Search NASA⌕ Search

SEARCH · Search NASA

Results for “interface structure prediction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5

Test-Anchored Vibration Response Predictions for an Acoustically Energized Curved Orthogrid Panel with Mounted Components

A rich body of vibroacoustic test data was recently generated at Marshall Space Flight Center for a curved orthogrid panel typical of launch vehicle skin structures. Several test article configurations were produced by adding component equipment of differing weights to the flight-like vehicle panel. The test data were used to anchor computational predictions of a variety of spatially distributed responses including acceleration, strain and component interface force. Transfer functions relating the responses to the input pressure field were generated from finite element based modal solutions and test-derived damping estimates. A diffuse acoustic field model was employed to describe the assumed correlation of phased input sound pressures across the energized panel. This application demonstrates the ability to quickly and accurately predict a variety of responses to acoustically energized skin panels with mounted components. Favorable comparisons between the measured and predicted responses were established. The validated models were used to examine vibration response sensitivities to relevant modeling parameters such as pressure patch density, mesh density, weight of the mounted component and model form. Convergence metrics include spectral densities and cumulative root-mean squared (RMS) functions for acceleration, velocity, displacement, strain and interface force. Minimum frequencies for response convergence were established as well as recommendations for modeling techniques, particularly in the early stages of a component design when accurate structural vibration requirements are needed relatively quickly. The results were compared with long-established guidelines for modeling accuracy of component-loaded panels. A theoretical basis for the Response/Pressure Transfer Function (RPTF) approach provides insight into trends observed in the response predictions and confirmed in the test data. The software modules developed for the RPTF method can be easily adapted for quick replacement of the diffuse acoustic field with other pressure field models; for example a turbulent boundary layer (TBL) model suitable for vehicle ascent. Wind tunnel tests have been proposed to anchor the predictions and provide new insight into modeling approaches for this type of environment. Finally, component vibration environments for design were developed from the measured and predicted responses and compared with those derived from traditional techniques such as Barrett scaling methods for unloaded and component-loaded panels.

Frady, Gregory P.↗

Utilizing Photogrammetry and Strain Gage Measurement to Characterize Pressurization of an Inflatable Module

This paper documents the integration of a large hatch penetration into an inflatable module. This paper also documents the comparison of analytical load predictions with measured results utilizing strain measurement. Strain was measured by utilizing photogrammetric measurement and through measurement obtained from strain gages mounted to selected clevises that interface with the structural webbings. Bench testing showed good correlation between strain measurement obtained from an extensometer and photogrammetric measurement especially after the fabric has transitioned through the low load/high strain region of the curve. Test results for the full-scale torus showed mixed results in the lower load and thus lower strain regions. Overall strain, and thus load, measured by strain gages and photogrammetry tracked fairly well with analytical predictions. Methods and areas of improvements are discussed.

Valle, Gerard D.↗

Constitutive Modeling of Nanotube/Polymer Composites with Various Nanotube Orientations

In this study, a technique has been proposed for developing constitutive models for polymer composite systems reinforced with single-walled carbon nanotubes (SWNT) with various orientations with respect to the bulk material coordinates. A nanotube, the local polymer adjacent to the nanotube, and the nanotube/polymer interface have been modeled as an equivalent-continuum fiber by using an equivalent-continuum modeling method. The equivalent-continuum fiber accounts for the local molecular structure and bonding information and serves as a means for incorporating micromechanical analyses for the prediction of bulk mechanical properties of SWNT/polymer composite. As an example, the proposed approach is used for the constitutive modeling of a SWNT/LaRC-SI (with a PmPV interface) composite system, with aligned nanotubes, three-dimensionally randomly oriented nanotubes, and nanotubes oriented with varying degrees of axisymmetry. It is shown that the Young s modulus is highly dependent on the SWNT orientation distribution.

Odegard, Gregory M.↗

NASA Langley developments in response calculations needed for failure and life prediction

NASA Langley developments in response calculations needed for failure and life predictions are discussed. Topics covered include: structural failure analysis in concurrent engineering; accuracy of independent regional modeling demonstrated on classical example; functional interface method accurately joins incompatible finite element models; interface method for insertion of local detail modeling extended to curve pressurized fuselage window panel; interface concept for joining structural regions; motivation for coupled 2D-3D analysis; compression panel with discontinuous stiffener coupled 2D-3D model and axial surface strains at the middle of the hat stiffener; use of adaptive refinement with multiple methods; adaptive mesh refinement; and studies on quantity effect of bow-type initial imperfections on reliability of stiffened panels.

Housner, Jerrold M.↗

A Feasibility Study of Synthesizing Subsurfaces Modeled with Computational Neural Networks

This paper investigates the feasibility of synthesizing substructures modeled with computational neural networks. Substructures are modeled individually with computational neural networks and the response of the assembled structure is predicted by synthesizing the neural networks. A superposition approach is applied to synthesize models for statically determinate substructures while an interface displacement collocation approach is used to synthesize statically indeterminate substructure models. Beam and plate substructures along with components of a complicated Next Generation Space Telescope (NGST) model are used in this feasibility study. In this paper, the limitations and difficulties of synthesizing substructures modeled with neural networks are also discussed.

Wang, John T.↗

An analysis of fiber-matrix interface failure stresses for a range of ply stress states

A graphite/bismaleimide laminate was prepared without the usual fiber treatment and was tested over a wide range of stress states to measure its ply cracking strength. These tests were conducted using off-axis flexure specimens and produced fiber-matrix interface failure data over a correspondingly wide range of interface stress states. The absence of fiber treatment, weakened the fiber-matrix interfaces and allowed these tests to be conducted at load levels that did not yield the matrix. An elastic micromechanics computer code was used to calculate the fiber-matrix interface stresses at failure. Two different fiber-array models (square and diamond) were used in these calculations to analyze the effects of fiber arrangement as well as stress state on the critical interface stresses at failure. This study showed that both fiber-array models were needed to analyze interface stresses over the range of stress states. A linear equation provided a close fit to these critical stress combinations and, thereby, provided a fiber-matrix interface failure criterion. These results suggest that prediction procedures for laminate ply cracking can be based on micromechanics stress analyses and appropriate fiber-matrix interface failure criteria. However, typical structural laminates may require elastoplastic stress analysis procedures that account for matrix yielding, especially for shear-dominated ply stress states.

Crews, J. H.↗

Observation and Modeling of Single Wall Carbon Nanotube Bend Junctions

Single wall carbon nanotube (SWNT) bends, with diameters from approx. 1.0 to 2.5 nm and bend angles from 18 deg. to 34 deg., are observed in catalytic decomposition of hydrocarbons at 600 - 1200 C. An algorithm using molecular dynamics simulation (MD) techniques is developed to model these structures that are considered to be SWNT junctions formed by topological defects (i.e. pentagon-heptagon pairs). The algorithm is used to predict the tube helicities and defect configurations for bend junctions using the observed tube diameters and bend angles. The number and arrangement of the defects at the junction interfaces are found to depend on the tube helicities and bend angle. The structural and energetic calculations using the Brenner potential show a number of stable junction configurations for each bend angle with the 34 deg. bends being more stable than the others. Tight binding calculations for local density of state (LDOS) and transmission coefficients are carried out to investigate electrical properties of the bend junctions.

Han, Jie↗

Near-contact diffusion and compensation in extrinsic photoconductors

Carrier diffusion from heavily doped contact regions has been experimentally monitored with resistivity measurements of variable thickness Si:P extrinsic photoconductors (n(+) -n-n(+)). Modeling of free carrier diffusion at the interface of heavily doped contacts and highly resistive bulk at low temperatures predicts extended regions (5-30 microns) of excess carriers in high purity materials so that, in thin device structures, free carrier diffusion profiles from each contact will overlap and determine the resistivity of the device. In this work, a decrease in resistivity of four orders of magnitude was observed in a 5-micron thick structure compared to a 10-micron thick device. The resistivity of an ohmic structure in the thin limit is strongly dependent on the bulk and near-contact compensation, and resistivity measurements can be used as a sensitive measure of compensation at interfaces or in the tail of implanted layers.

Olsen, C. S.↗

Decoupled dynamic analysis of combined systems by iterative determination of interface accelerations

A dynamic analysis technique is presented that can be used to determine the response of a discrete model of a large linear structural system composed of multiple substructures. The technique circumvents the costly computation of the modal characteristics of the combined system. This is accomplished by relying on a predictor-corrector scheme to converge iteratively to the interface accelerations of the combined system, while the equations of motions of the individual structures are integrated separately. In this regard, the temporal slopes of the interface accelerations (jerks) are computed at each time point of integration to predict the interface accelerations at the next time point. The proposed technique is exemplified by conducting a Space Shuttle landing loads analysis; the obtained numerical data demonstrate its reliability and efficiency.

Spanos, P. D.↗

A numerical study of mixing in supersonic combustors with hypermixing injectors

A numerical study was conducted to evaluate the performance of wall mounted fuel-injectors designed for potential Supersonic Combustion Ramjet (SCRAM-jet) engine applications. The focus of this investigation was to numerically simulate existing combustor designs for the purpose of validating the numerical technique and the physical models developed. Three different injector designs of varying complexity were studied to fully understand the computational implications involved in accurate predictions. A dual transverse injection system and two streamwise injector designs were studied. The streamwise injectors were designed with swept ramps to enhance fuel-air mixing and combustion characteristics at supersonic speeds without the large flow blockage and drag contribution of the transverse injection system. For this study, the Mass-Averaged Navier-Stokes equations and the chemical species continuity equations were solved. The computations were performed using a finite-volume implicit numerical technique and multiple block structured grid system. The interfaces of the multiple block structured grid systems were numerically resolved using the flux-conservative technique. Detailed comparisons between the computations and existing experimental data are presented. These comparisons show that numerical predictions are in agreement with the experimental data. These comparisons also show that a number of turbulence model improvements are needed for accurate combustor flowfield predictions.

Lee, J.↗

A numerical study of mixing in supersonic combustors with hypermixing injectors

A numerical study was conducted to evaluate the performance of wall mounted fuel-injectors designed for potential Supersonic Combustion Ramjet (SCRAM-jet) engine applications. The focus of this investigation was to numerically simulate existing combustor designs for the purpose of validating the numerical technique and the physical models developed. Three different injector designs of varying complexity were studied to fully understand the computational implications involved in accurate predictions. A dual transverse injection system and two streamwise injector designs were studied. The streamwise injectors were designed with swept ramps to enhance fuel-air mixing and combustion characteristics at supersonic speeds without the large flow blockage and drag contribution of the transverse injection system. For this study, the Mass-Average Navier-Stokes equations and the chemical species continuity equations were solved. The computations were performed using a finite-volume implicit numerical technique and multiple block structured grid system. The interfaces of the multiple block structured grid systems were numerically resolved using the flux-conservative technique. Detailed comparisons between the computations and existing experimental data are presented. These comparisons show that numerical predictions are in agreement with the experimental data. These comparisons also show that a number of turbulence model improvements are needed for accurate combustor flowfield predictions.

Lee, J.↗

NASA Engineering and Safety Center Technical Bulletin No. 22-04: Uncertainty Quantification of Reduced Order Structural Dynamic Models

Uncertainty quantification (UQ) provides statistical bounds on prediction accuracy based on finite element model (FEM) uncertainty. An alternate method for UQ, called the Hybrid Parametric Variation (HPV) combines a parametric variation of the Hurty/Craig-Bampton (HCB) fixed-interface (FI) modal frequencies with a nonparametric variation (NPV) method. This provides a UQ method that can be traced to test data, which can be updated as additional data and improved correlated models become available.

Uncertainty Quantification↗

Modeling Autogenous Pressurization and Draining of a Cryogenic Storage Tank in Normal Gravity

A two-phase CFD model for autogenous pressurization and draining of a cryogenic storage tank is presented using both the Sharp Interface and Volume-Of-Fluid (VOF) approaches for capturing the front and the associated interfacial heat, mass and momentum transfer between the liquid and vapor regions. Both models are validated against data provided by the Cryogenic Propellant Storage and Transfer (CPST) Engineering Development Unit (EDU) experiment. The results of the autogenous pressurization are presented first, focusing on the phase change and turbulence effects on the tank pressure and temperature predictions. Both the Sharp Interface (SI-CFD) and VOF (VOF-CFD) multiphase models predict tank pressure during pressurization within 3% of the measured values. The sensitivity of key physical and numerical parameters of the problem are tested using the Sharp Interface model. Effects of the accommodation coefficient (AC), and the computational grid structure are studied. The second part of this paper is devoted to validating the SI-VOF model, with an enhanced capability of moving the liquid-vapor interface, against the draining segment of the EDU experiment. The VOF-CFD model was also used to simulate tank draining and its results were compared with the results of the Sharp Interface model with the moving interface. Both models predict tank pressure during draining within 3.5% of the measured values. Pressure decrease rate is underpredicted by both models during the first 100 seconds of draining but matches the experimental rate for the rest of the simulation.

Computational Fluid Dynamics↗

Modeling Autogenous Pressurization and Draining of a Cryogenic Storage Tank in Normal Gravity

A two-phase CFD model for autogenous pressurization and draining of a cryogenic storage tank is presented using both the Sharp Interface and Volume-Of-Fluid (VOF) approaches for capturing the front and the associated interfacial heat, mass and momentum transfer between the liquid and vapor regions. Both models are validated against data provided by the Cryogenic Propellant Storage and Transfer (CPST) Engineering Development Unit (EDU) experiment1. The results of the autogenous pressurization are presented first, focusing on the phase change and turbulence effects on the tank pressure and temperature predictions. Both the Sharp Interface (SI-CFD) and VOF (VOF-CFD) multiphase models predict tank pressure during pressurization within 3% of the measured values. The sensitivity of key physical and numerical parameters of the problem are tested using the Sharp Interface model. Effects of the accommodation coefficient (AC), and the computational grid structure are studied. The second part of this paper is devoted to validating the SI-VOF model, with an enhanced capability of moving the liquid-vapor interface, against the draining segment of the EDU experiment. The VOF-CFD model was also used to simulate tank draining and its results were compared with the results of the Sharp Interface model with the moving interface. Both models predict tank pressure during draining within 3.5% of the measured values. Pressure decrease rate is underpredicted by both models during the first 100 seconds of draining but matches the experimental rate for the rest of the simulation.

Computational Fluid Dynamics↗

Cluster expansion by transfer learning for phase stability predictions

Recent progress towards universal machine-learned interatomic potentials holds considerable promise for materials discovery. Yet the accuracy of these potentials for predicting phase stability may still be limited. In contrast, cluster expansions provide accurate phase stability predictions but are computationally demanding to parameterize from first principles, especially for structures of low dimension or with a large number of components, such as interfaces or multimetal catalysts. We overcome this trade-off via transfer learning. Using Bayesian inference, we incorporate prior statistical knowledge from machine-learned and physics-based potentials, enabling us to sample the most informative configurations and to efficiently fit first-principles cluster expansions. Furthermore, this algorithm is tested on Pt:Ni, showing robust convergence of the mixing energies as a function of sample size with reduced statistical fluctuations.

36 MATERIALS SCIENCE↗

Improved Model for MOS Breakdown

With an improved model, accelerated high-field tests can be used to predict gate-oxide breakdown in metal-oxide-semi-conductor (MOS) structures. Principal mechanism in MOS breakdown is mobile-ion emission from metal/oxide interface, which occurs during application of positive gate-bias field. Breakdown is related to clustering of emitted ions at localized defect sites in oxide/silicon interface. Using new model to interpret data, tests that normally take several weeks at low fields to accumulate sufficient statistics can be completed in only a few hours at high fields.

Li, S. P.↗

Advanced Computational Modeling Approaches for Shock Response Prediction

Motivation: (1) The activation of pyroshock devices such as explosives, separation nuts, pin-pullers, etc. produces high frequency transient structural response, typically from few tens of Hz to several hundreds of kHz. (2) Lack of reliable analytical tools makes the prediction of appropriate design and qualification test levels a challenge. (3) In the past few decades, several attempts have been made to develop methodologies that predict the structural responses to shock environments. (4) Currently, there is no validated approach that is viable to predict shock environments overt the full frequency range (i.e., ~100 Hz to 10 kHz). Scope: (1) Model, analyze, and interpret space structural systems with complex interfaces and discontinuities, subjected to shock loads. (2) Assess the viability of a suite of numerical tools to simulate transient, non-linear solid mechanics and structural dynamics problems, such as shock wave propagation.

Derkevorkian, Armen↗

Prediction of carbon nanostructure mechanical properties and the role of defects using machine learning

Graphene-based nanostructures hold immense potential as strong and lightweight materials, however, their mechanical properties such as modulus and strength are difficult to fully exploit due to challenges in atomic-scale engineering. This study presents a database of over 2,000 pristine and defective nanoscale CNT bundles and other graphitic assemblies, inspired by microscopy, with associated stress–strain curves from reactive molecular dynamics (MD) simulations using the reactive INTERFACE force field (IFF-R). These 3D structures, containing up to 80,000 atoms, enable detailed analyses of structure-stiffness-failure relationships. By leveraging the database and physics- and chemistry-informed machine learning (ML), accurate predictions of elastic moduli and tensile strength are demonstrated at speeds 1,000 to 10,000 times faster than efficient MD simulations. Hierarchical Graph Neural Networks with Spatial Information (HS-GNNs) are introduced, which integrate chemistry knowledge. HS-GNNs as well as extreme gradient boosted trees (XGBoost) achieve forecasts of mechanical properties of arbitrary carbon nanostructures with only 3 to 6% mean relative error. The reliability equals experimental accuracy and is up to 20 times higher than other ML methods. Predictions maintain 8 to 18% accuracy for large CNT bundles, CNT junctions, and carbon fiber cross-sections outside the training distribution. The physics- and chemistry-informed HS-GNN works remarkably well for data outside the training range while XGBoost works well with limited training data inside the training range. The carbon nanostructure database is designed for integration with multimodal experimental and simulation data, scalable beyond 100 nm size, and extendable to chemically similar compounds and broader property ranges. The ML approaches have potential for applications in structural materials, nanoelectronics, and carbon-based catalysts.

Winetrout, Jordan J.↗