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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Design and Commissioning of a Deuterium-Tritium Gas Delivery System for Muon Catalyzed Fusion in a Diamond Anvil Cell

We report the design, commissioning, and operation of deuterium-deuterium (DD) and deuterium-tritium (DT) gas delivery systems developed to load a diamond anvil cell (DAC) beam target for muon-catalyzed fusion (muCF). The DAC approach enables DT fuel to be compressed to GPa pressures at more than twice the liquid density and heated from cryogenic temperatures through 500 K, opening access to a substantially expanded parameter range for muCF kinetics and yield measurements. In this approach, DT is cryo-condensed to a liquid in a minichamber and then compressed in the DAC using a helium-driven pneumatic membrane, achieving high pressures in a millimeter-scale DT sample volume. A DD gas delivery system was designed and used to validate the experimental apparatus, measure the gas quantities needed for filling, develop operational experience, and collect kinetics and yield data with DD targets. The DT gas delivery system adds tritium-specific capabilities for inventory minimization, secondary containment, and activity monitoring. The DT system integrates depleted uranium storage beds and a liquid helium cryogenic condenser used for pressure building and cryopumping. High-purity delivery is provided by a rapid-response palladium permeator. The system is housed in a helium-atmosphere glovebox held at negative pressure with continuous cleanup. We present the process and instrumentation design, a failure modes and effects analysis (FMEA), and data from the experiment's in situ Raman spectrometer, which provides direct confirmation of target loading and composition through the optically clear diamond anvils. The 2024 and 2025 DT campaigns achieved repeatable target fills and operation with no measurable tritium releases to the stack, demonstrating safe, high-purity DT loading at novel density-temperature conditions for muCF studies.

Koukina, Elena [Acceleron Fusion]↗
DOE OSTI2022

Diagnosing magnetic fields in cylindrical implosions with oblique proton radiography

Two experiments at the OMEGA Laser System used oblique proton radiography to measure magnetic fields in cylindrical implosions with and without an applied axial magnetic field. Although the goal of both experiments was to measure the magnitude of the compressed axial magnetic field in the core of the implosion, this field was obfuscated by two features in the coronal plasma produced by the compression beams: an azimuthal self-generated magnetic field and small length scale, high-amplitude structures attributed to collisionless effects. In order to understand these features, synthetic radiographs are generated using fields produced by 3D HYDRA simulations. These synthetic radiographs reproduce the features of the experimental radiographs with the exception of the small-scale structures. A direct inversion algorithm is successfully applied to a synthetic radiograph but is only partially able to invert the experimental radiographs in part because some protons are blocked by the field coils. The origins of the radiograph features and their dependence on various experimental parameters are explored. Furthermore, the results of this analysis should inform future measurements of compressed axial magnetic fields in cylindrical implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

In Situ X-ray Diffraction of High Density Polyethylene During Dynamic Compression: Polymer Chain Compression and Phase Transformations

Polymers are widely implemented materials often used for safety and security in our daily lives. However, we do not have a thorough understanding of the phase transformations of these materials when exposed to extreme condition, high strain rate, events. To study polymers in these severe environments, we performed plate impact experiments that impart a one-dimensional shock wave, at high pressures and temperatures, to observe the materials response. Generally, velocimetry is the experimental diagnostic used to capture the movement of high velocity interfaces to then calculate the mechanical variables associated with shock compression. However, when a material undergoes a phase transition, such as between two crystalline phases or melting to decomposition during shock compression, velocimetry does not explicitly indicate what structural change occurred. At the Dynamic Compression Sector at the Advanced Photon Source gas gun driven compression has been paired with x-ray diffraction, providing the ability to study both the shock parameters and structural changes concurrently. We explored high density polyethylene (HDPE) both on its reactants Hugoniot (<10.12 GPa) and within its transition region (24.3 GPa) where HDPE is hypothesized to decompose from reactants to products. With x-ray diffraction we observed both polymer chain compression and crystal structure reorientation from orthorhombic to monoclinic above 6 GPa, as well as either a possible phase change or chemical decomposition at 24.3 GPa. With these experiments we were able to determine the crystalline and amorphous Hugoniot loci at pressures below the polymer transition region.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks

There has been much recent interest in designing symmetry-aware neural networks (NNs) exhibiting relaxed equivariance. Such NNs aim to interpolate between being exactly equivariant and being fully flexible, affording consistent performance benefits. In a separate line of work, certain structured parameter matrices -- those with displacement structure, characterized by low displacement rank (LDR) -- have been used to design small-footprint NNs. Displacement structure enables fast function and gradient evaluation, but permits accurate approximations via compression primarily to classical convolutional neural networks (CNNs). In this work, we propose a general framework -- based on a novel construction of symmetry-based structured matrices -- to build approximately equivariant NNs with significantly reduced parameter counts. Our framework integrates the two aforementioned lines of work via the use of so-called Group Matrices (GMs), a forgotten precursor to the modern notion of regular representations of finite groups. GMs allow the design of structured matrices -- resembling LDR matrices -- which generalize the linear operations of a classical CNN from cyclic groups to general finite groups and their homogeneous spaces. We show that GMs can be employed to extend all the elementary operations of CNNs to general discrete groups. Further, the theory of structured matrices based on GMs provides a generalization of LDR theory focussed on matrices with cyclic structure, providing a tool for implementing approximate equivariance for discrete groups. We test GM-based architectures on a variety of tasks in the presence of relaxed symmetry. We report that our framework consistently performs competitively compared to approximately equivariant NNs, and other structured matrix-based compression frameworks, sometimes with a one or two orders of magnitude lower parameter count.

Samudre, Ashwin↗
DOE OSTI2021

An Experimental Study of Uncertainty Considerations Associated with Predicting Auto-ignition Timing using Livengood-Wu Integral Method

The application of the Livengood-Wu (LW) integral method as a tool to estimate knock onset in spark ignited (SI) engines and combustion phasing in advanced compression ignition (ACI) engines has been demonstrated through simulations several times. In this study, the effect of uncertainties associated with parameters required for the LW integral method, when used as a tool for model based control of ignition timing in an ACI engine, were experimentally studied using five full boiling range gasoline fuels. As a first step, the method was applied to experimental data from a rapid compression machine and it was found that the ability of the LW integral method to predict ignition timing was very sensitive to the performance of the chemical kinetic model of each fuel. The method was subsequently applied to experimental data from a single-cylinder gasoline engine with simple approximations for the LW integral input parameters, and it was found that the predicted time of ignition was significantly different from the actual start of combustion. Systematic evaluation of various parametric uncertainties conducted thereafter showed that the uncertainty in cylinder charge temperature has the greatest influence. Improved methods of estimating cylinder charge temperature are proposed to account for the previously determined corrections, to enable the use of the LW integral method for model based control of ignition timing.

Compression Ignition↗
DOE OSTI2022

The structure of cluster merger shocks: turbulent width and the electron heating time-scale

We present a new 2MsChandra observation of the cluster merger Abell 2146, which hosts two huge M ~ 2 shock fronts each ~500 kpc across. For the first time, we resolve and measure the width of cluster merger shocks. The best-fitting width for the bow shock is 17 ± 1kpc and for the upstream shock is 10.7 ± 0.3 kpc. A narrow collisionless shock will appear broader in projection if its smooth shape is warped by local gas motions. We show that both shock widths are consistent with collisionless shocks blurred by local gas motions of 290 ± 30 km s –1 . The upstream shock forms later on in the merger than the bow shock and is therefore expected to be significantly narrower. From the electron temperature profile behind the bow shock, we measure the time-scale for the electrons and ions to come back into thermal equilibrium. We rule out rapid thermal equilibration of the electrons with the shock-heated ions at the 6σ level. The observed temperature profile instead favours collisional equilibration. For these cluster merger shocks, which have low sonic Mach numbers and propagate through a high β plasma, we find no evidence for electron heating over that produced by adiabatic compression. Our findings are expected to be valid for collisionless shocks with similar parameters in other environments and support the existing picture from the solar wind and supernova remnants. Furthermore, the upstream shock is consistent with this result but has a more complex structure, including a ~2ke V increase in temperature ~50 kpc ahead of the shock.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Hybrid Simulations of FRC Merging and Compression

An improved understanding of field-reversed configuration (FRC) merging and stability in high acceleration and compression magnetic fields is needed to speed up the development of the pulsed fusion concept developed at Helion Energy. All previous theoretical and simulation work on FRC merging and compression was performed using two-dimensional (2D) magnetohydrodynamic (MHD) models. The results of novel 2D hybrid simulations (fluid electrons and full-orbit kinetic ions) of FRC merging and compression are presented. Results of kinetic and MHD simulations, computed using the HYM code, are compared and analyzed. In cases without axial magnetic compression, both the MHD and hybrid simulations show a high sensitivity to the initial parameters (i.e. FRC separation, velocity, normalized separatrix radius, and plasma viscosity), showing that FRCs with large elongation and separatrix radius either do not merge or merge partially, forming a doublet FRC. In conclusion, application of a mirror coil field at the FRC ends with increasing strength is shown to lead to fast and complete merging of the FRCs in MHD and kinetic simulations.

FRC↗
DOE OSTI2023

Same-sided successive-shock HED instability experiments

Inertial confinement fusion (ICF) and high-energy density (HED) physics experiments experience complicated forcing for instability growth and mix due to the ubiquitous presence of multiple shocks interacting with perturbations on multiple material interfaces. One common driver of instability growth is successive shocks from the same direction. However, there is a severe lack of analytic work and modeling validation for same-sided successive shocks since they are extremely difficult to achieve with conventional (non-HED) drivers. Successive shocks access a large instability parameter space; idealized fluid theory [K. O. Mikaelian, Phys. Rev. A 31, 410 (1985)] predicts 15 different interface evolution scenarios for a sinusoidal perturbation. Growth becomes more complex for multi-mode, compressible HED systems. The Mshock campaign is the first experiment in any fluid regime to probe a wide portion of successive shock parameter space. This is enabled by our development of a hybrid direct/indirect drive platform capable of creating independently controllable successive shocks on the National Ignition Facility. These experiments have delivered the first data capable of rigorously challenging our models and their ability to accurately capture Richtmyer–Meshkov growth under successive shocks. Single-mode and two-mode experiments have successfully demonstrated the ability to access and control the various growth scenarios of the shocked interface, including re-inversion, freeze out, and continued growth. Simulations and theoretical modeling are shown to accurately capture the experimental observations in the linear growth phase, giving us confidence in our ICF/HED design codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Nuclear data uncertainty propagation and modeling uncertainty impact evaluation in neutronics core simulation

Uncertainty analysis is a critical requirement in reactor simulation as it is used to quantify the reliability of best-estimate calculation. A comprehensive uncertainty analysis should characterize all sources of uncertainties in a computationally-feasible and scientifically-defendable manner. Here we employ a well-established reduced order modeling (ROM) based uncertainty quantification methodology to propagate uncertainties throughout neutronic calculations. ROM relies on recent advances in randomized data mining techniques applied to large data streams. In our proposed implementation, the nuclear data uncertainties are first propagated from multi-group level through lattice physics calculation to generate few-group parameter uncertainties, described using a vector of mean values and a covariance matrix. Employing an ROM-based compression of the covariance matrix, the few-group uncertainties are then propagated through downstream core simulation in a computationally efficient manner. This straightforward approach, albeit efficient as compared to brute force forward and/or adjoint-based methods, often employs a number of assumptions that have been unquestioned in the literature of neutronic uncertainty analysis. This manuscript argues that these assumptions could introduce another source of uncertainty referred to as modeling uncertainties, whose magnitude needs to be quantified in tandem with nuclear data uncertainties. Thus, our primary goal is to explore the interactions between these two uncertainty sources in order to assess whether modeling uncertainties have an impact on parameter uncertainties. To explore this endeavor, the impact of a number of modeling assumptions on core attributes uncertainties is quantified. The study employs a CANDU reactor model, with Serpent and NEWT as lattice physics solvers and NESTLE-C as core simulator. The modeling assumptions investigated include those related with the uncertainty propagation method employed, e.g., deterministic vs. stochastic, the few-group energy structure employed to represent the cross-sections, the resonance treatment in lattice physics calculation, the reference values for the cross-section, and the number of samples employed to render ROM compression. Results indicate that some of the modeling assumptions could have a non-negligible impact on the core responses propagated uncertainties, highlighting the need for a more comprehensive approach to combine parameter and modeling uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Compression behavior of microcrystalline cellulose spheres: Single particle compression and confined bulk compression across regimes

Particle characteristics can drastically influence the process-structure-property-performance aspects of granular materials in compression. In this study, we aim to computationally simulate the mechanical processes of stress redistribution in compacts including the kinematics of particle rearrangement during densification and particle deformation leading to fragmentation. Confined compression experiments are conducted with three sets of commercial microcrystalline cellulose particles nearly spherical in shape with different mean particle size. Experimentally measured compression curves from tall powder columns are fitted with the Kenkre et al. (J. of American Chemical Society, Vol. 79, No. 12) model. This model provides a basis to derive several common two-parameter literature models and as a framework to incorporate statistical representations of critical particle behaviors. We focus on the low-stress compression data and the model comparisons typically not discussed in the literature. Furthermore, additional single particle compressions report fracture strength with particle size for comparison to the apparent particle strength extracted from bulk compression data.

42 ENGINEERING↗
DOE OSTI2021

Oxidation and pyrolysis of methyl propyl ether

The ignition, oxidation, and pyrolysis chemistry of methyl propyl ether (MPE) was probed experimentally at several different conditions, and a comprehensive chemical kinetic model was constructed to help understand the observations, with many of the key parameters computed using quantum chemistry and transition state theory. Experiments were carried out in a shock tube measuring time variation of CO concentrations, in a flow tube measuring product concentrations, and in a rapid compression machine (RCM) measuring ignition delay times. The detailed reaction mechanism was constructed using the Reaction Mechanism Generator software. Sensitivity and flux analyses were used to identify key rate and thermochemical parameters, which were then computed using quantum chemistry to improve the mechanism. Validation of the final model against the 1-20 bar 600-1500 K experimental data is presented with a discussion of the kinetics. The model is in excellent agreement with most of the shock tube and RCM data. Strong non-monotonic variation in conversion and product distribution is observed in the flow-tube experiments as the temperature is increased, and unusually strong pressure dependence and significant heat release during the compression stroke is observed in the RCM experiments. These observations are largely explained by a close competition between radical decomposition and addition to O2 at different sites in MPE; this causes small shifts in conditions to lead to big shifts in the dominant reaction pathways. The validated mechanism was used to study the chemistry occurring during ignition in a diesel engine, simulated using Ignition Quality Test (IQT) conditions. At the IQT conditions, where the MPE concentration is higher, bimolecular reactions of peroxy radicals are much more important than in the RCM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Generation of strong fields with subcritical density plasmas to study the phase transitions of magnetized warm dense matter

Warm dense matter (WDM) is a regime where Fermi degenerate electrons play an important role in the macroscopic properties of a material. Recent experiments have brought us closer to understanding unmagnetized processes in WDM, but magnetized WDM remains unexplored because kilotesla magnetic fields are required. Although there are examples of field compression generating such fields by imploding pre-magnetized targets, these existing methods give no independent control over the parameters of the magnetized plasma and result in limited laser access for sample creation and diagnosis. In this paper, numerical simulations show that kilotesla magnetic fields can be obtained by shining laser beams onto the inner surface of a cylindrical target, rather than on the outer surface. This approach relies on field compression by a low-density, high-temperature plasma, rather than a high-density, low-temperature plasma, used in the more conventional approach. With this novel configuration, the region of peak magnetic field is mostly free of plasma, hence, other beams can reach a sample placed in the region of the peak field to form WDM and diagnose it.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Assessment of a tomography-informed polyhedral discrete element modelling approach for complex-shaped granular woody biomass in stress consolidation

The design of handling equipment for granular biomass primarily requires experiments. Discrete element models (DEM) can provide designers with detailed insight into the behaviour of granular materials. However, granular biomass comprising complex-shaped particles is difficult to model with DEM. A tomography-informed DEM approach and an exhaustive assessment of the ability of the approach to predict the bulk behaviour of milled pines using experimental data is presented. Nano-CT scan was conducted to obtain 3D particle surface geometries as the basis for particle shape approximation by a polyhedral model and a sphero-polyhedral model. These models were applied in the simulation of a compressibility test. Our parametric study showed that particle Young's modulus and restitution coefficient are the two main properties influencing the simulated bulk behaviour of the DEM particles and that the level of approximating DEM particle shape for real particles is critical for accurately replicating the bulk behaviour of milled pines. The polyhedral model demonstrated better suitability than its sphero-polyhedral counterpart for modelling pine particles. The polyhedral model calibrated in a compressibility test was then applied in the simulations of a friction test without additional parameter tuning. Interlocking was dominant in the shear of bulk pine particles. Remarkably, the polyhedral model predicted the frictional behaviour of the pine particles when compared to the experimental results. The limitations of the model, as well as possible ways for enhancement, are discussed. This work provided novel insights into the suitability of complex-shaped DEM models for granular woody biomass.

Biomass flow↗
DOE OSTI2025

Bayesian learning with Gaussian processes for low-dimensional representations of time-dependent nonlinear systems

This work presents a data-driven method for learning low-dimensional time-dependent physics-based surrogate models whose predictions are endowed with uncertainty estimates. We use the operator inference approach to model reduction that poses the problem of learning low-dimensional model terms as a regression of state space data and corresponding time derivatives by minimizing the residual of reduced system equations. Standard operator inference models perform well with accurate training data that are dense in time, but producing stable and accurate models when the state data are noisy and/or sparse in time remains a challenge. Another challenge is the lack of uncertainty estimation for the predictions from the operator inference models. Our approach addresses these challenges by incorporating Gaussian process surrogates into the operator inference framework to (1) probabilistically describe uncertainties in the state predictions and (2) procure analytical time derivative estimates with quantified uncertainties. The formulation leads to a generalized least-squares regression and, ultimately, reduced-order models that are described probabilistically with a closed-form expression for the posterior distribution of the operators. The resulting probabilistic surrogate model propagates uncertainties from the observed state data to reduced-order predictions. Furthermore, we demonstrate the method is effective for constructing low-dimensional models of two nonlinear partial differential equations representing a compressible flow and a nonlinear diffusion–reaction process, as well as for estimating the parameters of a low-dimensional system of nonlinear ordinary differential equations representing compartmental models in epidemiology.

Data-driven model reduction↗
DOE OSTI2020

Automated Fitting of a Semi-empirical Multiphase Equation of State for Carbon

The equation of state (EOS) of carbon is important in high explosive, geophysical, and inertial confinement fusion applications. Within the semi-empirical Sesame framework, the EOS of each phase is represented by a sum of cold, vibrational, and thermal electronic Helmholtz free energy contributions. Each phase has ~5-10 independent parameters that are adjusted to reproduce single-phase data (e.g., thermal expansion, isothermal compression) as well as experimentally- and computationally- derived phase boundaries. Manual calibration of the full multiphase EOS is arduous. We present our progress in development of automated EOS parameterization based on minimization of an objective function. Here, this function encodes deviation of model EOS results from experimental/computational benchmarks. Optimization is implemented as a combination of global (particle swarm) and local optimization techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Highly efficient libraries design for saturation mutagenesis

Abstract Saturation mutagenesis is a semi-rational approach for protein engineering where sites are saturated either entirely or partially to include amino acids of interest. We previously reported on a codon compression algorithm, where a set of minimal degenerate codons are selected according to user-defined parameters such as the target organism, type of saturation and usage levels. Here, we communicate an addition to our web tool that considers the distance between the wild-type codon and the library, depending on its purpose. These forms of restricted collections further reduce library size, lowering downstream screening efforts or, in turn, allowing more comprehensive saturation of multiple sites. The library design tool can be accessed via http://www.dynamcc.com/dynamcc_d/. Graphical Abstract

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Nonlinear ablative Rayleigh-Taylor instability: Increased growth due to self-generated magnetic fields

The growth rate of the nonlinear ablative Rayleigh-Taylor (RT) instability is enhanced by magnetic fields self-generated by the Biermann battery mechanism; a scaling for this effect with perturbation height and wavelength is proposed and validated with extended-magnetohydrodynamic simulations. The magnetic flux generation rate around a single RT spike is found to scale with the spike height. The Hall parameter, which quantifies electron magnetization, is found to be strongly enhanced for short-wavelength spikes due to Nernst compression of the magnetic field at the spike tip. Furthermore, the impact of the magnetic field on spike growth is through both the suppressed thermal conduction into the unstable spike and the Righi-Leduc heat flow deflecting heat from the spike tip to the base. Righi-Leduc is found to be the dominant effect for small Hall parameters, while suppressed thermal conduction dominates for large Hall parameters. These results demonstrate the importance of considering magnetic fields in all perturbed inertial confinement fusion hot spots.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Effect of geometry and operational parameters on the dehumidification performance of a desiccant coated heat exchanger

Solid desiccant dehumidification systems are an alternative to vapor-compression-based air dehumidification systems. They use solid desiccant materials to adsorb air moisture in space cooling. DCHE can integrate the cooling component in the heat exchanger to achieve higher dehumidification capacity. Comprehensive numeric modeling would be necessary to assist in the design and operation of the DCHE under development to achieve maximum performance. Here, we provide the details of a heat and mass transfer model developed for this purpose. The model aims to cover a gap in existing models by independently modeling heat transfer on the solid desiccant, fin, and tube. The model results were compared with an experimental reference for validation. The air outlet humidity and temperature results for dehumidification and regeneration showed a deviation lower than 15% from the experiment. The validated model was used to perform a parametric study for a series of design and operating conditions. The parametric analysis showed that an increase of 25% in desiccant layer thickness and thermal contact resistance between solid elements reduces moisture removal by 9.1% and 1%, respectively. These results indicate the need to independently model the desiccant layer.

42 ENGINEERING↗