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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 487 records · Page 27

Estimating ionization states and continuum lowering from ab initio path integral Monte Carlo simulations for warm dense hydrogen

Warm dense matter (WDM) is an active field of research, with applications ranging from astrophysics to inertial confinement fusion. Ionization degree and continuum lowering are important quantities to understand how materials behave under these conditions, but can be difficult to diagnose since experimental campaigns are limited and often require model-dependent analysis. This is especially true for hydrogen, which has a comparably low scattering cross section, making high-quality data particularly difficult to obtain. Consequently, building equation of state tables often relies on simulations in combination with untested approximations to extract properties from experiments. Here, we investigate an approach for extracting the ionization potential depression and ionization degree—quantities which are otherwise not directly accessible from the physical model—from first-principles path integral Monte Carlo (PIMC) simulations utilizing a chemical model. In contrast to experimental measurements, where noise and nonequilibrium effects add to the uncertainty of the inferred parameters, PIMC simulations provide a clean signal with well-defined thermodynamic conditions. Comparisons against commonly used models show a qualitative agreement, but we find deviations primarily for the high-density and high-temperature cases. We also demonstrate the decreasing sensitivity of the dynamic structure factor with respect to both ionization and continuum lowering for increasing scattering angles in x-ray Thomson scattering experiments. Our work has important implications for the design of future experiments, but also offers qualitative understanding of structure factors and the imaginary-time correlation function obtained from first-principles quantum Monte Carlo simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Legal Judgment Prediction Based on Multiclass Information Fusion

Legal judgment prediction (LJP), as an effective and critical application in legal assistant systems, aims to determine the judgment results according to the information based on the fact determination. In real-world scenarios, to deal with the criminal cases, judges not only take advantage of the fact description, but also consider the external information, such as the basic information of defendant and the court view. However, most existing works take the fact description as the sole input for LJP and ignore the external information. We propose a Transformer-Hierarchical-Attention-Multi-Extra (THME) Network to make full use of the information based on the fact determination. We conduct experiments on a real-world large-scale dataset of criminal cases in the civil law system. Experimental results show that our method outperforms state-of-the-art LJP methods on all judgment prediction tasks.

Zhu, Kongfan↗

WarpX: Delivering Unprecedented Particle-in-Cell Simulation Capability

Since 1939, more than 30 percent of all Nobel prizes in physics and four of the past 14 prizes in chemistry have been awarded for work with particle accelerators. These tools are now used to treat cancer and produce medical supplies, support research in applied fields such as pharmaceuticals, create microcircuits, and sterilize food—and the applications list continues to grow. However, the size of the facilities needed to house these machines—which are often dozens of kilometers long—has limited their future potential. Thus, researchers are motivated to create novel particle accelerator designs that provide new imaging capability but have a much smaller footprint. The Exascale Computing Project’s WarpX application captures the full complexity of the acceleration processes within plasma-based design, supporting the rapid and cost-efficient development of tens of thousands of new particle accelerators for various applications from improving human health to nuclear fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A fusion based plasma propulsion system

The Fusion Plasma Propulsion System scoping study was performed to investigate the possibilities of a fusion powered plasma propulsion system for space applications. Specifically, it was to be compared against existing electric propulsion concepts for a manned Mars mission. Design parameters consist of 1000 N thrust for 500 days, and the minimum mass possible. This investigation is briefly presented and conclusions drawn.

George, J. A.↗

Loading Considerations for Implementing Friction STIR Welding for Large Diameter Tank Fabrication

The main objectives of the research presented here are to determine the reaction loads associated with friction stir welding (FSW) and to determine the suitability of an existing welding fixture for implementing this welding process in the fabrication of large diameter tanks. Friction stir welding is a relatively new process which is being investigated as a method for joining aluminum alloys. The aluminum-lithium alloy, Al-Li 2195, which is being used to fabricate the super-light-weight shuttle external tank has proven difficult to join using fusion techniques. Therefore, FSW and its potential applicability to joining Al-Li 2195 are of particular interest to NASA.

Adams, Glynn↗

Data Acquisition Systems

In the mid-1980s, Kinetic Systems and Langley Research Center determined that high speed CAMAC (Computer Automated Measurement and Control) data acquisition systems could significantly improve Langley's ARTS (Advanced Real Time Simulation) system. The ARTS system supports flight simulation R&D, and the CAMAC equipment allowed 32 high performance simulators to be controlled by centrally located host computers. This technology broadened Kinetic Systems' capabilities and led to several commercial applications. One of them is General Atomics' fusion research program. Kinetic Systems equipment allows tokamak data to be acquired four to 15 times more rapidly. Ford Motor company uses the same technology to control and monitor transmission testing facilities.

Source record↗

Radiation Heat Transfer Modeling Improved for Phase-Change, Thermal Energy Storage Systems

Spacecraft solar dynamic power systems typically use high-temperature phase-change materials to efficiently store thermal energy for heat engine operation in orbital eclipse periods. Lithium fluoride salts are particularly well suited for this application because of their high heat of fusion, long-term stability, and appropriate melting point. Considerable attention has been focused on the development of thermal energy storage (TES) canisters that employ either pure lithium fluoride (LiF), with a melting point of 1121 K, or eutectic composition lithium-fluoride/calcium-difluoride (LiF-20CaF2), with a 1040 K melting point, as the phase-change material. Primary goals of TES canister development include maximizing the phase-change material melt fraction, minimizing the canister mass per unit of energy storage, and maximizing the phase-change material thermal charge/discharge rates within the limits posed by the container structure.

Kerslake, Thomas W.↗

NASA Armstrong Flight Research Center Dynamics and Controls (530)

AFRC Controls and Dynamics Branch - Research Areas: - Traditional GN&C - Classical and advanced control algorithms - Risk based approaches for safety critical applications - Integration of novel sensors and sensor fusion (FOSS, LIDAR, etc.) - Trajectory optimization and control - Flight/System Dynamics - Equations of Motion and integrated modeling of vehicles and vehicle systems - Unique and novel vehicle dynamics - Methods for extracting relevant vehicle dynamic information from flight data - Human and vehicle interfaces and interactions - Handling Qualities and Pilot-in-the-loop oscillations (PIO) predictions and design metrics - Ride quality research - Autonomy - Novel algorithms, sensors, and sensor fusion - Bounding risk for testing automated systems - Pilot/Operator interactions - Engineering Support and Airworthiness Assessments - Aircraft modifications and experimental configurations

Chris Miller↗

A high strength Al-2Ni-0.5Zr conductor alloy fabricated via laser powder bed fusion

There is a current need for new aluminum alloy design strategies to target applications requiring high strength and conductivity with reductions in mass. A new lightweight Al-2Ni-0.5Zr (wt. %) conductor alloy was fabricated using laser powder bed fusion. A design of experiments probed the alloy's solidification cracking susceptibility. It was observed that solidification cracking was generally reduced with fast scan speeds, above 1500 mm/s, and smaller hatch spacings. The different cooling rates throughout the melt pool produced a heterogeneous distribution of cellular and equiaxed Al 3 Ni precipitates in the as-printed alloy. Additionally, the rapid solidification characteristic of laser powder bed fusion created a super-saturated Zr solid solution. An aging heat treatment at 375 °C for 24 h imparted strengthening through the precipitation of L1 2 -Al 3 Zr nanoprecipitates, which counteracted the softening caused by the fragmentation and coarsening of Al 3 Ni precipitates. The yield strength increased from 138 MPa in the as-printed condition to 168 MPa after aging, while the ductility remained constant at ∼21%. The aging treatment simultaneously increased the electrical conductivity from 40.8% IACS (International Annealed Copper Standard) to 53.5% IACS. Modeling of the strengthening mechanisms and electrical conductivity contributions rationalized the simultaneous increase in strength and conductivity upon aging. Furthermore, the strengthening efficacy of the Al 3 Ni and L1 2 -Al 3 Zr precipitates, combined with the low Ni and Zr solubility in the FCC Al matrix, facilitated both high strength and electrical conductivity. Overall, the combination of strength and electrical conductivity positions this alloy as a suitable choice for additively manufactured lightweight conductors.

Additive manufacturing↗

Trace impurity transport in multi-species plasmas with large particle fluxes

A burning fusion plasma has a large inwards flux of fuel and outwards flux of ash. Existing impurity transport theories do not account for a steady-state environment of such large fluxes. In this paper, we extend classical transport theory to account for a background of such fluxes. In a mainly two-ion species magnetized plasma, with oppositely directed density gradients maintained by oppositely directed sources of the two species, trace impurity ions are shown to align with the larger mass ions. This unexpected behavior is derived analytically and simulated numerically using the MITNS (Multiple-Ion Transport Numerical Solver) code. Overall, the result suggests a potential advantage of edge-fueled p-B11 fusion in extracting high-Z impurities, and possible applications in plasma-based separation methods.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Preliminary Design of Ironless Linear Induction Motors for ITER MSE Shutter Actuators

In this article, the shutters need to be closed or opened during the operation and calibration period time for the fusion diagnostic systems, such as the International Thermonuclear Experimental Reactor (ITER) motional stark effect (MSE). Standard electric motors and actuators will not work in a strong magnetic field environment due to the presence of the magnetic field of fusion reactors. The innovative linear induction motor (LIM) with an ironless feature overcomes this kind of challenge and can be used for any application that requires controlled motion with a large stroke in the magnetic field environment. It consists of a high-electrical conductivity plate like copper and three-phase motor windings with nonferrous or stainless-steel stators. The conductor plate attached with the shutter is simply driven by the underneath three-phase linear windings to achieve linear motion. The motor drive can be controlled remotely by a controller using the electrical connection, so no sensitive electronic components are located in the harsh environment where the motor itself is located. The design requirements and test facility have been described. Several 3-D transient Maxwell electromagnetic (EM) models with different locations of three-phase linear motor windings and shutter stators have been analyzed and evolved to meet any applications allowed in the harsh environment inside the vacuum vessel of fusion reactors. The preliminary design results are presented in this article.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Performance of Pulsed Thermal Tomography Imaging with Machine Learning-Based Classification of Defects in Additively Manufactured Structures

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermal Tomography Imaging (PTT) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTT capabilities in detecting and visualizing microscopic defects in metallic specimens. The thermal tomography (TT) algorithm obtains depth reconstructions of spatial effusivity from the data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring of images with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images. CNN is trained on a database of TT images created for a set of simulated metallic structures with elliptical subsurface voids. Test of CNN performance demonstrate the ability to classify radii and angular orientation of subsurface defects in TT images. In addition, we have shown that CNN trained on elliptical defects is capable of classifying irregular-shaped defects obtained from scanning electron microscopy (SEM) of stainless steel sections printed with LPBF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

GLUE Code: A framework handling communication and interfaces between scales

Many scientific applications are inherently multiscale in nature. Such complex physical phenomena often require simultaneous execution and coordination of simulations spanning multiple time and length scales. This is possible by combining expensive small-scale simulations (such as molecular dynamics simulations) with larger scale simulations (such continuum limit/hydro solvers) to allow for considerably larger systems using task and data parallelism. However, the granularity of the tasks can be very large and often leads to load imbalance. Traditionally, we use approximations to streamline the computation of the more costly interactions and this introduces trade-offs between simulation cost and accuracy. In recent years, the available computational power and the advances in machine learning have made computing these scale-bridging interactions and multiscale simulations more feasible. One driving application has been plasma modeling in inertial confinement fusion (ICF), which is fundamentally multiscale in nature. This requires deep understanding of how to extrapolate microscopic information into macroscopically relevant scales. For example, in ICF one needs an accurate understanding of the connection between experimental observables and the underlying microphysics. The properties of the larger scales are often affected by the microscale behavior incorporated usually into the equations of state and ionic and electronic transport coefficients (Liboff, 1959; Rinderknecht et al., 2014; Rosenberg et al., 2015; Ross et al., 2017). Instead of incorporating this information using reliable molecular dynamics (MD) simulations, one often needs to use theoretical models, due to the inability of MD to reach engineering scales (Glosli et al., 2007; Marinak et al., 1998). One approach to resolve this issue is by coupling two MD simulations of different scales via force interpolation, e.g., the AdResS method (Krekeler et al., 2018; Nagarajan et al., 2013). Another approach, which we will pursue in the scope of this work, is by enabling scale bridging between MD simulations and meso/macro-scale models through the development and support of application programming interfaces that these different applications can interact through.

54 ENVIRONMENTAL SCIENCES↗

Performance Validation of Pulsed Thermal Imaging System for In-Service Applications

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which has the capability of melting metallic powder and net shaping the structures with relatively high precision. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermography Imaging (PTI) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTI method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTI method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTI system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTI capabilities in detecting microscopic defects in metallic specimens. SS316 and IN718 specimens were developed with a pattern of subsurface calibrated flat bottom hole (FBH) defects with diameters from 500µm to 200µm. FBH’s were created with EDM (electron discharge machining) drill. PTI imaging data was processed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) algorithm. We show that defects as small as 200µm in SS316 and IN718 can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature.

42 ENGINEERING↗

Performance of Compact Pulsed Thermal Imaging System for In-Service Applications. Pulsed thermal tomography nondestructive examination of additively manufactured reactor materials and components

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which has the capability of melting metallic powder and net shaping the structures with relatively high precision. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to creep in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures nondestructively. Pulsed Thermography (PT) imaging provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. The data cube of PT measurements consists of surface temperature taken at sequential time intervals T(x,y,t). Material defects can be detected either by analyzing the thermograms T(x,y,t) data cube, or by using thermal tomography (TT) algorithm to obtain 3D spatial reconstruction of thermal effusivity e(x,y,z). To reduce the cost and enable in-service NDE in spatially constrained environment, it is highly desirable to develop PT with compact and inexpensive IR camera. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact PT system can also be used for in-service nondestructive evaluation (NDE) applications. However, data cube obtained with PT based on compact IR camera suffers from strong thermal noises and loss of features due to relatively low sampling rate. In this report we describe two unsupervised machine learning (ML) algorithms for enhancement of PT images obtained with compact IR camera. In one approach, we introduce Sparse Coding Discrete Cosine Transform (SC/DCT) algorithm to remove additive white Gaussian noise (AWGN) from spatial thermal effusivity reconstructions. In another approach we introduce a Spatial Temporal Denoised Thermal Source Separation (STDTSS) ML algorithm to process thermograms. The STDTSS algorithm consists of spatial and temporal denoising using Gaussian and Savitzky–Golay filtering, followed by the matrix decomposition using Principal Component Analysis (PCA), and Independent Component Analysis (ICA) to automatically detect flaws. In the work described in this report, we constructed a compact PT system using a relatively small and low-cost FLIR A65 camera, consisting on uncooled microbolometer detector. Performance of SC/DCT algorithm was demonstrated on enhancing TT images of Inconel 718 AM plate. Performance of the STDTSS methods was investigated using thermography data obtained from imaging stainless steel 316L specimens produced with LPBF method with imprinted calibrated porosity defects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗