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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Rocket engine diagnostics using neural networks

Two problems in applying neural networks to fault detection and identification are (1) the complexity of the sensor data to fault mapping and (2) the lack of sufficient training data. Here, methods are derived and tested in an architecture which addresses these two problems. First, the sensor data to fault mapping is decomposed into three simpler mappings which perform sensor data compression, hypothesis generation, and sensor fusion. Efficient training is performed for each mapping separately. Second, the neural network which performs sensor fusion is structured to detect new unknown faults for which training examples were not presented. These methods were tested on a task of fault detection and identification in the Space Shuttle Main Engine (SSME). Results indicate that the decomposed neural network architecture can be trained efficiently, can identify faults for which it has been trained, and can detect the occurrence of faults for which it has not been trained.

Whitehead, Bruce A.↗
NASA NTRS2018

Additive Manufacturing of Liquid Rocket Engine Combustion Devices: A Summary of Process Developments and Hot-Fire Testing Results

Additive Manufacturing (AM) of metals is a processing technology that has significantly matured over the last decade. For liquid propellant rocket engines, the advantages of AM for replacing conventional manufacturing of complicated and expensive metallic components and assemblies are very attractive. AM can significantly reduce hardware cost, shorten fabrication schedules, increase reliability by reducing the number of joints, and improve hardware performance by allowing fabrication of designs not feasible by conventional means. The NASA Marshall Space Flight Center (MSFC) has been involved with various forms of metallic additive manufacturing for use in liquid rocket engine component design, development, and testing since 2010. The AM technique most often used at the NASA MSFC has been powder-bed fusion or selective laser melting (SLM), although other techniques including laser directed energy deposition (DED), arc-based deposition, and laser-wire cladding techniques have also been used to develop several components. The purpose of this paper is to discuss the various internal programs at the NASA MSFC using AM to develop combustion devices hardware. To date at the NASA MSFC, combustion devices component hardware ranging in size from 100 lbf to 35,000 lbf have been designed and manufactured using SLM and deposition-based AM processes, and many of these pieces have been hot-fire tested. Combustion devices component hardware have included thrust chamber injectors, injector components such as faceplates, regeneratively-cooled combustion chambers, regeneratively-cooled nozzles, gas generator and preburner hardware, and augmented spark igniters. Ongoing and future developments for combustion devices have also included design of components sized for boost-class engines. Several design and hot-fire test iterations have been completed on these subscale and larger scale components, and a summary of these results will be presented as well.

Gradl, Paul↗
DOE OSTI2024

Enhanced joining strength in additive-manufactured polylactic-acid structures fused by embedded heated metallic meshes

Additively manufactured thermoplastic polymers, such as polylactic acid (PLA), hold significant promise for sustainable engineering structures, including wind turbine blades. Upscaling these structures beyond the limitations of 3D printer build volumes is a challenge; fusion joining presents a potential solution. This paper introduces a displacement-controlled resistance welding process for PLA, as an alternative to the typical force-controlled methods. Here, we investigated the bonding quality of resistance-welded and adhesive-bonded PLA beams through three-point bending and measured the surface deformations using digital image correlation. Different metal meshes (30%/0.11 mm Ni—Cu, 34%/0.07 mm Ni—Cu, and 36%/0.25 mm Co—Ni) served as heating elements. The process parameters were varied for the 34%/0.07 mm Ni—Cu mesh to identify an optimum set of parameters. Results showed that this optimized displacement-controlled welding achieved 94% of the original strength of monolithic samples. This indicates that the new welding process not only ensures high-quality bonding and fine surface finishing but also promotes sustainability, recyclability, and economic efficiency in various polymer and composite structural applications.

Additive manufacturing↗
DOE OSTI2025

Resonance ultrasound prediction of residual stress within a hybrid layer for additively manufactured samples

Hybrid additive manufacturing (AM) involves secondary processes or energy sources to alter specified locations within the build volume. Each hybrid step can refine the grain size, increase dislocation density, or modify residual stresses. Typically, the changes in mechanical properties are not confined within a single layer but have a compounding effect on preceding layers. Existing methods of measuring AM residual stress are limited in terms of their sensitivity, or they are destructive measurements. We propose using resonant ultrasound spectroscopy (RUS) to measure the residual stress in hybrid-AM components noninvasively, based on changes to the resonances, compared to a stress-free component. In this paper, we use finite element models to simulate residual stress in hybrid-AM components and to examine the sensitivity of RUS measurements in terms of frequency shifts and mode shapes with respect to single hybrid layers. Then, the RUS results are used to predict stress for a layer at a known location with unknown stress. Here, the approach highlights the capabilities of RUS to address an AM characterization challenge.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

In-Situ Alloying of GRCop-42 via Additive Manufacturing: Precipitate Analysis

GRCop-42, a Cu-4at% Cr-2at% Nb alloy, was designed as a high temperature, high strength, high heat flux material for rocket engine combustion chamber liners by NASA Glenn Research Center. In situ alloying of GRCop-42 (ISGRCop-42) using powder bed fusion (PBF) additive manufacturing (AM) takes elemental powders of Cu, Cr, and Nb to be introduced into the PBF environment and develop the GRCop alloy while simultaneously building an AM component. Elemental powders were milled together prior to printing in an effort to facilitate the alloying process. Success of the in situ alloying process may provide lower cost, faster lead times, alloying optimization, and more design freedom in the development of regeneratively-cooled rocket propulsion systems. Evaluation of the ISGRCop-42 was conducted using a phase extraction procedure to isolate the Cr2Nb precipitates from the pure Cu matrix. The isolated precipitates were then examined using x-ray powder diffraction (XRD), scanning electron microscopy (SEM), and energy dispersion spectroscopy (EDS). It was found that ISGRCop-42 successfully and repeatedly formed Cr2Nb at a yield as high as 89% of potential Cr2Nb. Further, it was identified that the preparation of the powder was the most influential factor in alloying success, and the second most influential factor was the laser power.

In Situ alloying↗
DOE OSTI2024

Multimodal sensor fusion for real-time standoff estimation in directed energy deposition

In Laser Powder-based Direct Energy Deposition (LP-DED) systems, achieving consistency, precision and quality of produced parts requires tight control over printing parameters. One of the critical parameters is the standoff distance. Maintaining an optimal standoff height is crucial for achieving correct laser power density and powder catchment efficiency, as both laser and powder streams are focused at this distance. Here, this study introduces a novel approach using multimodal sensor fusion to predict standoff height in real-time. The proposed system integrates two low-profile, cost-effective sensors: an RGB coaxial camera and a high frequency and high dynamic range microphone. By utilizing a simple fully connected neural network, trained on a limited dataset, data fusion of these sensors allowed for the real-time prediction of the standoff height. The results demonstrate high resolution and accuracy of the predictions across multiple geometries and a wide range of standoff heights. This approach offers a simple, and cost-effective solution for real-time standoff height monitoring and lays the groundwork for future integration into commercial LP-DED systems.

42 ENGINEERING↗
DOE OSTI2025

Cataloging Legacy Data from the Tritium Systems Test Assembly Program

The Tritium Systems Test Assembly (TSTA) at Los Alamos National Laboratory, operational from 1984 to 2001, was critical in advancing fusion fuel cycle technologies, including tritium storage, gas separation, and pumping. TSTA’s contributions, particularly in safe tritium operations, have influenced subsequent fusion projects. This paper discusses the ongoing effort to digitize and catalog TSTA’s historical data to create a searchable resource for the fusion research community. While the long-term objective is to develop a relational database for structured data management, the project remains in the early phase, with current efforts focused on scanning and indexing physical documents. Initial plans for database implementations are also presented, outlining key considerations for structure, query indexing, and standardization. As digitization progresses, future discussions will refine these implantation details to ensure an efficient and comprehensive system. This initiative aims to preserve critical legacy data, enhance the design of tritium system facilities, and support the next generation of fusion energy research.

42 ENGINEERING↗
DOE OSTI2024

A dynamic volumetric heat source model for laser additive manufacturing

Melt pool scale models of laser powder bed fusion (LPBF) offer insights into the process-structure-property relationships in additive manufacturing (AM). These models often neglect physical phenomena such as vapor cavity formation and fluid mechanics to reduce computational demands. Instead, volumetric heat source models are used to represent the effects that these phenomena have on the predicted melt pool dimensions. Generally, the dimensions and effective absorption of the volumetric heat source are calibrated to reproduce melt pool dimensions observed in metallographic cross sections taken from single-track experiments on bare plate. However, the transient nature of LPBF often deviates the melt pool dimensions from the assumed steady-state conditions of single-track experiments, motivating the need for a volumetric heat source model that more generally considers the dynamic relationship between melt pool shape and laser-material interactions. Here, we introduce a two-parameter volumetric heat source model that integrates several existing models into a generalized mathematical expression, providing independent control over the radial heat distribution via the parameter k and the volumetric shape of the heat source via the parameter m. This parameterization enables the calibration of melt pool shape predictions through simultaneous adjustment of these parameters, while keeping the radial heat source dimensions consistent with the experimental spot size (D4σ) and constraining the heat source depth and absorption to physically derived expressions for cavities. Consequently, the proposed volumetric heat source model adapts to changes in the local melt pool conditions due to scanning strategy and part geometry by dynamically adjusting the heat source depth and absorption. We demonstrate the capabilities of the proposed model through comparisons with a collection of experiments from the Additive Manufacturing Benchmark (AMBench).

36 MATERIALS SCIENCE↗
NASA NTRS1986

Advances in cryogenic engineering. Volume 31; Proceedings of the Cryogenic Engineering Conference, MIT, Cambridge, MA, Aug. 12-16, 1985

The present conference on the applications of state-of-the-art cryogenic engineering technologies considers topics associated with the development status of the 'Superconducting SuperCollider', superconducting magnetic energy storage methods, large magnets for fusion and other physics researches, cryogenic hardware improvements, and phenomena and applications of superconducting magnet-employing acoustic emission test equipment. Also discussed are design criteria for superconducting magnet stability, heat exchangers and heat transfer to liquid He and N, heat and mass transfer characteristics of He II, refrigeration techniques for magnetic resonance imaging and other small systems, refrigeration for liquefaction and for superconducting fusion as well as for accelerator and generator systems, magnetic refrigeration, cryocooling and refrigeration for space applications, the storage and transfer of cryogenic fluids, the properties of cryogenic liquids, and air liquefaction equipment.

Fast, R. W.↗
DOE OSTI2025

A future of inertial confinement fusion without laser-plasma instabilities

From the beginning of inertial confinement fusion (ICF) research, laser-plasma instabilities excited by narrowband lasers have limited the hydrodynamic design space of all laser-based approaches to inertial fusion energy (IFE). With advances in broadband laser technologies, the next generation of ICF drivers will likely have large bandwidth that is engineered to mitigate laser-plasma instabilities, thereby expanding the hydrodynamic design space to include both robust high yields (>200−MJ) with large-energy laser systems (>4 MJ) and high gains (>10) with moderate-energy laser facilities (<2 MJ). State-of-the-art simulations indicate that laser bandwidths of a few percent are required to mitigate instabilities for IFE-relevant conditions. To test these models and demonstrate that high-bandwidth lasers mitigate laser-plasma instabilities, the Fourth-generation Laser for Ultrabroadband eXperiments will be used with the OMEGA Laser System. The goal is to provide the community with the confidence to invest in a multiple-beam high-bandwidth laser facility that will demonstrate the necessary ablation pressures for robust direct-drive ignition without detrimental levels of hot electrons that degrade the implosion performance. It is important to recognize that the highest performing ICF implosions will likely never be completely LPI free because of the significant advantages to maximizing the laser intensity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Development, validation, and verification of multi-pass thermo-mechanical welding simulations using the open-source MOOSE framework: NeT TG4 benchmark weldment

This study develops and validates a sequentially coupled thermo-mechanical welding simulation for the three-pass 316L stainless steel NeT TG4 benchmark weldment using the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) and the Nuclear Engineering Material model Library (NEML). A diffused ellipsoidal heat source was calibrated against thermocouple data and weld macrographs to accurately model the fusion zone geometry and transient thermal fields. Material hardening is represented using the Lemaitre-Chaboche mixed isotropic-kinematic hardening model, while four annealing models - no annealing, single-stage at 1050 °C and 1300 °C, and two-stage at 800 °C/1300 °C - were implemented to assess the impact of annealing models on the accuracy of the predicted welding-induced plasticity, distortions, and residual stresses. The predictions were validated against experimental measurements and benchmarked against results from commercial software, demonstrating that thermo-mechanical MOOSE welding simulations achieve comparable accuracy with enhanced computational efficiency. This work highlights the potential of using open-source finite element frameworks like MOOSE for advanced manufacturing simulations.

Ji, Wendy [Australian Nuclear Science and Technolo↗
DOE OSTI2024

Technical report Letter: RAFM, ODS steels and MMLC for Nuclear energy application

The lifetime, thermodynamic efficiency, safety and economic viability of new generation fission and fusion reactor concepts can largely be tied to the mechanical performance and stability of structural alloys under extreme environments. In this context, engineered nano materials could have broad-reaching impact on the future of advanced nuclear fuel-cycle and reactors. These systems are characterized by a large number density of interfaces which are efficient sinks for point defects and moderately biased; therefore limiting the deleterious effects of irradiation. Broadly, nuclear nano-technology deals with the use of the latest engineered-nanomaterials for improving the nuclear power performances and safety in all areas of nuclear energy production to bring new generations of nuclear power units. New advanced fuel assembly designs also have implications for securities and safeguards. To support the readiness for potential future license applications, an understanding of the technologies that would enable new reactor designs in the areas of component performance and domestic safeguards is necessary. This technical report letter work explores the technical issues and potential regulatory considerations associated with developing and adopting fuel claddings made of advanced nano- materials. Specifically three classes of nanomaterials are considered: (i) reduced activation ferritic/martensitic (RAFM) steels, (ii)oxide dispersed steels (ODS) and (iii) multi-metallic layered composites (MMLC).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1984

Variable polarity plasma arc welding on the Space Shuttle external tank

Variable polarity plasma arc (VPPA) techniques used at NASA's Marshall Space Flight Center for the fabrication of the Space Shuttle External Tank are presentedd. The high plasma arc jet velocities of 300-2000 m/s are produced by heating the plasma gas as it passes through a constraining orifice, with the plasma arc torch becoming a miniature jet engine. As compared to the GTA jet, the VPPA has the following advantages: (1) less sensitive to contamination, (2) a more symmetrical fusion zone, and (3) greater joint penetration. The VPPA welding system is computerized, operating with a microprocessor, to set welding variables in accordance with set points inputs, including the manipulator and wire feeder, as well as torch control and power supply. Some other VPPA welding technique advantages are: reduction in weld repair costs by elimination of porosity; reduction of joint preparation costs through elimination of the need to scrape or file faying surfaces; reduction in depeaking costs; eventual reduction of the 100 percent-X-ray inspection requirements. The paper includes a series of schematic and block diagrams.

Nunes, A. C., Jr.↗
NASA NTRS1998

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.↗
DOE OSTI2025

Enhancing Automotive Intrusion Detection Through Multi-Modal Fusion: A CAN FD-LiDAR Approach

As vehicles become smarter and more autonomous, they increasingly depend on advanced sensors and communication technologies to operate securely. However, such growing dependence on technology—whether it’s CAN (Controller Area Network) for internal communication or LiDAR (Light Detection and Ranging) for sensing the world around them—also expands the attack surface for the types of cyber attacks. Traditional intrusion detection systems (IDS) typically monitor these systems in isolation, limiting their ability to detect sophisticated, crosssystem attacks. To address this, we propose a multi-modal fusion approach that combines real-world CAN FD signals (from the HCRL dataset) with LiDAR features (from the nuScenes dataset) to enhance attack detection. Our method employs a twostage ensemble approach. Calibrated XGBoost and LightGBM models initially process CAN FD (Fuzzing Data) and LiDAR data independently, detecting timing anomalies and space abnormalities. They are subsequently logarithmically combined with a logistic regression meta-model along with 17 engineered features capturing cross-modal behavior, prediction conflicts, and nonlinear interactions. This approach achieves an AUC of 0.87 and an F1-score of 0.82, surpassing single-modality baselines and early fusion methods, at merely 2 ms inference latency. Compared with deep learning competitors, it is 3 times more efficient, providing a lightweight, interpretable, and real time solution to automotive cybersecurity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Path Length Matching and Phase control for Coherently Combined Fiber Laser Arrays (1DPATH)

Coherently combined fiber lasers are literally the future of all lasers. Through coherent combining the high efficiency, ruggedness, and low cost of fiber lasers can be synthesized into any laser imaginable. Lasers of any wavelength, pulse characteristics, energy, average power, or beam output shape can be created through the coherent combination of a low cost base fiber laser. We now have the opportunity to move from traditional “Analog” lasers with their bulk optics, big optical benches, strict cleanliness requirements and high cost and fragility towards “Digital Lasers” where the output beams are shaped to provide characteristics like Orbital Angular Momentum to not only specify the traditional laser characteristics but also the output beam patterns as well. This will enable future applications such as Wakefield Accelerators, petawatt lasers, particle beam control, as well as Inertial Confinement Fusion Drivers and a host of other medical, scientific, and industrial uses.

42 ENGINEERING↗
DOE OSTI2024

Source shape estimation for neutron imaging systems using convolutional neural networks

Neutron imaging systems are important diagnostic tools for characterizing the physics of inertial confinement fusion reactions at the National Ignition Facility (NIF). In particular, neutron images give diagnostic information on the size, symmetry, and shape of the fusion hot spot and surrounding cold fuel. Images are formed via collection of neutron flux from the source using a system of aperture arrays and scintillator-based detectors. Currently, reconstruction of fusion source geometry from the collected neutron images is accomplished by solving a computationally intensive maximum likelihood estimation problem via expectation maximization. In contrast, it is often useful to have simple representations of the overall source geometry that can be computed quickly. In this work, we develop convolutional neural networks (CNNs) to reconstruct the outer contours of simple source geometries. We compare the performance of the CNN for penumbral and pinhole data and provide experimental demonstrations of our methods on both non-noisy and noisy data.

Machine learning, neutron imaging, source reconstr↗