1. June 2-3, 2004 HAPL meeting, UCLA 1 Progress on Target Survival Presented by A.R. Raffray Other Contributors: B. Christensen, M. S. Tillack UCSD D. Goodin General Atomics HAPL Meeting UCLA Los Angeles, CA June 2-3, 2004

2. HAPL meeting, UCLA 2 Outline Benchmark analysis with U. Roch. LLE (D. Harding) -Purchase more advanced version of “DSMC” -Number flux and heat flux analysis -Effect of accommodation and sticking coefficients Modeling experimental results from LANL (J. Hoffer/D. Geller)

3. DS2V was Purchased for Modeling the Thermal Loading from the Background Gas Figure Above Shows the Temperature Field Around a Direct Drive Target. Xe flowing at 400 m/s in the positive x-dir.4000 K Xe stream temperature. 3.22x10 21 m -3 Xe stream density. Sticking coefficient = 0. Target surface temperature = 18 K. Capabilities: Axisymmetric flow. Adjustable sticking (condensation) coefficient. Adjustable accommodation coefficient. Output: Heat flux, number flux, drag force,etc… Injected Target Modeling: Simulated by flow over stationary target (hydrodynamic similarity). Could not find a correct way of modeling moving target in stationary gas with this version.

4. The Number Flux and Heat Flux at the Target Reach Quasi-Steady State in a Short Time Figure Above Shows the Number Flux and Heat Flux Around a Direct Drive Target. Xe stream flowing at 400 m/s. 4000 K stream temperature. 3.22x10 21 m -3 stream density. Sticking coefficient = 0. Target surface temperature = 18 K.

5. June 2-3, 2004 HAPL meeting, UCLA 5 As the Stream Density Is Increased the Sticking Coefficient (sigma) Has a Greater Effect The number flux is not a function of the sticking coefficient (sigma) when the stream density is low. The number flux decreases with increasing sigma when the stream density is high. Kinetic theory and DS2V show good agreement (sigma=1, no shielding effect). Low Density Stream, n = 3.22x10 19 m -3 High Density Stream, n = 3.22x10 21 m -3

6. June 2-3, 2004 HAPL meeting, UCLA 6 The Heat Flux is Significantly Affected by the Stream Density, Temperature, and Sticking Coefficient The effect of latent heat is not included in DS2V; needs to be included in post processing. By neglecting the latent heat the “shielding” effect of a non- condensing gas (sigma = 0) is seen. Virtually no “shielding” for the low density stream. Significant “shielding” for the high density stream. The rapid change in heat flux with position suggests that the average max. heat flux could be reduced by tumbling the target. Low Density Stream, n = 3.22x10 19 m -3 High Density Stream, n = 3.22x10 21 m -3

7. June 2-3, 2004 HAPL meeting, UCLA 7 Conclusions from DS2V Study Simulate injected target situation by flow over stationary target (hydrodynamic similarity) The number flux and heat flux at the target reach quasi-steady state in a relatively short time (no need to run longer except if outside conditions (gas) change) The effect of latent heat is not included in DS2V; needs to be included in post processing. “Shielding” effect dependent on sticking coefficient for high density gas -Virtually no “shielding” for the low density stream (~1 mTorr). -Significant “shielding” for the high density stream ( q’’ reduced by a factor of 2 or more when sigma changes from 1 to 0 for example case at ~100 mTorr) Experimental determination of the sticking coefficient is needed (U. Roch.) The accommodation coefficient should also be determined if the sticking coefficient is found to be significantly less than one.

8. June 2-3, 2004 HAPL meeting, UCLA 8 Initial Modeling of Direct Heating Experiments at LANL (J. Hoffer/D. Geller) epoxy layer coil 1-D spherical numerical model. Constant heat flux. Initial temperature = 18 K. DT thickness = 400  m.

9. June 2-3, 2004 HAPL meeting, UCLA 9 The Time to Triple Point, as Predicted by the Two Numerical Models, is Generally Consistent with Experimental Results

10. June 2-3, 2004 HAPL meeting, UCLA 10 There are Large Differences in the Melt Layer Thickness Results

11. June 2-3, 2004 HAPL meeting, UCLA 11 Summary Encouraging that melting time seems to be predicted quite accurately, Some question marks on melt layer thickness experimental and modeling results Modeling these experimental results can be improved: -Create 1-D cylindrical model. -Allow for variable heat flux (for melt layer computations) -Code optimization: meshing, time-steps, assumed temperature range over which melting occurs -Modeling experimental set-up Experimental uncertainties need to be better understood -Measurement; how to specify melt layer boundary -Heat flux changes when melting starts Working with our LANL colleagues on how to produce experimental results more amenable for our model and on how to improve model to simulate a wider range of experimental conditions

12. June 2-3, 2004 HAPL meeting, UCLA 12 Brian has completed his MS Thesis on this - a summary of which will be submitted for journal publication Thesis defense next week His results has shed much light on the different processes affecting target survival He has included recommendation on future work (2-D or quasi 2-D modeling + experiments) We have identified a new student to continue this work as from the Fall (after the “Olympics”!) Please Refer to Brian Christensen’s Poster for More Details on our 1-D Target Thermomechanics Modeling (Including Phase Change) and DS2V Modeling