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检索条件"任意字段=International Conference on Computer Modeling and Simulation"

共 35215 条记录，以下是211-220 订阅

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Multiphysics Blast simulation for 3D UAV Control Applications

Multiphysics Blast Simulation for 3D UAV Control Application...

引用

international conference on Unmanned Aircraft Systems (ICUAS)

作者： Surabhi Parab Jincheng Zhang Andrew Willis Electrical and Computer Engineering University of North Carolina at Charlotte Charlotte NC USA

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

This paper presents a novel simulation framework designed for high-fidelity multi-physics simulation of shock waves due to blast phenomena. The framework includes simulation of the physical pressure wave and the acoustic and visual phenomena associated with the blast event using the Gazebo environment. The framework integrates advanced technologies, including the Robot Operating System (ROS), QGroundControl, and PX4 Software-In-The-Loop (SITL), to synchronize visual, acoustic, and dynamic pressure data, ensuring realistic and efficient simulations. A key innovation in this framework is the use of a client-server architecture, which enables realtime adjustments and precise multimedia data synchronization, effectively minimizing latency and improving overall simulation quality and allowing multi-vehicle simulations in a single virtual scene. The specialized plugins employed for rendering and acoustic modeling capture the intricate dynamics of explosions, enhancing the realism of visual and auditory representations. Creation of this technology allows development of control algorithms that improve autonomous vehicle control algorithms in the presence of extreme perturbations with impacts in autonomous vehicle safety and defense sectors. The proposed framework offers a robust solution for interactive simulations, demonstrating significant advancements in both the fidelity and applicability of blast effect modeling.

关键词： Training Visualization Three-dimensional displays Heuristic algorithms Autonomous aerial vehicles Acoustics Real-time systems Safety Synchronization Vehicle dynamics

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Research on Characteristics simulation Method in Blanket Pebble Beds Based on Percolation Theory

Research on Characteristics Simulation Method in Blanket Peb...

引用

Smart Grid and Artificial Intelligence (SGAI), international conference on

作者： Ziyang Wang Yuntao Song Mingzhun Lei Jian Wang University of Science and Technology of China Institute of Plasma Physics Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China Institute of Plasma Physics Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China

ISBN: (数字)9798331518806

ISBN: (纸本)9798331518813

The solid tritium breeder blanket is one of the most promising candidates for fusion reactor blankets. However, the simulation of processes such as pebble bed filling and purging is computationally intensive due to the millions of pebbles contained within a single blanket module. Given the structural and physical similarities between pebble beds and porous media, this study develops a simulation program based on percolation theory to characterize the filling and purging behaviors of blanket pebble beds. A percolation network model was constructed through computer programming to simulate fluid flow within the pebble bed, enabling the calculation of pressure drop and velocity distribution under various operating conditions. The simulation results were compared with experimental data, showing excellent agreement and validating the accuracy and reliability of the percolation network model. The results demonstrate that the model based on percolation theory significantly improves computational efficiency while maintaining high accuracy, thereby reducing computational resource requirements. This approach provides a robust theoretical framework and technical support for the rapid modeling and efficient simulation of blanket pebble beds.

关键词： Analytical models Accuracy Computational modeling Fluid flow Fusion reactors Solids Filling Data models Numerical models Computational efficiency

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XGSybil :A Framework for modeling and Identifying Sybil Attacks in Intelligent Transportation Systems

XGSybil :A Framework for Modeling and Identifying Sybil Atta...

引用

IEEE Students' conference on Electrical, Electronics and computer Science (SCEECS)

作者： Hemanth S Patel Mohd Faizan Khan Aysha Rahbar Nagasundari S N.P. Yashwanth PES University Bangalore India

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

With the increasing adoption of autonomous vehicles, ensuring the security of Vehicular Ad-Hoc Networks (VANETs) is critical to maintaining road safety and efficiency. Among the potential threats, Sybil attacks pose a significant challenge by enabling malicious vehicles to illegitimately assume multiple identities, disrupting communication and causing traffic mismanagement. This paper addresses the simulation and detection of Sybil attacks in Intelligent Transportation systems using a combination of network simulation and machine learning. Realistic traffic environments are replicated using tools such as OpenStreetMap, SUMO, and OMNeT++, and attack scenarios are simulated to generate datasets. A machine learning model, trained on these datasets, detects Sybil attacks by analyzing vehicle acceleration and behavioral patterns. The proposed approach successfully identifies malicious nodes, invalidates fraudulent messages, and mitigates their impact, thereby enhancing the security and reliability of autonomous vehicle networks. This study provides a robust framework for Sybil attack detection and contributes to the broader field of secure intelligent transportation systems.

关键词： Analytical models Protocols Computational modeling computer network reliability Vehicular ad hoc networks Real-time systems Security Reliability Autonomous vehicles Edge computing

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PI-Type Sliding Mode Fractional-Order Synchronization of a Memristive Chua Circuit

PI-Type Sliding Mode Fractional-Order Synchronization of a M...

引用

Control, Automation, and Instrumentation (IC2AI), international conference on

作者： Dorukhan Astekin Fatih Adigüzel Control and Automation Engineering Yildiz Technical University Istanbul Turkey

ISBN: (数字)9798331529604

ISBN: (纸本)9798331529611

In this study, a sliding mode fractional-order synchronization is proposed for the memristive chaotic Chua system. After the integer-order model of the chaotic memristive Chua system is given, a PI-type sliding surface-based controller structure combined with the fractional derivative operator is devised. The stability analysis of the synchronization closed-loop system is proven in the sense of Lyapunov theory. To demonstrate the effectiveness and applicability of the proposed controller structure, the fractional-order derivative operator in the controller structure is considered with two different fractional orders, and computer-based numerical simulation studies are performed comparatively.

关键词： Uncertainty Sensitivity System dynamics simulation Main-secondary Stability analysis Robustness Synchronization Closed loop systems Integrated circuit modeling

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ARMS: Activity-Resource Modelling Simulator 16th

ARMS: Activity-Resource Modelling Simulator

引用

16th EAI international conference on simulation Tools and Techniques, SIMUTools 2024

作者： Di Iorio, Angelo Ferrati, Marco Rossi, Davide Department of Computer Science and Engineering University of Bologna Bologna Italy

ISBN: (纸本)9783031873447

Activity-based process modeling languages, such as Business Process Model and Notation (BPMN), face challenges in accurately representing manufacturing processes, limiting their effectiveness for simulation purposes. In contrast, specialized manufacturing process simulation tools typically adopt a resource-based approach which, while effective in certain aspects, often lacks robust process modeling capabilities and requires custom coding to define detailed system behaviors. Although prior research has explored extending BPMN to better support manufacturing scenarios, there is still a lack of tools that integrate both activity-centric and resource-centric approaches for comprehensive modeling and simulation. In this work, we address this gap by proposing a novel metamodel that extends BPMN with enhanced resource capabilities. We present a process modeler that allows users to design manufacturing processes and a corresponding simulator that uses these models to generate insightful information about the process performance through simulation. The solution proposed is then validated using both made-up and real-world manufacturing scenarios. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Forming

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TERA: A simulation Environment for Terrain Excavation Robot Autonomy

TERA: A Simulation Environment for Terrain Excavation Robot ...

引用

IEEE international conference on simulation, modeling, and Programming for Autonomous Robots (SIMPAR)

作者： Christo Aluckal Roopesh Vinodh Kumar Lal Sean Courtney Yash Turkar Yashom Dighe Youngjin Kim Jake Gemerek Karthik Dantu Computer Science and Engineering University at Buffalo Buffalo NY Moog Constructions Moog Inc. Buffalo NY

ISBN: (数字)9798331516857

ISBN: (纸本)9798331516864

Developing excavation autonomy is challenging given the environments where excavators operate, the complexity of physical interaction and the degrees of freedom of operation of the excavator itself. simulation is a useful tool to build parts of the autonomy without the complexity of experimentation. Traditional excavator simulators are geared towards high fidelity interactions between the joints or between the terrain but do not incorporate other challenges such as perception required for end-end autonomy. A complete simulator should be capable of supporting real-time operation while providing high fidelity simulation of the excavator(s), the environment, and their interaction. In this paper we present TERA (Terrain Excavation Robot Autonomy), a simulator geared towards autonomous excavator applications based on Unity3D/AGX that provides the extensibility and scalability required to study full autonomy. It provides the ability to configure the excavator and the environment per the user requirements. We also demonstrate realistic dynamics by incorporating a time-varying model that introduces variations in the system’s responses. The simulator is then evaluated with different scenarios such as track deformation, velocities on different terrains, similarity of the system with the real excavator and the overall path error to show the capabilities of the simulation. TERA source will be available at https://***/tera on publication.

关键词： Deformation Scalability Programming Excavation Real-time systems Extensibility Complexity theory Time-varying systems Autonomous robots

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Enhancing the Autonomy of Soft Robots in Minimally Invasive Surgeries Through computer Vision 2

Enhancing the Autonomy of Soft Robots in Minimally Invasive ...

引用

2nd international conference on Advanced Innovations in Smart Cities, ICAISC 2025

作者： Alsirhani, Hams M Elhag, Salma King Abdulaziz and His Companions Foundation for Giftedness and Creativity 'Mawhiba' Riyadh Saudi Arabia King Abdul-Aziz University Department of Information Systems Jeddah Saudi Arabia

ISBN: (纸本)9798331506995

Researchers have recognized the potential of employing soft robots in minimally invasive surgeries (MIS), which could significantly reduce the side effects associated with traditional surgical methods and enhance patient outcomes. However, the extent to which this potential is realized depends on the level of autonomy achieved by the soft robots. Lower levels of autonomy necessitate increased hands-on involvement during MIS, potentially compromising the robots' ability to perform procedures with consistent accuracy. Consequently, achieving high levels of accuracy in the autonomy of soft robots remains a significant challenge. The autonomy of these robots is influenced by various factors, including their capacity to accurately classify their surroundings, particularly anatomical structures, which is crucial for effective decision-making. To address the challenge posed by our research question, How can the application of Deep Neural Networks (DNNs) and Deep Reinforcement Learning (DRL) improve the autonomy of soft robots in performing complex tasks in MIS, particularly in the precise classification of anatomical structures and decision making?, we conducted an in-depth literature review and investigation into the integration of DNNs and DRL within this context. Our study used a modeling and simulation methodology to evaluate and quantify the benefits of incorporating these advanced AI techniques. Through this approach, we measured the effects of DNNs and DRL on enhancing the autonomy of soft robots, particularly in their ability to perform complex tasks in MIS with improved precision and decision-making capabilities. This work represents a step toward optimizing robotic autonomy in surgical environments, potentially leading to more efficient and accurate outcomes in minimally invasive procedures. © 2025 IEEE.

关键词： Robotic surgery

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Improving Cloud Energy Efficiency through Machine Learning Models 33

Improving Cloud Energy Efficiency through Machine Learning M...

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33rd Euromicro international conference on Parallel, Distributed, and Network-Based Processing, PDP 2025

作者： Cesario, Eugenio Lindia, Paolo Lobello, Federica Vinci, Andrea Zarin, Shabnam Capalbo, Santina University of Calabria DICES Department Rende Italy University of Calabria DIMES Department Rende Italy CNRNational Research Council of Italy Rende Italy Monmouth University Computer Science Department West Long BranchNJ United States

ISBN: (纸本)9798331524937

The rapid growth of Cloud Computing and the expansion of large data centers have led to significant increases in energy consumption for hardware and cooling systems. This surge in power usage has raised operational costs, making energy efficiency a pressing issue for data center management. Virtual Machines (VMs) consolidation is a widely studied strategy to mitigate these costs by minimizing the number of active physical servers while maintaining user Service Level Agreements (SLAs). However, the success of consolidation largely depends on accurately forecasting VM resource needs. This paper presents the design and development of an energy-aware VMs allocation system that leverages predictive machine learning models to forecast future computational demands (CPU) of each VM. By anticipating these needs, the system optimally allocates VMs to available servers, effectively balancing energy savings with performance. A preliminary experimental evaluation, conducted on synthetic data, leverages predictive modeling within a server simulation to assess CPU and energy usage, demonstrating the effectiveness of energy-aware VMs allocation in optimizing resource utilization and reducing energy consumption. © 2025 IEEE.

关键词： Energy efficiency

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Rack Sensor Metrics Odyssey: Analyzing Sensor Behavior with Random Forest and kNN for Strategic Job Allocation Insights

Rack Sensor Metrics Odyssey: Analyzing Sensor Behavior with ...

引用

IEEE Students' conference on Electrical, Electronics and computer Science (SCEECS)

作者： Angelina George B. M. Beena Department of Computer Science & Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

Data centers are vital to modern computing but contribute significantly to carbon emissions due to their high energy consumption. To address this, machine learning models can optimize resource allocation by analyzing sensor metrics. In this study, the Random Forest Regressor was chosen for its ability to capture sensor behavior, even showing negative R 2 values, aligning with observed patterns. Meanwhile, k-Nearest Neighbors (kNN) emerged as the best model for learning from the same data, despite irregularities, with R 2 values ranging between 0.6 and 1. This analysis supports sustainable data center management by enhancing energy efficiency and minimizing environmental impact. Future work will explore the integration of these models into simulation environments.

关键词： Data centers Analytical models Biological system modeling Computational modeling Nearest neighbor methods Green computing Data models Resource management Sustainable development Random forests

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simulation Exploration Experience (SEE) Introductory Tutorial 24

Simulation Exploration Experience (SEE) Introductory Tutoria...

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Proceedings of the Winter simulation conference

作者： Maziar Ghorbani Anastasia Anagnostou Nura T. Abubakar Hridyanshu Aatreya Damon Curry Simon J. E. Taylor Modelling & Simulation Group Dept. of Computer Science Brunel University London Uxbridge UK Pitch Technologies US Orlando FL USA

ISBN: (纸本)9798331534202

This paper presents an introductory tutorial based on the simulation Exploration Experience (SEE) 2024, highlighting a collaborative effort by NASA, SISO and international academic partners to model lunar facilities and habitats through the High-Level Architecture (HLA) for distributed simulations. Focused on federating simulations of lunar infrastructure, this paper outlines methodical steps for creating and executing models that incorporate communication systems and 3D visualizations to support educational and research initiatives in space exploration. Reflecting on SEE 2024's advancements, the tutorial emphasizes significant progress in using simulation technology to promote innovation and collaboration across various scientific disciplines. This contribution, intended for discussion at the Winter simulation conference (WSC) 2024, showcases the role of HLA runtime infrastructure (RTI) in enabling realistic and interoperable simulation environments, enriching the discourse on simulation education.

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