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At least 1,225 records · Page 68

Progressive Damage and Failure Analysis of Bonded Composite Joints at High Energy Dynamic Impacts

Both wing and fuselage structures utilize bonded composite joints for structural efficiency in modern commercial and military aircraft. To ensure compliance with certification requirements mechanical fasteners are typically used as a failsafe mechanism for appropriate strength in the event of complete stiffener disbond. However, the use of fasteners decreases the structural efficiency of the structure by adding weight. This establishes the requirement to better exploit the efficiency of bonded structures and fully understand the failure behavior of adhesively bonded composite structures, particularly when subjected to elevated loading rates due to high energy dynamic impacts (HEDI). For this reason, the NASA Advanced Composite Consortium (ACC) HEDI team developed an experimentation and numerical modeling program for high rate loading of composite joints. In the present work, the response of adhesively bonded composite joints subjected to elevated loading rates is studied numerically and validated against experimental results. Due to dynamic considerations of experiments, the idea of wedge insert was extended to use with Split Hopkinson Pressure Bar (SHPB) testing techniques. Mode-I and Mode-II test configurations were simulated to evaluate the capability of two continuum damage material (CDM) models in LS-DYNA, namely MAT162 and MAT261. Three different levels of fidelity were considered to investigate the level of detail required to numerically predict the failure behavior and the results from high fidelity analysis are presented.

MAT261↗

Design for Manufacturing Tool for Automated Fiber Placement Structures - Verification and Validation

A tool has been developed to address the growing Design for Manufacturing needs for composite structures, specifically those manufactured with automated fiber placement. This manufacturing approach presents unique challenges associated with puckers and wrinkling, tow overlaps and gaps, fiber deviation, and laminate strength. Achieving a satisfactory laminate design usually requires finding compromises between those four areas. The developed tool, dubbed the Central Optimizer, assists with the process of balancing competing design metrics in automated fiber placement. This tool was developed under the NASA Advanced Composites Consortium with input from industry partners. Under this program, the Central Optimizer has been exercised on three different structures to verify its functionality and validate ability to improve the design process for automated fiber placement structures.

August T Noevere↗

TPSAS-NF1676L-12829-DND

Collaborative research between NASA and U.S. rotorcraft companies through the Vertical Lift Consortium, to design, test, and analyze representative validation test articles. - Representative problems and designs developed with partners - Validation articles and characterization specimens manufactured by partners - Develop analytical models to predict delamination behavior using commercial codes, characterization data, and test article data - NASA Space Act Agreement (SAA1-818) with CRI, August 2007 August 2012; funded through Subsonic Rotary Wing program

Gretchen B Murri↗

TPSAS-NF1676L-32030-DND

Composite structures are often difficult to inspect due to the anisotropic nature of the material systems and the range of flaws and defects that can arise in the manufacturing process. NASA?s Advanced Composites Project, a public-private partnership between government, universities and industry, seeks to address improved methods, tools, and protocols to reduce the development and certification timeline for composite materials and structures. The rapid inspection of composites is one of the three focused research areas of the project. One deliverable of the project is to develop an NDE Methods and Capabilities Handbook. This Handbook provides a publically available guidance document that facilitates the selection of appropriate NDE techniques and provides recommended protocols for detecting and characterizing common flaw types in solid laminate polymer matrix composite (PMC) structures. The Handbook will reduce the time required to develop qualified inspection processes for composite aircraft structures during the development, certification, and manufacturing phases by providing a reference that helps minimize trial and error and provides guidance on best practices, techniques, and settings, for specific flaw types and geometries. The Handbook will include an NDE Guidance Matrix that provides an applicability rating for NDE techniques as they apply to given flaw types. NDE techniques will include, but is not limited to ultrasound, laser based ultrasound, infrared thermography, and x-ray CT. Flaw types will include, but are not limited to porosity, delamination, voids, AFP defects and impact damage. The Handbook will contain details that support the applicability rating including, but not limited to, specimen details, inspection parameters, data analysis techniques, inspection efficiency (speed & cost), and limitations. This presentation will describe key Handbook activities with examples of the techniques and flaw types examined by the Advanced Composite Consortium members.

Patricia A Howell↗

TPSAS-NF1676L-25778-DND

Testing required to design and certify aircraft structures has increased dramatically with the growth in use of composite materials, and the development time and cost have become an issue as industry looks towards the next generation of aircraft. To help address this challenge, NASA has formed an industry-spanning consortium with the goal of cutting by 30% today's 10-year timeline for developing and certifying composite aircraft structures. This goal is to be achieved by infusing leading edge, physics-based tools to improve the prediction of the response and failure of composite aerospace structures. The plan for the public-private partnership of NASA, the FAA, airframe manufacturers, aircraft engine manufacturers, and several universities is to conduct joint research under the five-year Advanced Composites Program (ACP). The emphasis of the ACP project is the development of damage prediction and non-destructive inspection methods capabilities that are sufficiently reliable to enable a reduction in the element and subcomponent testing necessary for design and certification. ACP also is expected to create rapid design tools to speed preliminary design and improve safety and performance. A critical element of this research concerns the residual strength of postbuckled stiffened panels with impact damage. This presentation will discuss different aspects of ongoing research on the prediction of structural collapse due to skin/stiffener separation. In particular, the presentation will examine issues that must be addressed in the analysis, such as R-curve toughening, delamination migration, bridging, as well as some unexpected effects of ply orientation.

Carlos G Davila↗

Improved Benchmarking of Cohesive Elements in Abaqus Standard for Predicting Disbond and Delamination in Composite Structures

Traditional approaches for aircraft certification require the assumption of an initial flaw condition, either represented as barely visible impact damage (BVID) or through inclusion of a Teflon insert to serve as surrogate damage. Based on the initial composite damage state, the structure must be shown to demonstrate structural durability and damage tolerance (DaDT) according to the following criteria: a. Damage displays no detrimental growth under cyclic loading b. The structure is able to sustain design limit load (DLL) Currently, the only available manner for validating structural performance is through test. Since damage can occur over a wide variety of areas within a structure, this approach has proven to be increasingly expensive and time consuming for composite airframes and acreage structure within the design-test-certification building block. A further complicating factor is the requirement to accurately capture the most critical damage morphologies as a starting condition. To understand the severity of the damage, it is either required to experimentally determine the most critical areas at tremendous expense or rely on legacy data of similar structural testing, which limits design space expansion. A preferred solution is to use advanced analysis to provide improved understanding of load margins for critical locations based on a wide variety of potential starting damage conditions. The standard industry approach for DaDT certification adheres to the use of the traditional virtual crack closure technique (VCCT) method. VCCT is generally a preferred method because it conforms to the current certification principles of damage from a known flaw, and when used correctly, can be effective at predicting delamination propagation under static and cyclic loading. The VCCT method requires the inclusion of an initial flaw in the finite element (FE) model requiring a-priori knowledge of the flaw location. This in turn requires a plethora of analysis cases to be examined to cover a reasonable span of potential damage states. Additionally, the VCCT approach requires node-to-node connectivity rendering it incompatible with the best practices and approaches for using continuum damage mechanics (CDM) based progressive damage and failure analysis (PDFA) tools within a typical FE solver. Alternatives to VCCT have emerged in the form of cohesive elements which utilize the cohesive zone model (CZM). Unlike VCCT which models linear elastic fracture mechanics, cohesive elements couples continuum and fracture based responses through the use of bilinear traction separation laws. These laws are defined based on a penalty stiffness, a cohesive strength, and a strain energy release rate. The approach can be mesh regularized with native cohesive elements within many FE solvers such as Abaqus and LS-DYNA. In Phase I of the NASA Advanced Composites Consortium (ACC) post-buckled stiffened panel with BVID, Strength and Life [1], the performance of cohesive elements were benchmarked in comparison to VCCT and LEFM solutions and showed good agreement using Abaqus explicit [2]. To realize savings on current and future programs, it is still necessary to close technical gaps related to the use of cohesive elements with Abaqus Standard. Within a program environment, standard finite element analysis is the preferred analytical capability for quasi-static loading as it eliminates uncertainty due to oscillatory behavior commonly seen with explicit analysis. This oscillatory behavior creates difficulties in writing margins of safety based on the analysis. The use of negative tangent stiffness material models complicates convergence which typically requires the use of numerical controls such as viscous damping to overcome. To date, there has not been a comprehensive study on how to establish best practices for cohesive element convergence for predictive capability within the Abaqus implicit solver. In pursuit of these goals, under the NASA ACC program, several numerical benchmark problems were proposed including pure mode I (double cantilevered beam – DCB), pure mode II (end notch flexure – ENF), and symmetric/unsymmetric evolving mixed mode (single leg bend – SLB). This paper focuses on the use of cohesive elements to model the delamination through the use of CZM. Specifically, finite element models for the DCB, ENF, symmetric SLB, and unsymmetric SLB, are developed and various solution controls for convergence are studied to develop a best practice. Once the best practice has been developed, the predictive capability of the objective CZM model is used to analyze the hat pull-off strength of a standard hat stiffened configuration under various loading conditions.

Abaqus↗

Maximizing Spaceflight Biological Data with Omics Analytics: The NASA GeneLab Database

NASA’s GeneLab includes an open-access repository of some 250+ omics datasets generated by biological experiments relevant to spaceflight including simulated cosmic radiation and microgravity. In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics background, GeneLab has become a knowledgebase platform converting raw genetic and proteomic signatures found in flight samples into biological and physiological meanings. A large community of more than 100 scientists has rallied behind GeneLab and organized into four Analysis Working Groups (AWGs: Animal, Plant, Microbe, and Multi-Omics). Together, the AWGs have gained scientific recognition worldwide by establishing a consortium in charge of adopting new complex standards for data analysis workflows and omics sample processing in a rapidly evolving field. We will demonstrate the usage of the repository with smart search capability, an online controlled-access toolshed "Galaxy" to process user data with vetted standard workflows, a workspace for data sharing and a data submission portal with ontology control for better metadata curation. The GeneLab visualization portal will also be demonstrated, showing how anyone without formal training in bioinformatics can now browse the space biology omics data to discover new biology and potential solutions to improve life in space.

Sylvain Vincent Costes↗

DAAC Collaboration Overview for AGU

The Atmospheric Science Data Center (ASDC), Goddard Earth Sciences Data and Information Systems Center (GES DISC), Socioeconomic Data and Applications Center (SEDAC), Oak Ridge National Laboratory (ORNL), Land Processes DAAC, Alaska Satellite Facility (ASF), as well as NASA Global Imagery Browse Service (GIBS), Earth Science Data Systems (ESDS) Geographic Information Systems Team (EGIST), Earthdata Content Delivery Team, ArcGIS Online Governance Team, and the Systematic Data Transformation ACCESS team have come together to establish the ArcGIS DAAC Collaboration. This coalition of participants will demonstrate their use of the ArcGIS Enterprise to support Earth science research, applied science, and outreach using Earth Observing System Data and Information System (EOSDIS) data. This includes the use of web services to fuse data products across space and time through services (e.g. ArcGIS Image Services, Open Geospatial Consortium (OGC) Web Coverage Service (WCS), and OGC Web Mapping Services (WMS)) for analysis in Jupyter notebooks, desktop tools, and web based applications.

Matthew Steven Tisdale↗

NASA Advanced Composites Project

The recently-completed NASA Advanced Composites Project (ACP) successfully developed several new technologies aimed at reducing the timeline to design and certify composite aircraft structures. Advancements in the areas of manufacturing simulation, nondestructive inspection and advanced structural design and analysis methodologies were completed in late 2019 under the Advanced Composites Consortium (ACC) public/private partnership as well as NRA-funded university contracts. In the area of Structures, the ACC made significant improvements in rapid design tools for preliminary sizing of structure, along with developing detailed static and fatigue strength prediction methods and methods for modeling high energy impact events in composite structures. These new methodologies and toolsets were validated against a range of representative test data using a comprehensive verification and validation approach which has been published and is now used extensively on other programs. Specific new tool improvements supported by ACC include NASA’s CompDam code and Floating Node Method code. CompDam is now available from NASA as open source code. The team alsoworked on improved impact modeling using LS-Dyna™ and improved delamination modeling using Abaqus™. Rapid design tool improvements are available through Hypersizer. The ACC team released well over 50 publications documenting these method improvements, and the ACP recently received the prestigious NASA Group Achievement Award for their work.Typical Hat Stiffened Panel Test Article Used for Method Validation

ACC↗

LISA Activities at NASA

NASA will participate as a junior partner in the ESA-led LISA mission, which will provide the first view of the universe in milliHertz gravitational waves. While the exact set of NASA-provided contributions is still under negotiation, they are expected to include significant contributions to the LISA instrument and participation in the scientific operations of the observatory. The NASA LISA Study Office is tasked with coordinating NASA’s activities on LISA including the development of a number of technologies as candidate contributions to the LISA payload as well as collaboration with ESA and the LISA Consortium on development of the LISA spacecraft, instrument, data analysis infrastructure, and science case. This talk will provide an overview of these activities, their current status, and an outlook for progress in the near-term.

Ira Thorpe↗

GeneLab: The NASA System Biology Platform for Space Omics Repository, Analysis and Visualization

NASA’s GeneLab includes an open-access repository of some 250+ omics datasets generated by biological experiments relevant to spaceflight including simulated cosmic radiation and microgravity. In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics background, GeneLab has become a knowledgebase platform converting raw genetic and proteomic signatures found in flight samples into biological and physiological meanings. A large community of more than 100 scientists has rallied behind GeneLab and organized into four Analysis Working Groups (AWGs: Animal, Plant, Microbe, and Multi-Omics). Together, the AWGs have gained scientific recognition worldwide by establishing a consortium in charge of adopting new complex standards for data analysis workflows and omics sample processing in a rapidly evolving field. We will demonstrate the usage of the repository with smart search capability, an online controlled-access toolshed "Galaxy" to process user data with vetted standard workflows, a workspace for data sharing and a data submission portal with ontology control for better metadata curation. The GeneLab visualization portal will also be demonstrated, showing how anyone without formal training in bioinformatics can now browse the space biology omics data to discover new biology and potential solutions to improve life in space.

GeneLab↗

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over 60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗

The ANGSA Program: A Low-cost Lunar "Sample Return Mission". An Overview and Progress over the Last 18 Months

The Apollo Program returned 381 kg of samples. Analyses of these samples have provided fundamental insights into the origin and history of the Earth-Moon system and how planets and even solar systems work. These samples have provided ground truth for every post-Apollo mission to the Moon for the interpretation of remotely sensed data. After 50 years of analysis and study, our sophistication for handling and examining samples has greatly increased. Some special samples that were collected or preserved in unique containers or environments remain unexamined by standard or advanced analytical approaches. The Apollo Next Generation Sample Analysis (ANGSA) Program was designed to examine a subset of these special samples. The ANGSA consortium consists of 9 original teams funded by NASA that have combined into a single science team referred to as the ANGSA Science Team. The program was designed to function as the sample analysis portion of a sample return mission with processing, preliminary examination, and analyses utilizing new and improved technologies and recent mission observations. The ANGSA Program links the first generation of lunar explorers (Apollo) with future explorers of the Moon (Artemis). The purpose of this abstract is to highlight the ANGSA samples, science and engineering goals, and progress made so far. Related abstracts and talks will focus on the links between Apollo and Artemis, geologic context, and initial examination, processing, and results.

F M McCubbin↗

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗

Chip Scale Package Implementation Challenges

The JPL-led MicrotypBGA Consortium of enterprises representing government agencies and private companies have joined together to pool in-kind resources for developing the quality and reliability of chip scale packages (CSPs) for a variety of projects.

chipscale↗

Ball Grid Array Reliability Assessment for Aerospace Applications

Reliability of Ball Grid Array(BGAs) was evaluated with special emphasis on space applications. This work was performed as part of a consortium led by the Jet Propulsion Laboratory (JPL) to help build the infrastructure necessary for implementation of this technology. Nearly 200 test vehicles, each with four packages, were assembled and tested using an experimental design.

Aerospace↗

The InSAR Scientific Computing Environment 3.0: A Flexible Framework for NISAR Operational and User-Led Science Processing

The InSAR Scientific Computing Environment (ISCE) was first developed under the NASA Advanced Information Systems Technology as a flexible, extensible object-oriented framework for Interferometric Synthetic Aperture Radar (InSAR) processing. The ISCE framework uses Python 3 at the workflow level, controlling modules of compiled code for functional processing, and managing inputs, outputs, and other flow control services. The currently released version, called ISCE 2.1, is distributed to the research community through the Western North America InSAR Consortium under a research license. The ISCE team is working on the next generation of the code in order to prepare for the NASAISRO SAR (NISAR) mission operational processing. Innovations in this code include augmentation or conversion of the custom Python framework elements in ISCE with the Pyre framework, new workflows for interferometric and polarimetric stack processing, a more intuitive and graphically based user interface, and flow control for hybrid computing environments including CPU/GPU clusters, logging and error tracking facilities, and new more efficient computational modules that exploit graphical processor units (GPUs) when available. The ISCE 3.0 framework is designed to work in an operational environment as well as on a single user’s laptop or compute cluster, with services to discover capabilities and scale computations accordingly.

Buckley, Sean M.↗

Leading University Students to the Edge of Space

For over 16 years, the Louisiana Space Grant Consortium (LaSPACE), the NASA Balloon Program Office (BPO), and the NASA Columbia Scientific Balloon Facility (CSBF) have collaborated in a series of high altitude balloon-based programs involving hands-on authentic learning experiences that expose university students and other participants to technical skills, teamwork dynamics, and effective communication methods. Such programs go beyond what is possible to achieve in a normal classroom and help prepare future engineers and scientists for a successful aerospace workforce career. In our collaborative effort, LaSPACE has focused on the program content and student mentoring while NASA BPO and CSBF provide balloon flight support and operations. The entry-level Louisiana Aerospace Catalyst Experiences for Students (LaACES) builds students’ skills in basic electronics, sensor interfacing, real-time programming, mechanical development, and project management. These skills are then applied to the design, development, fabrication, and flight of a small (∼500 gram) balloon payload. Finally, the payloads are flight-tested to an altitude of ∼30 km using a 2 kg latex sounding balloon. The LaACES program includes a set of lectures, activities, and Arduino Mega based electronic kits that are used for skill building and as a core control system for the student payload. The more advanced High Altitude Student Platform (HASP) is designed to carry ∼twelve 3 to 20 kg student payloads to an altitude of about 36 kilometers with flight durations of 10 to 20 hours using a ∼311,500 cubic meter, zero pressure balloon. HASP provides all student payloads with power, downlink telemetry, uplink commanding, and real-time HD video for instrument control and assessment during the flight. While originally developed for university students, these programs have been adapted to projects focused on high school teachers as well as affecting minorities underrepresented in aerospace related science and engineering fields. We are now in the process of adapting the LaACES materials to a pre-engineering curriculum for high school students as well as for widespread access over the internet. During this presentation, we will provide details of both the LaACES and HASP programs, how these programs have engaged participants from all demographic groups, and our current plans for continuing and expanding upon our success.

University↗