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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Space Launch System Core Stage Green Run Base Heating: Anomaly, Mitigation and Flight Redesign

The NASA Space Launch System (SLS) vehicle is composed of four RS-25 liquid oxygen and hydrogen rocket engines in the Core Stage (CS). The SLS Core Stage went through Green Run hot-fire testing at NASA Stennis Space Center’s B-2 test facility in 2021. The main goal of this testing was to confirm Core Stage tanking, propulsion and thrust vector control systems operations and performance to verify with predicted models. Two hot-fire (HF) test sequences were performed with the first one (HF1) in January for a test duration of 70 seconds and the second (HF2) testing completed in March for a test duration of 500 seconds. This paper focuses on the base heating anomalies observed during HF1 and HF2 where an extensive fire was observed along the Core Stage base heat shield during test operations. This environment was not anticipated and led to extensive unplanned damage to the thermal protection system which was augmented for flight. Green Run observations also led to a reassessment of flight environments for Artemis I. This paper discusses the potential cause of the anomalies, the flow physics, the reconstructed base environments, and mitigation plans for HF2 and flight.

aerothermodynamics↗
NASA NTRSDate not supplied

Space Launch System Core Stage Green Run Base Heating: Anomaly, Mitigation and Flight Redesign

The NASA Space Launch System (SLS) vehicle is composed of four RS-25 liquid oxygen and hydrogen rocket engines in the Core Stage (CS). The SLS Core Stage went through Green Run hotfire testing at NASA Stennis Space Center’s B-2 test facility in 2021. The main goal of this testing was to confirm Core Stage tanking, propulsion and thrust vector control systems operations and performance to verify with predicted models. Two hot-fire (HF) test sequences were performed with the first one (HF1) in January for a test duration of 70 seconds and the second (HF2) testing completed in March for a test duration of 500 seconds. This paper focuses on the base heating anomalies observed during HF1 and HF2 where an extensive fire was observed along the Core Stage base heat shield during test operations. This environment was not anticipated and led to extensive unplanned damage to the thermal protection system which was augmented for flight. Green Run observations also led to a reassessment of flight environments for Artemis I. This paper discusses the potential cause of the anomalies, the flow physics, the reconstructed base environments, and mitigation plans for HF2 and flight.

aerothermodynamics↗
DOE OSTI2023

Enabling Cybersecurity, Situational Awareness and Resilience in Distribution Grids with High Penetration of Photovoltaics (CARE-PV) (Final Report)

Since legacy distribution systems have very limited visibility beyond the substation, high penetration of PV at the grid edge presents some unique operational challenges. One approach to address these challenges is to use information from advanced metering infrastructure (AMI) and µPMUs. However, exploiting this information is impacted by a number of factors, including multi-timescale measurements, volume of data generated, communication network impairments (e.g., information loss and latency) and susceptibility to cyber-attacks. Therefore, one of the critical tasks involved in the management of a distribution grid is to develop complete situational awareness by integrating cyber-security mechanisms with state estimation strategies and leveraging this situational awareness to assure energy services at strategic locations while exploiting AMI/PV inverter/ µPMU data. This CARE-PV project addresses the fundamental challenges in situational awareness and resilience to cyber and physical vectors by exploiting the synergy between innovative modeling, estimation, data analytics, testing and validation using smart PV inverters designed at K-State and facilities at NREL. Specifically, the project involved the development, testing and validation of the following novel enabling technologies: (Thrust 1) Resilience to cyber vectors that impact data integrity was addressed via a two-level defense strategy that combines cyber intrusion detection using self-learning, cooperative smart PV inverters, and a novel moving target defense framework to combat data integrity attacks. (Thrust 2) Resilience to cyber-physical vectors that impact situational awareness by limiting data availability was addressed via novel centralized and decentralized, sparsity-based static and dynamic state estimation approaches that enhance observability even when the underlying system is unobservable. (Thrust 3) Leveraging a unique probabilistic sensitivity analysis approach accompanied by one-of-a-kind dominant influencer set computation, the vulnerability of critical infrastructure at strategic locations was evaluated so that proactive PV-based control strategies can be used to support operations under normal/outage scenarios. These CARE-PV project innovations were demonstrated on both small-scale IEEE and larger utility-scale testbeds (Thrust 4). Feedback from Industry Advisory Board members was used to formulate a commercialization pathway for a subset of CARE-PV technologies. These CARE-PV technologies will ultimately lead to reliable and secure, large-scale integration of renewable energy and mitigate the risk of energy disruption resulting from cyber incidents and other emerging threats within the energy environment.

14 SOLAR ENERGY↗
DOE OSTI2014

Parametrization of textural patterns in {sup 123}I-ioflupane imaging for the automatic detection of Parkinsonism

Purpose: A novel approach to a computer aided diagnosis system for the Parkinson's disease is proposed. This tool is intended as a supporting tool for physicians, based on fully automated methods that lead to the classification of{sup 123}I-ioflupane SPECT images. Methods: {sup 123}I-ioflupane images from three different databases are used to train the system. The images are intensity and spatially normalized, then subimages are extracted and a 3D gray-level co-occurrence matrix is computed over these subimages, allowing the characterization of the texture using Haralick texture features. Finally, different discrimination estimation methods are used to select a feature vector that can be used to train and test the classifier. Results: Using the leave-one-out cross-validation technique over these three databases, the system achieves results up to a 97.4% of accuracy, and 99.1% of sensitivity, with positive likelihood ratios over 27. Conclusions: The system presents a robust feature extraction method that helps physicians in the diagnosis task by providing objective, operator-independent textural information about{sup 123}I-ioflupane images, commonly used in the diagnosis of the Parkinson's disease. Textural features computation has been optimized by using a subimage selection algorithm, and the discrimination estimation methods used here makes the system feature-independent, allowing us to extend it to other databases and diseases.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1988

Parafrase restructuring of FORTRAN code for parallel processing

Parafrase transforms a FORTRAN code, subroutine by subroutine, into a parallel code for a vector and/or shared-memory multiprocessor system. Parafrase is not a compiler; it transforms a code and provides information for a vector or concurrent process. Parafrase uses a data dependency to reveal parallelism among instructions. The data dependency test distinguishes between recurrences and statements that can be directly vectorized or parallelized. A number of transformations are required to build a data dependency graph.

Wadhwa, Atul↗
DOE OSTI2026

PIP-II LLRF Master Oscillator and Precision Reference Line- Station Level Design and Testing

The PIP-II superconducting linac at Fermilab requires a highly stable RF Reference Line to maintain phase synchronization throughout the accelerator. Temperature-induced changes in the electrical length of long coaxial cables can introduce phase drift and measurement errors. The reference-line architecture mitigates these effects by phase averaging the forward and reflected RF signals, while a phase-locked loop anchors the system to the master oscillator. This work focuses on the characterization, validation, and mechanical integration of station-level RF assemblies using CAD modeling, vector network analyzer measurements, and spectrum analyzer testing. PID-controlled thermal plates will stabilize critical RF components and further reduce temperature-dependent phase and amplitude variations. These methods support repeatable, standardized designs that can be reliably integrated across the different reference-line stations.

Mosher, Alexander [U. Illinois, Chicago; Fermilab]↗
DOE OSTI2026

PIP-II LLRF Master Oscillator and Precision Reference Line - Station Level Design and Testing

The PIP-II superconducting linac at Fermilab requires a highly stable RF Reference Line to maintain phase syn- chronization throughout the accelerator. Temperature- induced changes in the electrical length of long coaxial cables can introduce phase drift and measurement errors. The reference-line architecture mitigates these effects by phase averaging the forward and reflected RF signals, while a phase-locked loop anchors the system to the mas- ter oscillator. This work focuses on the characterization, validation, and mechanical integration of station-level RF assemblies using CAD modeling, vector network analyzer measurements, and spectrum analyzer testing. PID-controlled thermal plates will stabilize critical RF components and further reduce temperature-dependent phase and amplitude variations. These methods sup- port repeatable, standardized designs that can be reliably integrated across the different reference-line stations.

Mosher, Alexander [U. Illinois, Chicago]↗
NASA NTRS1972

Performance testing of a solid propellant pulsed plasma microthruster.

Extensive performance testing has been carried out on a solid propellant, pulsed plasma microthruster essentially identical to the four units aboard the DOD, Lincoln Experimental Satellite (LES)-6. Tests include measurements of thrust, specific impulse, thrust vector, impulse bit repeatability, intermittency and endurance. The results show good impulse bit repeatability and a well defined thrust vector. The impulse bit, with a 1.85-joule input, was found to be approximately 26 micronewton-seconds at 190 seconds specific impulse. Based upon the results of the intermittency tests, a better understanding of the intermittency mechanism has been achieved.

Williams, T. E.↗
DOE OSTI2022

Improving the accuracy of discretisations of the vector transport equation on the lowest-order quadrilateral Raviart-Thomas finite elements

Within finite element models of fluids, vector-valued fields such as velocity or momentum variables are commonly discretised using the Raviart-Thomas elements. However, when using the lowest-order quadrilateral Raviart-Thomas elements, standard finite element discretisations of the vector transport equation typically have a low order of spatial accuracy. This paper describes two schemes that improve the accuracy of transporting such vector-valued fields on two-dimensional curved manifolds. The first scheme that is presented reconstructs the transported field in a higher-order function space, where the transport equation is then solved. The second scheme applies a mixed finite element formulation to the vector transport equation, simultaneously solving for the transported field and its vorticity. In this work, an approach to stabilising this mixed vector-vorticity formulation is presented that uses a Streamline Upwind Petrov-Galerkin (SUPG) method. These schemes are then demonstrated, along with their accuracy properties, through some numerical tests. Two new test cases are used to assess the transport of vector-valued fields on curved manifolds, solving the vector transport equation in isolation. The improvement of the schemes is also shown through two standard test cases for rotating shallow-water models.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Development of iterative techniques for the solution of unsteady compressible viscous flows

During the past two decades, there has been significant progress in the field of numerical simulation of unsteady compressible viscous flows. At present, a variety of solution techniques exist such as the transonic small disturbance analyses (TSD), transonic full potential equation-based methods, unsteady Euler solvers, and unsteady Navier-Stokes solvers. These advances have been made possible by developments in three areas: (1) improved numerical algorithms; (2) automation of body-fitted grid generation schemes; and (3) advanced computer architectures with vector processing and massively parallel processing features. In this work, the GMRES scheme has been considered as a candidate for acceleration of a Newton iteration time marching scheme for unsteady 2-D and 3-D compressible viscous flow calculation; from preliminary calculations, this will provide up to a 65 percent reduction in the computer time requirements over the existing class of explicit and implicit time marching schemes. The proposed method has ben tested on structured grids, but is flexible enough for extension to unstructured grids. The described scheme has been tested only on the current generation of vector processor architecture of the Cray Y/MP class, but should be suitable for adaptation to massively parallel machines.

Hixon, Duane↗
NASA NTRS2017

Performance Verification and Testing of the COWVR Instrument Antenna

The Compact Ocean Wind Vector Radiometer (COWVR) is a technology demonstration mission, developed at the Jet Propulsion Laboratory (JPL), and scheduled for launch in 2016. The goal of COWVR is to provide the same windvector retrieval accuracy of other instruments, like WindSat, while reducing the total mass and using less power. In this paper, we present an overview of the COWVR instrument, and a detailed description of the EM (Electromagnetic) modeling of the antenna system and the test campaign carried out at JPL to assess its performance. Special emphasis has been placed on assessing the accuracy of the predictions made with the RF (Radio Frequency) model. We will show that the predicted radiation patterns are accurate enough so one can use them for orbit radiometer calibration.

Radiation Patterns↗
NASA NTRS1982

Tests and analysis of a vented D thrust deflecting nozzle on a turbofan engine

The objectives were to: obtain nozzle performance characteristics in and out of ground effects; demonstrate the compatibility of the nozzle with a turbofan engine; obtain pressure and temperature distributions on the surface of the D vented nozzle; and establish a correlation of the nozzle performance between small scale and large scale models. The test nozzle was a boilerplate model of the MCAIR D vented nozzle configured for operation with a General Electric YTF-34-F5 turbofan engine. The nozzle was configured to provide: a thrust vectoring range of 0 to 115 deg; a yaw vectoring range of 0 to 10 deg; variable nozzle area control; and variable spacing between the core exit and nozzle entrance station. Compatibility between the YTF-34-T5 turbofan engine and the D vented nozzle was demonstrated. Velocity coefficients of 0.96 and greater were obtained for 90 deg of thrust vectoring. The nozzle walls remained cool during all test conditions.

Roseberg, E. W.↗
DOE OSTI2026

Unsupervised domain adaptation for radioisotope identification in gamma spectroscopy

Training machine learning models for radioisotope identification using gamma spectroscopy remains an elusive challenge for many practical applications, largely stemming from the difficulty of acquiring and labeling large, diverse experimental datasets. Simulations can mitigate this challenge, but the accuracy of models trained on simulated data can deteriorate substantially when deployed to an out-of-distribution operational environment. In this study, we demonstrate that unsupervised domain adaptation (UDA) can improve the ability of a model trained on synthetic data to generalize to a new testing domain, provided unlabeled data from the target domain are available. Conventional supervised techniques are unable to utilize this data because the absence of isotope labels precludes defining a supervised classification loss. Instead, we first pretrain a spectral classifier using labeled synthetic data and subsequently leverage unlabeled target data to align the learned feature representations between the source and target domains. We compare a range of different UDA techniques, finding that minimizing the maximum mean discrepancy (MMD) between source and target feature vectors yields the most consistent improvement to testing scores. For instance, using a custom transformer-based neural network, we achieved a testing accuracy of $0.904 \pm 0.022$ on an experimental LaBr test set after performing unsupervised feature alignment via MMD minimization, compared to $0.754 \pm 0.014$ before alignment. Overall, our results highlight the potential of using UDA to adapt a radioisotope classifier trained on synthetic data for real-world deployment.

Lalor, Peter W.↗
DOE OSTI2026

In situ quantification of fracture slip induced by hydraulic injections in a deep borehole: A comparison of two different borehole techniques

In situ measurements of fracture deformation during fluid injection are rare, yet essential for understanding the mechanical response of fractured rock. In this study, we evaluate the reliability of two methods by comparing their slip vector estimates: high-resolution borehole acoustic televiewer images captured before and after injection tests, and displacement data from a three-component borehole deformation probe recorded during the injections. Acoustic televiewer images capture only final in-plane displacement, whereas three-component borehole deformation measurements provide full 3D, transient fracture movement. Four injection tests in a fractured granitic rock mass along an inclined borehole at the Bedretto Underground Laboratory (Switzerland), beneath more than 1100 m of overburden, were analyzed. The two methods yielded consistent kinematics and comparable slip magnitudes, typically in the range of 0.2 – 0.6 mm. Angular differences between estimated slip directions ranged from 0.2° to 28°. For two test intervals with pre-existing fractures optimally oriented for slip, the measured slip vectors agreed with forward-modeled slip vectors based on the regional in situ stress field, supporting the Wallace–Bott hypothesis. Measurable shear displacement was identified in two test intervals containing fractures oriented nearly perpendicular to the least principal stress, including a newly formed hydraulic fracture. This demonstrates that even fractures unfavorably oriented for slip can undergo shear due to local stress perturbations around an inclined borehole.

Acoustic televiewer↗
DOE OSTI2020

Multi-Axis Resonant Plate Shock Testing Evaluation and Test Specification Development

Resonant plate testing is a shock test method that is frequently used to simulate pyroshock events in the laboratory. Recently, it was discovered that if the unit under test is installed at an off-center location, a tri-axial accelerometer would record a shock response in three directions and the resulting shock response spectra implied that the test may have qualified the component in three directions simultaneously. The purpose of this research project was to evaluate this idea of multi-axis shock testing to determine if it was truly a multi-axis shock environment and if such a test could be used as an equivalent component qualification test. A study was conducted using generic, additively manufactured components tested on a resonant plate, along with an investigation of plate motion to evaluate the component response to off- center plate excitation. The data obtained here along with the analytical simulations performed indicate that off-center resonant plate tests are actually not three-axis shock tests, but rather single axis shocks at an arbitrary angle dictated by the location of the unit under test on the plate. This conclusion is supported by the fact that only one vectored shock input is provided to the component in a resonant plate test. Thus, the output response is a coupled response of the transverse plate vibration and the rotational motion of the component on the plate. Additionally, a multi-axis shock test defined by three single axis test environments always results in a significant component over-test in one direction.

42 ENGINEERING↗
NASA NTRS1993

Direct correlation of test-analysis cross-orthogonality

This paper presents an alternative to the correlation of individual components of a mode shape vectors by directly examining the sensitivity of the cross-orthogonality between test and analytical mode shapes. If the test and analysis mode shapes are identical, the diagonal elements of the cross-orthogonality will be identical to the test orthogonality matrix, so the cross-orthogonality matrix provides a concise measure of the 'closeness' between test and analysis mode shapes. There are two major advantages to the cross-orthogonality correlation approach. The first is that a direct correlation of this matrix will more directly meet the goal of the correlation effort (measured by cross-orthogonality). Secondly, and more importantly, the correlation of cross-orthogonality greatly reduces the amount of data that needs to be handled when compared to the correlation of mode shapes.

Blelloch, P. A.↗
DOE OSTI2016

Development of a 300°C 3C Fiber Optic Downhole Seismic Receiver Array for Surveying and Monitoring of Geothermal Reservoirs

To address the critical site characterization and monitoring needs for Enhance Geothermal Systems (EGS) programs, US Department of Energy (DOE) awarded Paulsson, Inc. in 2011 a contract to design, build and test a high temperature fiber optic based ultra-large bandwidth clamped borehole seismic vector array capable of deploying a large number of 3C sensor pods suitable for deployment into high temperature and high pressure boreholes. Paulsson, Inc. has completed a design or a unique borehole seismic system consisting of a novel drill pipe based deployment system that includes a hydraulic clamping mechanism for the sensor pods, a new sensor pod design and most important – a unique fiber optic seismic vector sensor with technical specifications and capabilities that far exceed the state of the art seismic sensor technologies. These novel technologies were all applied to the new borehole seismic system. In combination these technologies will allow for the deployment of up to 1,000 3C sensor pods in vertical, deviated or horizontal wells. Laboratory tests of the fiber optic seismic vector sensors developed during this project have shown that the new borehole seismic sensor technology is capable of generating outstanding high vector fidelity data with extremely large bandwidth: 0.01 – 6,000 Hz. Field tests have shown that the system can record events at magnitudes much smaller than M-4.0 at frequencies over 2,000 Hz. The sensors have also proved to be about 100 times more sensitive than the regular coil geophones that are used in borehole seismic systems today. The fiber optic seismic sensors have furthermore been qualified to operate at temperatures over 300°C (572°F). The data telemetry fibers used for the seismic vector sensors in the system are also used to simultaneously record Distributed Temperature Sensor (DTS) and Distributed Acoustic Sensor (DAS) data allowing additional value added data to be recorded simultaneously with the seismic vector sensor data.

02 PETROLEUM↗
NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗