Article
Computer Science, Interdisciplinary Applications
Jiexiang Hu, Lili Zhang, Quan Lin, Meng Cheng, Qi Zhou, Huaping Liu
Summary: The paper proposed a new multi-fidelity surrogate model-based robust optimization method to address prediction uncertainty, achieving better optimal design solutions.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Computer Science, Interdisciplinary Applications
Jiachang Qian, Yuansheng Cheng, Anfu Zhang, Qi Zhou, Jinlan Zhang
Summary: The study introduces a metamaterial vibration isolator with a honeycomb structure and validates its performance through finite element modeling and experiments. It proposes a multi-fidelity sequential optimization approach to accelerate the design process.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Computer Science, Interdisciplinary Applications
Qi Guo, Jiutao Hang, Suian Wang, Wenzhi Hui, Zonghong Xie
Summary: This paper presents an efficient design optimization method assisted by multi-fidelity surrogate models for buckling design of variable stiffness composites. By using hierarchical Kriging and global optimization method, the effectiveness and robustness of the method are demonstrated through two case studies.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Computer Science, Artificial Intelligence
Lili Zhang, Yuda Wu, Ping Jiang, Seung-Kyum Choi, Qi Zhou
Summary: The NHLF-Co-Kriging method proposed in this work is able to handle multiple non-hierarchical low-fidelity models effectively by optimizing scale factors, providing more accurate MF surrogate models under a limited computational budget.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Engineering, Multidisciplinary
Haoxiang Xue, Massimiliano Gobbi, Andrea Matta
Summary: Optimizing the suspension system of road vehicles is crucial for improving ride comfort. This study proposes a multi-fidelity surrogate-based optimization framework, which demonstrates good accuracy and high efficiency compared to other methods. It is successfully applied to different types of vehicle suspension optimization problems, showing robustness and efficiency.
OPTIMIZATION AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
John D. Jakeman, Sam Friedman, Michael S. Eldred, Lorenzo Tamellini, Alex A. Gorodetsky, Doug Allaire
Summary: We present an adaptive algorithm for constructing surrogate models of multi-disciplinary systems composed of a set of coupled components. The algorithm introduces coupling variables with unknown distributions to independently build surrogates for each component. The surrogates are then combined to form an integrated-surrogate, which greatly reduces the cost compared to the original model. The algorithm minimizes the error in the integrated-surrogate by allocating training data based on the contribution of each component-surrogate. Extensive numerical results demonstrate the accuracy and efficiency of the algorithm compared to black-box methods.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Xiaonan Lai, Yong Pang, Fuwen Liu, Wei Sun, Xueguan Song
Summary: This paper proposes a novel multi-fidelity surrogate model (MFS-DVC) based on design variable correlations, which introduces local characteristics to the scaling factors and enables adaptive adjustments. The experimental results demonstrate that MFS-DVC achieves competitive performance in terms of prediction accuracy and robustness.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Energy & Fuels
Lian Wang, Yuedong Yao, Tao Zhang, Caspar Daniel Adenutsi, Guoxiang Zhao, Fengpeng Lai
Summary: This paper proposes a self-adaptive multi-fidelity surrogate-assisted multi-objective production optimization algorithm (SAMFS-MOPO) to reduce the computational burden and improve the accuracy of the surrogate model. By using two fidelity samples to establish a multi-fidelity surrogate model, and using i-updating and g-updating strategies to update the model during the optimization process, this method demonstrates superior performance in convergence, diversity, and efficiency compared to other conventional methods.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2022)
Article
Automation & Control Systems
Yunyang Zhang, Zhiqiang Gong, Weien Zhou, Xiaoyu Zhao, Xiaohu Zheng, Wen Yao
Summary: In this paper, a novel deep multi-fidelity modeling method is proposed to improve the prediction performance by utilizing low-fidelity data and reducing the dependence on high-fidelity data. A concise pre-train and fine-tune paradigm is proposed for efficient model construction, and a physics-driven self-supervised learning method is introduced to further reduce the reliance on labeled low-fidelity data. Experimental results show that the proposed method significantly enhances the accuracy of the model and reduces the requirement for high-fidelity data.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Jiexiang Hu, Yutong Peng, Quan Lin, Huaping Liu, Qi Zhou
Summary: This paper proposes a conservative multi-fidelity modeling method that integrates the performance of different error metrics. By reasonably weighting the bootstrap method and mean-square-error method, the method calculates the safety margin of the surrogate model, resulting in a more accurate conservative model and better optimal solutions in optimization problems.
ENGINEERING WITH COMPUTERS
(2022)
Article
Engineering, Multidisciplinary
Xinshuai Zhang, Fangfang Xie, Tingwei Ji, Zaoxu Zhu, Yao Zheng
Summary: The study establishes an effective optimization framework of aerodynamic shape design based on the multi-fidelity deep neural network (MFDNN) model, achieving high accuracy by blending different fidelity information. The proposed framework significantly improves optimization efficiency and outperforms single-fidelity methods.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Huan Zhao, Zheng-Hong Gao, Lu Xia
Summary: Surrogate models are widely used in uncertainty-based design optimization, but they often have accuracy and sensitivity issues. To address these challenges, a UBDO framework based on multi-fidelity polynomial chaos-Kriging is proposed, with particular superiority for complex aerodynamic applications.
COMPUTERS & FLUIDS
(2022)
Article
Engineering, Aerospace
Zengcong LI, Kuo Tian, Shu Zhang, Bo Wang
Summary: To accelerate multi-objective optimization for expensive engineering cases, this study presents a KE-VFS-CMA-ES model which is based on knowledge extraction and variable-fidelity surrogate-assisted covariance matrix adaptation evolution strategy. In the first part, the KE-VFS model is established by using a low-fidelity surrogate model to obtain low-fidelity non-dominated solutions, extracting knowledge using the K-means clustering algorithm and space-filling strategy, and combining high-fidelity and low-fidelity sample points. In the second part, a novel model management based on the MHVI criterion and pre-screening strategy is proposed. The results demonstrate the excellent efficiency, robustness, and applicability of KE-VFS-CMA-ES compared to other multi-objective optimization algorithms.
CHINESE JOURNAL OF AERONAUTICS
(2023)
Article
Mechanics
Kuo Tian, Zengcong Li, Jiaxin Zhang, Lei Huang, Bo Wang
Summary: This paper proposes a novel establishment method of the variable-fidelity surrogate model driven by transfer learning for shell buckling prediction problems, aiming to achieve higher prediction accuracy. The TL-VFSM is constructed through two steps and verified by engineering examples for its effectiveness and efficiency.
COMPOSITE STRUCTURES
(2021)
Article
Mechanics
Kwangkyu Yoo, Omar Bacarreza, M. H. Ferri Aliabadi
Summary: A novel multi-fidelity modeling-based optimization framework is developed for robust design of composite structures in this paper. The proposed framework offers significant savings in computation time compared to conventional methods, while maintaining an acceptable level of accuracy. By incorporating ANNs and multi-level optimization approach, the framework utilizes both High-Fidelity Model (HFM) and Low-Fidelity Model (LFM) to cover different design spaces.
COMPOSITE STRUCTURES
(2021)
Article
Plant Sciences
Peng Jin, Yan Ji, Quanting Huang, Peiyuan Li, Jinmei Pan, Hua Lu, Zhe Liang, Yingyan Guo, Jiahui Zhong, John Beardall, Jianrong Xia
Summary: This study examined the long-term adaptive responses of phytoplankton to high CO2 conditions and found that it leads to a decrease in photosynthesis and respiration. The results also indicate that metabolism reduction plays an important role in the adaptive mechanisms of phytoplankton to climate change.
Review
Hematology
Mengying Gao, Jinbo Huang, Yingqi Shao, Meili Ge, Xingxin Li, Jing Zhang, Min Wang, Neng Nie, Peng Jin, Yizhou Zheng
Summary: This study retrospectively analyzed the management and outcomes of anti-thymocyte globulin (ATG) administration for platelet transfusion refractoriness (PTR) in severe aplastic anemia (SAA) patients. The results showed that ATG was effective in rapidly relieving PTR symptoms, with nearly half of the patients responding immediately after the first dose of ATG. Some patients experienced severe bleeding after ATG treatment, but effective platelet transfusion could quickly alleviate the bleeding events, while non-responders may suffer from aggravated bleeding.
TRANSFUSION AND APHERESIS SCIENCE
(2022)
Article
Nutrition & Dietetics
Jianping Xiong, Haitao Hu, Wenzhe Kang, Xinxin Shao, Yang Li, Peng Jin, Yantao Tian
Summary: This study investigates the connection between sarcopenia and interleukin-16 (IL-16) expression and their relation to gastric cancer (GC) survival. The results show that sarcopenia and high IL-16 expression are independent factors predicting overall survival and relapse-free survival in GC patients. Furthermore, there is a higher occurrence of high IL-16 expression in GC patients with sarcopenia. Sarcopenia accompanied by high IL-16 expression suggests a poorer prognosis in GC patients.
Article
Multidisciplinary Sciences
Liujun Xu, Jinrong Liu, Peng Jin, Guoqiang Xu, Jiaxin Li, Xiaoping Ouyang, Ying Li, Cheng-Wei Qiu, Jiping Huang
Summary: The curved space-time produced by black holes leads to the intriguing trapping effect. So far, metadevices have enabled analogous black holes to trap light or sound in laboratory spacetime. However, trapping heat in a conductive environment is still challenging because diffusive behaviors are directionless.
NATIONAL SCIENCE REVIEW
(2023)
Article
Electrochemistry
Junfeng Li, Hui Xing, Peng Jin, Mingyan Li, Haiyan Liu
Summary: An electrochemical immunosensor for highly sensitive AFP detection was developed using a modified glassy carbon electrode. The sensor exhibited linear detection of AFP in the concentration range of 0.1 to 100 ng/mL with a limit of detection of 0.041 ng/mL. It also showed excellent anti-interference properties.
INTERNATIONAL JOURNAL OF ELECTROCHEMICAL SCIENCE
(2022)
Article
Thermodynamics
Wei Wu, Peng Jin, Shuai Zhao, Yunjun Luo
Summary: This paper investigates the effect of ammonium perchlorate (AP) on the slow cook-off response of hydroxyl-terminated block copolyether (HTPE) propellants. The results show that an increase in AP content or a decrease in AP diameter leads to a more violent slow cook-off response. The possible mechanism for this is the thermal damage of the propellant during the slow cook-off test, which increases the combustion sensitivity of the damaged propellant.
THERMOCHIMICA ACTA
(2022)
Article
Thermodynamics
Binzhen Zhou, Jianjian Hu, Peng Jin, Ke Sun, Ye Li, Dezhi Ning
Summary: By studying a hybrid system consisting of a semi-submersible platform and heaving point absorber wave energy converters (WECs), this research has found that a new prominent power peak occurs in the so-called synchronized mode regardless of the layout of the WECs. In this mode, the power of a single WEC can increase by up to 41.4% and the total power by up to 26.7%, but the heave motion of the platform increases. The WECs have a small impact on the surge motion and pitch motion of the platform except for near the synchronized mode frequency, where they reduce the resonant heave motion at the natural frequency. This study provides valuable insights into the dynamic and power performance of wind-wave hybrid systems, offering detailed configurations and potential guidance for practical design and application.
Article
Multidisciplinary Sciences
Peng Jin, Jinrong Liu, Liujun Xu, Jun Wang, Xiaoping Ouyang, Jian-Hua Jiang, Jiping Huang
Summary: Thermal metamaterials provide rich control of heat transport by breaking the Onsager reciprocity and introducing thermal convection, leading to a regime beyond effective heat conduction. A continuous switch from thermal cloaking to thermal concentration is demonstrated in a liquid-solid hybrid thermal metamaterial with external tuning. This switch is achieved by tuning the liquid flow, resulting in a topology transition in the virtual space of the thermotic transformation. These findings illustrate the extraordinary heat transport in complex multicomponent thermal metamaterials and pave the way toward an unprecedented regime of heat manipulation.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Engineering, Chemical
Daoguang Teng, Peng Jin, Shiqiao Yang, Wenhuan Guo, Zhuang Zhao, Guoli Zhou, Peng Li, Yijun Cao
Summary: Cost-effective polycyclic aromatic hydrocarbons (PAHs) were used to fabricate hyper-cross-linked polymers (HCLPs) via an external cross-linker knitting method (ECLKM) followed by N-source impregnation modification. The resulting materials exhibited high thermal stability, large specific surface areas, narrow pore distributions, and high pore volumes. The effects of porosities and N-doping modification on the CO2 capture capacities of HCLPs were fully studied, and it was found that porosities played a dominant role in the CO2 uptake process compared to N-doping modification. This study provides a simple strategy for constructing HCLPs with excellent CO2 capture performances using PAHs.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2023)
Article
Mechanics
Bin-zhen Zhou, Zhi Zheng, Yu Wang, Peng Jin, Lin Cui, Liang Cheng
Summary: An optimization method is proposed to determine the dimensions of a hybrid system consisting of a spar-type floating offshore wind turbine and a heaving annular wave energy converter (WEC). The synchronized mode, where the natural frequency of the system matches the peak wave frequency, is found to be the most effective in terms of wave energy production.
JOURNAL OF HYDRODYNAMICS
(2023)
Article
Physics, Applied
Fubao Yang, Peng Jin, Min Lei, Gaole Dai, Jun Wang, Jiping Huang
Summary: The proposed space-time-coding electromagnetic metasurface introduces the temporal dimension into artificial structure design, expanding its digital application in information processing. However, the absence of temporal dimension in thermal digital metamaterial limits the synergetic modulation of thermal signal in time and space. This study introduces temporal modulation into existing spatially variable thermal coding structures and proposes a space-time thermal binary coding scheme, demonstrating a practical strategy for thermal binary coding and providing a prototype for spatiotemporal regulation of thermal signal.
PHYSICAL REVIEW APPLIED
(2023)
Article
Chemistry, Multidisciplinary
Kai Wang, Feng Wan, Ling Luo, Pengyu Cao, Lei Han, Peng Jin
Summary: This paper investigates the buckling enhancement of the negative Poisson's ratio (NPR) effect on a laminated plate under uniaxial compression with an in-plane translational restraint. By studying the buckling equation and lamination parameters, it is found that the critical buckling load of an NPR-laminated composite can be increased due to the induced tension force on the unloaded direction under compression. The Poisson's ratio contours and buckling load enhancement are analyzed, and the inverse problem of deciding the laminate configuration is solved using the particle swarm optimization (PSO) algorithm.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Multidisciplinary
Peng Jin, Liujun Xu, Guoqiang Xu, Jiaxin Li, Cheng-Wei Qiu, Jiping Huang
Summary: Heat-enhanced thermal diffusion metamaterials powered by deep learning enable automatic temperature sensing and adjustment with high tunability and stable thermal performance.
ADVANCED MATERIALS
(2023)
Article
Engineering, Marine
Binzhen Zhou, Qi Zhang, Jianjian Hu, Peng Jin, Hengming Zhang, Siming Zheng
Summary: The wave power absorption of a heaving-body wave energy converter can be improved by deploying it near a coastal wall, harbour pier, or breakwater and making it highly asymmetric. This research proposes a semi-analytical model to analyze the coupling between the geometric asymmetry of the converter and the partial reflecting boundaries of the walls. Results show that the wall increases the power performance by increasing the reflection rate.
Article
Chemistry, Inorganic & Nuclear
Wangqiang Shen, Lei Lou, Yiao Wei, Lipiao Bao, Guangqing Xu, Peng Jin, Jun Lv, Xing Lu
Summary: In this study, a dysprosium-containing mono-EMF with a C-84 cage, possessing rare D-2(21) symmetry, was successfully synthesized. Theoretical calculations revealed that the encapsulation of a trivalent Dy ion in the carbon cage is energetically more favorable than other C-84-based mono-EMFs. This work not only expands the trivalent mono-EMF family but also provides insights into the unique structures and stabilities of such novel EMFs.
INORGANIC CHEMISTRY FRONTIERS
(2023)