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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

An Evidenced-Based Approach for Estimating Decompression Sickness Risk in Aircraft Operations

Estimating the risk of decompression Sickness (DCS) in aircraft operations remains a challenge, making the reduction of this risk through the development of operationally acceptable denitrogenation schedules difficult. In addition, the medical recommendations which are promulgated are often not supported by rigorous evaluation of the available data, but are instead arrived at by negotiation with the aircraft operations community, are adapted from other similar aircraft operations, or are based upon the opinion of the local medical community. We present a systematic approach for defining DCS risk in aircraft operations by analyzing the data available for a specific aircraft, flight profile, and aviator population. Once the risk of DCS in a particular aircraft operation is known, appropriate steps can be taken to reduce this risk to a level acceptable to the applicable aviation community. Using this technique will allow any aviation medical community to arrive at the best estimate of DCS risk for its specific mission and aviator population and will allow systematic reevaluation of the decisions regarding DCS risk reduction when additional data are available.

Robinson, Ronald R.↗
NASA NTRS1982

The reduction, verification and interpretation of MAGSAT magnetic data over Canada

Research into an approach for altitude adjustments for MAGSAT or similar data acquired over a range of altitudes is progressing. The technique shows promise not only in the production of refined anomaly maps but also in the derivation of regional charts of the magnetic elements from satellite and ground data. Correlations between MAGSAT anomalies and other geophysical and geological data are being explored further and quantitative modelling of some features has begun. The form of some anomalies may change as the maps are refined by the technique being developed. Emphasis is being given to the Canadian regions, although analogous features elsewhere are being considered.

Coles, R. L.↗
NASA NTRS2010

Large Field Photogrammetry Techniques in Aircraft and Spacecraft Impact Testing

The Landing and Impact Research Facility (LandIR) at NASA Langley Research Center is a 240 ft. high A-frame structure which is used for full-scale crash testing of aircraft and rotorcraft vehicles. Because the LandIR provides a unique capability to introduce impact velocities in the forward and vertical directions, it is also serving as the facility for landing tests on full-scale and sub-scale Orion spacecraft mass simulators. Recently, a three-dimensional photogrammetry system was acquired to assist with the gathering of vehicle flight data before, throughout and after the impact. This data provides the basis for the post-test analysis and data reduction. Experimental setups for pendulum swing tests on vehicles having both forward and vertical velocities can extend to 50 x 50 x 50 foot cubes, while weather, vehicle geometry, and other constraints make each experimental setup unique to each test. This paper will discuss the specific calibration techniques for large fields of views, camera and lens selection, data processing, as well as best practice techniques learned from using the large field of view photogrammetry on a multitude of crash and landing test scenarios unique to the LandIR.

Littell, Justin D.↗
NASA NTRS1992

Residual acceleration data on IML-1: Development of a data reduction and dissemination plan

The main thrust of our work in the third year of contract NAG8-759 was the development and analysis of various data processing techniques that may be applicable to residual acceleration data. Our goal is the development of a data processing guide that low gravity principal investigators can use to assess their need for accelerometer data and then formulate an acceleration data analysis strategy. The work focused on the flight of the first International Microgravity Laboratory (IML-1) mission. We are also developing a data base management system to handle large quantities of residual acceleration data. This type of system should be an integral tool in the detailed analysis of accelerometer data. The system will manage a large graphics data base in the support of supervised and unsupervised pattern recognition. The goal of the pattern recognition phase is to identify specific classes of accelerations so that these classes can be easily recognized in any data base. The data base management system is being tested on the Spacelab 3 (SL3) residual acceleration data.

Rogers, Melissa J. B.↗
DOE OSTI2024

Alternating-bias assisted annealing of amorphous oxide tunnel junctions

Superconducting quantum bits (qubits) rely on ultra-thin, amorphous oxide tunneling barriers that can have significant inhomogeneities and defects as grown. This can result in relatively large uncertainties and deleterious effects in the circuits, limiting the scalability. Finding a robust solution to the junction reproducibility problem has been a long-standing goal in the field. Here, we demonstrate a transformational technique for controllably tuning the electrical properties of aluminum-oxide tunnel junctions. This is accomplished using a low-voltage, alternating-bias applied individually to the tunnel junctions, with which resistance tuning by more than 70% can be achieved. The data indicates an improvement of coherence and reduction of two-level system defects. Transmission electron microscopy shows that the treated junctions are predominantly amorphous, albeit with a more uniform distribution of alumina coordination across the barrier. This technique is expected to be useful for other devices based on ionic amorphous materials.

36 MATERIALS SCIENCE↗
NASA NTRS1974

The 1974 NASA-ASEE summer faculty fellowship aeronautics and space research program

Research activities by participants in the fellowship program are documented, and include such topics as: (1) multispectral imagery for detecting southern pine beetle infestations; (2) trajectory optimization techniques for low thrust vehicles; (3) concentration characteristics of a fresnel solar strip reflection concentrator; (4) calaboration and reduction of video camera data; (5) fracture mechanics of Cer-Vit glass-ceramic; (6) space shuttle external propellant tank prelaunch heat transfer; (7) holographic interferometric fringes; and (8) atmospheric wind and stress profiles in a two-dimensional internal boundary layer.

Obrien, J. F., Jr.↗
NASA NTRS1992

Acetate concentrations and oxidation in salt marsh sediments

Acetate concentrations and rates of acetate oxidation and sulfate reduction were measured in S. alterniflora sediments in New Hampshire and Massachusetts. Pore water extracted from cores by squeezing or centrifugation contained in greater than 0.1 mM acetate and, in some instances, greater than 1.0 mM. Pore water sampled nondestructively contained much less acetate, often less than 0.01 mM. Acetate was associated with roots, and concentrations varied with changes in plant physiology. Acetate turnover was very low whether whole core or slurry incubations were used. Radiotracers injected directly into soils yielded rates of sulfate reduction and acetate oxidation not significantly different from core incubation techniques. Regardless of incubation method, acetate oxidation did not account for a substantial percentage of sulfate reduction. These results differ markedly from data for unvegetated coastal sediments where acetate levels are low, oxidation rate constants are high, and acetate oxication rates greatly exceed rates of sulfate reduction. The discrepancy between rates of acetate oxidation and sulfate reduction in these marsh soils may be due either to the utilization of substrates other than acetate by sulfate reducers or artifacts associated with measurements of organic utilization by rhizosphere bacteria. Care must be taken when interpreting data from salt marsh sediments since the release of material from roots during coring may affect the concentrations of certain compounds as well as influencing results obtained when sediment incubations are employed.

Source record↗
NASA NTRS1999

System Analyses of Pneumatic Technology for High Speed Civil Transport Aircraft

The primary aspiration of this study was to objectively assess the feasibility of the application of a low speed pneumatic technology, in particular Circulation Control (CC) to an HSCT concept. Circulation Control has been chosen as an enabling technology to be applied on a generic High Speed Civil Transport (HSCT). This technology has been proven for various subsonic vehicles including flight tests on a Navy A-6 and computational application on a Boeing 737. Yet, CC has not been widely accepted for general commercial fixed-wing use but its potential has been extensively investigated for decades in wind tunnels across the globe for application to rotorcraft. More recently, an experimental investigation was performed at Georgia Tech Research Institute (GTRI) with application to an HSCT-type configuration. The data from those experiments was to be applied to a full-scale vehicle to assess the impact from a system level point of view. Hence, this study attempted to quantitatively assess the impact of this technology to an HSCT. The study objective was achieved in three primary steps: 1) Defining the need for CC technology; 2) Wind tunnel data reduction; 3) Detailed takeoff/landing performance assessment. Defining the need for the CC technology application to an HSCT encompassed a preliminary system level analysis. This was accomplished through the utilization of recent developments in modern aircraft design theory at Aerospace Systems Design Laboratory (ASDL). These developments include the creation of techniques and methods needed for the identification of technical feasibility show stoppers. These techniques and methods allow the designer to rapidly assess a design space and disciplinary metric enhancements to enlarge or improve the design space. The takeoff and landing field lengths were identified as the concept "show-stoppers". Once the need for CC was established, the actual application of data and trends was assessed. This assessment entailed a reduction of the wind tunnel data from the experiments performed by Mr. Bob Englar at the GTRI. Relevant data was identified and manipulated based on the required format of the analysis tools utilized. Propulsive, aerodynamic, duct sizing, and vehicle sizing investigations were performed and information supplied to a detailed takeoff and landing tool, From the assessments, CC was shown to improve the low speed performance metrics, which were previously not satisfied. An HSCT with CC augmentation does show potential for full-scale application. Yet, an economic assessment of an HSCT with and without CC showed that a moderate penalty was incurred from the increased RDT&E costs associated with developing the CC technology and slight increases in empty weight.

Mavris, Dimitri N.↗
DOE OSTI2020

An investigation of Newton-Sketch and subsampled Newton methods

Sketching, a dimensionality reduction technique, has received much attention in the statistics community. In this paper, we study sketching in the context of Newton's method for solving finite-sum optimization problems in which the number of variables and data points are both large. In this work, we study two forms of sketching that perform dimensionality reduction in data space: Hessian subsampling and randomized Hadamard transformations. Each has its own advantages, and their relative tradeoffs have not been investigated in the optimization literature. Additionally, our study focuses on practical versions of the two methods in which the resulting linear systems of equations are solved approximately, at every iteration, using an iterative solver. The advantages of using the conjugate gradient method vs. a stochastic gradient iteration are revealed through a set of numerical experiments, and a complexity analysis of the Hessian subsampling method is presented.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1997

Experimental Evaluation of the Penalty Associated With Micro-Blowing for Reducing Skin Friction

A micro-blowing technique (MBT) experiment was conducted in the Advanced Nozzle and Engine Components Test Facility at the NASA Lewis Research Center. The objectives of the test were to evaluate the pressure-drag penalty associated with the MBT and to provide additional information about the porous plates used for micro-blowing. The results showed that 1 of 12 plates tested could reduce the total drag (skin-friction drag plus pressure drag) below a solid flat plate value. The results of this experiment and prior data showed that a total drag reduction below a solid flat plate value was possible. More tests are needed to find an optimal MBT skin and to find a technique to reduce pressure drag.

Hwang, Danny P.↗
DOE OSTI2020

Scalable line and plane relaxation in a parallel structured multigrid solver

The efficient solution of sparse, linear systems that arise through the discretization of partial differential equations remains a key challenge for a range of high performance scientific simulations. One approach for reducing data movement and improving performance is by exposing and exploiting structure in a problem through the use of robust structured multilevel solvers. By choosing coarsening that preserves the structure of the problem, these methods maintain efficient structured computation and communication throughout the multigrid hierarchy. However, when coarsening is not permitted to be dependent on the operator, anisotropy must be addressed by the smoother — producing error compatible for coarse-grid correction with structured coarsening. Here, the components required in a scalable parallel structured solver are described with a focus on memory and communication efficiency of robust smoothers. While the implementation of communication and memory reduction techniques in smoothers integrated in a complete 3D solver present a significant engineering challenge, a novel approach is proposed that addresses these challenges systematically through a change to the solver’s execution model. Enabled by user-level threading paired with a set of data and communication abstractions, this approach permits seamless aggregation of communication in plane smoothers — directly reusing code for a 2D distributed multilevel cycle. Results show an effective reduction in communication costs for coarse-grid problems, and result in a speedup of 8.7x in smoothing routines shown in Fig. 12 using this approach. This produces a significant improvement to strong scalability while maintaining favorable weak scaling behavior. Finally, a parallel scaling study using a series of refined meshes is included that demonstrates the effectiveness of this approach in an application of interest.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Error-Bounded Learned Scientific Data Compression with Preservation of Derived Quantities

Scientific applications continue to grow and produce extremely large amounts of data, which require efficient compression algorithms for long-term storage. Compression errors in scientific applications can have a deleterious impact on downstream processing. Thus, it is crucial to preserve all the “known” Quantities of Interest (QoI) during compression. To address this issue, most existing approaches guarantee the reconstruction error of the original data or primary data (PD), but cannot directly control the problem of preserving the QoI. In this work, we propose a physics-informed compression technique that is composed of two parts: (i) reduction of the PD with bounded errors and (ii) preservation of the QoI. In the first step, we combine tensor decompositions, autoencoders, product quantizers, and error-bounded lossy compressors to bound the reconstruction error at high levels of compression. In the second step, we use constraint satisfaction post-processing followed by quantization to preserve the QoI. To illustrate the challenges of reducing the reconstruction errors of the PD and QoI, we focus on simulation data generated by a large-scale fusion code, XGC, which can produce tens of petabytes in a single day. The results show that our approach can achieve a high compression amount while accurately preserving the QoI within scientifically acceptable bounds.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Machine learning-assisted identification of potential sources of bias in measurements of prompt-fission neutron spectra

Unrecognized sources of uncertainty (USU) can bias the reported mean and/or covariance of experimental nuclear data. These biases, in turn, can propagate through evaluated nuclear data to application simulations or may poorly inform nuclear theory that is fitted to the experimental data. Such unknown sources of bias must be tied to the inherent physical constituents of the measurements such as the characteristics of a detector response or a background reduction technique. Here, in this article, a sparse Bayesian learning model is used to support experts in their efforts to identify and characterize USU in experimental prompt fission neutron spectra (PFNS) for spontaneous fissioning of 252 Cf by linking observed biases to features of the measurement system. Three different bias components were found. The first acts as a verification case for the algorithm as it identifies a bias coming from a well-known source related to the use of 6 Li in the neutron detection system. The second two cases demonstrate how this method can benefit the evaluation of experimental nuclear data by identifying, quantifying, and relating unknown biases to potential causes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Combining lattice QCD and phenomenological inputs on generalised parton distributions at moderate skewness

Abstract We present a systematic study demonstrating the impact of lattice QCD data on the extraction of generalised parton distributions (GPDs). For this purpose, we use a previously developed modelling of GPDs based on machine learning techniques fulfilling the theoretical requirements of polynomiality, a form of positivity constraint and known reduction limits. A special care is given to estimate the uncertainty stemming from the ill-posed character of the connection between GPDs and the experimental processes usually considered to constrain them, like deeply virtual Compton scattering (DVCS). Moke lattice QCD data inputs are included in a Bayesian framework to a prior model based on an Artificial Neural Network. This prior model is fitted to reproduce the most experimentally accessible information of a phenomenological extraction by Goloskokov and Kroll. We highlight the impact of the precision, correlation and kinematic coverage of lattice data on GPD extraction at moderate $$\xi $$ ξ which has only been brushed in the literature so far, paving the way for a joint extraction of GPDs.

Physics↗
NASA NTRS1992

Life support systems for Mars transit

The structural elements of life-support systems are reviewed in order to assess the suitability of specific features for use during a Mars mission. Life-support requirements are estimated by means of an approximate input/output analysis, and the advantages are listed relating to the use of recycling and regeneration techniques. The technological options for regeneration are presented in categories such as CO2 reduction, organics removal, polishing, food production, and organics oxidation. These data form the basis of proposed mission requirements and constraints as well as the definition of what constitutes an adequate reserve. Regenerative physical/chemical life-support systems are championed based exclusively on the mass savings inherent in the technology. The resiliency and 'soft' failure modes of bioregenerative life-support systems are identified as areas of investigation.

Macelroy, R. D.↗
NASA NTRS1992

Elevated acetate concentrations in the rhizosphere of Spartina alterniflora and potential influences on sulfate reduction

Acetate is important in anaerobic metabolism of non-vegetated sediments but its role in salt marsh soils was not investigated thoroughly. Acetate concentrations, oxidation (C-14) and SO4(2-) reduction (S-35) were measured in S. alterniflora soils in NH and MA. Pore water from cores contained greater than 0.1 mM acetate and in some instances greater than 1.0 mM. Non-destructive samples contained less than 0.01 mM. Acetate was associated with roots and concentrations were highest during vegetative growth and varied with changes in plant physiology. Acetate turnover was very low whether whole core or slurry incubations were used. Radiotracers injected directly into soils yielded rates of SO4(2-) reduction and acetate oxidation not significantly different from core incubation techniques. Regardless of incubation method, acetate oxidation did not account for a significant percentage of SO4(2-) reduction. These results differ markedly from data for non-vegetated coastal sediments where acetate levels are low, oxidation rate constants are high and acetate oxidation rates greatly exceed rates of SO4(2-) reduction. The discrepancy between rates of acetate oxidation and SO4(2-) reduction in marsh soils may be due either to the utilization of substrates other than acetate by SO4(2-) reducers or artifacts associated with measurements of organic utilization by rhizosphere bacteria.

Hines, Mark E.↗
DOE OSTI2026

Ensemble Kalman filter for data assimilation coupled with low-resolution computations techniques applied in fluid dynamics

This paper presents an innovative Reduced-order model (ROM) for merging experimental and simulation data using data assimilation (DA) to estimate the "True" state of a fluid dynamics system, leading to more accurate predictions. Our methodology introduces a novel approach by implementing the ensemble Kalman filter (EnKF) within a reduced-dimensional framework, grounded in a robust theoretical foundation and applied to fluid dynamics. To address the substantial computational demands of DA, the proposed ROM employs low-resolution (LR) techniques to drastically reduce computational costs. This innovative approach involves downsampling datasets for DA computations, followed by an advanced reconstruction technique based on low-cost singular value decomposition (lcSVD). The lcSVD method, a key innovation in this paper, has never been applied to DA before and offers a highly efficient way to enhance resolution with minimal computational resources. Our results demonstrate significant reductions in both computation time and RAM usage through these LR techniques without compromising the accuracy of the estimations. For instance, in a turbulent test case, for a data compression rate of 15.9, the LR approach can achieve a speed-up of 13.7 and a RAM compression of 90.9% while maintaining a low relative root mean square error (RRMSE) of 2.6%, compared to 0.8% in the high-resolution (HR) reference. Furthermore, we highlight the effectiveness of the EnKF in estimating and predicting the state of fluid flow systems based on limited observations and given low-fidelity numerical data. This paper highlights the potential of the proposed DA method in fluid dynamics applications, particularly for improving computational efficiency in CFD and related fields. Its ability to balance accuracy with low computational and memory costs makes it especially suitable for large-scale and real-time applications, such as environmental monitoring or engineering design. This method will be incorporated into ModelFLOWs-app.

Data Assimilation↗
DOE OSTI2025

Final report- UFL - RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗