Browse Topic: Safety
ABSTRACT The modeling of a buried charge is a very complex engineering task since many Design Variables need to be considered. The variables in question are directly related to the method chosen to perform the analysis and the process modeled. In order to have a Predictive Tool two main objectives have to be carried out, the first is a verification of the numerical approach with experimental data, the second objective is a sensitivity study of the numerical and process parameters. The emphasis of the present study covers the second objective. To perform this task a comprehensive sensitivity study of fourteen Design Variables was completed which required 1000+ computational hours. The modeling approach that was chosen was the Discrete Particle Method (DPM) to model the Soil and HE and the Finite Element Method for the Structure. The basis for the study was a blast event applied to a model of the TARDEC Generic Vehicle Hull. The Response Parameter was chosen to be the Total Blast Impulse
ABSTRACT This paper reviews the Army Generic Hull [1-5] as a vital developmental tool for underbody blast modeling and simulation applications. Since 2010, it has been used extensively to help calibrate and validate various numerical software codes and methodologies. These are being used extensively today in the development of underbody armor, as well as mine blast subsystems such as seats, to protect both military vehicles and their occupants. In the absence of easily shareable information in this domain due to data classification, this specially formulated product is a valuable part of any toolset for underbody blast development and product design. Citation: K. Kulkarni, S. Kankanalapalli, V. Babu, J. Ramalingam, R. Thyagarajan, “The Army Generic Hull As A Vital Developmental Tool For Underbody Blast Applications,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 16-18, 2022
ABSTRACT Teleoperated ground vehicles are an integral part of the U.S. Army and Marine Corps long range vision and a key transition technology for fully autonomous vehicles. However, the combination of marginally-stable vehicle dynamics and limited perception are a key challenge facing teleoperation of such platforms at higher speeds. New technologies for enhancing operator perception and automatically detecting and mitigating rollover risk are needed to realize sufficient safety and performance in these applications. This paper presents three rollover mitigation concepts for high speed teleoperation of heavy tactical vehicles, including model-predictive warning, negative obstacle avoidance, and reactive brake controls. A modeling and simulation approach was used to evaluate these concepts within the Autonomous Navigation Virtual Environment Laboratory (ANVEL). Vehicle models for both the M1078 cargo truck and RG-31 MRAP were used throughout concept evaluation over terrain ranging from
ABSTRACT Over the course of typical survivability analyses for underbody blast events, a multitude of individual cases are examined where charge size, charge location relative to the vehicle, and vehicle clearance from the ground are varied, so as to arrive at a comprehensive assessment. While multi-physics computational tools have reduced the expense and difficulty of testing each loading case experimentally, these tools still often require significant execution and wall-clock times to perform the simulations. In efforts to greatly reduce the time required to conduct a holistic survivability analysis, Fast Running Models (FRMs) have been implemented and validated to act as a surrogate for the computationally expensive finite element tools in use today. Built using a small set of simulations, FRMs generate loading data in a matter of seconds, representing a significant improvement in survivability analysis turnaround time
ABSTRACT The age of large autonomous ground vehicles has arrived. Wherever vehicles are used, autonomy is desired and, in most cases, being studied and developed. The last barrier is to prove to decision makers (and the general public) that these autonomous systems are safe. This paper describes a rigorous safety testing environment for large autonomous vehicles. Our approach to this borrows elements from game theory, where multiple competing players each attempt to maximize their payout. With this construct, we can model an environment that as an agent that seeks poor performance in an effort to find the rare corner cases that can lead to automation failure
ABSTRACT V-shaped hulls for vehicles, to mitigate buried blast loads, are typically formed by bending plate. Such an approach was carried out in fabricating small test articles and testing them with buried-explosive blast load in Southwest Research Institute’s (SwRI) Landmine Test Fixture. During the experiments, detailed time dependent deflections were recorded over a wide area of the test article surface using the Dynamic Deformation Instrumentation System (DDIS). This information allowed detailed comparison with numerical simulations that were performed with LS-DYNA. Though in general there is good agreement on the deflection, in the specific location of the bends in the steel the agreement decreases in the lateral cross section. Computations performed with empirical blast loads developed by SwRI and by more computationally intensive ALE methods in LS-DYNA produced the same results. Computations performed in EPIC showed the same result. The metal plate was then bent numerically so
ABSTRACT The study describes the development of a plug-in module of the realistic 3D Digital Human Modeling (DHM) tool RAMSIS that is used to optimize product development of military vehicle systems. The use of DHM in product development has been established for years. DHM for the development of military vehicles requires not only the representation of the vehicle occupants, but also the representation of equipment and simulation of the impact of such equipment on the Warfighter. To simulate occupants in military vehicles, whether land or air based, realistically, equipment must become an integral part of the extended human model. Simply attaching CAD-geometry to one manikin’s element is not sufficient. Equipment size needs to be scalable with respect to anthropometry, impact on joint mobility needs to be considered with respect to anatomy. Those aspects must be integrated in posture prediction algorithms to generate objective, reliable and reproducible results to help design engineers
ABSTRACT This study applies an augmentation to systems engineering methodology based on the integration of adaptive capacity, which produces enhanced resilience in technological systems that operate in complex operating environments. The implementation of this methodology enhances system resistance to top-level function failure or accelerates the system’s functional recovery in the event of a top-level function failure due to functional requirement shift, evolutions, or perturbations. Specifically, this study employs a methodology to integrate adaptive resilience and demonstrates key aspects of its implementation in a relevant explosive reactive armor (ERA) system case study. The research and resulting methodology supplements and enhances traditional systems engineering processes by offering systems designers a method to integrate adaptive capacity into systems, enhancing their resilient resistance, or recovery to top-level function failure in complex operating environments. This
ABSTRACT Significant Design for Reliability (DfR) methodology challenges are created with the integration of autonomous vehicle technologies via applique systems in a ground military vehicle domain. Voice of the customer data indicates current passenger vehicle usage cycles are typically 5% or less (approximately 72 minutes of use in a twenty-four hour period) [2]. The time during which vehicles currently lay dormant due to drivers being otherwise occupied could change with autonomous vehicles. Within the context of the fully mature autonomous military vehicle environment, the daily vehicle usage rate could grow to 95% or more. Due to this potential increase in the duty or usage cycle of an autonomous military vehicle by an order of magnitude, several issues which impact reliability are worth exploring. Citation: M. Majcher, J. Wasiloff, “New Design for Reliability (DfR) Needs and Strategies for Emerging Autonomous Ground Vehicles”, In Proceedings of the Ground Vehicle Systems
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