Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “multiscale analysis”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

TPS Certification by Analysis: Model-Driven Characterization of Properties and Failure in Woven Thermal Protection Systems

Woven, ablative thermal protection system (TPS) materials provide a robust option for aggressive (re)entries and thus have been baselined for the upcoming Mars Sample Return (MSR) mission's Earth Entry System (EES). The reliability requirements for MSR-EES necessitate understanding of material property variability, which could be significant given the complex structure and anisotropic nature of properties in TPS weaves, as well as the response to potential impact with micrometeoroids or orbital debris during the EES re-entry. The TPS Certification by Analysis effort within the Entry Systems Modeling project seeks to provide computational models and analyses that support the certification against such material-based risks. For the present talk, focus will be given to the characterization of baseline woven TPS material properties and mechanical failure limits, which entails (1) use of computational techniques (e.g., machine learning) to interpret computed tomography images of the weave to generate representative structural models and (2) application of multiscale material modeling approaches to characterize thermomechanical and failure properties.

thermal protection systems↗
NASA NTRS2018

Energy Conversion and Partition in the Asymmetric Reconnection Diffusion Region

We investigate the energy conversion and partition in the asymmetric reconnection diffusion region using two-dimensional particle-in-cell simulations and Magnetosphere Multiscale (MMS) mission observations. Under an upstream condition with equal temperatures in the two inflow regions, the simulation analysis indicates that the energy partition between ions and electrons depends on the distance from the X-line. Within the central electron diffusion region (EDR), nearly all dissipated electromagnetic field energies are converted to electrons. From the EDR to the ion diffusion region (IDR) scales, the rate of the electron energy gain decreases to be lower than that of ions. A magnetopause reconnection event inside the IDR observed by MMS shows comparable ion and electron energy gains, consistent with the simulation result in the transition region from EDR to IDR. At the EDR scale, the electron energization is mainly by the reconnection electric field (E(sub r)); in-plane electric fields (E(sub xz)) provide additional positive contributions near the X-line and do negative work on electrons beyond the EDR. The guide field reduces the electron energization by both E(sub r) and E(sub xz) in the EDR. For ion energization, E(sub r) and E(sub xz) have comparable contributions near the time of the peak reconnection rate, while E(sub xz) dominants at later time. At the IDR scale, the guide field causes asymmetry in the amount of the energy gain and energization mechanisms between two exhausts but does not have significant effects on energy partition. Our study advances understanding of ion and electron energization in asymmetric reconnect IDRs.

Wang, Shan↗
NASA NTRS2021

The Dynamics of a High Mach Number Quasi-Perpendicular Shock: MMS Observations

Shock parameters at Earth’s bow shock, in rare instances, can approach the Mach numbers predicted at astrophysical shocks and supernova remnants. We present our analysis of a high Alfv ́en Mach number (MA= 27) shock, by utilizing multipoint measurements from the Magnetospheric Multiscale (MMS) spacecraft during a crossing of Earth’s quasi-perpendicular bow shock. We find that the shock dynamics are mostly driven by reflected ions, perturbations that they generate, and nonlinear amplification of the perturbations. Our analyses indicate that reflected ions create modest magnetic enhancements upstream of the shock front which evolve in a nonlinear manner as they traverse the shock foot. They can transform into proto-shocks that propagate at small angles to the magnetic field and towards the bow shock. The nonstationary bow shock shows signatures of both reformation and surface ripples. Our observations indicate that although shock reformation occurs, the main shock layer never disappears. These observations are at high plasmaβ, a parameter regime which has not been well explored by numerical models.

H Madanian↗
NASA NTRSDate not supplied

MISTRAL: Concept and Analysis of Persistent Airborne Localization of GHG Emissions

In this study, we propose a concept for localizing and mitigating greenhouse gases and other emissions from areas of various sizes, using a multiscale, airborne localization fleet, supported by information from satellites. Our objective is a rapidly implementable capability for the reduction of atmospheric methane by empowering the communities in proximity to emissions to actively contribute to methane mitigation via fleet operations by local governments, first responders, and individuals . Fully autonomous operations are economically desirable and technically feasible now. However, the development of regulations for autonomous operations is in early stages. Since rapid impact is critical to reducing emissions, the concept starts with remotely controlled vehicles. As regulations for autonomous operations reach maturity, the concept can be easily transitioned from the remotely piloted to autonomous mode. We report on a preliminary system analysis of the concept. Localization of methane emissions from the Permian Basin oil and gas production site serves as the design reference mission; however, the airborne concept is applicable to a broad range of use cases, and we describe several in this analysis. We consider leveraging satellite and ground-based resources within the airborne concept of operations. The study analyses uninhabited aerial system localization operations under the most conservative assumptions on resources and available information. Even under these assumptions, the concept is shown to be viable for local community operations.

airborne methane localization↗
NASA NTRSDate not supplied

Materials Informatics at NASA GRC: Machine Learning Surrogate Modeling, Data Management, and Integrated Toolsets for Establishing/Maintaining the Digital Thread

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which heavily depend on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results that is findable and usable, along with integrated, efficient toolsets for effectively passing information across various length and time scales across such models. At the NASA Glenn Research Center under the Transformational Tools and Technologies Project, significant recent efforts have been directed towards establishing the required cyberinfrastructure to enable optimized ICME processes and the design of “fit-for-purpose” materials to achieve the goals outlined in the NASA Vision 2040 report. Such efforts include development of multiscale physics-based material models, which can be used to train highly efficient surrogate machine learning models, development of best practices and infrastructure for effective, traceable materials information management, and development of toolsets that integrate with physics-based codes, machine learning models, and an information management system to enable high throughput of materials data collection and analysis, establishment of digital twins and the digital thread, and automation of the ICME design process for material optimization.

Machine Learning↗
NASA NTRSDate not supplied

A Convolutional Neural Network for Multiscale Modeling of Composite Materials

An artificial convolutional neural network was created to efficiently mimic a micromechanics model, the High Fidelity Generalized Method of Cells, for use in multi-scale structural finite element analysis. The network was found to quickly and accurately replicate the stiffness predicted by the micromechanics model using a 2D image of an idealized representative volume element of a fiber/matrix microstructure. The long-term goal of this work is to efficiently apply multi-scale methods for predicting the damage progression of a composite structure.

Composites↗
NASA NTRS2023

Prediction of Stiffness and Fatigue Lives of Polymer Matrix Composite Laminates Using Artificial Neural Networks

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, both Python and MATLAB-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been developed for both platforms. Results show that the both neural net types can provide an excellent estimate of initial stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminate. RNNs are better able to capture the shape of the fatigue curve of a laminate. This tool can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. The associated surrogate models could also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make multiscale analyses a viable industrial tool for large scale structural problems.

Composite↗
NASA NTRSDate not supplied

Data-Based Modeling of MMS/FPI Microchannel Plate Detector Resistance Using Temperature Proxy

The Magnetospheric MultiScale (MMS) space physics mission studies magnetic reconnection in the Earth’s magnetosphere. This work presents the results of an analysis of the resistance of the microchannel plates (MCP) included in the particle spectrometers, which are components of the Fast Plasma Investigation (FPI) aboard each MMS spacecraft. We found that a proxy for the resistance of the MCPs can be estimated from the MCP bias voltage and MCP high voltage power supply (HVPS) temperature. This estimation of MCP resistance allows for an accurate determination of nominal MCP current.

Joseph Patton↗
NASA NTRS1992

Satellite Analyses of Cirrus Cloud Properties During the FIRE Phase 2 Cirrus Intensive Field Observations over Kansas

The First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) Phase II Intensive Field Observations (IFO) were taken over southeastern Kansas between November 13 and December 7,1991, to determine cirrus cloud properties. The observations include in situ microphysical data; surface, aircraft, and satellite remote sensing; and measurements of divergence over meso- and smaller-scale areas using wind profilers. Satellite remote sensing of cloud characteristics is an essential aspect for understanding and predicting the role of clouds in climate variations. The objectives of the satellite cloud analysis during FIRE are to validate cloud property retrievals, develop advanced methods for extracting cloud information from satellite-measured radiances, and provide multiscale cloud data for cloud process studies and for verification of cloud generation models. This paper presents the initial results of cloud property analyses during FIRE-II using Geostationary Operational Environmental Satellite (GOES) data and NOAA Advanced Very High Resolution Radiometer (AVHRR) radiances.

Minnis, Patrick↗
NASA NTRS2020

Hierarchical Coupling of Molecular Dynamics and Micromechanics to Predict the Elastic Properties of Three-Phase and Four-Phase Silicon Carbide Composites

The results obtained from previously conducted molecular dynamics analysis of silicon carbide (-SiC (6H, 4H, & 2H-SiC), -SiC (3C SiC)), silicon and boron nitride, were utilized as inputs in the MAC/GMC micromechanics software to model and evaluate the elastic properties of three-phase SiC/BN/SiC and four-phase SiC/BN/Si/SiC composites. This method of analysis eliminates the need for back-calculation of the apparent properties of the base constituents from the measured ceramic matrix composites properties. The multiscale models are validated against the available data in literature.

Aluko, Olanrewaju↗
NASA NTRS2014

A Multiscale Progressive Failure Modeling Methodology for Composites that Includes Fiber Strength Stochastics

A multiscale modeling methodology was developed for continuous fiber composites that incorporates a statistical distribution of fiber strengths into coupled multiscale micromechanics/finite element (FE) analyses. A modified two-parameter Weibull cumulative distribution function, which accounts for the effect of fiber length on the probability of failure, was used to characterize the statistical distribution of fiber strengths. A parametric study using the NASA Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) was performed to assess the effect of variable fiber strengths on local composite failure within a repeating unit cell (RUC) and subsequent global failure. The NASA code FEAMAC and the ABAQUS finite element solver were used to analyze the progressive failure of a unidirectional SCS-6/TIMETAL 21S metal matrix composite tensile dogbone specimen at 650 degC. Multiscale progressive failure analyses were performed to quantify the effect of spatially varying fiber strengths on the RUC-averaged and global stress-strain responses and failure. The ultimate composite strengths and distribution of failure locations (predominately within the gage section) reasonably matched the experimentally observed failure behavior. The predicted composite failure behavior suggests that use of macroscale models that exploit global geometric symmetries are inappropriate for cases where the actual distribution of local fiber strengths displays no such symmetries. This issue has not received much attention in the literature. Moreover, the model discretization at a specific length scale can have a profound effect on the computational costs associated with multiscale simulations.models that yield accurate yet tractable results.

Generalized Method of Cells↗
NASA NTRS2016

Steepening of Waves at the Duskside Magnetopause

Surface waves at the magnetopause flanks typically feature steeper, i.e., more inclined leading (antisunward facing) than trailing (sunward facing) edges. This is expected for Kelvin-Helmholtz instability (KHI) amplified waves. Very rarely, during northward interplanetary magnetic field (IMF) conditions, anomalous inverse steepening has been observed. The small-scale tetrahedral configuration of the Magnetospheric Multiscale spacecraft and their high time resolution measurements enable us to routinely ascertain magnetopause boundary inclinations during surface wave passage with high accuracy by four-spacecraft timing analysis. At the dusk flank magnetopause, 77%/23% of the analyzed wave intervals exhibit regular inverse steepening. Inverse steepening happens during northward IMF conditions, as previously reported and, in addition, during intervals of dominant equatorial IMF. Inverse steepening observed under the latter conditions may be due to the absence of KHI or due to instabilities arising from the alignment of flow and magnetic fields in the magnetosheath.

Plaschke, F.↗
NASA NTRSDate not supplied

Py MILab: Capturing, Analyzing and Storing Test Data

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which is heavily dependent on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results. Populating searchable information management systems with such rich data sets is often burdensome for data producers, resulting in a lack of findable data for modelers to validate and verify their models. To overcome these cultural barriers to ICME, NASA has developed of various database-integration toolsets that perform both data management activities within the organization’s best practices with additional functionality that relieves the effort of the data producer and promotes adoption of information management system. One such tool currently under development is Py MILab, an automatic framework for automatic capturing, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. TMAnalysis is a Python-based tool that performs automatic data reduction and analysis of uniaxial thermomechanical test data. The TMAnalysis toolset can be implemented within the Analysis module of Py MILab, and thus requires a populated neutral file form the Raw Data Module of Py MILab and outputs a Analysis neutral file compatible with the Database Module of Py MILab. TMAnalysis is able to perform automatic segmentation of multistage tests and perform data analysis and reduction, including determination of point-wise properties in tension, compression, and shear, analysis of stress relaxation tests, creep analysis and zone identification, and combination of these stage types for tests with complex loading histories. The TMAnalysis code is accompanied with a graphical user interface (GUI) that allows users to easily analyze test data in bulk, verify the automatic, consistent analysis performed by the backend code, and edit stage segmentation if necessary before producing the output neutral files, ensuring data is properly analyzed and maintained with full traceability.

Data management↗
NASA NTRS2020

A Multiscale Cohesive Law for Carbon Fiber Networks

Better predictive models of mechanical failure in low-weight heat shield composites would aid material certification for missions with aggressive atmospheric entry conditions. Here, we develop such a model for the rapid engineering analysis of the failure limits of phenolic impregnated carbon ablator (PICA) - a leading heat shield material whose structural component is a carbon fiber network. We hypothesize inelastic deformation failure mechanisms and model their behavior using molecular dynamics simulations to calculate the binding energy. We then upscale this binding energy to the macroscale using a renormalization argument. The approach delivers insightful and reasonably accurate macroscale predictions that compare favorably to experiments. In application, the model is validated for a particular variety of PICA by comparison to experiment and would then be used to study design scenarios in different entry conditions.

W. SCHILL↗
NASA NTRS1997

Advanced Modeling Techniques to Study Anthropogenic Influences on Atmospheric Chemical Budgets

This research work is a collaborative effort between research groups at MCNC and the University of North Carolina at Chapel Hill. The overall objective of this research is to improve the level of understanding of the processes that determine the budgets of chemically and radiatively active compounds in the atmosphere through development and application of advanced methods for calculating the chemical change in atmospheric models. The research performed during the second year of this project focused on four major aspects: (1) The continued development and refinement of multiscale modeling techniques to address the issue of the disparate scales of the physico-chemical processes that govern the fate of atmospheric pollutants; (2) Development and application of analysis methods utilizing process and mass balance techniques to increase the interpretive powers of atmospheric models and to aid in complementary analysis of model predictions and observations; (3) Development of meteorological and emission inputs for initial application of the chemistry/transport model over the north Atlantic region; and, (4) The continued development and implementation of a totally new adaptive chemistry representation that changes the details of what is represented as the underlying conditions change.

Mathur, Rohit↗
NASA NTRSDate not supplied

Application of a Rapid Design Tool to a 3D Woven Structural Joint

The optimization of composite structural joints is an iterative process and a multiscale problem. High fidelity finite element modeling of joints with 3D woven and laminated materials can become computationally expensive. The aim of this paper is to establish a reliable analysis process for the optimization of a composite Y-joint (curved Pi-joint), to be used in an aircraft fuselage, using commercial rapid joint design, analysis, and optimization software. The rapid joint design tool was investigated as a substitute and/or complement to a finite element analysis software. A composite Pi-joint and a composite Y-joint were evaluated using the rapid joint design tool to determine the applicability and limits of the software. Furthermore, three main preliminary parametric studies were performed to better understand the capability of the tool in predicting the stress distributions and trends in the Y-joint. The parameters investigated were the joint curvature, the laminated skin thickness, the adhesive systems, and the ply composition. Lastly, trends in predicted failure load were produced as a function of skin thickness (16ply, 24ply and 32ply). Failure loads were found with varying joint curvature and skin thickness using stress-based adherend failure criterion. The rapid joint design tool was also validated against existing experimental results.

Bonded Joints↗