Browse Topic: Analysis methodologies
ABSTRACT This paper addresses some aspects of an on-going multiyear research project of GP Technologies for US Army TARDEC. The focus of the research project has been the enhancement of the overall vehicle reliability prediction process. This paper describes briefly few selected aspects of the new integrated reliability prediction approach. The integrated approach uses both computational mechanics predictions and experimental test databases for assessing vehicle system reliability. The integrated reliability prediction approach incorporates the following computational steps: i) simulation of stochastic operational environment, ii) vehicle multi-body dynamics analysis, iii) stress prediction in subsystems and components, iv) stochastic progressive damage analysis, and v) component life prediction, including the effects of maintenance and, finally, iv) reliability prediction at component and system level. To solve efficiently and accurately the challenges coming from large-size
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 Use of Model-Based Design (MBD) processes for embedded controls software Development has been purported for nearly the last decade to result in cost, quality, and delivery improvements. Initially the business case for MBD was rather vague and qualitative in nature, but more data is now becoming available to support the premise for this development methodology. Many times the implementation of MBD in an organization is bundled with other software process improvements such as CMMI or industry safety standards compliance, so trying to unbundle the contributions from MBD has been problematic. This paper addresses the dominant factors for MBD cost savings and the business benefits that have been realized by companies in various industries engaged in MBD development. It also summarizes some key management best practices and success factors that have helped organizations achieve success in MBD deployment
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 Problem: The traditional four (4) methods for improving reliability; 1) High design safety margin, 2) Reduction in component count or system architectural complexity, 3) Redundancy, and 4) Back-up capability, are often ignored or perceived as being excessively costly in weight, space claim as well as money. Solution 1: Discussed here are the practical and very cost effective methods for achieving improved reliability by Functional Interface Stress Hardening (FISHtm or FISHingtm). The Author has been able to apply FISH to eliminate 70-92% of unscheduled equipment downtime, within 30-60 days, for more than 30 of the Fortune 500 and many other large companies which utilize automation controls, computers, power electronics and hydraulic control systems. Solution 2: From Structured Innovation the 33 DFR Methods & R-TRIZ Tool can be used to grow or improve reliability, via rapid innovation. The R-TRIZ tool) is provided so that users can instantly select the best 2, 3 or 4 of these
ABSTRACT The Joint Operational Energy Initiative (JOEI) models energy (and all classes of supply) consumption, generation, and sustainment across a virtual battlefield area of operations utilizing the System of Systems Analysis Toolset (SoSAT) and the Fully Burdened Cost Tool (FBCT). Recent advances in SoSAT provide a capability to model condition-based scenarios that better represent complex dynamic scenario changes and provide more accurate, realistic operational scenario and sustainment modeling. In addition, the JOEI team developed a new operational metric called Combat Effective Operational Endurance (CEOE) using SoSAT system-level outputs to determine unit combat power over time based on system availability and system combat weights. FBCT improvements include increased synchronization with SoSAT and expansion of capabilities to model Class V (ammunition), Class VII (major end item) transport, troop movement, convoy generation and higher fidelity cost allocation. The new SoSAT
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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