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Experimental study of damage to double-hull structure by underwater explosions of three charge types - blasting, shaped, and linear shaped charges

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International Journal of Impact Engineering 2025年 203卷

作者： Zhang, Zhifan Yang, Shuxin Zhang, Shenhe Wang, Longkan Sui, Yutong Li, Tao Zhang, Guiyong State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment School of Naval Architecture Engineering Dalian University of Technology Dalian116024 China China Ship Research and Development Academy Beijing100192 China School of Mechanical Engineering Key Laboratory of Advanced Intelligent Protective Equipment Technology Ministry of Education Hebei University of Technology Tianjin300401 China Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration Shanghai 200240 China

In recent years, due to the improvement in ship protection capabilities, near-field underwater explosions no longer pose fatal damage to ships. Since stiffened plates are typical structures in ships, studying the impact of underwater explosions with different types of explosives on ships is of great significance. This experiment investigated the damage characteristics of blasting, shaped, and linear shaped charges on the same type of stiffened plate. The experimental results indicate that linear shaped charges can create larger penetration holes on target plates, but they suffer from insufficient flight capability. In contrast, shaped charges exhibit stronger penetrating power, yet they lack sufficient damage capability against target plates. Although the penetration capability of blasting charges is inferior to the first two, its overall deflection of the plate frame exceeds that caused by shaped charges and linear shaped charges by 1.6 % and 5.7 %, respectively. To further investigate the penetration process and the load characteristics of the penetrator, a finite element model was established in this paper. The numerical results show that there is no significant difference in jet length and velocity between the two models, but the shapes of the jet tips differ, and the computational results are in good agreement with the experimental results, confirming the validity of the Arbitrary Lagrangian-Eulerian (ALE) method. © 2025 Elsevier Ltd

关键词： Underwater explosions

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Bubble dynamics and structural damage caused by underwater explosion

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International Journal of Mechanical Sciences 2025年 297-298卷

作者： Li, Hailong Zhang, Jingyuan Wang, Longkan Li, Bing Zhang, Zhifan Zhang, Guiyong Zong, Zhi State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment School of Naval Architecture Engineering Dalian University of Technology Dalian116024 China China Ship Research and Development Academy Beijing100192 China 91439 Troops Liaoning Dalian116041 China Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration Shanghai200240 China Fuyao University of Science and Technology Fuzhou350100 China

In ocean engineering, curved structures are commonly used in various marine applications, including unmanned underwater vehicles (UUVs) and autonomous underwater vehicles (AUVs). However, the interaction between underwater explosions (UNDEX) and such elastic-plastic curved structures remains insufficiently understood, particularly regarding bubble dynamics and water jet loading near deformable boundaries. To address this gap, this study presents a combined experimental and numerical investigation of UNDEX near an elastic-plastic curved double-hull structure—a configuration that has received limited prior attention. Shockwave and bubble pulsation pressures were recorded using pressure sensors, and bubble motion and jet formation were captured via high-speed imaging. Numerical simulations using the coupled Eulerian-Lagrangian (CEL) method were performed to complement the experiments, covering 63 representative cases. Compared to shockwave loading alone, the combined action of shockwave, bubble, and water jet increased the outer hull deflection by 184 %, highlighting the critical role of multi-source interactions. Two key parameters—distance parameter (γ) and ring rib position (β)—were systematically varied to assess their influence on bubble behavior, jet dynamics, and structural damage. This study contributes new insights into the emergence of mutually deviating water jets and proposes a classification of six typical bubble shapes, four fundamental jet units, and five distinct jet types near elastic-plastic boundaries. These findings enhance the understanding of fluid-structure interaction (FSI) under multi-source loading and reveal the structural vulnerability associated with bubble pulsation and jet impact. The results underscore the importance of considering these coupled effects in the design and protection of marine structures exposed to underwater explosions. © 2025

关键词： Marine applications

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Analysis for blockchain application quality 2

Analysis for blockchain application quality

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2nd International Workshop on Experience with SQuaRE Series and Its Future Direction, IWESQ 2020

作者： Xu, Jiajin Zhang, Huan Gong, Jiayu Shanghai Key Laboratory of Computer Software Evaluation Shanghai Computer Software Technology Development Center Shanghai China

With the maturity and popularity of blockchain technology, it has applied to many industries, such as financial sector, logistics, notarization and so on, but there is no correct quality model to describe the brockchain software. This paper we combined with the general software quality model(SQuaRE), formed a suitable quality model of the blockchain platform (Hyperledger Fabric) and expound its special quality measure. The research result of this paper can be applied to test or evaluate of blockchain application. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Quality control

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center-guided Classifier for Semantic Segmentation of Remote Sensing Images

arXiv

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arXiv 2025年

作者： Zhang, Wei Ma, Mengting Jiang, Yizhen Lian, Rongrong Wu, Zhenkai Cui, Kangning Ma, Xiaowen School of Software Technology Zhejiang University Hangzhou310027 China Innovation Center of Yangtze River Delta Zhejiang University Zhejiang Jiaxing314103 China School of Computer Science and Technology Zhejiang University Hangzhou310027 China Department of Mathematics City University of Hong Kong Hong Kong Noah’s Ark Lab Huawei Shanghai201206 China

Compared with natural images, remote sensing images (RSIs) have the unique characteristic. i.e., larger intraclass variance, which makes semantic segmentation for remote sensing images more challenging. Moreover, existing semantic segmentation models for remote sensing images usually employ a vanilla softmax classifier, which has three drawbacks: (1) non-direct supervision for the pixel representations during training;(2) inadequate modeling ability of parametric softmax classifiers under large intraclass variance;and (3) opaque process of classification decision. In this paper, we propose a novel classifier (called centerSeg) customized for RSI semantic segmentation, which solves the abovementioned problems with multiple prototypes, direct supervision under Grassmann manifold, and interpretability strategy. Specifically, for each class, our centerSeg obtains local class centers by aggregating corresponding pixel features based on ground-truth masks, and generates multiple prototypes through hard attention assignment and momentum updating. In addition, we introduce the Grassmann manifold and constrain the joint embedding space of pixel features and prototypes based on two additional regularization terms. Especially, during the inference, centerSeg can further provide interpretability to the model by restricting the prototype as a sample of the training set. Experimental results on three remote sensing segmentation datasets validate the effectiveness of the model. Besides the superior performance, centerSeg has the advantages of simplicity, lightweight, compatibility, and interpretability. Code is available at https://***/xwmaxwma/rssegmentation. © 2025, CC BY.

关键词： Semantic Segmentation

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An Evaluation System for Large Language Models based on Open-Ended Questions 11

An Evaluation System for Large Language Models based on Open...

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11th IEEE International Conference on Cyber Security and Cloud Computing, CSCloud 2024

作者： Cao, Zhiyuan Ma, Zeyu Chen, Mingang Computer and Information Engineering College Shanghai Polytechnic University Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer Software Technology Shanghai China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer software Technology Mathematical and Science College Shanghai Normal University Shanghai China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer software Technology Shanghai China

ISBN: (纸本)9798350376982

We designed a large language model evaluation system based on open-ended questions. The system accomplished multidimensional evaluation of LLMs using open-ended questions, and it presented evaluation results with evaluation reports. Currently, the evaluation of large-scale language models often exists with two prominent limitations: (1) The evaluation methods are often single-minded, resulting in less credible results. (2) Most evaluations are based on datasets with closed-ended questions, treating generative large language models as discriminative models, which fails to adequately reflect the high output flexibility characteristic of these models. For these two limitations, we proposed an evaluation system for LLMs based on open-ended questions. Our experiments on the adapted open-source datasets demonstrated the effectiveness of this system. © 2024 IEEE.

关键词： Natural language processing systems

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OpenLS-DGF: An Adaptive Open-Source Dataset Generation Framework for Machine Learning Tasks in Logic Synthesis

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IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Ni, Liwei Wang, Rui Liu, Miao Meng, Xingyu Lin, Xiaoze Liu, Junfeng Luo, Guojie Chu, Zhufei Qian, Weikang Yang, Xiaoyan Xie, Biwei Li, Xingquan Li, Huawei Chinese Academy of Sciences State Key Lab of Processors Institute of Computing Technology Beijing100190 China Pengcheng Laboratory Shenzhen518055 China University of Chinese Academy of Sciences Beijing101408 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China University of Chinese Academy of Sciences School of Computer Science and Technology Beijing100049 China Peking University School of Computer Science Center for Energy-Efficient Computing and Applications Beijing100871 China Ninbo University Faculty of Electrical Engineering and Computer Science Ninbo315211 China Shanghai Jiao Tong University University of Michigan-Shanghai Jiao Tong University Joint Institute MoE Key Laboratory of Artificial Intelligence Shanghai200240 China Hangzhou Dianzi University School of Electronics and Information Engineering Hangzhou311121 China

This paper introduces OpenLS-DGF, an adaptive logic synthesis dataset generation framework, to enhance machine learning (ML) applications within the logic synthesis process. Previous dataset generation flows were tailored for specific tasks or lacked integrated ML capabilities. While OpenLS-DGF supports various machine learning tasks by encapsulating the three fundamental steps of logic synthesis: Boolean representation, logic optimization, and technology mapping. It preserves the original information in both Verilog and ML-friendly GraphML formats. The Verilog files offer semi-customizable capabilities, enabling researchers to insert additional steps and incrementally refine the generated dataset. Furthermore, OpenLS-DGF includes an adaptive circuit engine that facilitates the final dataset management and downstream tasks. The generated OpenLS-D-v1 dataset comprises 46 combinational designs from established benchmarks, totaling over 966,000 Boolean circuits. OpenLS-D-v1 supports integrating new data features, making it more versatile for new tasks. This paper demonstrates the versatility of OpenLS-D-v1 through four distinct downstream tasks: circuit classification, circuit ranking, quality of results (QoR) prediction, and probability prediction. Each task is chosen to represent essential steps of logic synthesis, and the experimental results show the generated dataset from OpenLSDGF achieves prominent diversity and applicability. The source code and datasets are available at https://***/Logic-Factory/ACE/blob/master/OpenLS-DGF. © 1982-2012 IEEE.

关键词： Information management

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Research on Measuring Method of Function Size of Information System 26

Research on Measuring Method of Function Size of Information...

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26th ACIS International Winter Conference on software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD-Winter 2023

作者： Chunye, Du Shanghai Development Center of Computer Software Technology Shanghai Key Laboratory of Computer Software Testing &evaluating Shanghai China

ISBN: (纸本)9798350345865

With the rapid development of software industry, a variety of new technologies are produced. Research and development in cloud computing, big data, artificial intelligence, the Internet of Things, blockchain, and other related fields continue to prosper. The increasing lines of code, function points, escalating scale of software systems, and the rising complexity of software development collectively complicate software cost estimation. This article studies how to estimate the size, workload, and cost of an information system using functional scale measurement methods. © 2023 IEEE.

关键词： Information systems

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A Novel Scene Coupling Semantic Mask Network for Remote Sensing Image Segmentation

arXiv

引用

arXiv 2025年

作者： Ma, Xiaowen Lian, Rongrong Wu, Zhenkai Guan, Renxiang Hong, Tingfeng Zhao, Mengjiao Ma, Mengting Nie, Jiangtao Du, Zhenhong Song, Siyang Zhang, Wei School of Software Technology Zhejiang University Hangzhou310027 China Noah's Ark Lab Huawei Shanghai201206 China School of Computer Science and Technology Zhejiang University Hangzhou310027 China School of Computer Science and Technology Northwestern Polytechnical University Xian710072 China School of Earth Sciences Zhejiang University Hangzhou310027 China School of Computer Science and Technology National University of Defense Technology Changsha410073 China School of Computing and Mathematical Sciences University of Leicester United Kingdom Innovation Center of Yangtze River Delta Zhejiang University Jiaxing314103 China

As a common method in the field of computer vision, spatial attention mechanism has been widely used in semantic segmentation of remote sensing images due to its outstanding long-range dependency modeling capability. However, remote sensing images are usually characterized by complex backgrounds and large intra-class variance that would degrade their analysis performance. While vanilla spatial attention mechanisms are based on dense affine operations, they tend to introduce a large amount of background contextual information and lack of consideration for intrinsic spatial correlation. To deal with such limitations, this paper proposes a novel scene-Coupling semantic mask network, which reconstructs the vanilla attention with scene coupling and local global semantic masks strategies. Specifically, scene coupling module decomposes scene information into global representations and object distributions, which are then embedded in the attention affinity processes. This Strategy effectively utilizes the intrinsic spatial correlation between features so that improve the process of attention modeling. Meanwhile, local global semantic masks module indirectly correlate pixels with the global semantic masks by using the local semantic mask as an intermediate sensory element, which reduces the background contextual interference and mitigates the effect of intra-class variance. By combining the above two strategies, we propose the model SCSM, which not only can efficiently segment various geospatial objects in complex scenarios, but also possesses inter-clean and elegant mathematical representations. Experimental results on four benchmark datasets demonstrate the the effectiveness of the above two strategies for improving the attention modeling of remote sensing images. For example, compared to the recent advanced method LOGCAN++, the proposed SCSM has 1.2%, 0.8%, 0.2%, and 1.9% improvements on the LoveDA, Vaihingen, Potsdam, and iSAID datasets, respectively. The dataset and cod

关键词： Semantic Segmentation

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Analysis for Microservice Architecture Application Quality Model and Testing Method 26

Analysis for Microservice Architecture Application Quality M...

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26th ACIS International Winter Conference on software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD-Winter 2023

作者： Gong, Jiayu Cai, Lizhi Shanghai Development Center of Computer Software Technology Shanghai Key Laboratory of Computer Software Testing & Evaluation Shanghai China

ISBN: (纸本)9798350345865

In recent years, microservice architectures have benefited from low coupling and high cohesion characteristics, allowing flexible on-demand deployment of complex applications and simplifying the difficulty of developing and maintaining large software systems. However, there is limited research on quality models and testing methods for microservice architectures, which leads to the problem that microservice architecture applications are difficult to test and evaluate. This paper analyzes the main problems when microservice architecture applications face quality measurement and software testing, further improves and refines the quality model of microservice architecture applications on the basis of the existing ISO software product quality model, and introduces testing methods for microservice architecture applications, which can provide reference for the construction of microservice architecture applications. © 2023 IEEE.

关键词： software testing

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Research on stream processing engine and benchmarking framework 19

Research on stream processing engine and benchmarking framew...

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19th IEEE International Conference on Networking, Sensing and Control, ICNSC 2022

作者： Le, Qionghua Chen, Mingang Chen, Wenjie Shanghai Development Center of Computer Software Technology Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai China

ISBN: (纸本)9781665472432

Stream computing engine is an important part of big data system, and benchmarking is one of the main means to measure the engine's performance. In this paper, we compare the differences between two engines, Spark Streaming and Flink, in stream processing technologies. Then the open source benchmarking frameworks supporting stream processing and their respective characteristics are studied, and the HiBench testing framework is selected to test the two stream processing engines. The test results show that Flink is better than Spark Streaming in terms of performance in shuffle, stateful computation and windowed computation. © 2022 IEEE.

关键词： Benchmarking

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