium-ion batteries are widely used, the thermal safety issues remain a concern. This article focuses on phase-change-material (PCM)-based battery thermal management systems (BTMs) and highlights the importance of meeting prerequisites for heat dissipation and thermal hazard mitigation. It compares the thermo-physical properties of modified PCMs and the structural design of structure-enhanced PCM-based BTMs. Future research directions for system resilience are proposed.
ENERGY STORAGE MATERIALS
(2022)
Review
Energy & Fuels
Ao Li, Jingwen Weng, Anthony Chun Yin Yuen, Wei Wang, Hengrui Liu, Eric Wai Ming Lee, Jian Wang, Sanghoon Kook, Guan Heng Yeoh
Summary: With the increasing use of lithium-ion batteries, particularly in electric vehicles, it is important to improve the thermal and fire resilience of battery systems. Computational simulations provide a solution to battery thermal management system design, but it requires significant computational power and time. Machine learning models play a vital role in the safety management of battery systems, aiding in temperature prediction and safety diagnosis. This review article summarizes the literature on machine learning models in battery thermal management systems and provides guidelines for future design optimization.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Public, Environmental & Occupational Health
Dongli Gao, Wei Xie, Ruifeng Cao, Eric Wai Ming Lee, Richard Kwok Kit Yuen, Jingwen Weng
Summary: Exit choice is crucial for pedestrian safety and evacuation efficiency in emergencies. This paper contributes by using cumulative prospect theory to predict exit choice and summarizing and examining different decision-making rules. The predictions from Max and Expo showed higher realism, while the results from Ratio were more robust, as indicated by the parameters of Accuracy and F1-score.
JOURNAL OF SAFETY SCIENCE AND RESILIENCE
(2023)
Article
Public, Environmental & Occupational Health
Rui Feng Cao, Eric Wai Ming Lee, Wei Xie, Dong Li Gao, Qian Chen, Anthony Chun Yin Yuen, Guan Heng Yeoh, Richard-Kwok-Kit Yuen
Summary: This study developed a fire-integrated evacuation model that considers the effects of spreading fire hazards on evacuees. It also introduced a quantitative approach to evaluate evacuees' fire risks and stress levels. The results demonstrate the importance of minimizing pre-evacuation time in fire emergencies.
JOURNAL OF SAFETY SCIENCE AND RESILIENCE
(2023)
Article
Public, Environmental & Occupational Health
Wei Xie, Dongli Gao, Ruifeng Cao, Eric Wai Ming Lee, Richard Kwok Kit Yuen, Jingwen Weng
Summary: This study developed a social force model integrated with a group force to understand leadership dynamics during evacuation. The transfer entropy (TE) method was applied to detect leadership based on movement information. The results showed that TE accurately measured leadership and found that leaders exerted increasing influence over time, while followers' influence diminished. Spatial positions were found to be correlated with leadership emergence.
JOURNAL OF SAFETY SCIENCE AND RESILIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Dongli Gao, Eric Wai Ming Lee, Yiu Yin Lee
Summary: Numerous studies have shown that exit choice is crucial in saving lives during building evacuation. People often rely on preferences rather than strategic and rational decisions due to their limited ability to perceive and combine multiple factors. The context effect, which refers to preference reversals depending on the availability of other options, plays an important role in decision-making behavior.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Physics, Multidisciplinary
Zhi Chao Zhang, Han Bo Li, Eric Wai Ming Lee, Yi Ma, Wen Ke Zhang, Meng Shi
Summary: This study conducted evacuation experiments in Minecraft under fire emergency conditions and found that people tend to detour in advance to avoid the fire. The formation of a self-organized queue and sequential passage through the exit characterized the evacuations in corridor-like rooms. The research demonstrated the feasibility of using Minecraft to simulate fire evacuations.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Ecology
Meng Shi, Hanbo Li, Zhichao Zhang, Eric Wai Ming Lee
Summary: This study developed an objective approach using an artificial neural network (ANN) model to determine the location of a fire source. The ANN model was trained using samples obtained from computational fluid dynamics simulations, and a data preprocessor was designed to transform simulation results into a format compatible with the ANN model. The model's predictive performance was improved using bootstrap aggregation and evaluated through leave-one-out approach.
Article
Computer Science, Interdisciplinary Applications
Sensen Xing, Cheng Wang, Wei Wang, Rui Feng Cao, Anthony Chun Yin Yuen, Eric Wai Ming Lee, Guan Heng Yeoh, Qing Nian Chan
Summary: This paper proposes an extended FFCA model that integrates the natural step length into pedestrian movement, allowing pedestrians to occupy multiple grids and expanding the interaction area. Through simulation of evacuation scenarios, the model accurately reproduces density-velocity relations and matches experimental results. Compared to traditional models, this model generates more reasonable velocity variations and evacuation paths.
SIMULATION MODELLING PRACTICE AND THEORY
(2024)
Article
Thermodynamics
Pengcheng Zhao, Jingang Wang, Liming Sun, Yun Li, Haiting Xia, Wei He
Summary: The production of green hydrogen through water electrolysis is crucial for renewable energy utilization and decarbonization. This research explores the optimal electrode configuration and system design of compactly-assembled industrial electrolyzer. The findings provide valuable insights for industrial application of water electrolysis equipment.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
V. Baiju, P. Abhishek, S. Harikrishnan
Summary: Thermally driven adsorption desalination systems (ADS) have gained attention as an eco-friendly solution for water scarcity. However, they face challenges related to low water productivity and scalability. To overcome these challenges, integrating ADS with other desalination technologies can create a small-scale hybrid system. This study proposes integrating ADS with a Thermo Electric Dehumidification (TED) unit to enhance its performance.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
C. X. He, Y. H. Liu, X. Y. Huang, S. B. Wan, Q. Chen, J. Sun, T. S. Zhao
Summary: A decentralized centroid multi-path RC network model is constructed to improve the temperature prediction accuracy compared to traditional RC models. By incorporating multiple heat flow paths and decentralizing thermal capacity, a more accurate prediction is achieved.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Chaoying Li, Meng Wang, Nana Li, Di Gu, Chao Yan, Dandan Yuan, Hong Jiang, Baohui Wang, Xirui Wang
Summary: There is an urgent need to shift away from heavy dependence on fossil fuels and embrace renewable energy sources, particularly in the energy-intensive oil refining process. This study presents an innovative concept called the Solar Oil Refinery, which applies solar energy in oil refining. A solar multi-energies-driven hybrid chemical oil refining system that utilizes solar pyrolysis and electrolysis has been developed, significantly improving solar utilization efficiency, cracking rate, and hydrogen yield.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Chao Ma, Guanghui Wang, Dingbiao Wang, Xu Peng, Yushen Yang, Xinxin Liu, Chongrui Yang, Jiaheng Chen
Summary: This study proposes a bio-inspired fish-tail wind rotor to improve the wind power efficiency of the traditional Savonius rotor. Through transient simulations and orthogonal experiments, the key factors affecting the performance are identified. A response surface model is constructed to optimize the power coefficient, resulting in an improvement of 9.4% and 6.6% compared to the Savonius rotor.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Sina Bahmanziari, Abbas-Ali Zamani
Summary: This paper proposes a new framework for improving electrical energy harvesting from piezoelectric smart tiles through a combination of magnetic plucking, mechanical impact, and mechanical vibration force mechanisms. Experimental results demonstrate a significant increase in energy yield and average energy harvesting time compared to other mechanisms.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Nanjiang Dong, Tao Zhang, Rui Wang
Summary: This study establishes a multiobjective mixed-variable configuration optimization model for a comprehensive combined cooling, heating, and power energy system, and proposes an efficient generating operator to optimize this model. The experimental results show that the proposed algorithm performs better than other state-of-the-art algorithms.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Ahmed E. Mansy, Eman A. El Desouky, Tarek H. Taha, M. A. Abu-Saied, Hamada El-Gendi, Ranya A. Amer, Zhen-Yu Tian
Summary: This study aims to convert office paper waste into bioethanol through a sustainable pathway. The results show that physiochemical and enzymatic hydrolysis of the waste can yield a high glucose concentration. The optimal conditions were determined using the Box-Behnken design, and a blended membrane was used for ethanol purification.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Sven Klute, Marcus Budt, Mathias van Beek, Christian Doetsch
Summary: Heat pumps are crucial for decarbonizing heat supply, and steam generating heat pumps have the potential to decarbonize the industrial sector. This paper presents the current state, technical and economic data, and modeling principles of steam generating heat pumps.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Le Zhang, To-Hung Tsui, Yen Wah Tong, Pruk Aggarangsi, Ronghou Liu
Summary: This study investigates the effectiveness of a current-carrying-coil-based magnetic field in promoting anaerobic digestion of chicken manure. The results show that the applied magnetic field increases methane yield, decreases carbon dioxide production, and reduces the concentration of ammonia nitrogen. Microbial community analysis reveals the enrichment of certain methanogenic genera and enhanced metabolic pathways. Pilot-scale experiments confirm the technical effectiveness of the magnetic field assistance in enhancing anaerobic digestion of chicken manure.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Bo Chen, Ruiqing Ma, Yang Zhou, Rui Ma, Wentao Jiang, Fan Yang
Summary: This paper presents an advanced energy management strategy for fuel cell hybrid electric heavy-duty vehicles, focusing on speed planning and energy allocation. By utilizing predictive co-optimization control, this strategy ensures safe inter-vehicle distance and minimizes energy demand. Simulation results demonstrate the effectiveness of the proposed method in reducing fuel cell degradation cost and overall operation cost.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Fabio Fatigati, Roberto Cipollone
Summary: Organic Rankine Cycle-based microcogeneration systems that use solar sources to generate electricity and hot water can help reduce CO2 emissions in residential energy-intensive sectors. The adoption of a recuperative heat exchanger in these systems improves efficiency, reduces thermal power requirements, and saves on electricity costs.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Lipeng He, Renwen Liu, Xuejin Liu, Xiaotian Zheng, Limin Zhang, Jieqiong Lin
Summary: This research proposes a piezoelectric-electromagnetic hybrid energy harvester (PEHEH) for low-frequency wave motion and self-sensing wave environment monitoring. The PEHEH shows promising power output and the ability to self-power and self-sense the wave environment.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Shangling Chu, Yang Liu, Zipeng Xu, Heng Zhang, Haiping Chen, Dan Gao
Summary: This paper studies a distributed energy system integrated with solar and natural gas, analyzes the impact of different parameters on its energy utilization and emissions reduction, and obtains the optimal solution through an optimization algorithm. The results show that compared to traditional separation production systems, this integrated system achieves higher energy utilization and greater reduction in carbon emissions.
ENERGY CONVERSION AND MANAGEMENT
(2024)
Article
Thermodynamics
Qingpu Li, Yaqi Ding, Guangming Chen, Yongmei Xuan, Neng Gao, Nian Li, Xinyue Hao
Summary: This paper proposes and studies a piston-type thermally-driven pump with a structure similar to a linear compressor, aiming to eliminate the high-quality energy consumption of existing pumps and replace mechanical pumps. The coupling mechanism of working fluid flow and element dimension is analyzed based on force analysis, and experimental data analysis is used to determine the pump operation stroke. Theoretical simulation is conducted to analyze the correlation mechanism of the piston assembly. The research shows that the thermally-driven pump can greatly reduce power consumption and has potential for industrial applications.
ENERGY CONVERSION AND MANAGEMENT
(2024)