检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Bürchner, Tim Radtke, Lars Kopp, Philipp Computational Modeling and Simulation Technische Universität München Germany Institute for Ship Structural Design and Analysis Technische Universität Hamburg Germany Chair of Data Science in Civil Engineering Bauhaus-Universität Weimar Germany

Immersed boundary finite element methods allow the user to bypass the potentially troublesome task of boundary-conforming mesh generation. However, they suffer from the influence of cut elements, i.e., elements that are intersected by the physical domain boundaries. When combined with explicit time integration, poorly cut elements with little support in the physical domain have a detrimental effect on the critical time step size, thereby hampering the application of immersed boundary methods to wave propagation simulations. In this paper, we investigate the stabilizing effect of the finite cell method concerning explicit time integration. Starting with an analytical solution of an example with one degree of freedom, we systematically study the influence of α-stabilization on the maximum eigenvalue and thus on the critical time step size. The analysis is then complemented by a numerical study of an example with one element and an increasing polynomial degree. We demonstrate that the critical time step size does not decrease below a certain limit, even when further reducing the cut fraction of the element. This minimum critical time step size is controlled by the chosen α value and becomes less severe for higher dimensions. Increasing the polynomial degree has little effect on the degradation of the minimum critical time step size. Finally, we provide an estimate of the minimum critical time step size depending on the chosen stabilization parameter α and the dimension of the problem. Based on this estimate, we propose a modified CFL condition for the finite cell method, the validity of which we demonstrate on a numerical example of a perforated plate. © 2025, CC BY.

关键词： Boundary element method

来源：评论

学校读者我要写书评

暂无评论

Conceptual Development of a Probabilistic Graphical Framework for Assessing Port Resilience 23rd

Conceptual Development of a Probabilistic Graphical Framewor...

引用

23rd International Conference on Harbor, Maritime and Multimodal Logistics Modelling and simulation, HMS 2021

作者： Smith, Katherine Diaz, Rafael Shen, Yuzhong Longo, Francesco Virginia Modeling Analysis & Simulation Center Old Dominion University 1030 University Blvd SuffolkVA23435 United States Department of Computational Modeling and Simulation Engineering Old Dominion University 1300 Engineering & Computational Sciences Building NorfolkVA23529 United States Mechanical Department University of Calabria Via Pietro Bucci Arcavacata CS Rende87036 Italy

ISBN: (纸本)9788885741591

Technological advances such as cyber physical systems and autonomous vehicles combined with increased disruptions including the Covid-19 pandemic and coastal natural disasters have heightened the importance of port risk analysis methodologies and frameworks that can accurately quantify and optimize resilience. This work presents the conceptual development of a novel combination of analysis methodologies linking a probabilistic graphic approach on a network of risk events with a functional dependency approach on a system network. Key advantages of these two methodologies are the ability to model and learn causal interactions rather than simply correlations and a high level of computational efficiency. This combination of robustness and flexibility offers the ability to quickly analyze multiple port configurations in order to invest in efforts that maximize the resilience-cost ratio. In addition, the methodology opens the door for real-time anomaly detection and causal analysis in order to enhance efforts in the protecting against attacks on infrastructure and in particular cyber physical systems. © 2021 The Authors.

关键词： Cyber Physical System

来源：评论

学校读者我要写书评

暂无评论

Combined Deep Learning and Classical Potential Approach for modeling Diffusion in UiO-66

Combined Deep Learning and Classical Potential Approach for ...

引用

2023 AIChE Annual Meeting

作者： Achar, Siddarth K. Wardzala, Jacob J. Bernasconi, Leonardo Zhang, Linfeng Johnson, J. Karl Department of Chemical & Petroleum Engineering University of Pittsburgh PittsburghPA15261 United States Computational Modeling & Simulation Program University of Pittsburgh PittsburghPA15260 United States Center for Research Computing Department of Chemistry University of Pittsburgh PittsburghPA15260 United States DP Technology Beijing100080 China AI for Science Institute Beijing100080 China

modeling of diffusion of adsorbates through porous materials with atomistic molecular dynamics (MD) can be a challenging task if the flexibility of the adsorbent needs to be included. This is because potentials need to be developed that accurately account for the motion of the adsorbent in response to the presence of adsorbate molecules. In this work, we show that it is possible to use accurate machine learning atomistic potentials for metal−organic frameworks in concert with classical potentials for adsorbates to accurately compute diffusivities though a hybrid potential approach. As a proof-of-concept, we have developed an accurate deep learning potential (DP) for UiO-66, a metal− organic framework, and used this DP to perform hybrid potential simulations, modeling diffusion of neon and xenon through the crystal. The adsorbate−adsorbate interactions were modeled with Lennard−Jones (LJ) potentials, the adsorbent−adsorbent interactions were described by the DP, and the adsorbent−adsorbate interactions used LJ cross-interactions. Thus, our hybrid potential allows for adsorbent−adsorbate interactions with classical potentials but models the response of the adsorbent to the presence of the adsorbate through near-DFT accuracy DPs. This hybrid approach does not require refitting the DP for new adsorbates. We calculated self-diffusion coefficients for Ne in UiO-66 from DFT-MD, our hybrid DP/LJ approach, and from two different classical potentials for UiO-66. Our DP/LJ results are in excellent agreement with DFT-MD. We modeled diffusion of Xe in UiO-66 with DP/LJ and a classical potential. Diffusion of Xe in UiO-66 is about a factor of 30 slower than that of Ne, so it is not computationally feasible to compute Xe diffusion with DFT-MD. Our hybrid DP−classical potential approach can be applied to other MOFs and other adsorbates, making it possible to use an accurate DP generated from DFT simulations of an empty adsorbent in concert with existing classical potentials for ads

关键词： Molecular dynamics

来源：评论

学校读者我要写书评

暂无评论

Matrix Stiffness Regulates Mechanotransduction and Vascular Network Formation of Hipsc-Derived Endothelial Progenitors Encapsulated in 3d Hydrogels

SSRN

引用

SSRN 2025年

作者： Han, Jiwan Halwachs, Kathleen West, Toni Larsen, Bryce Sacks, Michael S. Rosales, Adrianne M. Zoldan, Janet Department of Biomedical Engineering The University of Texas at Austin AustinTX United States Department of Chemical Engineering The University of Texas at Austin AustinTX United States James T. Willerson Center for Cardiovascular Modeling and Simulation The Oden Institute for Computational Engineering and Sciences AustinTX United States

The mechanical properties of the extracellular matrix (ECM), particularly stiffness, regulate endothelial progenitor responses during vascular development, yet their behavior in physiologically compliant matrices (10 kPa), our results emphasize that vascularization is not solely driven by the most mechanotransductive environment but rather by a balance of compliance, contractility, and cell-induced remodeling. These findings underscore the need to design hydrogels that provide sufficient mechanotransduction for endothelial maturation while maintaining compliance to support dynamic vascular morphogenesis. This work provides a mechanically tuned framework for optimizing microenvironments to balance endothelial differentiation and vascular network formation in tissue engineering and regenerative medicine. © 2025, The Authors. All rights reserved.

关键词： Endothelial cells

来源：评论

学校读者我要写书评

暂无评论

Cyber Deception Metrics For Interconnected Complex Systems

Cyber Deception Metrics For Interconnected Complex Systems

引用

simulation Winter Conference

作者： Md Ali Reza Al Amin Sachin Shetty Charles Kamhoua Computational Modeling and Simulation Engineering Old Dominion University Norfolk VA USA US Army Research Laboratory Adelphi MD USA

ISBN: (纸本)9781665476621

Cyber attackers' evolving skills cause it challenging to secure the network. Thus it is paramount to characterize adversarial strategies and estimate the attacker's capability. Furthermore, estimating the adversarial capability can aid the cyber defender when deciding to place deceptive elements in the network. In this paper, we address the problem of characterizing adversarial strategies and develop a suite of metrics that quantify the opportunity and capability of the adversary. Using these metrics, the cyber defender can estimate the attacker's capability. In our simulation, we incorporated the developed metrics to estimate adversary capabilities based on the attacker's aggression, knowledge, and stealthiness level. To minimize the adversarial impact, we consider placing decoy nodes as deceptive elements in the network and measure the effectiveness of having decoy nodes. Our experimental evaluation suggests that placing decoy nodes in the network can effectively increase the attacker's resource usage and decrease the win percentage.

关键词： Measurement Bayes methods Complex systems

来源：评论

学校读者我要写书评

暂无评论

High-Speed simulation of the 3D Behavior of Myocardium Using a Neural Network PDE Approach 11th

High-Speed Simulation of the 3D Behavior of Myocardium Using...

引用

11th International Conference on Functional Imaging and modeling of the Heart, FIMH 2021

作者： Zhang, Wenbo Li, David S. Bui-Thanh, Tan Sacks, Michael S. Willerson Center for Cardiovascular Modeling and Simulation Oden Institute for Computational Engineering and Sciences Department of Biomedical Engineering University of Texas at Austin AustinTX78712 United States Oden Institute for Computational Engineering and Sciences Department of Aerospace Engineering and Engineering Mechanics University of Texas at Austin AustinTX78712 United States

ISBN: (纸本)9783030787097

The full characterization of three-dimensional (3D) mechanical behaviour of myocardium is essential in understanding their function in health and disease. The hierarchical structure of myocardium results in their highly anisotropic mechanical behaviors, with the spatial variations in fiber structure giving rise to heterogeneity. The optimal set of loading paths has been used to estimate the constitutive parameters of myocardium using a novel numerical-experimental approach with full 3D kinematically controlled (triaxial) experiments [1, 2]. Due to the natural variations in soft tissue structures, the mechanical behaviors of myocardium can vary dramatically within the same organ. To alleviate the associated computational costs for obtaining responses of myocardium under a range of loading conditions with a given realization of structure, we developed a neural network-based method integrated with finite elements. The boundary conditions were parameterized. The neural network generated a corresponding trial solution of the underling hyperelasticity problem for each boundary condition. Thus, the neural network approximated the parameter-to-state map. A physics-informed approach was used to train the neural network. Due to their learnability characteristics, the neural network was able to predict solutions for a range of boundary conditions with given individual specimen fiber structures. The neural network was validated with finite element solutions. This method will provide efficient and robust computational models for clinical evaluation to improve patient outcomes. © 2021, Springer Nature Switzerland AG.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Optical Imaging for Monitoring Pectus Excavatum Therapy

Optical Imaging for Monitoring Pectus Excavatum Therapy

引用

2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Kidane, Nahom Shen, Yuzhong Kelly, Robert E. Old Dominion University Department of Computational Modeling and Simulation Engineering Norfolk United States Children's Hospital of the King's Daughters and Eastern Virginia Medical School Norfolk United States

ISBN: (纸本)9781665401265

Pectus Excavatum (PE) is congenital chest wall deformity of unknown etiology that become more pronounced during early adolescence. PE is often accompanied by other problems such as fatigue, breathing issues, and even scoliosis. Severity is evaluated by calculating radiographically derived indices on cross-sectional imaging utilizing computed tomography (CT). For surgical and non-surgical treatments, monitoring improvements in the patient's chest shape is challenging. Tracking improvements with radiographically derived indices would be cost-prohibitive and unsafe. Therefore, we developed a non-invasive and objective method for measuring and visualizing the change in chest shape over time utilizing an inexpensive Microsoft Kinect camera. We have used this external surface scan Pectus Metric system for several months and recently posited alternative severity indices called the external Haller index (XHI) and external correction index (XCI) using these scans. We believe these new indexes will replace the gold standard, CT scan derived, Haller Index, without subjecting patients to ionizing radiation. This work outlines the non-invasive external indices calculation and discusses the clinical validity of the indices. © 2021 IEEE.

关键词： Ionizing radiation

来源：评论

学校读者我要写书评

暂无评论

A computational Pipeline for Patient-Specific Prediction of the Post-operative Mitral Valve Functional State 12th

A Computational Pipeline for Patient-Specific Prediction of...

引用

Functional Imaging and modeling of the Heart - 12th International Conference, FIMH 2023, Proceedings

作者： Liu, Hao Simonian, Natalie T. Pouch, Alison M. Gorman, III, Joseph H. Gorman, Robert C. Sacks, Michael S. James T. Willerson Center for Cardiovascular Modeling and Simulation The Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering The University of Texas at Austin AustinTX78712 United States Departments of Radiology and Bioengineering University of Pennsylvania PhiladelphiaPA19104 United States Gorman Cardiovascular Research Group Department of Surgery Smilow Center for Translational Research Perelman School of Medicine University of Pennsylvania PhiladelphiaPA19104 United States

ISBN: (纸本)9783031353017

Mitral valve (MV) repair is safer than replacement for mitral regurgitation (MR) treatment, but long-term outcomes remain suboptimal and poorly understood. Moreover, preoperative optimization is complicated due to the heterogeneity of MR presentations and potential repair configurations. We thus developed a patient-specific MV computational pipeline to quantitatively predict the post-repair MV functional state using standard-of-care preoperative imaging data alone. First, we built a finite-element model of the full patient-specific MV apparatus by quantifying the MV chordae tendinae (MVCT) distributions from 5 CT-imaged excised human hearts and incorporating this data with patient-specific MV leaflet geometries and and MVCT origin displacements from preoperative 3D echocardiography. We then calibrated the leaflet and MVCT pre-strains by simulating preoperative MV closure in order to tune the functionally equivalent, patient-specific mechanical behavior. With this fully calibrated MV model, we simulated undersized ring annuloplasty (URA) by modifying the annular displacement to match the applied ring size. In all patient cases, the postoperative geometries were predicted to within 1 mm of the target, and the MV leaflet strain fields demonstrated very good global and local correspondence to results from a previous heavily validated pipeline. Additionally, our model predicted increased postoperative posterior leaflet tethering in a recurrent patient, which is the likely driver of long-term MV repair failure. This pipeline allows us to predict postoperative outcomes using strictly preoperative clinical data, which lays the foundation for quantitative surgical planning, personalized patient selection, and ultimately, more durable MV repairs. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Echocardiography

来源：评论

学校读者我要写书评

暂无评论

AKM-FCCI: Secure Authentication and Key Management Mechanism for Fog Computing-Based IoT-Driven Critical Infrastructure

AKM-FCCI: Secure Authentication and Key Management Mechanism...

引用

International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Vijay Karnatak Neha Tripathi Amit Kumar Mishra Mohammad Wazid Ashok Kumar Das Mohsen Guizani Sachin Shetty Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Department of Computer Science and Engineering Graphic Era Hill University Dehradun India Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad India Machine Learning Department Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) Abu Dhabi UAE Department of Computational Modeling and Simulation Engineering Virginia Modeling Analysis and Simulation Center Old Dominion University Suffolk VA USA

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Critical infrastructure refers to the key systems, assets, and facilities, whether they are physical or virtual, that are necessary for the overall functioning of a country. As our reliance on technology and networked systems continues to expand, so does the significance of taking precautions to protect critical infrastructure from being compromised by cyberattacks. We need some security schemes to secure the communication happening in the critical infrastructure devices. Therefore, in this paper, we focus on the design of an authentication and key establishment scheme, which is used in the critical infrastructure to secure its data transmissions. A secure authentication and key management mechanism for fog computing-based IoT-driven critical infrastructures (in short, AKM-FCCI) is proposed in the paper. We then provide the network model and threat model of the proposed AKM-FCCI to explain its deployment and organization of devices and servers. The threat model further explains the various threats of this communication environment. In addition, the security analysis of AKM-FCCI is presented to demonstrate that it is secure against the many different kinds of attacks that could be launched against it. The comparisons demonstrate that the performance of AKM-FCCI is superior to that of the other currently used schemes. In addition to that, it offers a high level of security and utility. Therefore, the proposed AKM-FCCI is appropriate for use in protecting critical infrastructure equipment against a wide variety of threats.

关键词： Threat modeling Wireless communication Performance evaluation Authentication Organizations Critical infrastructure Safety

来源：评论

学校读者我要写书评

暂无评论

EM-PAD: An Effective Mechanism for Phishing Attack Detection

EM-PAD: An Effective Mechanism for Phishing Attack Detection

引用

International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Aakash Saksham Mittal Mohammad Wazid Amit Kumar Mishra Ashok Kumar Das Sachin Shetty Mohsen Guizani Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Department of Computer Science and Engineering Graphic Era Hill University Dehradun India Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad India Department of Computational Modeling and Simulation Engineering Virginia Modeling Analysis and Simulation Center Old Dominion University Suffolk VA USA Machine Learning Department Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) Abu Dhabi UAE

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

In the present era, the increasing number of network devices and ubiquitous computing leads to the flow of enormous amounts of data traffic, including sensitive and confidential information, on the internet and carrying out commercial and banking transactions online. This gives cybercriminals an opportunity to launch an attack like phishing to steal confidential information from the user and gain unauthorized access. This can be mitigated by the help of an intelligent machine learning-based phishing detection system, which can detect potential phishing attacks and take appropriate action. In this paper, we have addressed this major cyber issue and proposed a machine learning-based phishing detection scheme (in short, EM-PAD), which is trained on a benchmark dataset and evaluated on standard metrics: F1-score and Accuracy. The proposed model is compared with different existing schemes based on Accuracy, indicating that it has outperformed them with remarkable results.

关键词： Wireless communication Measurement Accuracy Phishing computational modeling Banking Benchmark testing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：