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At least 865 records · Page 48

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NASA NTRS1974

Optimization of self-acting herringbone-grooved journal bearings for maximum stability

Groove parameters were determined to maximize the stability of herringbone-grooved journal bearings. Parameters optimized were groove depth, width, length, and angle. Optimization was performed by using a small-eccentricity, infinite-groove analysis in conjunction with a previously developed Newton-Raphson procedure for bearings with the smooth member rotating or with the grooved member rotating at low compressibility numbers, and a newly developed vector technique for bearings with the grooved member rotating at high compressibility numbers. The design curves in this report enable one to choose the optimum bearing for a wide range of operating conditions. Compared with bearings optimized to maximize load capacity, bearings optimized for stability allow a thousandfold increase in bearing-supported mass in some cases before onset of instability, and lose no more than 77 percent of their load capacity in any case studied. Stability is much greater when the grooved member rotates.

Fleming, D. P.↗

NASA NTRS1975

Effect of processing variables on the thermophysical properties of polybenzimidazole foams

The relationships are described among prepolymer purity, processing parameters, and additives to the thermophysical and chemical properties of polybenzimidazole foams in the density range from 24 to 80 kg/cu m. Foam properties are shown to be affected by differences in prepolymer purity, curing schedule, and the presence of additives in the foam. High-temperature compressive properties were improved by postcuring at 527 C. Surfactant additives were found to improve uniformity of cell size. Foams were characterized according to high-temperature mechanical properties, density, porosity, thermal diffusivity, thermal conductivity, and specific heat.

Kourtides, D. A.↗

NASA NTRS1981

Determination of in vivo mechanical properties of long bones from their impedance response curves

A mathematical model consisting of a uniform, linear, visco-elastic, Euler-Bernoulli beam to represent the ulna or tibia of the vibrating forearm or leg system is developed. The skin and tissue compressed between the probe and bone is represented by a spring in series with the beam. The remaining skin and tissue surrounding the bone is represented by a visco-elastic foundation with mass. An extensive parametric study is carried out to determine the effect of each parameter of the mathematical model on its impedance response. A system identification algorithm is developed and programmed on a digital computer to determine the parametric values of the model which best simulate the data obtained from an impedance test.

Borders, S. G.↗

NASA NTRS1992

The effect of initial imperfections on shell stability: An updated review

The development of the Delft Interactive Shell Design Code (DISDECO) is described. The purpose is to make the accumulated theoretical, numerical, and practical knowledge of the last years readily accessible to users interested in the analysis of buckling sensitive structures. With this open ended, hierarchical, interactive computer code, the user can access workstation programs of increasing complexity. As a first update of DISDECO, the computational modules of the initial level were modified so as to handle combined loads consisting of axial compression, internal and external pressure, and clockwise or counter clockwise torque. The applied load is assumed to have a uniform spatial distribution and is divided into a fixed and a variable part. The magnitude of the variable part is allowed to vary in proportion to a load parameter Lambda. This leads to an eigenvalue problem for the critical lambda sub C.

Arbocz, J.↗

NASA NTRS1995

Hydrodynamics of coalescing binary neutron stars: Ellipsoidal treatment

We employ an approximate treatment of dissipative hydrodynamics in three dimensions to study the coalescence of binary neutron stars driven by the emission of gravitational waves. The stars are modeled as compressible ellipsoids obeying a polytropic equation of state; all internal fluid velocities are assumed to be linear functions of the coordinates. The hydrodynamics equations then reduce to a set of coupled ordinary differential equations for the evolution of the principal axes of the ellipsoids, the internal velocity parameters, and the binary orbital parameters. Gravitational radiation reaction and viscous dissipation are both incorporated. We set up exact initial binary equilibrium configurations and follow the transition from the quasi-static, secular decay of the orbit at large separation to the rapid dynamical evolution of the configurations just prior to contact. A hydrodynamical instability resulting from tidal interactions significantly accelerates the coalescence at small separation, leading to appreciable radial infall velocity and tidal lag angles near contact. This behavior is reflected in the gravitational waveforms and may be observable by gravitational wave detectors under construction. In cases where the neutron stars have spins which are not aligned with the orbital angular momentum, the spin-induced quadrupole moment can lead to precession of the orbital plane and therefore modulation of the gravitational wave amplitude even at large orbital radius. However, the amplitude of the modulation is small for typical neutron star binaries with spins much smaller than the orbital angular momentum.

Lai, Dong↗

NASA NTRS2011

Three-Dimensional Finite Element Ablative Thermal Response and Thermostructural Design of Thermal Protection Systems

A finite element ablation and thermal response program is presented for simulation of three-dimensional transient thermostructural analysis. The three-dimensional governing differential equations and finite element formulation are summarized. A novel probabilistic design methodology for thermal protection systems is presented. The design methodology is an eight step process beginning with a parameter sensitivity study and is followed by a deterministic analysis whereby an optimum design can determined. The design process concludes with a Monte Carlo simulation where the probabilities of exceeding design specifications are estimated. The design methodology is demonstrated by applying the methodology to the carbon phenolic compression pads of the Crew Exploration Vehicle. The maximum allowed values of bondline temperature and tensile stress are used as the design specifications in this study.

Dec, John A.↗

NASA NTRS2014

Expanding the Description of Spaceflight Effects beyond Bone Mineral Density [BMD]: Trabecular Bone Score [TBS] in ISS Astronauts

Dual-energy x-ray absorptiometry [DXA] is the widely-applied bone densitometry method used to diagnose osteoporosis in a terrestrial population known to be at risk for age-related bone loss. This medical test, which measures areal bone mineral density [aBMD] of clinically-relevant skeletal sites (e.g., hip and spine), helps the clinician to identify which persons, among postmenopausal women and men older than 50 years, are at high risk for low trauma or fragility fractures and might require an intervention. The most recognized osteoporotic fragility fracture is the vertebral compression fracture which can lead to kyphosis or hunched backs typically seen in the elderly. DXA measurement of BMD however is recognized to be insufficient as a sole index for assessing fracture risk. DXA's limitation may be related to its inability to monitor changes in structural parameters, such as trabecular vs. cortical bone volumes, bone geometry or trabecular microarchitecture. Hence, in order to understand risks to human health and performance due to space exposure, NASA needs to expand its measurements of bone to include other contributors to skeletal integrity. To this aim, the Bone and Mineral Lab conducted a pilot study for a novel measurement of bone microarchitecture that can be obtained by retrospective analysis of DXA scans. Trabecular Bone Score (TBS) assesses changes to trabecular microarchitecture by measuring the grey color "texture" information extracted from DXA images of the lumbar spine. An analysis of TBS in 51 ISS astronauts was conducted to assess if TBS could detect 1) an effect of spaceflight and 2) a response to countermeasures independent of DXA BMD. In addition, changes in trunk body lean tissue mass and in trunk body fat tissue mass were also evaluated to explore an association between body composition, as impacted by ARED exercise, and bone microarchitecture. The pilot analysis of 51 astronaut scans of the lumbar spine suggests that, following an ISS mission, DXA BMD and TBS are detecting different effects of ARED exercise and of ARED + Bisphosphonate on the lumbar spine of astronauts. There is emerging evidence associating reduced TBS with terrestrial metabolic bone disorders where a TBS <1.200 is associated with "degraded" while > 1.350 is associated with "normal." However, it is not possible to conclude how the spaceflight-induced changes in TBS increase risk for vertebral fractures in the astronaut or if changes in body composition of the trunk region could be an indirect method of assessing exercise effect on bone microarchitecture. More importantly, this pilot analysis demonstrates a new, minimal risk approach for monitoring changes to vertebral bone microarchitecture. This method could help assess the combined skeletal effects of spaceflight with the effects of aging in the astronaut after return to Earth.

Sibonga, J. D.↗

NASA NTRS1973

High speed flow past wings

The analytical solution to the transonic small perturbation equation which describes steady compressible flow past finite wings at subsonic speeds can be expressed as a nonlinear integral equation with the perturbation velocity potential as the unknown function. This known formulation is substituted by a system of nonlinear algebraic equations to which various methods are applicable for its solution. Due to the presence of mathematical discontinuities in the flow solutions, however, a main computational difficulty was to ensure uniqueness of the solutions when local velocities on the wing exceeded the speed of sound. For continuous solutions this was achieved by embedding the algebraic system in an one-parameter operator homotopy in order to apply the method of parametric differentiation. The solution to the initial system of equations appears then as a solution to a Cauchy problem where the initial condition is related to the accompanying incompressible flow solution. In using this technique, however, a continuous dependence of the solution development on the initial data is lost when the solution reaches the minimum bifurcation point. A steepest descent iteration technique was therefore, added to the computational scheme for the calculation of discontinuous flow solutions. Results for purely subsonic flows and supersonic flows with and without compression shocks are given and compared with other available theoretical solutions.

Norstrud, H.↗

DOE OSTI2025

Deciphering the small-angle scattering of polydisperse hard spheres using deep learning

We introduce a deep learning approach for analyzing the scattering function of the polydisperse hard sphere system. We use a variational autoencoder-based neural network to learn the bidirectional mapping between the scattering function and the system parameters, including the volume fraction and polydispersity. Such that the trained model serves both as a generator that produces a scattering function from the system parameters and an inferrer that extracts system parameters from the scattering function. We first generate a scattering dataset by carrying out molecular dynamics simulations of the polydisperse hard spheres modeled by the truncated-shifted Lennard-Jones model, then analyze the scattering function dataset using singular value decomposition to confirm the feasibility of dimensional compression. Then, we split the dataset into training and testing sets and train our neural network on the training set only. Our generator model produces a scattering function with significantly higher accuracy compared to the traditional Percus–Yevick approximation and β correction, and the inferrer model can extract the volume fraction and polydispersity with much higher accuracy than traditional model functions.

Ding, Lijie [ORNL] (ORCID:0000000227454606)↗

DOE OSTI2023

Lagrangian large eddy simulations via physics-informed machine learning

High-Reynolds number homogeneous isotropic turbulence (HIT) is fully described within the Navier–Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as large eddy simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about effects of subgrid scales on the resolved scales. Here, we take an alternative approach and design LES heuristics stated in terms of Lagrangian particles moving with the flow. Our Lagrangian LES, thus L-LES, is described by equations generalizing the weakly compressible smoothed particle hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from direct numerical simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The subgrid-scale contributions are modeled separately with physical constraints to account for the effects from unresolved scales. We build the resulting model under the differentiable programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our L-LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Unsupervised learning approaches to characterizing heterogeneous samples using X-ray single-particle imaging

One of the outstanding analytical problems in X-ray single-particle imaging (SPI) is the classification of structural heterogeneity, which is especially difficult given the low signal-to-noise ratios of individual patterns and the fact that even identical objects can yield patterns that vary greatly when orientation is taken into consideration. Proposed here are two methods which explicitly account for this orientation-induced variation and can robustly determine the structural landscape of a sample ensemble. The first, termed common-line principal component analysis (PCA), provides a rough classification which is essentially parameter free and can be run automatically on any SPI dataset. The second method, utilizing variation auto-encoders (VAEs), can generate 3D structures of the objects at any point in the structural landscape. Both these methods are implemented in combination with the noise-tolerant expand–maximize–compress (EMC) algorithm and its utility is demonstrated by applying it to an experimental dataset from gold nanoparticles with only a few thousand photons per pattern. Both discrete structural classes and continuous deformations are recovered. These developments diverge from previous approaches of extracting reproducible subsets of patterns from a dataset and open up the possibility of moving beyond the study of homogeneous sample sets to addressing open questions on topics such as nanocrystal growth and dynamics, as well as phase transitions which have not been externally triggered.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Machine learning-driven design and self-sensing capabilities of automotive bumper lattices for adaptive impact response

We present a novel approach to design an automotive bumper energy absorber using carbon fiber reinforced polymer composites, optimized to meet conflicting performance requirements for two distinct impact scenarios. The design must satisfy both a low-speed (2.5 mph) pendulum intrusion test, simulating vehicle-to-vehicle collisions, and a high-speed (25 mph) leg flexion test, replicating pedestrian impacts. These tests demand opposing deformation characteristics: high flexibility (deformation < 85 mm) for the former and high stiffness (deformation < 22 mm) for the latter. To address these contradictory requirements, we developed a machine learning (ML) framework for inverse optimization of lattice designs and material selection. Unlike traditional iterative design processes, our ML model directly outputs optimal design parameters and material choices based on target performance inputs. The energy absorber was fabricated using advanced additive manufacturing techniques, including extrusion deposition and digital light processing. The integration of carbon fibers provides multifunctionality to the bumper structure, enabling self-sensing capabilities through changes in electrical resistivity under compression. This electrical response demonstrates high repeatability under multiple cycles at 2% compression and exhibits distinct signatures during crack formation under high deformation. This research offers adaptive performance through innovative design methodologies and smart material integration. The approach has potential applications in various fields requiring adaptive energy absorption and real-time structural health monitoring.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗

DOE OSTI2023

Code for the manuscript "Lagrangian Large Eddy Simulations vis Physics-informed Machine Learning"

We would like to disclose a code based on Python/Pytorch, in which we implement the data-driven physics-informed machine learning of Lagrangian large eddy simulation that is described in the manuscript "Lagrangian Large Eddy Simulations via Physics-Informed Machine Learning ". High-Reynolds number Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as Large Eddy Simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about the effects of sub-grid scales on the resolved scales. Here, we take an alternative approach and design novel LES heuristics stated in terms of Lagrangian particles moving with the flow. Our \emph{Lagrangian LES}, thus L-LES, is described by equations generalizing the weakly compressible Smoothed Particle Hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from Direct Numerical Simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The sub-grid scale contributions are modeled separately with physical constraints to account for the effects from un-resolved scales. We build the resulting model under the Differentiable Programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our Lagrangian LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

Tian, Yifeng↗

NASA NTRS1974

A simple method of calculating power-law velocity profile exponents from experimental data

Analytical expressions for the effects of compressibility and heat transfer on laminar and turbulent shape factors H have been developed. Solving the turbulent equation for the power law velocity profile exponent N has resulted in a simple technique by which the N values of experimental turbulent profiles can be calculated directly from the integral parameters. Thus the data plotting, curve fitting, and slope measuring, which is the normal technique of obtaining experimental N values, is eliminated. The N values obtained by this method should be within the accuracy with which they could be measured.

Allen, J. M.↗

NASA NTRS1974

Quasi-static analysis of foil journal bearings for a Brayton cycle turboalternator

A quasi-static analysis is presented for foil journal bearings designed for a NASA Brayton Cycle Turboalternator. Included in the analysis are effects of 'slack' (due to flexural rigidity of the foil), of frictionally restrained extension of the foil-length in contact with cylindrical guides, of fluid inertia and compressibility, and of thermal expansion of rotor, foil and supporting structure. Comparisons are made with results of early experiments performed by Licht (1968, 1969) and recent data of Licht and Branger (1973). Variatons of film thickness, foil tension and bearing stiffness are presented graphically as functions of pertinent parameters for the case of operation in zero-gravity environment.

Eshel, A.↗

NASA NTRS1975

Lunar surface solar wind observations at the Apollo 12 and Apollo 15 sites

The solar wind-lunar magnetic field interaction is examined by comparing Apollo 12 and Apollo 15 solar wind spectrometric data. The instrumentation and data analysis methods are described along with the observations at the Apollo 15 site, and the data from the two sites are compared. The results show no noticeable differences between the properties of the upstream solar wind and the plasma observed at the Apollo 15 site (where the local magnetic field is relatively weak) and strong perturbations in the solar wind at the Apollo 12 site (where the field is relatively strong), which include deceleration, deflection, and heating of solar wind protons, focusing or defocusing of the ion flux, and an increased level of plasma parameter fluctuations. These effects are shown to require a charge-separated electric field above the lunar surface and a scale size of about 5 km for the local magnetic field at the Apollo 12 site and to suggest that local lunar magnetic field regions cause lunar limb compression waves which should be more noticeable for low solar wind dynamic pressures.

Clay, D. R.↗

NASA NTRS1980

Aero-optics overview

Various aero-optical phenomena are discussed with reference to their effect on airborne high energy lasers. Major emphasis is placed on: compressibility effects induced in the surrounding flow field; viscous effects which manifests themselves as aircraft boundary layers or shear layers; inviscid flow fields surrounding the aircraft due to airflow around protuberance such as laser turret assemblies; and shocks, established whenever local flow exceeds Mach one. The significant physical parameters affecting the interaction of a laser beam with a turbulent boundary layer are also described.

Gilbert, K. G.↗

NASA NTRS1987

Details of the computed flowfield over a circular cylinder at Reynolds number 1200

The application of an upwind-biased implicit approximate factorization Navier-Stokes algorithm to the unsteady impulsive start-up flow over a circular cylinder at Reynolds number 1200 is described. The complete form of the compressible Navier-Stokes equations is used, and the algorithm is second-order accurate in both space and time. The development with time of the shape and size of the separated vortical flow region is computed, as well as the time-variation of several boundary layer parameters and profile shapes. Computations, in general, show excellent agreement with experiment, although the present method predicts a more rapid onset of reversed flow on the cylinder than evidenced in experiment. The changes that the vortical region behind the cylinder undergoes as the symmetric flow transitions to periodic vortex shedding are discussed. The flow becomes periodic with a Strouhal frequency of 0.222, which compares well with the experimental value of approximately 0.21. The effect of grid density on the development of the unsteady flow is also shown.

Rumsey, C. L.↗