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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Development of an Input Suite for an Orthotropic Composite Material Model

An orthotropic three-dimensional material model suitable for use in modeling impact tests has been developed that has three major components elastic and inelastic deformations, damage and failure. The material model has been implemented as MAT213 into a special version of LS-DYNA and uses tabulated data obtained from experiments. The prominent features of the constitutive model are illustrated using a widely-used aerospace composite the T800S3900-2B[P2352W-19] BMS8-276 Rev-H-Unitape fiber resin unidirectional composite. The input for the deformation model consists of experimental data from 12 distinct experiments at a known temperature and strain rate: tension and compression along all three principal directions, shear in all three principal planes, and off axis tension or compression tests in all three principal planes, along with other material constants. There are additional input associated with the damage and failure models. The steps in using this model are illustrated composite characterization tests, verification tests and a validation test. The results show that the developed and implemented model is stable and yields acceptably accurate results.

finite element method↗
DOE OSTI2019

Cross-Categorical Transfer Learning based Composite Load Protection Modeling

Protection equipment is used to prevent damage to induction motor loads by isolating them from power systems in the event of severe faults. Modeling the response of induction motor loads and their protection is vital for power system planning and operation, especially in understanding system's dynamic performance and stability after a fault occurs. Induction motors are usually equipped with several types of protection with different operation mechanisms, making it challenging to develop adequate yet not overly complex protection models and determine their parameters for aggregate induction motor models. This paper proposes a novel cross-categorical transfer learning based framework to determine protection model parameters for aggregate induction motor loads in commercial buildings. Introducing a mathematical abstraction, the task of determining a suitable set of parameters for the protection model in composite load models is formulated as a combination of feature extraction using transferable layers, followed by affine operations through non-transferable layers applied on the previous extracted features. Numerical results are provided to illustrate the application of the framework.

transfer learning, Stacked Autoencoder, Composite ↗
NASA NTRS2018

A Nonlocal Progressive Damage Model for Composite Materials

Fiber reinforced composite materials are widely used in aerospace structures due to their high specific stiffness and strength. These materials exhibit complex deformation, damage and failure mechanisms under high strain rate loading conditions. Many different failure criteria have been proposed in literature to describe the damage initiation and evolution of fiber reinforced composite materials. Most of these damage models are based on a local framework. In a local framework, the material behavior is based on a point-wise constitutive relation which is independent of the effect of the surrounding points. These models include stiffness degradation when damage initiates in the material, which within a local framework leads to a highly mesh dependent result. This could be overcome using a nonlocal finite element approach. In the current work, a nonlocal formulation based on the work by Andrade et al [1] is adapted to describe composite material behavior. The LS-DYNA rate dependent progressive damage model, MAT162 is employed to detect the initiation and evolution of damage in orthotropic composite materials. This model is developed as a FORTRAN user material subroutine in the LS-DYNA environment. The results of MAT162 with and without the nonlocal formulation are compared at different mesh densities to validate the model. The numerical analysis exhibits the advantages of the nonlocal formulation.

Kodagali, Karan↗
NASA NTRS1979

The auroral ionosphere - Comparison of a time-dependent model with composition measurements

A time-dependent model of the auroral ionosphere including the odd nitrogen species, NO, N(D-2), and N(S-4), is used for comparison with data from a coordinated rocket-satellite measurement of an auroral event. The chemical scheme and the adopted rate coefficients have been shown to be compatible with daytime mid-latitude ionospheric chemistry. The electron flux and neutral atmospheric parameters measured on the satellite are used to compute the appropriate ionization and dissociation rates. The calculated NO(plus), O2(plus), O(plus), Ne, and NO densities agree well with the rocket measurements. The calculated N2(plus) densities are larger than the measured densities by a factor of 3 at most altitudes. The calculations show that the nitric oxide content of the aurora (about 1.2 times 10 to the 9th NO molecules/cu cm at 105 km) is below the saturation value.

Gerard, J.-C.↗
NASA NTRSDate not supplied

Application of the MAT 213 Composite Impact Model to NASA Problems of Interest

As composite materials are gaining increased use in aircraft components where impact resistance under high-energy impact conditions is important (such as the turbine engine fan case), the need for accurate material models to simulate the deformation, damage, and failure response of polymer matrix composites under impact conditions is becoming more critical.

Polymer Matrix Composites↗
NASA NTRS1990

Noise transmission characteristics of a large scale composite fuselage model

Results from an experimental test undertaken to study the basic noise transmission characteristics of a realistic, built-up composite fuselage model are presented. The floor-equipped stiffened composite cylinder was exposed to a number of different exterior noise source configurations in a large anechoic chamber. These exterior source configurations included two point sources located in the same plane on opposite sides of the cylinder, a single point source and a propeller simulator. The results indicate that the interior source field is affected strongly by exterior noise source phasing. Sidewall treatment is seen to reduce the overall interior sound pressure levels and dampen dominant acoustic resonances so that other acoustic modes can affect interior noise distribution.

Beyer, Todd B.↗
NASA NTRS1993

Accuracy of the Generalized Self-Consistent Method in Modelling the Elastic Behaviour of Periodic Composites

Local stress and strain fields in the unit cell of an infinite, two-dimensional, periodic fibrous lattice have been determined by an integral equation approach. The effect of the fibres is assimilated to an infinite two-dimensional array of fictitious body forces in the matrix constituent phase of the unit cell. By subtracting a volume averaged strain polarization term from the integral equation we effectively embed a finite number of unit cells in a homogenized medium in which the overall stress and strain correspond to the volume averaged stress and strain of the constrained unit cell. This paper demonstrates that the zeroth term in the governing integral equation expansion, which embeds one unit cell in the homogenized medium, corresponds to the generalized self-consistent approximation. By comparing the zeroth term approximation with higher order approximations to the integral equation summation, both the accuracy of the generalized self-consistent composite model and the rate of convergence of the integral summation can be assessed. Two example composites are studied. For a tungsten/copper elastic fibrous composite the generalized self-consistent model is shown to provide accurate, effective, elastic moduli and local field representations. The local elastic transverse stress field within the representative volume element of the generalized self-consistent method is shown to be in error by much larger amounts for a composite with periodically distributed voids, but homogenization leads to a cancelling of errors, and the effective transverse Young's modulus of the voided composite is shown to be in error by only 23% at a void volume fraction of 75%.

Walker, Kevin P.↗
DOE OSTI2021

$S$ parameter from a prototype composite-Higgs model

We have calculated the low-energy constant $L_{10}$ in a prototype composite Higgs model with dynamical fermions in two different representations of the gauge group. The resulting contribution of the new strong sector to the $S$ parameter is consistent with current bounds on the vacuum misalignment parameter. We end with a brief discussion of future directions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1986

A finite element overlay technique for modeling pinned composite joints

A finite element technique using overlaid plane stress elements is presented for modeling a pinned composite joint. The technique allows for discrete modeling of the pin and web regions of the joint in a two-dimensional (2-D) finite element analysis. Thus, predictive capability is substantially increased without the added complexity of a three-dimensional (3-D) analysis. The overlay technique requires a thorough evaluation of the model constraints between the joint components. Bearing panels are used to account for a reduced compressive modulus under bearing loads. Application of the plane stress overlay technique to the Filament Wound Case (FWC) Program is discussed. The experimental approach to determine bearing panel moduli using a double lap shear test is detailed, and finite element results are correlated with full-scale FWC joint test results.

Colvin, G. E.↗
NASA NTRSDate not supplied

Application of the MAT 213 Composite Impact Model to NASA Problems of Interest

A material model has been developed which incorporates several key capabilities which have been identified as lacking in currently available composite impact models. The material model utilizes experimentally based tabulated input to define the evolution of plasticity and damage as opposed to specifying discrete input parameters (such as modulus and strength). The material model has been implemented into LS-DYNA® as MAT 213. The model can simulate the nonlinear deformation, damage and failure that takes place in a composite under dynamic loading conditions. The deformation model utilizes an orthotropic plasticity formulation. For the damage model, the nonlinear unloading response that is observed prior to the point where the peak stress is reached can be simulated, as well as the stress degradation response that occurs after the peak stress is reached. A variety of failure models, including a generalized tabulated failure model which facilitates the utilization of general failure surfaces, have been implemented into MAT 213. Recent studies at NASA have concentrated on using MAT 213 to analyze both the impact and crush response of a variety of laminated and textile architectures. Several of these studies will be discussed in the presented paper. For example, a woven carbon/Kevlar composite is currently being examined for use in an energy absorber system for rotorcraft structures. MAT 213 analyses have been conducted to examine the ability of the model to accurately simulate the dynamic crush response of this material. Studies are also being conducted to examine the ability of MAT 213 to simulate the ballistic impact response of representative laminated and woven thermoplastic and thermoset matrix composites. NASA efforts are also concentrated on developing methods and processes for improving characterization methods and developing “best practices” for using MAT 213, a summary of which will be discussed in the paper.

Polymer Matrix Composites↗
NASA NTRSDate not supplied

Lessons Learned and Best Practices for Utilizing a Generalized Composite Impact Model

A material model which incorporates several key capabilities which have been identified as lacking in currently available composite impact models has been developed. The material model utilizes experimentally based tabulated input to define the evolution of plasticity and damage as opposed to specifying discrete input parameters (such as modulus and strength). It has been implemented into the commercially available transient dynamic finite element code LS-DYNA® as MAT_213. The model can simulate the nonlinear deformation, damage and failure that take place in a composite under dynamic loading conditions. As MAT_213 is now being used by a general user community that did not participate in the model development process, a number of issues have been identified that caused uncertainty in assembling a MAT_213 input deck and conducting a MAT_213 analysis. The overall goal of this effort is to develop a quantified set of lessons learned and best practices which will permit a new user to conduct useful MAT_213 simulations without needing to have detailed expert knowledge of the material model and its theoretical underpinnings.

Micromechanics↗
DOE OSTI2024

A layered solid finite element formulation with interlaminar enhanced displacements for the modeling of laminated composite structures

Accurate modeling of layered composite structures often requires the use of detailed finite element models which can sufficiently resolve the kinematics and material behavior within each layer of the composite. However, individually discretizing each material layer into finite elements presents a prohibitive computational expensive given the large number of thin layers comprising some laminated composites. To address these challenges, an 8-node layered solid hexahedral finite element is formulated with the aim of striking an appropriate balance between efficiency and fidelity. The element is discretized into an arbitrary number of distinct material layers, and employs reduced in-plane integration within each layer. The chosen reduced integration scheme is supplemented by a novel physical stabilization approach which includes layerwise enhancements to mitigate various forms of locking phenomena. The proposed framework additionally supports the inclusion of interlaminar enhanced displacements to better represent the kinematics of general layered composite materials. Finally, the described element formulation has been implemented in the ParaDyn finite element code, and its efficacy for modeling laminated composite structures is demonstrated on a variety of verification problems.

42 ENGINEERING↗
DOE OSTI2016

B-decay anomalies in a composite leptoquark model

Here, the collection of a few anomalies in semileptonic B-decays, especially in b → cτ$\overline{v}$, invites speculation about the emergence of some striking new phenomena, perhaps interpretable in terms of a weakly broken U(2) n flavor symmetry and of leptoquark mediators. We aim at a partial UV completion of this interpretation by generalizing the minimal composite Higgs model to include a composite vector leptoquark as well.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Mass–radius relation for rocky planets based on PREM

Several small dense exoplanets are now known, inviting comparisons to Earth and Venus. Such comparisons require translating their masses and sizes to composition models of evolved multi-layer interior planets. Such theoretical models rely on our understanding of the Earth’s interior, as well as independently derived equations of state, but so far have not involved direct extrapolations from Earth’s seismic model: the Preliminary Reference Earth Model (PREM). To facilitate more detailed compositional comparisons between small exoplanets and the Earth, we derive here a semi-empirical mass–radius relation for two-layer rocky planets based on PREM, (R/(R{sub ⊕}))=(1.07−0.21⋅CMF)⋅((M/(M{sub ⊕}))){sup 1/3.7}, where CMF stands for core mass fraction. It is applicable to 1 ∼ 8 M{sub ⊕} and a CMF of 0.0 ∼ 0.4. Applying this formula to Earth and Venus and several known small exoplanets with radii and masses measured to better than ∼30% precision gives a CMF fit of 0.26 ± 0.07.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Robust Time-Varying Parameter Identification for Composite Load Modeling

With the increasing integration of uncertain resources, e.g., renewables, electric vehicles, and demand responses, it is imperative to understand the characteristics of loads for power system analysis and control. Challenges of load modeling come from a variety of load components and time-varying compositions. In addition, the existence of outliers in measurements further complicates the problem. This paper proposes a robust time-varying parameter identification technique for composite ZIP and induction motor load models. A batch-model regression form, including time-varying parameters, is established based on state transition models and observation models with current observations and previous predictions to guarantee data redundancy. To deal with outliers, down-weighting coefficients of measurements are calculated with a projection statistics approach. Based on the batch-model regression and the down-weighting coefficients, parameter identification at each sample time is formulated as a weighted least squares optimization, which is solved by the Newton-Raphson approach with the previous estimated parameters as the initial iteration values. In addition, parameters' sensitivities to different outliers in measurements are analyzed. Results on the IEEE 57-bus system and IEEE 118-bus system show that the proposed algorithm can robustly identify time-varying parameters for the composite load models.

Composite load model↗
DOE OSTI2020

Open-Source High-Fidelity Aggregate Composite Load Models of Emerging Load Behaviors for Large-Sale Analysis

The goal of this project is to accurately model the dynamic loads for power system planning and operation and to address the challenges inherent in such modeling. Existing load models are inadequate to handle the increasing proliferation of residential air conditioner loads and distributed energy resources, the emerging trends of price-responsive demand, and the growing importance of protective devices in equipment and buildings. A need has emerged to develop a fundamentally new class of load models and next-generation data tools. This work proposes to develop a set of regional–level, scalable open source load models and tools, including large-scale aggregate load protection, concept of price responsive demand, advanced load composition data, next-generation load model data tools, and advanced composite load model calibration and validation frameworks to address new challenges in the representation of next-generation load models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Improving Access to the GEOS Composition Forecast Model with API Development and Ingestion into Google Earth Engine

The GEOS Composition Forecast (GEOS-CF) model produces forecast and historical estimates of atmospheric composition and meteorology fields, which provide useful insight into air quality issues and events. In a year for which Canadian wildfires created adverse air quality conditions in the eastern United States, access to model fields such as PM2.5 are in high demand. The GEOS-CF team at the NASA Global Modeling and Assimilation Office (GMAO) first developed in-house solutions to improve data access via the CF API, and recently partnered with Google to ingest a collated set of model diagnostics into the Google Earth Engine (GEE) data repository. GEOS-CF model output is also being ingested into AWS storage. Creating these various open access points to GEOS-CF model diagnostics provides the public with an opportunity to easily interact with air quality information. Users are able to use a temporally consistent global grid of air quality fields in machine learning applications, mapping tools, and data informatics. Hosting GEOS-CF forecasts and the historical timeseries of these chemistry and meteorology fields in GEE allows users to create dynamic JavaScript-based air quality applications in the GEE code editor. GEOS-CF users can also access the model output via the GEE Python application programming interface (API), making it easy to perform various analyses with Python. This presentation will show two examples of accessing the GEOS-CF model through GEE. The first is an example application made in the GEE code editor which allows users to view time series plots and downscaled maps of surface level NO2. The second example exhibits using the GEE Python API to create a machine learning model to temporally gap-fill between air quality observations. These examples are an introduction to the many possible benefits of having open access to the GEOS-CF model through multiple platforms.

Callum Wayman↗
NASA NTRSDate not supplied

Improving Access to the GEOS Composition Forecast Model with API Development and Ingestion into Google Earth Engine

The GEOS Composition Forecast (GEOS-CF) model produces forecast and historical estimates of atmospheric composition and meteorology fields, which provide useful insight into air quality issues and events. In a year for which Canadian wildfires created adverse air quality conditions in the eastern United States, access to model fields such as PM2.5 are in high demand. The GEOS-CF team at the NASA Global Modeling and Assimilation Office (GMAO) first developed in-house solutions to improve data access via the CF API, and recently partnered with Google to ingest a collated set of model diagnostics into the Google Earth Engine (GEE) data repository. GEOS-CF model output is also being ingested into AWS storage. Creating these various open access points to GEOS-CF model diagnostics provides the public with an opportunity to easily interact with air quality information. Users are able to use a temporally consistent global grid of air quality fields in machine learning applications, mapping tools, and data informatics. Hosting GEOS-CF forecasts and the historical timeseries of these chemistry and meteorology fields in GEE allows users to create dynamic JavaScript-based air quality applications in the GEE code editor. GEOS-CF users can also access the model output via the GEE Python application programming interface (API), making it easy to perform various analyses with Python. This presentation will show two examples of accessing the GEOS-CF model through GEE. The first is an example application made in the GEE code editor which allows users to view time series plots and downscaled maps of surface level NO 2 . The second example exhibits using the GEE Python API to create a machine learning model to temporally gap-fill between air quality observations. These examples are an introduction to the many possible benefits of having open access to the GEOS-CF model through multiple platforms.

Callum Wayman↗