Article
Engineering, Environmental
Katsuo Sasahara, Nobutaka Hiraoka, Naotaka Kikkawa, Kazuya Itoh
Summary: Surface displacements in a large-scale slope model increased both during and after slope excavation due to creep deformation under constant stress. The relationship between surface displacement velocity and acceleration fluctuated notably, and the trendlines generally agreed with the measured data at certain locations on the model slope. Steeper trendlines predicted earlier failure times for larger displacements close to failure conditions, but resulted in worse predictions for smaller displacements far from causing slope failure.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2021)
Article
Computer Science, Interdisciplinary Applications
Blanca Pablos, Matthias Gerdts
Summary: This study investigates the application of full discretization and a nonsmooth Newton method to large-scale optimal control problems. By discretizing state and control variables in time using a collocation method and utilizing a nonsmooth Newton method with a line search globalization strategy, an efficient solution is found. Reduction in computational effort is achieved through structure exploitation and substructure exploitation strategies, with the most efficient approach applied to a nonlinear version of the problem.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2021)
Article
Computer Science, Software Engineering
Di Zhang, Xiaoya Zhai, Xiao-Ming Fu, Heming Wang, Ligang Liu
Summary: We propose a novel topology optimization method to efficiently minimize the maximum compliance for a high-resolution model bearing uncertain external loads. Our method utilizes a modified power method that quickly computes the maximum eigenvalue to evaluate the worst-case compliance. By using the adjoint variable method, we perform sensitivity analysis and update the density variables to achieve optimized models with high efficiency.
COMPUTER GRAPHICS FORUM
(2022)
Article
Materials Science, Multidisciplinary
Yousef Nikravesh, Yinwei Zhang, Jian Liu, George N. Frantziskonis
Summary: This study presents a partition based topology optimization framework for the design of large-scale problems, specifically focusing on mechanical stiffness optimization. The method utilizes physical partitioning and assigns density design variables to each spatial partition, resulting in improved computational efficiency.
MECHANICS OF MATERIALS
(2022)
Article
Engineering, Multidisciplinary
Shuzhi Xu, Jikai Liu, Xinming Li, Yongsheng Ma
Summary: Additive manufacturing offers new possibilities for the design of fiber-reinforced composite structures. This research presents a dedicated topology optimization method for surface fiber reinforcement design, focusing on the modeling of fiber contents and addressing the reinforcement effect. The proposed method demonstrates its validity and effectiveness through numerical and experimental examples.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Abhinav Kulkarni, Messaoud Ahmed Ouameur, Daniel Massicotte
Summary: This study addresses the bottleneck issue in centralized Massive MIMO uplink detection techniques by adapting the decentralized Newton method, proposing ring and star hardware topologies for trade-off analysis. The ring topology offers high throughput with constant interconnect bandwidth, while the star topology provides lower latency with deterministic variation in hardware resource consumption. Through strategic optimizations, additional user equipment can be allocated with fractional increase in FPGA resource consumption and improved energy efficiency.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2021)
Article
Engineering, Electrical & Electronic
Takayuki Nagata, Keigo Yamada, Kumi Nakai, Yuji Saito, Taku Nonomura
Summary: The randomized group-greedy (RGG) method and its customized method are proposed for large-scale sensor selection problems. The customized method involves selecting a portion of the compressed sensor candidates using a low-cost method to compensate for the deterioration in the solution. The proposed method provides better optimization results than the original method with a similar computational cost.
IEEE SENSORS JOURNAL
(2023)
Article
Chemistry, Analytical
Zhihao Luo, Jingju Liu, Guozheng Yang, Yongheng Zhang, Zijun Hang
Summary: This paper proposes a large-scale network path probing approach to improve the efficiency of network path probing and reduce probing redundancy and network load. The approach improves the packet delivery order and the update strategy of time-to-live field values, resulting in a more efficient tool for path probing.
Article
Engineering, Mechanical
Zhenmin Li, Qinghua Song, Zhanqiang Liu, Haifeng Ma, Bing Wang, Yukui Cai
Summary: This work presents a predictive algorithm for the response of cantilever plates in unmeasured regions. The algorithm is based on the mode superposition method and the combination method of beam functions. It deduces the vibration mode function of the cantilever plate and updates mode coefficients in real time using measured responses. Displacements or accelerations of target positions are predicted using the mode matrix and mode coefficients. The method does not require specific load expression and distribution, and it is not dependent on finite element models or repeated iterations.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Environmental Sciences
Yu-Hong Yeung, David A. Barajas-Solano, Alexandre M. Tartakovsky
Summary: We developed a physics-informed machine learning approach for estimating transmissivity and hydraulic head in a subsurface flow model. The method, called PICKLE, demonstrated comparable accuracy to the standard MAP method but was significantly faster for large-scale problems. The approach used conditional Karhunen-Loeve expansions and mesh discretization to control the number of parameters without being limited by the mesh size.
WATER RESOURCES RESEARCH
(2022)
Article
Chemistry, Analytical
Yanlei Yin, Lihua Wang, Litong Zhang
Summary: In this paper, a multipopulation dynamic adaptive coevolutionary strategy is proposed to enhance the algorithm's global and local searching capability and optimization accuracy for large-scale optimization problems. The proposed algorithm exhibited a high optimization accuracy and converging rate for high-dimensional and large-scale complex optimization problems.
Article
Mathematics
Qi Tian, Xiaoliang Wang, Liping Pang, Mingkun Zhang, Fanyun Meng
Summary: A hybrid three-term conjugate gradient algorithm is proposed in this paper, possessing sufficient descent property and global convergence for large-scale unconstrained problems. Numerical results indicate that the proposed algorithm is more efficient and reliable compared to other methods.
Article
Engineering, Electrical & Electronic
Shaoyang Wang, Yong Li, Mingmin Zhang, Yanjian Peng, Ye Tian, Gang Lin, Fanrui Chang
Summary: This article presents a novel scheme of using the inductive power filtering method (IPFM) to solve the harmonic resonance issues in large-scale photovoltaic (PV) plants, taking actual engineering as a case study. The performance of power filters is improved by reshaping the impedance network of the PV plant using the special structure and dual zero-impedance design of IPFM, thus suppressing the harmonic resonance caused by the interaction between inverters and the power grid. The topology and components of the IPFM-based large-scale PV plant are introduced, and the mathematical model and simplified circuit are established. The feasibility of the proposal is verified through simulation and engineering tests.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Mathematics, Applied
Abderrahmane Ettahiri, Abdelkrim El Mouatasim
Summary: In this paper, a new approach is proposed to optimize a large-scale non-convex differentiable function under linear equality constraints. The proposed method, RPCGB, employs the conditional gradient to compute a search direction and utilizes a bisection algorithm to find an optimal line search, resulting in a decrease in the cost function. The RPCGB method is designed to ensure global convergence of the algorithm. The implementation and testing of the method are provided, along with numerical results of large-scale problems to demonstrate its efficiency.
Article
Operations Research & Management Science
Natasa Krejic, Greta Malaspina, Lense Swaenen
Summary: This article proposes a decoupling procedure that splits large-scale nonlinear least squares problems into a sequence of smaller independent problems, and analyzes this method. The smaller problems are modified to compensate for disregarded dependencies. The method, a modification of the Levenberg-Marquardt method, has lower computational costs. Global convergence and local linear convergence are proven under suitable sparsity assumptions. The method is tested on network localization simulated problems with up to one million variables, demonstrating its efficiency.
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Weihong Zhang, Hu Liu, Tong Gao
COMPUTERS & STRUCTURES
(2015)
Article
Computer Science, Interdisciplinary Applications
Hu Liu, Weihong Zhang, Tong Gao
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2016)
Article
Computer Science, Interdisciplinary Applications
Gao Tong, Xu Pengli, Zhang Weihong
COMPUTERS & STRUCTURES
(2016)
Article
Computer Science, Interdisciplinary Applications
Tong Gao, Libin Qiu, Weihong Zhang
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2017)
Article
Engineering, Multidisciplinary
Shouyu Cai, Weihong Zhang, Jihong Zhu, Tong Gao
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2014)
Article
Engineering, Multidisciplinary
Zhang WeiHong, Zhang ZhiDong, Zhu JiHong, Gao Tong
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2014)
Article
Computer Science, Interdisciplinary Applications
Weihong Zhang, Jungang Yang, Yingjie Xu, Tong Gao
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2014)
Review
Computer Science, Interdisciplinary Applications
Liang Meng, Weihong Zhang, Dongliang Quan, Guanghui Shi, Lei Tang, Yuliang Hou, Piotr Breitkopf, Jihong Zhu, Tong Gao
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2020)
Article
Computer Science, Interdisciplinary Applications
Tao Liu, Ji-Hong Zhu, Wei-Hong Zhang, Hua Zhao, Jie Kong, Tong Gao
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2019)
Article
Computer Science, Interdisciplinary Applications
Cao Niu, Weihong Zhang, Tong Gao
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2019)
Article
Engineering, Aerospace
Guanghui Shi, Chengqi Guan, Dongliang Quan, Dongtao Wu, Lei Tang, Tong Gao
CHINESE JOURNAL OF AERONAUTICS
(2020)
Article
Engineering, Multidisciplinary
Lei Tang, Tong Gao, Longlong Song, Liang Meng, Chengqi Zhang, Weihong Zhang
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2019)
Article
Engineering, Multidisciplinary
Weihong Zhang, Linying Zhao, Tong Gao
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2017)
Article
Engineering, Multidisciplinary
Weihong Zhang, Linying Zhao, Tong Gao, Shouyu Cai
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2017)