Browse Topic: Occupant protection
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 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 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 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 The Blast Event Simulations sysTem (BEST) is a synthesis tool that provides a seamless and easy-to-use coupling between existing and commercially available LS-DYNA solvers and Anthropomorphic Test Device (ATD) models for a complete sequence of explosive simulations. BEST driven simulations capture the soil/explosive/vehicle/occupant interaction. In this paper a blast simulation analysis conducted by BEST for a generic but representative vehicle is presented. The vehicle is subjected to the blast load created by an explosive buried underneath the vehicle. An ATD model is placed inside the vehicle in order to capture the loads created on the lower legs of an occupant due to the explosion. Technical details with respect to the various models engaged in the simulation are presented first. The results and the physical insight which can be gained by the analysis are discussed. A series of design modifications which add minimal weight are introduced in the vehicle structure, such as
ABSTRACT Computational models are widely used in the prediction of occupant injury responses and vehicle structural performance of ground vehicles subjected to underbody blasts. Although these physics based computational models incorporate all the material and environment data, the classic models are typically deterministic and do not capture the potential variations in the design, testing and operating parameters. This paper investigates the effect of one such variation in physical tests, namely, variations in the position of occupant setup on the occupant injury responses. To study the effects of occupant position, a series of vertical drop tower tests were performed in a controlled setup. A vertical drop tower test involves an Anthropomorphic Test Device (ATD) dummy positioned on a seat and the setup is dropped on an energy attenuating surface, thus producing a desired shock pulse on the seat structure. The experimental data was analyzed for sensitivity of occupant position and ATD
ABSTRACT TARDEC researched head impact protective, energy attenuating materials for use in U.S. Army Ground System Vehicle (GSV) applications. The purpose of the project is to reduce potential head impact related mounted crew injuries and deaths which may occur during underbody blast, crash and rollover events. Commercial-off-the-shelf materials were evaluated for their energy attenuating performance. Exposed surface materials in combination with core material were also researched and evaluated. Baseline vehicle testing was conducted to understand the current head impact criterion. The results of this effort identified solutions which may potentially meet the needs of the Army to reduce head impact related injuries which may occur during crash, rollover and blast events. TARDEC used the knowledge gained from this project to create performance specification requirements for interior head impact protective components and materials for use in U.S. Army vehicles
ABSTRACT Fiber reinforced thermoset composites are well known for delivering 50% or more weight savings when compared with steel components while also providing strength, stiffness, and toughness. Nanoparticle additives have been shown to significantly increase the mechanical properties of thermoplastic and thermoset polymer matrices over the base matrix values. Extensive testing and characterization of composites containing graphene nanoplatelets (GnP) has been conducted and reported by XG Sciences’ (XGS) collaborators at the Michigan State University (MSU) Composite Materials and Structures Center. In a recent program with U.S. Army Tank Automotive Research, Development and Engineering Center (TARDEC), MSU investigated lightweight composites for blast and impact protection. High strain rate test facilities as well as high speed photography and non-destructive interferometry-based evaluation techniques were used to evaluate blast performance. The experimental results are presented
ABSTRACT Motorized ground forces spend considerable resources in equipping for situational awareness capabilities. Given requirements spanning command, control, surveillance, and reconnaissance of a battlefield, there has been no single mast technology that can support each of these with elevated sensors and weapons. A tough, extremely low weight modular mast system has been designed to be quickly attached or removed from a ground vehicle to provide different operational capabilities depending on the payload. The design allows for easy modification to fit functional needs on different vehicles and platforms. At the heart of the technology is a proprietary super-fiber pressurized tube which elevates the payload on a column of moderate gas pressure eliminating cumbersome hydraulic/mechanical systems. An internal, simple alignment system and gyroscope-maintained verticality allow a stable, elevated platform without introducing instability to the vehicle. The system is capable of
ABSTRACT The Optical Warhead Lethality Sensor Suite (OWLSS) was designed specifically for tracking dense, fast fragment fields generated in warhead arena testing. OWLSS is an optimized hardware/software solution for measuring correlated properties of detonating warhead fragment distributions. The OWLSS automated track algorithm returns time-dependent 3D position, velocity, size, aerodynamic drag, and mass estimates for each fragment tracked. These data products fill a significant gap in our ability to characterize munitions for weapon effectiveness modeling. Furthermore, the system is modular and can be reconfigured for many tracking applications. In this paper, we present an overview of legacy arena measurement techniques, an overview of the OWLSS optical tracking approach, and we discuss how OWLSS can be employed to collect test data needed to improve the survivability of armored vehicles. Citation: J. P. Burke, Jr, J. Roe, S. F. Henke, B. P. Walker, W. Koons, “An Enhanced Optical
ABSTRACT As part of DARPA’s Adaptive Vehicle Make (AVM) portfolio of programs, blast and ballistic survivability analysis tools were developed. The intent of these tools was to facilitate design and design optimization by making it possible for designers to perform survivability analysis from CAD and to automate the survivability analysis pipeline to allow optimization codes to invoke the survivability tools and obtain results. This paper describes some of the tools and their capabilities through highlighting five innovations utilized in the program: multi-fidelity modeling; automated meshing and welding; uncertainty quantification and 95% bounds; a large material property database and more accurate blast loads; and automating the entire computational pipeline
Energy efficiency in both internal combustion engine (ICE) and electric vehicles (EV) is a strategic advantage of automotive companies. It provides a better user experience that emanates amongst others from the reduction in operation expenses, particularly critical for fleets, and the increase in range. This is especially important in EVs where customers may experience range anxiety. The energetical impact of using the air conditioning system in vehicles is not negligible with power consumptions in the range of kilowatts, even with a stopped vehicle. This becomes particularly important in areas with high temperature and humidity levels where the usage of the air conditioning systems becomes safety factor. In such areas, drivers are effectively forced to use the air conditioning system continuously. Hence, the air conditioning system becomes an ideal choice to deploy control strategies for optimized energy usage. In this paper, we propose and implement a control strategy that allows a
Effective thermal management is crucial for vehicles, impacting both passenger comfort and safety, as well as overall energy efficiency. Electric vehicles (EVs) are particularly sensitive to thermal considerations, as customers often experience range anxiety. Improving efficiency not only benefits customers by extending vehicle range and reducing operational costs but also provides manufacturers with a competitive edge and potential revenue growth. Additionally, efficient thermal management contributes to minimizing the environmental impact of the vehicle throughout its lifespan. Digital twins have gained prominence across various industries due to their ability to accelerate development while minimizing testing costs. Some applications have transitioned to comprehensive three-dimensional models, while others employ model reduction techniques or hybrid approaches that combine different modeling methods. The discovery of unknown working mechanisms, more efficient and effective control
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