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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 1,297 records · Page 72

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DOE OSTI2022

Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18–72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18–73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I 2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen’s d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Modifying the Asynchronous Jacobi Method for Data Corruption Resilience

Moving scientific computation from high-performance computing (HPC) and cloud computing (CC) environments to devices on the edge, i.e., physically near instruments of interest, has received tremendous interest in recent years. Such edge computing environments can operate on data in situ, offering enticing benefits over data aggregation to HPC and CC facilities that include avoiding costs of transmission, increased data privacy, and real-time data analysis. Because of the inherent unreliability of edge computing environments, new fault-tolerant approaches must be developed before the benefits of edge computing can be realized. Motivated by algorithm-based fault tolerance, a variant of the asynchronous Jacobi (ASJ) method is developed that achieves resilience to data corruption by rejecting solution approximations from neighbor devices according to a bound derived from convergence theory. Numerical results on a two-dimensional Poisson problem show that the new rejection criterion, along with a novel approximation to the shortest path length on which the criterion depends, restores convergence for the ASJ variant in the presence of certain types data corruption. Numerical results are obtained for when the singular values in the analytic bound are approximated. Additional linear systems are also explored, one with a more dense sparsity pattern and one that includes advection. All results indicate that successful resilience to data corruption depends on whether the bound tightens fast enough to reject corrupted data before the iteration evolution deviates significantly from that predicted by the convergence theory defining the bound. This observation generalizes to future work on algorithm-based fault tolerance for other asynchronous algorithms, including upcoming approaches that leverage Krylov subspaces.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1977

Experimental evaluation of the tensor polynomial criterion for designing composite structures

A comprehensive experimental and analytical evaluation of the tensor polynomial failure criterion was undertaken to determine its capability for predicting the ultimate strength of a composite limina subject to a plane stress state. Results are presented demonstrating that a quadratic formulation is too conservative and a cubic representation is required. Strength comparisons with test data derived from glass/epoxy and graphite/epoxy tubular specimens are also provided to validate the cubic strength criterion. Environmental effects including ambient temperature, exposure to vacuum, length of post-cure time, and rate of cool down were also investigated. Behavior changes associated with polymer (epoxy) matrix composites were determined in terms of variations in stiffness and tensile strength.

Tennyson, R. C.↗

NASA NTRS1978

Evaluation of the tensor polynomial failure criterion for composite materials

Tennyson, R. C.↗

NASA NTRS1980

Spin prediction techniques

The NASA Langley Research Center has the responsibility to advance the state-of-the-art in the area of stall/spin technology. This includes the development and validation of experimental and analytical techniques for the prediction of stall/spin characteristics. As a part of this effort, a rotary balance facility located in the Langley spin tunnel was developed two and a half years ago to rapidly identify an airplane's aerodynamic characteristics in a rotational flow environment. On-line rotary balance data plots and on-line predicted steady spin modes permit the designer to develop, on site, a configuration highly resistant to spins, or one which has good spin characteristics, i.e., no spin equilibrium conditions possible with lateral-directional controls neutral, if the airplane is to be used for acrobatic maneuvers or training. The rotary balance data are also used to compute time histories of a spin's incipient, developed, and recovery phases. These spin analysis techniques and their correlation with spin tunnel model and full-scale flight results are discussed herein.

Bihrle, W., Jr.↗

NASA NTRS1995

Updated Fatigue-Crack-Growth And Fracture-Mechanics Software

NASA/FLAGRO 2.0 developed as analytical aid in predicting growth and stability of preexisting flaws and cracks in structural components of aerospace systems. Used for fracture-control analysis of space hardware. Organized into three modules to maximize efficiency in operation. Useful in: (1) crack-instability/crack-growth analysis, (2) processing raw crack-growth data from laboratory tests, and (3) boundary-element analysis to determine stresses and stress-intensity factors. Written in FORTRAN 77 and ANSI C.

Forman, Royce G.↗

NASA NTRS1997

Rotordynamic Instability Problems in High-Performance Turbomachinery 1996

The first rotordynamics workshop proceedings emphasized a feeling of uncertainty in predicting the stability of characteristics of high-performance turbomachinery. In the second workshop proceedings these uncertainties were reduced through programs established to systematically resolve problems, with emphasis on experimental validation of the forces that influence rotordynamics. In the third proceedings many programs for predicting or measuring forces and force coefficients in high-performance turbomachinery produced results. Data became available for designing new machines with enhanced stability characteristics or for upgrading existing machines. In the fourth proceedings there emerged trends towards a more unified view of rotordynamic instability problems and several encouraging new analytical developments. The fifth workshop supported the continuing trend toward a unified view with several new developments in the design and manufacture of new turbomachineries with enhanced stability characteristics along with new data and associated numerical/theoretical results. The sixth workshop report provided field experience and experimental results, and expanded the use of computational and control techniques with integration of damper, bearing, and eccentric seal operation results. The seventh workshop report provided field experiences, numerical, theoretical, and experimental results and control methods for seals, bearings, and dampers with some attention given to variable thermophysical properties and turbulence measurements, and introduction of two-phase flow results. In the present workshop, active magnetic bearings (AMB's) evolve into a new method of measuring rotordynamic coefficients with discussions on honeycomb seals, drop of magnetically supported rotors, seals, bearings and dampers with new data being reported. The intent of the workshop and this proceedings is to provide a continuing impetus for an understanding and resolution of these problems.

Source record↗

NASA NTRS1999

Analysis and Testing of High Temperature Fibrous Insulation for Reusable Launch Vehicles

Analytical models were developed to model the heat transfer through high-temperature fibrous insulation used in metallic thermal protection systems on reusable launch vehicles. The optically thick approximation was used to simulate radiation heat transfer through the insulation. Different models for gaseous conduction and solid conduction in the fibers, and for combining the various modes of heat transfer into a local, volume-averaged, thermal conductivity were considered. The governing heat transfer equations were solved numerically, and effective thermal conductivities were calculated from the steady-state results. An experimental apparatus was developed to measure the apparent thermal conductivity of insulation subjected to pressures, temperatures and temperature gradients representative of re-entry conditions for launch vehicles. The apparent thermal conductivity of an alumina fiber insulation was measured at nominal densities of 24, 48 and 96 kg/cu m. Data were obtained at environmental pressures from 10(exp 4) to 760 torr, with the insulation cold side maintained at room temperature and its hot side temperature varying up to 1000 C. The experimental results were used to evaluate the analytical models. The best analytical model resulted in effective thermal conductivity predictions that were within 8% of experimental results.

Daryabeigi, Kamran↗

NASA NTRS2011

Peer Review of Launch Environments

Catastrophic failures of launch vehicles during launch and ascent are currently modeled using equivalent trinitrotoluene (TNT) estimates. This approach tends to over-predict the blast effect with subsequent impact to launch vehicle and crew escape requirements. Bangham Engineering, located in Huntsville, Alabama, assembled a less-conservative model based on historical failure and test data coupled with physical models and estimates. This white paper summarizes NESC's peer review of the Bangham analytical work completed to date.

Wilson, Timmy R.↗

NASA NTRS2010

Atmospheric Delay Reduction Using KARAT for GPS Analysis and Implications for VLBI

We have been developing a state-of-the-art tool to estimate the atmospheric path delays by raytracing through mesoscale analysis (MANAL) data, which is operationally used for numerical weather prediction by the Japan Meteorological Agency (JMA). The tools, which we have named KAshima RAytracing Tools (KARAT)', are capable of calculating total slant delays and ray-bending angles considering real atmospheric phenomena. The KARAT can estimate atmospheric slant delays by an analytical 2-D ray-propagation model by Thayer and a 3-D Eikonal solver. We compared PPP solutions using KARAT with that using the Global Mapping Function (GMF) and Vienna Mapping Function 1 (VMF1) for GPS sites of the GEONET (GPS Earth Observation Network System) operated by Geographical Survey Institute (GSI). In our comparison 57 stations of GEONET during the year of 2008 were processed. The KARAT solutions are slightly better than the solutions using VMF1 and GMF with linear gradient model for horizontal and height positions. Our results imply that KARAT is a useful tool for an efficient reduction of atmospheric path delays in radio-based space geodetic techniques such as GNSS and VLBI.

Ichikawa, Ryuichi↗

NASA NTRS2003

Rate Constant for the Reaction CH3 + CH3 Yields C2H6 at T = 155 K and Model Calculation of the CH3 Abundance in the Atmospheres of Saturn and Neptune

The column abundances of CH3 observed by the Infrared Space Observatory (ISO) satellite on Saturn and Neptune were lower than predicted by atmospheric photochemical models, especially for Saturn. It has been suggested that the models underestimated the loss of CH3 due to poor knowledge of the rate constant k of the CH3 + CH3 self-reaction at the low temperatures and pressures of these atmospheres. Motivated by this suggestion, we undertook a combined experimental and photochemical modeling study of the CH3 + CH3 reaction and its role in determining planetary CH3 abundances. In a discharge flow-mass spectrometer system, k was measured at T = 155 K and three pressures of He. The results in units of cu cm/molecule/s are k(0.6 Torr) = 6.82 x 10(exp -11), k(1.0 Torr) = 6.98 x 10(exp -11), and k(1.5 Torr) = 6.91 x 10(exp -11). Analytical expressions for k were derived that (1) are consistent with the present laboratory data at T = 155 K, our previous data at T = 202 K and 298 K, and those of other studies in He at T = 296-298 K and (2) have some theoretical basis to provide justification for extrapolation. The derived analytical expressions were then used in atmospheric photochemical models for both Saturn and Neptune. These model results reduced the disparity with observations of Saturn, but not with observations of Neptune. However, the disparity for Neptune is much smaller. The solution to the remaining excess CH3 prediction in the models relative to the ISO observations lies, to a large extent, elsewhere in the CH3 photochemistry or transport, not in the CH3 + CH3 rate.

Cody, Regina J.↗

NASA NTRS1981

Shaded computer graphic techniques for visualizing and interpreting analytic fluid flow models

Mathematical models which predict the behavior of fluid flow in different experiments are simulated using digital computers. The simulations predict values of parameters of the fluid flow (pressure, temperature and velocity vector) at many points in the fluid. Visualization of the spatial variation in the value of these parameters is important to comprehend and check the data generated, to identify the regions of interest in the flow, and for effectively communicating information about the flow to others. The state of the art imaging techniques developed in the field of three dimensional shaded computer graphics is applied to visualization of fluid flow. Use of an imaging technique known as 'SCAN' for visualizing fluid flow, is studied and the results are presented.

Parke, F. I.↗

DOE OSTI2024

CCUS 2024, Interpreting the strain tensor Larry Murdoch Interpreting strain tensor data to characterize and monitor reservoirs for CO2 storage and other applications

Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and this has opened the door to new opportunities for characterization and monitoring during CCUS. We have demonstrated this method by deploying strainmeters at shallow depths (30 to 40m) and then conducting injection well tests in an underlying reservoir at 530m depth. The resulting data indicated that the horizontal strain at shallow strainmeters was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 ne/d over a few days (1 nanostrain = 1 part per billion strain). We then used the strain data to estimate reservoir properties, geometry and pressure through inversion of poroelastic forward models using both numerical and novel analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed fast, closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. This approach markedly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. Bayesian inversion is important because it provides predictions with uncertainties, which makes the results useful for decision making. We have shown with field tests and simulations that the strain tensor in the caprock is sensitive to pressure in the reservoir, reservoir properties and boundaries, and pressure in the caprock caused by leaks. These results indicate that measuring and interpreting the shallow strain tensor could be a valuable tool for both initial reservoir characterization efforts and long-term monitoring during CCUS. Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and our objective was to evaluate opportunities for strain monitoring during characterization and monitoring for CCUS. Our approach was to deploy strainmeters at shallow depths (30 to 40m) and then conduct injection well tests in an underlying reservoir at 530m depth. The results indicate that the horizontal strain at shallow strainmeters was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 ne/d over a few days (1 nanostrain = 1 part per billion strain). We then used the strain data to estimate reservoir properties, geometry and pressure through inversion of poroelastic forward models using both numerical and novel analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed fast, closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. This approach markedly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. Bayesian inversion is important because it provides predictions with uncertainties, which makes the results useful for decision making. In conclusion, we have shown with field tests and simulations that the strain tensor in the caprock is sensitive to pressure in the reservoir, reservoir properties and boundaries, and pressure in the caprock caused by leaks. These results indicate that measuring and interpreting the shallow strain tensor could be a valuable tool for both initial reservoir characterization efforts and long-term monitoring during CCUS.

Murdoch, Larry↗

DOE OSTI2024

Taylor-Expansion-Based Robust Power Flow in Unbalanced Distribution Systems: A Hybrid Data-Aided Method

Traditional power flow methods often adopt certain assumptions designed for passive balanced distribution systems, thus lacking practicality for unbalanced operation. moreover, their computation accuracy and efficiency are heavily subject to unknown errors and bad data in measurements or prediction data of distributed energy resources (ders). to address these issues, this paper proposes a hybrid data-aided robust power flow algorithm in unbalanced distribution systems, which combines taylor series expansion knowledge with a data-driven regression technique. the proposed method initiates a linearization power flow model to derive an explicitly analytical solution by modified taylor expansion. to mitigate the approximation loss that surges due to the der integration and bad data, we further develop a data-aided robust support vector regression approach to estimate the errors efficiently. comparative analysis in the 13-bus and 123-bus ieee unbalanced feeders shows that the proposed hybrid algorithm achieves superior computational efficiency, with guaranteed accuracy and robustness against outliers.

data-driven↗

NASA NTRS1974

A review of averaging techniques and their application to orbit determination systems

The theory of numerical averaging and analytical averaging will be reviewed and the application of these techniques to orbit and parameter estimation problems will be presented. Comparisons will be made between utilizing mean elements versus tracking data as the observation types. Results will be presented comparing the accuracy and efficiency of the combined orbit estimation and orbit prediction problem using averaged equations of motion, the Cowell equations of motion and the Brouwer general perturbation theory. The problem of converting the averaged element space back to osculating element space for orbit operations will also be discussed.

Velez, C. E.↗

NASA NTRS1980

Predicting propulsion system drag

DONBOL computer program analytically predicts axisymmetric nozzle afterbody pressure distributions and drag. Predictions are based on Neumann solution for inviscid external flow coupled with modified Reshotko-Tucker integral boundary layer technique, control volume method of Presz for calculating flow in separated region, and inviscid one dimensional solution for jet exhaust flow. Comparisons with experimental data indicate program accurately predicts pressure distributions of boattail afterbodies for which jet exhaust plume can be simulated by solid body. For other configurations, nozzle pressure drag seems to be significantly underpredicted. Method is limited to subsonic free stream mach numbers below those for which flow over body becomes sonic.

Putnam, L. E.↗

NASA NTRS1983

Design of sidewall treatment of cabin noise control of a twin engine turboprop aircraft

An analytical procedure was used to predict the noise transmission into the cabin of a twin engine general aviation aircraft. This model was then used to optimize the interior A weighted noise levels to an average value of about 85 dBA. The surface pressure noise spectral levels were selected utilizing experimental flight data and empirical predictions. The add on treatments considered in this optimization study include aluminum honeycomb panels, constrained layer damping tape, porous acoustic blankets, acoustic foams, septum barriers and limp trim panels which are isolated from the vibration of the main sidewall structure. To reduce the average noise level in the cabin from about 102 kBA (baseline) to 85 dBA (optimized), the added weight of the noise control treatment is about 2% of the total gross takeoff weight of the aircraft.

Vaicaitis, R.↗

NASA NTRS1985

Estimating the R-curve from residual strength data

A method is presented for estimating the crack-extension resistance curve (R-curve) from residual-strength (maximum load against original crack length) data for precracked fracture specimens. The method allows additional information to be inferred from simple test results, and that information can be used to estimate the failure loads of more complicated structures of the same material and thickness. The fundamentals of the R-curve concept are reviewed first. Then the analytical basis for the estimation method is presented. The estimation method has been verified in two ways. Data from the literature (involving several materials and different types of specimens) are used to show that the estimated R-curve is in good agreement with the measured R-curve. A recent predictive blind round-robin program offers a more crucial test. When the actual failure loads are disclosed, the predictions are found to be in good agreement.

Orange, T. W.↗