Article
Construction & Building Technology
Hakan Ibrahim Tol, Habtamu Bayera Madessa
Summary: This study proposes a simplified building model based on the physical building thermal model using resistance and capacitance network. The model effectively mimics the transient building thermal behaviour under various operational strategies and occupant behaviour. The case study demonstrates that the integrated behaviour of building components under a given control strategy enables the simulation of different control strategies for large-scale district heating systems.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Thermodynamics
Jaewan Joe, Piljae Im, Borui Cui, Jin Dong
Summary: This study investigates the applicability of a lumped building modeling approach to model-based predictive control (MPC) and compares the performances of detailed and lumped models under different boundary conditions. The results suggest that the proposed lumped model approach can achieve some savings, but the savings potential is lower than that of the detailed model.
Article
Automation & Control Systems
Joseph Lorenzetti, Andrew McClellan, Charbel Farhat, Marco Pavone
Summary: This article proposes a reduced-order model predictive control scheme to solve robust, output feedback, constrained optimal control problems for high-dimensional linear systems. Computational efficiency is achieved using projection-based reduced-order models, with guarantees on robust constraint satisfaction and stability.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Astronomy & Astrophysics
Hong Qi, Vivien Raymond
Summary: This passage discusses the capabilities and challenges of the next generation of gravitational wave observatories, as well as the recently exploited techniques for reducing parameter estimation computational costs. Additionally, it introduces a Python-based reduced order quadrature building code to accelerate parameter estimation of gravitational waves.
Article
Construction & Building Technology
Qiong Chen, Nan Li
Summary: Reduced-order models (ROMs) can significantly reduce computation costs while maintaining high-fidelity performance for model predictive control. However, the physical meaning of the building thermal model order reduction at the theoretical level has not been fully explored, although the mathematical validity of the reduction process and results is unquestionable. The interpretability of the building low-dimensional model at the physical level is essential for improving the model's reliability.
ENERGY AND BUILDINGS
(2023)
Article
Construction & Building Technology
Maximilian Mork, Nick Materzok, Andre Xhonneux, Dirk Mueller
Summary: This paper presents a nonlinear hybrid Model Predictive Control (MPC) approach for building energy systems based on Modelica. The approach considers the nonlinearities and discontinuities commonly found in building energy systems and uses a time-variant linearization approach to approximated nonlinear optimization problems. The proposed approach demonstrates good control quality and integration of multiple integer characteristics in a simulation study.
ENERGY AND BUILDINGS
(2022)
Article
Computer Science, Interdisciplinary Applications
Xuewen Zhang, Minghao Han, Xunyuan Yin
Summary: In this paper, an efficient data-driven predictive control approach is proposed for general nonlinear processes using a reduced-order Koopman operator. A Kalman-based method is used to select lifting functions for Koopman identification. The selected lifting functions are used to project the original nonlinear state-space into a higher-dimensional linear function space, where linear models can be constructed for the underlying nonlinear process.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Biology
Hossein Moshfegh, Farshad Tajeddini, Hossein Ali Pakravan, Mojtaba Mahzoon, Ehsan Azadi Yazdi, Hamed Bazrafshan Drissi
Summary: A mathematical model of dynamic changes of calcium and NO concentration in the coronary artery was developed to simulate the effect of NO release and investigate its impact on the hemodynamics. The study also explored the influence of hematocrit on the flow rate, revealing biphasic behavior for flow rate, wall shear stress, and Ca2+ but triphasic behavior for NO concentration and dilation percent. The model was found to effectively predict the behavior of arteries after releasing NO during cardiac pacing, providing valuable insights for understanding vessel damage mechanisms and potential cardiovascular disease prevention.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Automation & Control Systems
Xu Cai, Xin Zhang, Xuyang Lou, Wei Wu
Summary: This paper presents a model predictive control strategy for piecewise affine systems with dead zone constraints using the mixed logical dynamical modeling approach. The proposed strategy involves transforming the systems into mixed logic dynamical models and applying a predictive control scheme based on this model. The effectiveness of the approach is demonstrated through numerical examples.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Multidisciplinary Sciences
Scott T. Keene, Akshay Rao, George G. Malliaras
Summary: In this study, in situ measurements of electrochemical (de)doping of an archetypal OMIEC were used to inform a quasi-field drift-diffusion model, accurately capturing experimentally measured ion transport. The research found that the chemical potential of holes represents a major driving force for mixed charge transport. Numerical simulations showed that the competition between hole drift and diffusion leads to diffuse space charge regions in spite of high charge densities, unique to mixed conducting systems.
Article
Computer Science, Interdisciplinary Applications
Cheng Huang, Karthik Duraisamy
Summary: This study presents an adaptive projection-based reduced-order model (ROM) formulation for model-order reduction of chaotic and convection-dominant physics problems. The basis is adapted at every time-step of the on-line execution to account for the unresolved dynamics, promoting stability and robustness. Non-local information is efficiently incorporated in the basis adaptation, significantly enhancing the predictive capabilities of the resulting ROMs. The comprehensive ROM formulation enables efficient and accurate predictions in chaotic, multi-scale, and transport-dominated problems.
JOURNAL OF COMPUTATIONAL PHYSICS
(2023)
Article
Energy & Fuels
Laura Maier, Marius Schoenegge, Sarah Henn, Dominik Hering, Dirk Mueller
Summary: Model predictive control can reduce heating systems' operating costs and energy consumption, especially for heat pumps. This study develops two different air-source heat pump modeling approaches using the supply temperature as a control variable and compares them with a simplified linear model. The results show that both the piecewise linear model and the quadratic model have lower operating costs and energy demand compared to the simplified linear model, but they require longer computation times. Future work is recommended to apply this method to other types of heat pumps and coupled building energy systems to further validate its feasibility.
Article
Engineering, Biomedical
Alireza Mojahed, Javid Abderezaei, Efe Ozkaya, Lawrence Bergman, Alexander Vakakis, Mehmet Kurt
Summary: Sports-related traumatic brain injuries are a major cause of head injuries worldwide, and helmets play a crucial role in protecting against these injuries. However, current helmet designs often overlook the importance of regional brain deformations, particularly near deep white matter structures like the corpus callosum. This study develops a dynamic model of the skull-brain-helmet system to investigate the impact of various helmet parameters on head and corpus callosum dynamics. The findings show that the optimal helmet coupling values differ for minimizing corpus callosum dynamics compared to skull and brain dynamics, indicating the need to consider tissue-level dynamics in helmet design.
ANNALS OF BIOMEDICAL ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Yongjun Yan, Nan Li, Jinlong Hong, Bingzhao Gao, Jia Zhang, Hong Chen, Jing Sun, Ziyou Song
Summary: This study proposes an eco-coasting strategy that calculates the optimal timing and duration of coasting maneuvers using road information preview. By evaluating different coasting mechanisms, it is found that the engine start/stop method performs better in terms of fuel consumption and travel time. The online performance of the eco-coasting strategy is evaluated using Mixed Integer Model Predictive Control (MIMPC), and simulation results show that it achieves near-optimal performance and outperforms the rule-based method.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Automation & Control Systems
Kaixuan Chen, Jin Lin, Yiwei Qiu, Feng Liu, Yonghua Song
Summary: This article proposes a model predictive control framework with deep learning-based reduced-order modeling for cooperative wind farm control. The framework successfully captures the dominant wake steering dynamics in an efficient manner, and the derived wind farm reduced-order model is embedded in a novel wind farm automatic generation control framework. The effectiveness of the deep learning-based wind farm reduced-order model is validated through case studies, showing improved control performance in terms of wind direction variability and dynamic power tracking.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Automation & Control Systems
P. Feyel, G. Duc, G. Sandou
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2019)
Article
Automation & Control Systems
Sophie Frasnedo, Guillaume Sandou, Gilles Duc, Cedric Chapuis, Philippe Feyel
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2019)
Article
Green & Sustainable Science & Technology
Nicolo Gionfra, Guillaume Sandou, Houria Siguerdidjane, Damien Faille, Philippe Loevenbruck
Article
Thermodynamics
Nicolas Lamaison, Simon Collette, Mathieu Vallee, Roland Baviere
Review
Energy & Fuels
Gaelle Faure, Mathieu Vallee, Cedric Paulus, Tuan Quoc Tran
Article
Thermodynamics
Mathieu Vallee, Thibaut Wissocq, Yacine Gaoua, Nicolas Lamaison
Summary: This paper investigates various types of faults in District Heating & Cooling (DHC) systems and highlights the hindrance of data lack in developing data-driven models for fault detection and diagnosis (FDD). The study provides a reference dataset based on simulation to evaluate Machine Learning (ML) models for fault detection. The dataset covers six types of DHC system components and is provided as Open Data with corresponding documentation.
Article
Energy & Fuels
Jaume Fito, Mathieu Vallee, Alain Ruby, Etienne Cuisinier
Summary: This article compares the robustness of two Smart Energy Systems architectures at district level using a case study. The study concludes that the multi-source architecture is more robust than the electricity-driven architecture when facing uncertainties in space heating demands and heat pump performance.
Proceedings Paper
Automation & Control Systems
Maxime Pouilly-Cathelain, Philippe Feyel, Gilles Duc, Guillaume Sandou
2020 59TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC)
(2020)
Proceedings Paper
Automation & Control Systems
Benjamin Bocquillon, Philippe Feyel, Guillaume Sandou, Pedro Rodriguez-Ayerbe
ICINCO: PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS
(2020)
Proceedings Paper
Automation & Control Systems
Maxime Pouilly-Cathelain, Philippe Feyel, Gilles Duc, Guillaume Sandou
ICINCO: PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS
(2020)
Proceedings Paper
Automation & Control Systems
Nicolo Gionfra, Guillaume Sandou, Houria Siguerdidjane, Damien Faille, Philippe Loevenbruck
INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, ICINCO 2017
(2020)
Proceedings Paper
Automation & Control Systems
Maxime Pouilly-Cathelain, Philippe Feyel, Gilles Duc, Guillaume Sandou
ICINCO: PROCEEDINGS OF THE 16TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL 1
(2019)
Proceedings Paper
Automation & Control Systems
C. Stoica Maniu, G. Sandou, V Letort-Le Chevalier
Article
Thermodynamics
Yong Cheng, Fukai Song, Lei Fu, Saishuai Dai, Zhiming Yuan, Atilla Incecik
Summary: This paper investigates the accessibility of wave energy absorption by a dual-pontoon floating breakwater integrated with hybrid-type wave energy converters (WECs) and proposes a hydraulic-pneumatic complementary energy extraction method. The performance of the system is validated through experiments and comparative analysis.
Article
Thermodynamics
Jing Gao, Chao Wang, Zhanwu Wang, Jin Lin, Runkai Zhang, Xin Wu, Guangyin Xu, Zhenfeng Wang
Summary: This study aims to establish a new integrated method for biomass cogeneration project site selection, with a focus on the application of the model in Henan Province. By integrating Geographic Information System and Multiple Criterion Decision Making methods, the study conducts site selection in two stages, providing a theoretical reference for the construction of biomass cogeneration projects.
Article
Thermodynamics
Mert Temiz, Ibrahim Dincer
Summary: The current study presents a hybrid small modular nuclear reactor and solar-based system for sustainable communities, integrating floating and bifacial photovoltaic arrays with a small modular reactor. The system efficiently generates power, hydrogen, ammonia, freshwater, and heat for residential, agricultural, and aquaculture facilities. Thermodynamic analysis shows high energy and exergy efficiencies, as well as large-scale ammonia production meeting the needs of metropolitan areas. The hybridization of nuclear and solar technologies offers advantages of reliability, environmental friendliness, and cost efficiency compared to renewable-alone and fossil-based systems.
Editorial Material
Thermodynamics
Wojciech Stanek, Wojciech Adamczyk
Article
Thermodynamics
Desheng Xu, Yanfeng Li, Tianmei Du, Hua Zhong, Youbo Huang, Lei Li, Xiangling Duanmu
Summary: This study investigates the optimization of hybrid mechanical-natural ventilation for smoke control in complex metro stations. The results show that atrium fires are more significantly impacted by outdoor temperature variations compared to concourse/platform fires. The gathered high-temperature smoke inside the atrium can reach up to 900 K under a 5 MW train fire energy release. The findings provide crucial engineering insights into integrating weather data and adaptable ventilation protocols for smoke prevention/mitigation.
Article
Thermodynamics
Da Guo, Heping Xie, Mingzhong Gao, Jianan Li, Zhiqiang He, Ling Chen, Cong Li, Le Zhao, Dingming Wang, Yiwei Zhang, Xin Fang, Guikang Liu, Zhongya Zhou, Lin Dai
Summary: This study proposes a new in-situ pressure-preserved coring tool and elaborates its pressure-preserving mechanism. The experimental and field test results demonstrate that this tool has a high pressure-preservation capability and can maintain a stable pressure in deep wells. This study provides a theoretical framework and design standards for the development of similar technologies.
Article
Thermodynamics
Aolin Lai, Qunwei Wang
Summary: This study assesses the impact of China's de-capacity policy on renewable energy development efficiency (REDE) using the Global-MSBM model and the difference-in-differences method. The findings indicate that the policy significantly enhances REDE, promoting technological advancements and marketization. Moreover, regions with stricter environmental regulations experience a higher impact.
Article
Thermodynamics
Mostafa Ghasemi, Hegazy Rezk
Summary: This study utilizes fuzzy modeling and optimization to enhance the performance of microbial fuel cells (MFCs). By simulating and analyzing experimental data sets, the ideal parameter values for increasing power density, COD elimination, and coulombic efficiency were determined. The results demonstrate that the fuzzy model and optimization methods can significantly improve the performance of MFCs.
Article
Thermodynamics
Zhang Ruan, Lianzhong Huang, Kai Wang, Ranqi Ma, Zhongyi Wang, Rui Zhang, Haoyang Zhao, Cong Wang
Summary: This paper proposes a grey box model for fuel consumption prediction of wing-diesel hybrid vessels based on feature construction. By using both parallel and series grey box modeling methods and six machine learning algorithms, twelve combinations of prediction models are established. A feature construction method based on the aerodynamic performance of the wing and the energy relationship of the hybrid system is introduced. The best combination is obtained by considering the root mean square error, and it shows improved accuracy compared to the white box model. The proposed grey box model can accurately predict the daily fuel consumption of wing-diesel hybrid vessels, contributing to operational optimization and the greenization and decarbonization of the shipping industry.
Article
Thermodynamics
Huayi Chang, Nico Heerink, Junbiao Zhang, Ke He
Summary: This study examines the interaction between off-farm employment decisions between couples and household clean energy consumption in rural China, and finds that two-paycheck households are more likely to consume clean energy. The off-farm employment of women is a key factor driving household clean energy consumption to a higher level, with wage-employed wives having a stronger influence on these decisions than self-employed ones.
Article
Thermodynamics
Hanguan Wen, Xiufeng Liu, Ming Yang, Bo Lei, Xu Cheng, Zhe Chen
Summary: Demand-side management is crucial to smart energy systems. This paper proposes a data-driven approach to understand the relationship between energy consumption patterns and household characteristics for better DSM services. The proposed method uses a clustering algorithm to generate optimal customer groups for DSM and a deep learning model for training. The model can predict the possibility of DSM membership for a given household. The results demonstrate the usefulness of weekly energy consumption data and household socio-demographic information for distinguishing consumer groups and the potential for targeted DSM strategies.
Article
Thermodynamics
Xinglan Hou, Xiuping Zhong, Shuaishuai Nie, Yafei Wang, Guigang Tu, Yingrui Ma, Kunyan Liu, Chen Chen
Summary: This study explores the feasibility of utilizing a multi-level horizontal branch well heat recovery system in the Qiabuqia geothermal field. The research systematically investigates the effects of various engineering parameters on production temperature, establishes mathematical models to describe their relationships, and evaluates the economic viability of the system. The findings demonstrate the significant economic feasibility of the multi-level branch well system.
Article
Thermodynamics
Longxin Zhang, Songtao Wang, Site Hu
Summary: This investigation reveals the influence of tip leakage flow on the modern transonic rotor and finds that the increase of tip clearance size leads to a decline in rotor performance. However, an optimal tip clearance size can extend the rotor's stall margin.
Article
Thermodynamics
Kristian Gjoka, Behzad Rismanchi, Robert H. Crawford
Summary: This paper proposes a framework for assessing the performance of 5GDHC systems and demonstrates it through a case study in a university campus in Melbourne, Australia. The results show that 5GDHC systems are a cost-effective and environmentally viable solution in mild climates, and their successful implementation in Australia can create new market opportunities and potential adoption in other countries with similar climatic conditions.
Article
Thermodynamics
Jianwei Li, Guotai Wang, Panpan Yang, Yongshuang Wen, Leian Zhang, Rujun Song, Chengwei Hou
Summary: This study proposes an orientation-adaptive electromagnetic energy harvester by introducing a rotatable bluff body, which allows for self-regulation to cater for changing wind flow direction. Experimental results show that the output power of the energy harvester can be greatly enhanced with increased rotatory inertia of the rotating bluff body, providing a promising solution for harnessing wind-induced vibration energy.
