Simulating Underbelly Blast Events using Abaqus/Explicit - CEL

Transcription

1 U.S. Army Research, Development and Engineering Command Simulating Underbelly Blast Events using Abaqus/Explicit - CEL J. Jablonski, P. Carlucci (U.S. Army ARDEC) R. Thyagarajan (U.S. Army TARDEC) B. Nandi, J. Arata (SIMULIA) 2012 SIMULIA Customer Conference May 17, 2012 DISTRIBUTION STATEMENT A Distribution Unlimited Approved for Public Release

2 Preliminaries Energetic Material A substance which can quickly convert its chemical energy to other energy forms. Explosives Rapid production of high pressure gaseous products (pressure-volume work). Tremendous power output to surroundings. Propellants Similar to that of an explosive but with slower production of gaseous products. Use gaseous products to move an object as opposed to destroy it. Pyrotechnics Gradual conversion of chemical energy to heat and light. Useful for celebrating Independence Day. Blast Event The act of a shock wave formed by an explosion interacting with a structure. Far-field blast event Developed shock wave propagating through ambient medium. Near-field blast event Highly irregular shock wave. Explosive products and ejected material also interact with structure. 2

3 Motivation Near-field blast events of great relevance to many Department of Defense applications. Survivability Improving structures and vehicles against IED attacks. Underbelly blast. Lethality Neutralization of fortifications, vehicles, personnel. Munitions Design Optimization of warhead payloads. A predictive modeling capability of underbelly blast events is essential. Modeling and simulation can be used to down-select design concepts, requiring fewer tests, reducing costs. Understanding and insight of the governing physics allows for better designs. Validation of any modeling approach is necessary. Can we compare the model to a test that encompasses the physics of interest? Yes, tests conducted by Defence R&D Canada (DRDC) Valcartier serve as a benchmark for modeling underbelly blast events on vehicles. 3

4 Modeling Approach One-way coupled approach Use an analytical or empirical blast model to predict the loading to a structure. CONWEP Pressure correlations for air blast events. U.S. Army TACOM Impulse Model Impulse to plate due to buried mine. Apply loading to a finite element model of the structure to determine its response. Accurate results are possible when the blast models are used within their calibrated/assumed bounds. Otherwise further calibration is needed. Limited predictive capability. Fully-coupled approach Explicitly model the detonation process and the evolution of explosive products while simultaneously performing structural calculations on all relevant mediums (i.e. soil, air, water) and the structure. Higher fidelity but more computationally expensive. Best hope for predictive results. 4

5 Modeling Approach How can we model an underbelly blast using Abaqus/Explicit? Approach: Use the coupled Eulerian-Lagrange (CEL) capability in Abaqus/Explicit to fully couple the blast event with the structure. Soil, explosive, and air modeled as Eulerian material. Test structure modeled as Lagrangian material. Fluid-structure interactions captured by default contact algorithm in CEL. Weights Support Stand Ambient air (not shown) Box-beam Frame Target Plate Soil Mine 5

6 Soil Modeling Simplified Hybrid Elastic-Plastic (SHEP) model Constitutive model developed by U.S. Army - ERDC to characterize geological materials under explosive loading. Empirically calibrated for different soil types via mechanical testing. Implemented into Abaqus/Explicit as a VUMAT Exponential yield surface (pressure dependent) Hydrostatic behavior dependent on soil compaction 6

7 Explosive Modeling Detonation Process: Programmed Burn Simple model for detonation User defines initiation point Material point converts completely to explosive products when hit by detonation wave Equation of State: Jones-Wilkins-Lee (JWL) Empirically derived equation of state Coefficients obtained from cylinder expansion test Fairly accurate for ideal explosives until ~8 times volume expansion Geometry and thermo-chemical effects are ignored P 2 P A 1 ω e 1 B 1 ω e = R V R2V RV 1 R2V + ωe + V P 1 t d = x x P D CJ O P s = Ae R V 1 + Be R V 2 + CV ( ω+ 1) O 7

8 Model Overview Part Description Support Stand Treated as a rigid body. Meshed with 56,565 C3D8R elements. Weight Treated as a rigid body. Meshed with 800 C3D8R elements. Box-beam Frame Target Plate Soil Mine Ambient Air Modeled as SAE 1020 steel with linear elasticity. Meshed with 88,816 C3D8R elements. Modeled as a 1.25 thick 5083-H131 aluminum solid with linear elasticity, Johnson-Cook plasticity, and Johnson-Cook damage. Modeled using a simplified hybrid elastic-plastic model calibrated to a sandy soil at a density of 2300 kg/m 3. Explosive products modeled as C-4 using the JWL equation of state. Detonation process approximated through programmed burn calculations. Modeled using ideal gas assumptions at standard ambient temperature and pressure conditions. Air Soil Mine Note that the soil, mine, and ambient air are all defined within the Eulerian domain, which was meshed with 795,982 EC3D8R elements. The assignment of these three materials within the Eulerian domain is shown above. 8

9 Results Results agree with experiment: Maximum plate deflection within 5% of experiment Profile of plate deformation matches reasonably 9

10 Comparison Final deformation profile of plate Predicting maximum residual plate deflection: Modeling Approach Abaqus/Explicit Coupled Eulerian-Lagrangian LS-DYNA CONWEP Boundary condition LS-DYNA U.S. Army TACOM Impulse Model for initial conditions Error -2.7 % % 72.8% Deflection of the center of the test plate was accurately predicted by the simulation. The overall deformation profile of the plate was reasonably predicted by the simulation. Deformation away from center of plate is under predicted. 10

11 Modeling Error t = 50μs t =100μs t = 350μs t = 400μs Predicted deformation is most accurate where the soil impacts plate. Evidence that momentum transfer between soil and plate is accurately captured. This is to be expected since the actual soil density of the experiment was known. Deformation is under predicted further from the center of the plate. Not surprising since the soil model used is only a rough approximation of the actual soil conditions. Soil dispersion likely incorrect. It is conjectured that additional soil was ejected away from the plate center in the actual experiment. 11

12 Conclusions Applying a fully coupled Eulerian-Lagrangian approach to modeling underbelly blast on vehicles is accurate in capturing the deformation of the structures of interest. Model accuracy and fidelity is superior to traditional one-way coupled approaches using un-calibrated blast models. The entire finite element model, with specific emphasis on the empirical constants for the relevant constitutive models was defined a priori and not adjusted to improve correlation with the experiment. Intended to replicate production-level constraints. Reasonable predictive capability was demonstrated. Accurate constitutive models are vital to avoid modeling error. The computational requirements for this simulation were appropriate for the resources available within the U.S. Army ARDEC. A single analysis required five hours of computing time on twenty-four 2.67 GHz cores. 12

13 Questions? Contact Information: Jonathan Jablonski Mechanical Engineer U.S. Army ARDEC Fuze and Precision Armaments Technology Directorate Analysis and Evaluation Technology Division Picatinny Arsenal, NJ [Phone] [Fax] 13