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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Impact of first-principles properties of deuterium–tritium on inertial confinement fusion target designs

A comprehensive knowledge of the properties of high-energy-density plasmas is crucial to understanding and designing low-adiabat, inertial confinement fusion (ICF) implosions through hydrodynamic simulations. Warm-dense-matter (WDM) conditions are routinely accessed by low-adiabat ICF implosions, in which strong coupling and electron degeneracy often play an important role in determining the properties of warm dense plasmas. The WDM properties of deuterium–tritium (DT) mixtures and ablator materials, such as the equation of state, thermal conductivity, opacity, and stopping power, were usually estimated by models in hydro-codes used for ICF simulations. In these models, many-body and quantum effects were only approximately taken into account in the WMD regime. Moreover, the self-consistency among these models was often missing. To examine the accuracy of these models, we have systematically calculated the static, transport, and optical properties of warm dense DT plasmas, using first-principles (FP) methods over a wide range of densities and temperatures that cover the ICF “path” to ignition. These FP methods include the path-integral Monte Carlo (PIMC) and quantum-molecular dynamics (QMD) simulations, which treat electrons with many-body quantum theory. The first-principles equation-of-state table, thermal conductivities (κ{sub QMD}), and first principles opacity table of DT have been self-consistently derived from the combined PIMC and QMD calculations. They have been compared with the typical models, and their effects to ICF simulations have been separately examined in previous publications. In this paper, we focus on their combined effects to ICF implosions through hydro-simulations using these FP-based properties of DT in comparison with the usual model simulations. We found that the predictions of ICF neutron yield could change by up to a factor of ∼2.5; the lower the adiabat of DT capsules, the more variations in hydro-simulations. The FP-based properties of DT are essential for designing ICF ignition targets. Future work on first-principles studies of ICF ablator materials is also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Plasma viscosity with mass transport in spherical inertial confinement fusion implosion simulations

The effects of viscosity and small-scale atomic-level mixing on plasmas in inertial confinement fusion(ICF) currently represent challenges in ICF research. Many current ICF hydrodynamic codes ignore the effects of viscosity though recent research indicates viscosity and mixing by classical transport processes may have a substantial impact on implosion dynamics. In this paper, we have implemented a Lagrangian hydrodynamic code in one-dimensional spherical geometry with plasmaviscosity and mass transport and including a three temperature model for ions, electrons, and radiation treated in a gray radiation diffusion approximation. The code is used to study ICF implosion differences with and without plasmaviscosity and to determine the impacts of viscosity on temperature histories and neutron yield. It was found that plasmaviscosity has substantial impacts on ICF shock dynamics characterized by shock burn timing, maximum burn temperatures, convergence ratio, and time history of neutron production rates. Finally, plasmaviscosity reduces the need for artificial viscosity to maintain numerical stability in the Lagrangian formulation and also modifies the flux-limiting needed for electron thermal conduction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Clinical Significance of Accounting for Tissue Heterogeneity in Permanent Breast Seed Implant Brachytherapy Planning

Purpose: The inhomogeneity correction factor (ICF) method provides heterogeneity correction for the fast calculation TG43 formalism in seed brachytherapy. This study compared ICF-corrected plans to their standard TG43 counterparts, looking at their capacity to assess inadequate coverage and/or risk of any skin toxicities for patients who received permanent breast seed implant (PBSI). Methods and Materials: Two-month postimplant computed tomography scans and plans of 140 PBSI patients were used to calculate dose distributions by using the TG43 and the ICF methods. Multiple dose-volume histogram (DVH) parameters of clinical target volume (CTV) and skin were extracted and compared for both ICF and TG43 dose distributions. Short-term (desquamation and erythema) and long-term (telangiectasia) skin toxicity data were available on 125 and 110 of the patients, respectively, at the time of the study. The predictive value of each DVH parameter of skin was evaluated using the area under the receiver operating characteristic (ROC) curve for each toxicity endpoint. Results: Dose-volume histogram parameters of CTV, calculated using the ICF method, showed an overall decrease compared to TG43, whereas those of skin showed an increase, confirming previously reported findings of the impact of heterogeneity with low-energy sources. The ICF methodology enabled us to distinguish patients for whom the CTV V{sub 100} and V{sub 90} are up to 19% lower compared to TG43, which could present a risk of recurrence not detected when heterogeneity are not accounted for. The ICF method also led to an increase in the prediction of desquamation, erythema, and telangiectasia for 91% of skin DVH parameters studied. Conclusions: The ICF methodology has the advantage of distinguishing any inadequate dose coverage of CTV due to breast heterogeneity, which can be missed by TG43. Use of ICF correction also led to an increase in prediction accuracy of skin toxicities in most cases.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

What Machine Learning Can and Cannot Do for Inertial Confinement Fusion

Machine learning methodologies have played remarkable roles in solving complex systems with large data, well-defined input–output pairs, and clearly definable goals and metrics. The methodologies are effective in image analysis, classification, and systems without long chains of logic. Recently, machine-learning methodologies have been widely applied to inertial confinement fusion (ICF) capsules and the design optimization of OMEGA (Omega Laser Facility) capsule implosion and NIF (National Ignition Facility) ignition capsules, leading to significant progress. As machine learning is being increasingly applied, concerns arise regarding its capabilities and limitations in the context of ICF. ICF is a complicated physical system that relies on physics knowledge and human judgment to guide machine learning. Additionally, the experimental database for ICF ignition is not large enough to provide credible training data. Most researchers in the field of ICF use simulations, or a mix of simulations and experimental results, instead of real data to train machine learning models and related tools. They then use the trained learning model to predict future events. This methodology can be successful, subject to a careful choice of data and simulations. However, because of the extreme sensitivity of the neutron yield to the input implosion parameters, physics-guided machine learning for ICF is extremely important and necessary, especially when the database is small, the uncertain-domain knowledge is large, and the physical capabilities of the learning models are still being developed. In this work, we identify problems in ICF that are suitable for machine learning and circumstances where machine learning is less likely to be successful. This study investigates the applications of machine learning and highlights fundamental research challenges and directions associated with machine learning in ICF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

A Review of Equation-of-State Models for Inertial Confinement Fusion Materials

Material equation-of-state (EOS) models, generally providing the pressure and internal energy for a given density and temperature, are required to close the equations of hydrodynamics. As a result they are an essential piece of physics used to simulate inertial con nement fusion (ICF) implosions. Historically, EOS models based on different physical/chemical pictures of matter have been developed for ICF relevant materials such as the deuterium (D2) or deuterium-tritium (DT) fuel, as well as candidate ablator materials such as polystyrene (CH), glow-discharge polymer (GDP), Berylium (Be), Carbon (C), and boron carbide (B 4 C). The accuracy of these EOS models can directly affect the reliability of ICF target design and understanding, as shock timing and material compressibility are essentially determined by what EOS models are used in ICF simulations. Systematic comparisons of current EOS models, benchmarking with experiments, not only help us to understand what model differences are and why they occur, but also to identify the state-of-the-art EOS models for ICF target designers to use. For this purpose, the first Equation of- State Workshop, supported by the US Department of Energy's ICF program, was held at the Laboratory for Laser Energetics (LLE), University of Rochester on 31 May - 2nd June, 2017. Finally, this paper presents a detailed review on the findings from this workshop: (1) 5-10% model-model variations exist throughout the relevant parameter space, and can be much larger in regions where ionization and dissociation are occurring, (2) the D 2 EOS is particularly uncertain, with no single model able to match the available experimental data, and this drives similar uncertainties in the CH EOS, and (3) new experimental capabilities such as Hugoniot measurements around 100 Mbar and high-quality temperature measurements are essential to reducing EOS uncertainty.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Alternative hot spot formation techniques using liquid deuterium-tritium layer inertial confinement fusion capsules

The baseline DT ice layer inertial confinement fusion (ICF) ignition capsule design requires a hot spot convergence ratio of ~34 with a hot spot that is formed from DT mass originally residing in a very thin layer at the inner DT ice surface. In the present paper, we propose alternative ICF capsule designs in which the hot spot is formed mostly or entirely from mass originating within a spherical volume of DT vapor. Simulations of the implosion and hot spot formation in two DT liquid layer ICF capsule concepts—the DT wetted hydrocarbon (CH) foam concept and the “fast formed liquid” (FFL) concept—are described and compared to simulations of standard DT ice layer capsules. 1D simulations are used to compare the drive requirements, the optimal shock timing, the radial dependence of hot spot specific energy gain, and the hot spot convergence ratio in low vapor pressure (DT ice) and high vapor pressure (DT liquid) capsules. 2D simulations are used to compare the relative sensitivities to low-mode x-ray flux asymmetries in the DT ice and DT liquid capsules. It is found that the overall thermonuclear yields predicted for DT liquid layer capsules are less than yields predicted for DT ice layer capsules in simulations using comparable capsule size and absorbed energy. However, the wetted foam and FFL designs allow for flexibility in hot spot convergence ratio through the adjustment of the initial cryogenic capsule temperature and, hence, DT vapor density, with a potentially improved robustness to low-mode x-ray flux asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

A novel method to recover DD fusion proton CR-39 data corrupted by fast ablator ions at OMEGA and the National Ignition Facility

CR-39 detectors are used routinely in inertial confinement fusion (ICF) experiments as a part of nuclear diagnostics. CR-39 is filtered to stop fast ablator ions which have been accelerated from an ICF implosion due to electric fields caused by laser-plasma interactions. In some experiments, the filtering is insufficient to block these ions and the fusion-product signal tracks are lost in the large background of accelerated ion tracks. A technique for recovering signal in these scenarios has been developed, tested, and implemented successfully. The technique involves removing material from the surface of the CR-39 to a depth beyond the endpoint of the ablator ion tracks. The technique preserves signal magnitude (yield) as well as structure in radiograph images. The technique is effective when signal particle range is at least 10 μm deeper than the necessary bulk material removal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗