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NASA NTRS2007

Adaptive Modeling of the International Space Station Electrical Power System

Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

Thomas, Justin Ray↗

DOE OSTI2024

Solidification and crystallographic texture modeling of laser powder bed fusion Ti-6Al-4V using finite difference-monte carlo method

Laser powder bed fusion (LPBF) additive manufacturing makes near-net-shaped parts with reduced material cost and time, rising as a promising technology to fabricate Ti-6Al-4V, a widely used titanium alloy in aerospace and medical industries. However, LPBF Ti-6Al-4V parts produced with 67° rotation between layers, a scan strategy commonly used to reduce microstructure and property inhomogeneity, have varying grain morphologies and weak crystallographic textures that change depending on processing parameters. Here, this study predicts LPBF Ti-6Al-4V solidification at three energy levels using a finite difference-Monte Carlo method and validates the simulations with large-area electron backscatter diffraction (EBSD) scans. The developed model accurately shows that a <001> texture forms at low energy and a <111> texture occurs at higher energies parallel to the build direction but with a lower strength than the textures observed from EBSD. A validated and well-established method of combining spatial correlation and general spherical harmonics representation of texture is developed to calculate a difference score between simulations and experiments. The quantitative comparison enables effective fine-tuning of nucleation density (N 0 ) input, which shows a nonlinear relationship with increasing energy level. Future improvements in texture prediction code and a more comprehensive study of N 0 with different energy levels will further advance the optimization of LPBF Ti-6Al-4V components. These developments contribute a novel understanding of crystallographic texture formation in LPBF Ti-6Al-4V, the development of robust model validation and calibration pipeline methodologies, and provide a platform for mechanical property prediction and process parameter optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Investigating Fast Scanning Calorimetry and Differential Scanning Calorimetry as Screening Tools for Thermoset Polymer Material Compatibility with Laser-Based Powder Bed Fusion

As additive manufacturing (AM) technology has developed and progressed, a constant topic of research in the area is expanding the library of materials to be used with these techniques. Among AM methods that utilize polymers, laser-based powder bed fusion (PBF-LB) has preferentially used thermoplastic polymers as its starting materials, but the deposition and material joining method employed in PBF-LB may also be compatible with powdered thermoset polymer precursors as feedstocks. To assess the compatibility of candidate thermosetting polymers and PBF-LB, characterization techniques and protocols that link fundamental material behavior to material behavior in the processing environment are needed. Therefore, the objectives of this work are to compare the curing behavior measured with two different calorimetry techniques that can operate in different heating rate regimes, differential scanning calorimetry (DSC) and fast scanning calorimetry (FSC), and to assess the capabilities of these techniques to act as materials screening tools for PBF-LB. A commercial polyester powder coating is used as a model material to evaluate the potential of obtaining complimentary information for material screening through a combination of calorimetry methods, and its non-isothermal curing behavior is measured at heating rates between 5 °C/min and 7500 °C/min. Curing exotherms are observed with both calorimetry techniques, and comparing the enthalpy associated with curing shows that incomplete curing occurs at higher heating rates, with relative conversion values of approximately 30%. The curing data are fit with two isoconversional models, Friedman and Starink, which show a reduced activation energy at higher heating rates as well, signifying a lower barrier to curing at the conditions used in the FSC experiments. Overall, the results of this work indicate that using these two calorimetry techniques as tiered screening tools can provide valuable information about how curing may proceed in PBF-LB and inform materials selection and design activities for additive manufacturing.

36 MATERIALS SCIENCE↗

NASA NTRS2003

A Plasmoid Thruster for Space Propulsion

There are a number of possible advantages to using accelerated plasmoids for in-space propulsion. A plasmoid is a compact plasma structure with an integral magnetic field. They have been studied extensively in controlled fusion research and are classified according to the relative strength of the poloidal and toroidal magnetic field (BP and Bt, respectively). An Object with B P t >> 1 is classified as a Field Reverse Configuration (FRC); if B, = Bt, it is called a Spheromak. The plasmoid thruster operates by producing FRC-like plasmoids, and subsequently ejecting them from the device at high velocity. The plasmoid is formed inside of a single turn conical theta-pinch coil. As this process is inductive, there are no electrodes. Similar experiments have yielded plasmoid velocities of at least 50 km/s (l), and calculations indicate that velocities in excess of 100 km/s should be possible. This concept should be capable of producing Isp s in the range of 5,000 - 10,000 s with thrust densities of order 10(exp 5) N/sq m. The current experiment is designed to produce jet powers in the range of 5-10 kW, although the concept should be scalable to several MW s. The plasmoids mass and velocity will be measured with a variety of diagnostics, including internal and external B-dot probes, flux loops, Langmuir probes, high-speed cameras, and a laser interferometer. Also of key importance will be measurements of the efficiency and mass utilization. Simulations of the plasmoid thruster using MOQUI, a time dependent MHD code, will be carried out concurrently with experimental testing.

Koelfgen, Syri J.↗

NASA NTRS2012

Lidar Remote Sensing of Forests: New Instruments and Modeling Capabilities

Lidar instruments provide scientists with the unique opportunity to characterize the 3D structure of forest ecosystems. This information allows us to estimate properties such as wood volume, biomass density, stocking density, canopy cover, and leaf area. Structural information also can be used as drivers for photosynthesis and ecosystem demography models to predict forest growth and carbon sequestration. All lidars use time-in-flight measurements to compute accurate ranging measurements; however, there is a wide range of instruments and data types that are currently available, and instrument technology continues to advance at a rapid pace. This seminar will present new technologies that are in use and under development at NASA for airborne and space-based missions. Opportunities for instrument and data fusion will also be discussed, as Dr. Cook is the PI for G-LiHT, Goddard's LiDAR, Hyperspectral, and Thermal airborne imager. Lastly, this talk will introduce radiative transfer models that can simulate interactions between laser light and forest canopies. Developing modeling capabilities is important for providing continuity between observations made with different lidars, and to assist the design of new instruments. Dr. Bruce Cook is a research scientist in NASA's Biospheric Sciences Laboratory at Goddard Space Flight Center, and has more than 25 years of experience conducting research on ecosystem processes, soil biogeochemistry, and exchange of carbon, water vapor and energy between the terrestrial biosphere and atmosphere. His research interests include the combined use of lidar, hyperspectral, and thermal data for characterizing ecosystem form and function. He is Deputy Project Scientist for the Landsat Data Continuity Mission (LDCM); Project Manager for NASA s Carbon Monitoring System (CMS) pilot project for local-scale forest biomass; and PI of Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) airborne imager.

Cook, Bruce D.↗

DOE OSTI2021

Predicting structural material degradation in advanced nuclear reactors with ion irradiation

Swelling associated with the formation and growth of cavities is among the most damaging of radiation-induced degradation modes for structural materials in advanced nuclear reactor concepts. Ion irradiation has emerged as the only practical option to rapidly assess swelling in candidate materials. For decades, researchers have tried to simulate the harsh environment in a nuclear reactor in the laboratory at an accelerated rate. Here we present the first case in which swelling in a candidate alloy irradiated ~ 2 years in a nuclear reactor was replicated using dual ion irradiation in ~ 1 day with precise control over damage rate, helium injection rate, and temperature and utilize physical models to predict the effects of radiation in reactors. The capability to predict and replicate the complex processes surrounding cavity nucleation and growth across many decades of radiation dose rate highlights the potential of accelerated radiation damage experiments. More importantly, it demonstrates the capability to predict the swelling evolution and the possibility to predict other features of the irradiated microstructure evolution that control material property degradation required to accelerate the development of new, radiation-tolerant materials.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Simulation of supersonic molecular beam injection fueling into H-mode plasmas on EAST using BOUT++

Transport dynamic 2D simulations for supersonic molecular beam injection (SMBI) fueling into H-mode deuterium plasmas on the Experimental Advanced Superconducting Tokamak (EAST) is first simulated using a seven-field two-fluid model in the BOUT++ framework. The SMB is assumed to be injected into plasma from the midplane at the low field side with a fixed width and constant molecular flux. The different densities and injection velocities of SMBI are investigated within the upper single-null geometry of EAST. The simulations indicate that the SMBI has a self-shielding effect on molecules' inward transport into the plasma, and the deposition of SMBI leads to a large increase in plasma density and decrease in plasma temperature. There is a velocity threshold for SMB penetrating the pedestal and depositing at the top of density pedestal. However, the deposition point would be back toward the plasma boundary after SMB arriving at the deepest penetration position. Comparing the different molecular injection velocities and densities, the outcomes demonstrate that the depth of deposition is closely related to the injection velocity rather than the molecular density. The simulated results show good agreement with the EAST experiments by comparing the electron density profiles obtained by simulation and experiment, respectively. These results will be helpful for guiding future experiments, as well as the design of the SMBI system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

3D Equilibrium Reconstruction and MHD Studies in Stellarators (Final Report)

This is the final technical report for the grant Three Dimensional Equilibrium Reconstruction and MHD Studies in Stellarators. The major goals of this project were to: further develop V3FIT code capabilities, continue to support experiments using the V3FIT code, continue theoretical support for the CTH experiment at Auburn, particularly in the area of NIMROD simulations of CTH discharges. Dr. Lopez Ortiz has made significant progress on his analysis of NIMROD simulations of CTH MHD phenomena. In particular, his study has focused on the fixed point dynamics and energy flow amongst toroidal Fourier modes in sawtooth oscillations simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Ionization-Based Optical Structures for the Control of Short-Pulse Lasers (Full LDRD Report)

High-power lasers require enormous beam sizes to avoid optics damage; without plasma control of light, future higher-power systems will have prohibitive costs. The laser-induced formation of ionization patterns in gases provides an opportunity to manipulate the spatial and temporal properties of femtosecond to picosecond beams with precise control at high intensity, providing a path towards compact multi-petawatt lasers. In this project, we proposed new concepts of diffractive optics elements relying on ionization-based structures, including a holographic lens and a compression grating. The theoretical characterization of these optical elements was supported by particle-in-cell simulations. Experiments have been carried out to achieve reflective elements (i.e., plasma-based gratings) that demonstrated high robustness and efficiencies on the order of 50%, which validates the feasibility of our new concepts and paves the way for future plasma-based high-power laser systems.

47 OTHER INSTRUMENTATION↗

NASA NTRSDate not supplied

Additive Manufacturing for Propulsion Systems

Additive Manufacturing (AM) has become a prominent technology of interest for manufacturing propulsion components and gaining attention across the aerospace industry. AM is maturing at a rapid pace and providing new design opportunities, novel materials, new industries and supply chains resulting in programmatic and technical performance improvements. The successful use of AM requires a methodical and intentional approach to understanding the concept to utilization lifecycle for AM. This course will provide an overview of the various steps in AM process trades, design, build process, post-processing, certification and infusion of AM. This will provide various lessons learned and experiences that were captured in a recent AIAA textbook titled "Metal Additive Manufacturing for Propulsion Applications" by the session chairs and industry colleagues. This course will include specific liquid rocket engine component examples and that went through the AM lifecycle including hot-fire testing.

Additive Manufacturing↗

DOE OSTI2025

Quantum Information for Fusion Energy Sciences (Final Technical Report)

The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer. In order to efficiently simulate plasma physics, an optimal control method which synthesizes, directly at the pulse level, any quantum gate on qubit and qutrit systems was developed. Using four superconducting transmon quantum processors at Rigetti and LLNL, it was demonstrated that any arbitrary quantum gate on qubits and qutrits could be implemented with high fidelity, leading to a significantly reduced length of a gate sequence. A problem of interest in FES is the nonlinear optical process of laser pulse compression within a plasma. Since quantum physics is linear, simulating nonlinear operations is not naturally feasible on a quantum computer, however it is possible to simulated a quantized version of the nonlinear process. A quantization approach to convert nonlinear wave-wave interaction problems to Hamiltonian simulation problems was developed and demonstrated using two qubits on a Rigetti device. In this experiment, a number of error suppression and mitigation techniques were investigated to determine how best to utilize the finite quantum resources. This study provides an example of how plasma problems may be solved on near-term, noisy quantum computing platforms and identified a promising set of techniques. Building on the insights of these experiments, the investigation turned to linear electron-plasma wave physics. A connection was identified between a local one-dimensional lattice spin model and linear wave phenomena, allowing a plasma physics problem to be efficiently mapped to the quantum computer. In this framework, reflection and transmission of plasma waves at a sharp boundary was studied, as well as the propagation of waves through an inhomogeneous plasma medium. In addition to the suite of error suppression and mitigation techniques developed, this experiment introduced the use of a digital-analog gate scheme designed to efficiently simulate the plasma Hamiltonian. With hardware available at the conclusion of the project, simulation at the scale of 9 qubits and 15 timesteps (60 entangling layers) was achieved.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Theory uncertainties of the irreducible background to VBF Higgs production

Higgs boson production through gluon fusion in association with two jets is an irreducible background to Higgs boson production through vector boson fusion, one of the most important channels for analyzing and understanding the Higgs boson properties at the Large Hadron Collider. Despite a range of available simulation tools, precise predictions for the corresponding final states are notoriously hard to achieve. Using state-of-the-art fixed-order calculations as the baseline for a comparison, we perform a detailed study of similarities and differences in existing event generators. We provide consistent setups for the simulations that can be used to obtain identical parametric precision in various programs used by experiments. We find that NLO calculations for the two-jet final state are essential to achieve reliable predictions.

Chen, Xuan [Shandong U.] (ORCID:0000000167722196)↗

DOE OSTI2026

Combination of searches for heavy vector boson resonances in proton-proton collisions at $\sqrt{s}=13$ TeV

A combined statistical analysis of searches for heavy vector boson resonances decaying into pairs of W, Z, or Higgs bosons, as well as into quark pairs $\left(\mathrm{q}\overline{\mathrm{q}},\mathrm{b}\overline{\mathrm{b}},\mathrm{t}\overline{\mathrm{t}},\mathrm{t}\overline{\mathrm{b}}\right)$ or lepton pairs ℓ + ℓ – , ℓ$\bar{v}$, with ℓ = e, μ, τ, is presented. The results are based on proton-proton collision data at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb −1 , collected by the CMS experiment from 2016 to 2018. No significant deviation from the expectations of the standard model is observed. The results are interpreted in the simplified heavy vector triplet (HVT) framework, setting 95% confidence level upper limits on the production cross sections and on the coupling strengths of the HVT bosons to standard model particles. The results exclude HVT resonances with masses below 5.5 TeV in a weakly coupled scenario, below 4.8 TeV in a strongly coupled scenario, and up to 2.0 TeV in the case of production via vector boson fusion. The combination provides the most stringent constraints to date on new phenomena predicted by the HVT model.

beyond Standard Model↗

DOE OSTI2024

Part-scale microstructure prediction for laser powder bed fusion Ti-6Al-4V using a hybrid mechanistic and machine learning model

Laser powder bed fusion (LPBF) Ti-6Al-4V is widely studied for use in structural applications in aerospace and medical industries, but mechanical anisotropy and microstructural inhomogeneity prohibits its wider adoption. Although successful microstructure prediction models have been developed, a remaining challenge is their limited integration across length/time scales and validation by experimental studies. Here, this work proposes a physics-augmented machine learning surrogate model to unite predictions of LPBF temperature, β phase morphology and texture, and α/α’ formation into a single framework that is calibrated and validated with experiments. First, a phase field (PF) model of the martensitic β→α’ transformation is developed and calibrated using data from in-situ synchrotron cyclic heating/cooling studies quantifying the variation of α phase fraction with time. In parallel, an established finite difference-Monte Carlo (FDMC) model predicts the part-scale temperature profile and β grain formation during solidification. A dataset is developed using LPBF cyclic temperature descriptors from the FDMC model as inputs and corresponding α/α’ phase fraction and width from the PF model as outputs. Five machine learning (ML) regression models are tested and optimized, having mean absolute error in testing ≤ 4 %, and the k-nearest neighbors (KNN) model is selected as the best performing. The KNN model is called at the nodal level during post-processing of the FDMC model to replace and downscale the response of the PF model. The combined agility and accuracy of the hybrid FDMC-ML model enables part-scale microstructure predictions that can be further used for property predictions to accelerate AM process optimization.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Development of multi-scale computational frameworks to solve fusion materials science challenges

Over the past two decades, the US-DOE has funded multiple projects that rely on high-performance computing and exascale computing platforms to accelerate scientific discoveries and address grand scientific challenges, such as harnessing fusion energy. In this article, we review in detail one of these efforts aimed at enhancing our capability to model plasma-facing materials subject to plasma and high-energy ion/neutron irradiation. The plasma surface interactions project has built a multi-scale modeling framework where many of the plasma- and high-energy ion/neutron irradiation-induced effects occurring in tungsten are explored. Here, this knowledge is used to develop atomistically-informed, high-fidelity continuum and meso-scale models that can be validated against experiments. We review the developments within this project, with attention to experimental validation efforts, and specifically highlight activities associated with: helium bubble bursting and equation of state, and hydrogen-helium interactions in tungsten; atomistically-informed model development for beryllium-tungsten material mixing; coupling of scrape-of-layer plasma, sheath and material models; and coupling of stochastic cluster-dynamics and crystal plasticity models to address radiation effects in tungsten under stress. Finally, we present how the project is preparing for future computational architectures, for instance through efforts to adapt atomistic methods to exascale computing.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Simultaneous measurements of unstable and stable Alfvén eigenmodes in JET

Here, we report the novel experimental observation of both unstable and stable toroidicity-induced Alfvén eigenmodes (TAEs) measured simultaneously in a JET tokamak plasma. The three-ion-heating scheme (D-DNBI-3He) is employed to accelerate deuterons to MeV energies, thereby destabilizing TAEs with toroidal mode numbers n = 3–5, each decreasing in mode amplitude. At the same time, the Alfvén eigenmode active diagnostic resonantly excites a stable n = 6 TAE with total normalized damping rate –γ/ω 0 ≈ 1%–4%. Hybrid kinetic-MHD modeling with codes NOVA-K and MEGA both find eigenmodes with similar frequencies, mode structures, and radial locations as in experiment. NOVA-K demonstrates good agreement with the n = 3, 4, and 6 TAEs, matching the damping rate of the n = 6 mode within uncertainties and identifying radiative damping as the dominant contribution. Improved agreement is found with MEGA for all modes: the unstable n = 3–5 and stable n = 2, 6 modes, with the latter two stabilized by higher intrinsic damping and lower fast ion drive, respectively. While some discrepancies remain to be resolved, this unique validation effort gives us confidence in TAE stability predictions for future fusion devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Preliminary results addressing material qualification using combined ion irradiation and modeling data

Additively-manufactured (AM) materials have attracted increasing attention in recent years as a new method to make novel and customized components. While AM and conventionally produced materials are compositionally similar, they do possess different microstructures, necessitating assessment of materials produced via AM for their behavior in reactor environments. Some microstructures unique to AM materials, such as compositional micro-inhomogeneity and dislocation cell structures, are of particular importance since they may lead to different radiation performance. The performance of AM materials for advanced nuclear reactor applications is of interest to the Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy. The AMMT program aims to demonstrate its new accelerated development and qualification methods via laser powder bed fusion (LPBF) 316 stainless steel (SS). Focusing on material bearing both 316L and 316H specifications, we integrate ion irradiation and modeling. This year, we focus on answering foundational questions related to process variability, alloy chemistry variation, and microchemical segregation. Experimental results provide information and motivate questions to the modeling effort, which aims to develop the ability to model radiation-driven microstructural evolution in additively-manufactured 316 stainless steel under a variety of advanced reactor conditions, including different temperatures, neutron spectra, and fluxes, in a sort of "virtual experiment". We perform in-situ and ex-situ ion irradiations and microstructural characterizations to support the development of AM materials for reactor applications, develop a phase field model of radiation-induced segregation in additively manufactured material with high angle grain boundaries and dislocation cells, and investigate the effect of carbon and chromium content on point defect behavior.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Effect of Impurity Atoms on Thermonuclear Yield

The presence of impurity atoms in an inertial confinement fusion (ICF) implosion can greatly affect the burning of the thermonuclear fuel. This is a serious concern for attaining ignition as high atomic number atoms, such as carbon, can mix into the hot spot and reach the deuterium–tritium (DT) fuel, absorb energy from the implosion, and radiate away that energy. The temperature of the DT fuel drops and reduces the reactivity of the fuel resulting in lower thermonuclear yield. Fuel impurities can also be a useful diagnostic as when higher-Z atoms, such as Ar, Kr, and Xe, are purposefully mixed into the fuel. From the spectra emitted by these atoms, the temperature and density of the fuel can be deduced. The long history of using such tracer atoms by the national ICF program shows the great advances in experimental technique, diagnostic instruments, and atomic-physics modeling over the past 50 years. A particular set of experiments, the “High-Z” campaign, is reviewed in depth as this was the most systematic study of tracer element composition and quantity ever reported. Difficulties in interpreting the results of those experiments due to the limited code capabilities at that time are discussed. A main concern for the High-Z campaign was the then current state of non-Local Thermodynamic Equilibrium (nLTE) atomic physics models. The present state of nLTE modeling and its implementation in Los Alamos’s multi-physics codes is discussed in this report. To further the understanding of the complex interaction of high-Z atoms in the gas, a survey of relevant existing experimental platforms at the National Ignition Facility (NIF) and the Omega Laser Facility are presented along with the current state of pertinent diagnostics at NIF and Omega. This review concludes with a discussion of the trade-off available between temperature and volume of the imploded ICF capsule with the goal of maximizing the total yield.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗