WHEN it comes to finding solutions to tough, national security challenges, scientists and engineers cannot always rely on experiments to ferret out the information they need. Many experiments would simply be too large, dangerous, or expensive to be feasible, leaving technical experts to reconcile knowledge gaps by other means.
Simulations have become an increasingly valuable tool, helping researchers better understand experimental results and bolstering confidence in solutions they develop for various problems. (See the box below.) Computational engineers at Lawrence Livermore focus most of their efforts on issues related to national security. Bob Ferencz, a group leader in Livermore’s Engineering Directorate, says, “We use simulation to evaluate high-consequence scenarios that we cannot easily test because of experimental costs or other concerns.”
For example, Laboratory engineers are applying the hydrostructural analysis codes ALE3D and ParaDyn to simulate physical events that last only a few microseconds to several hundred milliseconds and involve large material deformations, high strain rates, and strong shocks. ALE3D and ParaDyn can offer insight into the detonation process of high explosives and material collisions at hypervelocities, in which materials travel 2 kilometers or more per second. By continually developing and improving these computational methods, Laboratory scientists and engineers are providing decision makers with reliable data for evaluating national security efforts.
An Unexpected Twist
Underwater structures often suffer more severe damage from a blast than those surrounded by air because water has a higher density and is more incompressible than air. As a result of this tamping effect, the energy released during an explosive detonation couples to the structure more efficiently. “When trying to protect a structure from a blast, creating an appropriate standoff distance is normally the most inexpensive solution,” says Glascoe. “However, for this particular scenario, space was limited. The question we had to answer was what to do when the standoff distance is so tightly constrained.”
Using ALE3D, Glascoe and his team analyzed methods for diffusing explosive energy coupled to a vertical, partially submerged structure in a restricted space. The researchers simulated several possible tactics, specifically, placing an air gap or a matrix of air-filled media between the explosive source and the structure. In experiments, they used different-sized, water-filled aquariums fitted with aluminum plates to represent the structure and subjected each one to controlled blasts from explosives. When they analyzed the data, the results seemed rather strange. “At first, we thought there might have been an error in the data acquisition,” says Glascoe.
With an air gap in front of the plate, the plate unexpectedly became deformed over one area. The researchers hypothesized that a small, previously unaccounted-for water layer between the charge and air gap could be to blame. “We then ran ALE3D simulations to better understand the results and obtained the same focused deformation.” Instead of dispersing the energy from the shock wave, the water-tamped explosive projected the intervening water as a jet toward the plate. Conversely, tests with a matrix of air-filled tubes scattered the shock wave and prevented water jets from forming. Glascoe says, “This relatively heterogeneous material creates an impedance mismatch that disrupts and scatters the blast wave, providing protection across a large threat space.”
Glascoe is quick to point out the positives of computational power for understanding complex physics problems and evaluating solutions. “Once we understand the problem well enough to focus on a specific response—plate deformation, for example—we can use advanced sampling techniques to stitch together a comprehensive picture of the anticipated result with fewer simulations,” says Glascoe. Carefully analyzing the computational results also helps researchers optimize the design of future experiments. “Smart approaches to simulation save us time and money,” he says. The team is now integrating strategies developed in this study into plans for better protecting existing civil structures.
One strategy for neutralizing incoming threats is through a kinetic-kill approach, where an inert projectile, or kill vehicle, engages the incoming threat at a very high speed. MDA system architects are primarily concerned with intercept lethality, that is, whether the intercept event successfully destroys the threat. The ParaDyn code is well suited for examining such events because it allows engineers to analyze the transient dynamic response of three-dimensional solids and structures. It is especially effective at detailing the interaction between independent bodies, such as the incoming threat and the kill vehicle. “ParaDyn and ALE3D provide us with insight into the time sequence of events during an intercept,” says Kokko. “They help us determine the effectiveness of the kill vehicle in neutralizing a threat payload for a range of conditions.”
Engineers are also interested in understanding how the interceptor and threat break into pieces on impact. Livermore code developers have enhanced ParaDyn with advanced material models and improved numerical techniques to more accurately simulate an intercept event. Computational engineers, including Kokko, are working with the revised code to provide detailed information about the debris scene.
Simulation codes such as ParaDyn offer a cost-effective approach for system-level analysis at a time when expensive, full-scale experiments are becoming more difficult to stage. “We have been focused on establishing a basis of confidence in our modeling methodology to verify that simulations compare well with experimental results at the fundamental, component level and for scaled and full-scale systems,” says Kokko. Confidence in simulation results is essential to sponsors who rely on the data to make critical decisions, and the widespread adoption of physics-based numerical codes for analyzing such events makes this an ever-more important effort.
Two Codes Team Up
Successful demonstration of the technology led to an exciting partnership between the Laboratory and the Blast Protection for Platforms and Personnel HPC [high-performance computing] Software Applications Institute, sponsored by the Department of Defense’s High Performance Computing Modernization Program and headed by the Army Research Laboratory. The institute has embarked on a six-year program to develop a suite of tools for analyzing high-explosive blasts and mitigating the effects on military vehicle platforms and personnel. Says Ferencz, “Our primary contribution is to provide a simulation capability that enables efficient, accurate analysis of these complex problems.”
Building Confidence in Simulated Solutions
When researchers can obtain complex results in days instead of weeks, they can also dedicate more time to understanding an input parameter’s effect on code sensitivity. “Sensitivity studies are an important part of the analysis process,” says Kokko. “Investigating how results vary with assumptions across many scenarios helps us build confidence in our results.”
Studies that help validate the performance of computational codes are propelling viable, novel solutions to some of the nation’s greatest challenges. Says Kokko, “We have a responsibility to our sponsors to deliver accurate, reliable data so they can confidently make decisions regarding our national security.”
Key Words: ALE3D code, arbitrary Lagrangian–Eulerian (ALE) technique, computational engineering, embedded grid, ParaDyn code.
For further information contact Bob Ferencz (925) 422-0571 (email@example.com).
Lawrence Livermore National Laboratory
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