A Co-Simulation Environment for Virtual Prototyping of Ground Vehicles

2007 ◽  
Author(s):  
Makarand Datar ◽  
Michael Tercha ◽  
Charles Pergantis ◽  
Ali Manesh ◽  
Dan Negrut
Keyword(s):  
Virtual Prototyping ◽  
Extreme Environments ◽  
Third Party ◽  
Design Stage ◽  
Ground Vehicles ◽  
Vehicle Performance ◽  
Vehicle Simulation ◽  
Simulation Techniques ◽  
Heterogeneous Models ◽  
And Control

The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project is to promote the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance. To this end we concentrate our attention on two main aspects: (1) development of a family of tire and contact models suitable for simulations ranging from high accuracy to real time for on/off-road conditions and extreme environments, and (2) investigation of co-simulation techniques suitable from a numerical standpoint to support long simulations of heterogeneous models that contain vehicle, tire, terrain, powertrain, and controls subsystems.

Vehicle-Terrain Interaction Simulation With Parallelized Multiscale Moving Soil Patch Model

2019 ◽  
Author(s):  
Hiroki Yamashita ◽  
Guanchu Chen ◽  
Yeefeng Ruan ◽  
Paramsothy Jayakumar ◽  
Hiroyuki Sugiyama
Keyword(s):  
Interaction Model ◽  
Simulation Models ◽  
Vehicle Performance ◽  
Vehicle Simulation ◽  
Full Vehicle ◽  
Simulation Techniques ◽  
Patch Technique ◽  
Dynamics Models ◽  
Hierarchical Multiscale ◽  
Soil Patch

Abstract Although many physics-based off-road mobility simulation models are proposed and utilized for vehicle performance evaluation as well as for understanding of tire-soil interaction problems, full vehicle simulation on deformable terrain requires addressing the computational complexity associated with the large dimensional physics-based terrain dynamics models for practical use. This paper, therefore, presents a hierarchical multiscale tire-soil interaction model that is fully integrated into parallelized off-road mobility simulation framework. In particular, a co-simulation procedure is developed for full vehicle simulation with multiscale terrain dynamics models by exploiting the moving soil patch technique. To this end, a detailed off-road vehicle simulation model is divided into five subsystems: a multibody vehicle subsystem and four tire-soil subsystems composed of nonlinear FE tires and multiscale moving soil patches. The tire-soil subsystems are interfaced with the vehicle subsystem by MPI through force-displacement coupling. It is demonstrated that the proposed framework allows for alleviating computational intensity of a full vehicle simulation that involves complex hierarchical multiscale terrain dynamics models by effectively distributing computational loads with co-simulation techniques.

Sequentially Utility Maximizing Path Planning Using a Distributed Pool Architecture

2021 ◽  
Author(s):  
Calahan Mollan ◽  
Vijitashwa Pandey ◽  
Christopher Slon ◽  
David Gorsich
Keyword(s):  
Path Planning ◽  
Computational Effort ◽  
Ground Vehicles ◽  
Vehicle Performance ◽  
Vehicle Simulation ◽  
Communication Links ◽  
Geographically Distributed ◽  
Speed Up ◽  
Terrain Parameters ◽  
And Storage

Abstract Operation of ground vehicles in remote unstructured terrains is a challenging task. While information on terrain parameters such as elevation, slope, and soil content and its use in tasks such as path planning and vehicle simulation is immensely useful, it requires detailed analyses that are computationally expensive and time-consuming. At the same time, higher-level decisions made without a full understanding of the terrain properties and vehicle capabilities are bound to be suboptimal, possibly even leading to mission failure. In this paper, we approach the problem from a decision-making standpoint to address both the aspects described above. The approach divides a given terrain into smaller cells and progressively finds the path to the goal. At each step, the operator’s utility between competing immediate terrain cells is compared so that the vehicle chooses the best next step considering detailed vehicle simulation. To account for the increased computational effort, a pool-based distributed computing architecture is employed to speed-up pathfinding and provide resilience towards failure of processors and communication links. The pool architecture also admits heterogeneous, geographically distributed processors and storage locations. Concurrently, the multiattribute utility formulation takes into account the tradeoff between different attributes and the uncertainty in the vehicle performance. The proposed method can be used for medium and long-range navigation in unstructured environments for efficient rough path planning or re-planning based on changing mission requirements and dynamically arriving terrain data. The method is demonstrated on data acquired from USGS sources.

Modeling and Control of Hybrid Propulsion System for Ground Vehicles

2018 ◽  
Author(s):  
Yuan Zou ◽  
Junqiu Li ◽  
Xiaosong Hu ◽  
Yann Chamaillard
Keyword(s):  
Propulsion System ◽  
Ground Vehicles ◽  
Hybrid Propulsion ◽  
Modeling And Control ◽  
And Control

Assessment and Prediction of Privacy Concerns on Health Apps (Preprint)

2020 ◽  
Author(s):  
Reham AlTamime ◽  
Vincent Marmion ◽  
Wendy Hall
Keyword(s):  
Data Sharing ◽  
Mobile Applications ◽  
Retention Rate ◽  
Mobile Apps ◽  
Third Party ◽  
Privacy Concerns ◽  
Health Apps ◽  
Mobile Health Apps ◽  
Specific Factors ◽  
And Control

BACKGROUND Mobile apps and IoT-enabled smartphones technologies facilitate collecting, sharing, and inferring from a vast amount of data about individuals’ location, health conditions, mobility status, and other factors. The use of such technology highlights the importance of understanding individuals’ privacy concerns to design applications that integrate their privacy expectations and requirements. OBJECTIVE This paper explores, assesses, and predicts individuals’ privacy concerns in relation to collecting and disclosing data on mobile health apps. METHODS We designed a questionnaire to identify participants’ privacy concerns pertaining to a set of 432 mobile apps’ data collection and sharing scenarios. Participants were presented with 27 scenarios that varied across three categorical factors: (1) type of data collected (e.g. health, demographic, behavioral, and location); (2) data sharing (e.g., whether it is shared, and for what purpose); and, (3) retention rate (e.g., forever, until the purpose is satisfied, unspecified, week, or year). RESULTS Our findings show that type of data, data sharing, and retention rate are all factors that affect individuals’ privacy concerns. However, specific factors such as collecting and disclosing health data to a third-party tracker play a larger role than other factors in triggering privacy concerns. CONCLUSIONS Our findings suggest that it is possible to predict privacy concerns based on these three factors. We propose design approaches that can improve users’ awareness and control of their data on mobile applications

scholarly journals Multi-Blockchain-Based IoT Data Processing Techniques to Ensure the Integrity of IoT Data in AIoT Edge Computing Environments

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3515
Author(s):  
Sung-Ho Sim ◽  
Yoon-Su Jeong
Keyword(s):  
Low Cost ◽  
Third Party ◽  
Monitoring And Control ◽  
Constant Size ◽  
Computing Environments ◽  
Iot Devices ◽  
Cloud Servers ◽  
The Cost ◽  
Processing Techniques ◽  
And Control

As the development of IoT technologies has progressed rapidly recently, most IoT data are focused on monitoring and control to process IoT data, but the cost of collecting and linking various IoT data increases, requiring the ability to proactively integrate and analyze collected IoT data so that cloud servers (data centers) can process smartly. In this paper, we propose a blockchain-based IoT big data integrity verification technique to ensure the safety of the Third Party Auditor (TPA), which has a role in auditing the integrity of AIoT data. The proposed technique aims to minimize IoT information loss by multiple blockchain groupings of information and signature keys from IoT devices. The proposed technique allows IoT information to be effectively guaranteed the integrity of AIoT data by linking hash values designated as arbitrary, constant-size blocks with previous blocks in hierarchical chains. The proposed technique performs synchronization using location information between the central server and IoT devices to manage the cost of the integrity of IoT information at low cost. In order to easily control a large number of locations of IoT devices, we perform cross-distributed and blockchain linkage processing under constant rules to improve the load and throughput generated by IoT devices.

A Perspective on Modeling Materials in Extreme Environments: Oxidation of Ultrahigh-Temperature Ceramics

MRS Bulletin ◽  
2006 ◽  
Vol 31 (5) ◽  
pp. 410-418 ◽  
Author(s):  
Angelo Bongiorno ◽  
Clemens J. Först ◽  
Rajiv K. Kalia ◽  
Ju Li ◽  
Jochen Marschall ◽  
...  
Keyword(s):  
Modeling And Simulation ◽  
Atomistic Simulation ◽  
Extreme Environments ◽  
Protective Layer ◽  
Ceramic Composites ◽  
Atomistic Modeling ◽  
Temperature Oxidation ◽  
Simulation Techniques ◽  
Oxidation Resistant ◽  
Ultrahigh Temperature

AbstractThe broader context of this discussion, based on a workshop where materials technologists and computational scientists engaged in a dialogue, is an awareness that modeling and simulation techniques and computational capabilities may have matured sufficiently to provide heretofore unavailable insights into the complex microstructural evolution of materials in extreme environments.As an example, this article examines the study of ultrahigh-temperature oxidation-resistant ceramics, through the combination of atomistic simulation and selected experiments.We describe a strategy to investigate oxygen transport through a multi-oxide scale—the protective layer of ultrahigh-temperature ceramic composites ZrB2-SiC and HfB2-SiC—by combining first-principles and atomistic modeling and simulation with selected experiments.

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