Results for “RESEARCH PROGRAMS” — Page 27

DOE OSTI2026

Mechanical and durability properties of ultra-high-performance concrete of spent nuclear fuel dry storage systems: a review

Dry storage systems are used for interim storage of spent nuclear fuel (SNF). However, with the growing need to extend the operational periods of these systems, there are concerns about the degradation of their concrete overpacks, which could compromise the system's structural integrity and safety during hazardous events. Traditional concrete mixtures used in SNF dry storage systems have remained largely unchanged since their inception and often use conventional ingredients. These materials are susceptible to degradation mechanisms such as chemical attacks, alkali-silica reactions (ASR), and freeze–thaw cycles, which can lead to a loss of strength and durability over time. To address these challenges, this paper reviews the application of ultra-high-performance concrete (UHPC) as a promising alternative for spent nuclear fuel dry storage system overpacks. UHPC offers superior mechanical properties, exceptional durability, and reduced susceptibility to degradation mechanisms compared to conventional concrete. This paper focuses on the role of supplementary cementitious materials (SCMs) such as silica fume, fly ash, and metakaolin in enhancing UHPC performance for SNF storage applications. These SCMs have been shown to significantly improve the material’s microstructure, strength, and resistance to environmental stressors typically encountered in SNF storage environments. Moreover, incorporating SCMs supports sustainable construction by reducing cement consumption and associated carbon emissions. The review brings together existing research and experimental data, providing insights for engineers and researchers on developing UHPC mixtures that meet the rigorous demands of spent nuclear fuel dry storage systems, extending their service life and minimizing inspection intervals.

36 - MATERIALS SCIENCE↗

NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗

NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗

DOE OSTI2026

Associative polymers with controlled sticker placement: How reversible bond distribution and density govern polymer dynamics

Associative polymers with precisely arranged stickers offer opportunities to program material properties with molecular precision. Yet, it remains unclear how the placement and fraction of stickers dictate structure, dynamics, and macroscopic properties. By developing a model unentangled polymer system with hydrogen-bonding stickers, we show that randomly distributed stickers neither form clusters nor change flow properties, whereas stickers placed at chain ends drive nanocluster formation even at low concentrations. Adding more end stickers produces a rubbery plateau spanning eight decades in frequency with two distinct relaxation timescales, in contrast to the single plateau predicted by the classic sticky Rouse model. These results demonstrate that sticker distribution dictates whether associative polymers undergo nanocluster formation or microphase separation, while substantial alterations in dynamics and viscoelasticity require both sticker aggregation and thermomechanical stability of associated domains. Our findings resolve a longstanding debate on associative polymer dynamics and provide molecular design rules for programmable soft materials.

36 MATERIALS SCIENCE↗

NASA NTRS1996

Science Results from the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR): Progress Report

The Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) is the most advanced imaging radar system to fly in Earth orbit. Carried in the cargo bay of the Space Shuttle Endeavour in April and October of 1994, SIR-C/X-SAR simultaneously recorded SAR data at three wavelengths (L-, C-, and X-bands; 23.5, 5.8, and 3.1 cm, respectively). The SIR-C/X-SAR Science Team consists of 53 investigator teams from more than a dozen countries. Science investigations were undertaken in the fields of ecology, hydrology, ecology, and oceanography. This report contains 44 investigator team reports and several additional reports from coinvestigators and other researchers.

Diane L Evans↗

DOE OSTI2023

Smart Droplets Stabilized by Designer Surfactants: From Biomimicry to Active Motion to Materials Healing

The science and technologies of emulsion droplets have been a long‐term focus of extensive research endeavors for their practical utility across a breadth of industries, including pharmaceutical products, oil recovery processes, and the food sciences. However, with advances in materials chemistry and characterization tools, new emerging areas are arising with a focus on “smart droplets”. The versatility of emulsion droplets across is based on their ability to partition and create isolated systems with properties defined by the liquid–liquid interface, while preparative routes allow manipulation of droplet size, stability, and encapsulated contents. As described in this article, significant efforts are being devoted to creating new types of droplets by “activating” this interface through the incorporation of reactive structures that trigger droplet response to applied or environmental stimuli (e.g., pH, temperature, salt, or external fields). Moreover, parallels between droplets and live cells inspire efforts to conceive systems that resemble biological motifs or that can produce cellular behaviors that imitate biology (e.g., swarming, communication, or motion). Here, the authors highlight recent advances in smart droplets, with emphasis on organic, polymer, and/or particle surfactants that give rise to inter‐droplet communication (via aggregation, fusion, division, or mass transfer), droplet vehicles for controlled delivery, autonomous droplet motion, and tunable emulsion inversion. Especially emphasized is the macromolecular design to produce reactive and functional surfactants, which are crucial to responsive droplet behavior and their underlying mechanisms. More generally, the exquisite interplay between materials science and biology inspires the review of this research area that provides unique opportunities for insight and inspiration into the capabilities of new droplet designs.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Technology Demonstrator of an Americium-Fuelled Radioisotope Stirling Generator

Americium-241 is used as the fuel of choice in European Radioisotope Power Systems. The University of Leicester have developed a number of systems using this fuel type, including a 200 Wth heat source. To maximise the electrical output that can be generated from the heat source, the University of Leicester and NASA Glenn Research Center have collaborated on a radioisotope Stirling generator concept, building on the long heritage of dynamic power conversion developments at NASA GRC. Here we present the design of a technology demonstrator of the Americium-fuelled Radioisotope Stirling Generator (Am-RSG).

Americium-241↗

DOE OSTI2026

Powered By SAM [Slides]

The System Advisor Model(TM) (SAM) is a free, open-source desktop application for techno-economic analysis of energy technologies. By combining detailed performance modeling with financial analysis, SAM allows users to assess technology trade-offs, explore future scenarios, and make informed decisions about energy investments. Users also have access to model details and the ability to embed SAM's core models in their own applications. This webinar, hosted by National Laboratory of the Rockies researchers Janine Keith and Matt Prilliman, highlights how this widely used modeling tool supports data-driven decision-making for energy systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRSDate not supplied

High-Fidelity Modeling Approach for Coupling Thermal, Fluid, and Neutronic Analysis in an NTP Engine

Nuclear thermal propulsion (NTP), with its increased efficiency compared to traditional rocket engines, is a potentially enabling technology for space missions of higher complexity, such as delivering heavy machinery or crew to the moon or other planets. Thus, exploring modeling approaches that can effectively couple the thermal, fluid, and neutronic behaviors of NTP reactors is essential to mitigate cost and schedule challenges with hardware development. This paper details one such approach which utilizes Cardinal to unify reactor physics analysis performed using OpenMC, heat transfer analysis performed using the MOOSE framework, and thermal hydraulic analysis performed using the MOOSE Thermal Hydraulic Module. This approach is demonstrated with a proof of concept that focuses on a legacy reactor geometry from the historic NERVA program. This preliminary model found an overprediction in, when compared to the reference data, axial power peaking and the temperatures of both solids and fluids by roughly 20%. It is clear, however, that the model conserved a number of broad trends, and a few model refinements should reduce the observed error. This approach has definite merit and should enable the production of informative results for more modern NTP systems. This work is a first step in creating a transient reactor model that can be updated across a sequence of time steps based on continually fluctuating, time-dependent boundary conditions.

Nuclear Thermal Propulsion↗

DOE OSTI2026

Integration of Online Cross-Section Generation Capability with Depletion and Transient Solvers in Griffin

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE)-based reactor multiphysics analysis application jointly developed by Argonne and Idaho National Laboratories under the DOENE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In FY25, an online crosssection generation capability based on the Self-Shielding Application Programming Interface (SSAPI) was demonstrated for TRISO-fueled reactor problems under steady-state conditions. This fiscal year, that capability was extended to support depletion and transient multiphysics calculations, enabling high-fidelity analyses that generate self-shielded cross sections on the fly from the actual evolving composition and temperature states rather than from pre-tabulated libraries. For depletion, a two-way coupling was established in which SSAPI computes compact-averaged self-shielded cross sections that the depletion solver then uses to advance the Bateman equations, with the updated compositions returned to SSAPI at each step; the depletion module was refactored to support both library-based and SSAPI-based cross sections, and additional logic was added to track daughter isotopes and to exclude minor isotopes for efficiency. For transient analysis, the SSAPI multigroup library was extended with the kinetics data required for time-dependent calculations, the Improved Quasi-Static (IQS) scheme was coupled with SSAPI, and several supporting capabilities were implemented, including a self-shielding treatment that lets control rods and drums move within a self-shielded model, which had previously been impossible and had ruled out rod- and drum-movement transients with on-the-fly cross sections altogether, a new mixing scheme for delayed-neutron precursor decay constants, a checkpoint-based restart workflow, and performance improvements such as pointwise cross-section interpolation and the bypassing of unnecessary Dancoff factor calculations. The implemented capabilities were verified against Serpent Monte Carlo solutions. For depletion, a prismatic pin-cell problem based on a Next Generation Nuclear Plant (NGNP) Very High Temperature Reactor benchmark showed excellent agreement, with eigenvalue differences within 200 pcm over the entire burnup range (up to 140 MWD/kgU) and fission-product and actinide inventories agreeing to within 0.8% and 2.5%, respectively; a heat-pipe microreactor assembly problem with a much higher fuel loading confirmed the same behavior and quantified the bias introduced when the multigroup equivalence effect is neglected. For transient analysis, a pin-cell problem with a step reactivity insertion and temperature feedback reproduced the analytically expected asymptotic power and showed close agreement between the direct and IQS solutions, and a two-dimensional microreactor core problem with control-drum rotation exercised the new moving-drum self-shielding treatment and demonstrated successful coupling of the online crosssection generation with both the direct and IQS transient methods. The capability was further exercised on a full-core pebble-bed problem, in which Griffin was coupled with the System Analysis Module (SAM) to simulate load-following operation of the gPBR with the Doppler feedback resolved at the TRISO fuel kernel temperature. These developments in Griffin provide a convenient, high-fidelity approach to cross-section generation for advanced thermal reactors with geometrically complex and highly heterogeneous configurations, including TRISO-fueled prismatic and pebble-bed systems, and support steady-state, depletion, and transient multiphysics calculations. They also enable self-shielded cross sections to be evaluated directly at the actual coupled state of the system, thereby establishing a foundation for high-fidelity, fully coupled multiphysics analysis of advanced reactors

Park, H.↗

NASA NTRS2025

ISS Radiator Face Sheet Anomaly Investigation and Return to Function

Maintaining sufficient heat rejection on the International Space Station (ISS) is critical to the function of the Low-Earth Orbit station. The External Active Thermal Control System (EATCS) rejects the excess heat generated by the US On-Orbit Segment (USOS) modules. The system uses single-phase liquid ammonia to collect the heat and reject it to six radiators (three on the Starboard side, three on the Port side). Each radiator is made up of eight panels. In September 2008, imagery of the Starboard radiators was conducted and showed one of the panels’ face sheets had peeled up from the internal honeycomb core structure. Out of an abundance of caution, the radiator was isolated from the rest of the EATCS and the ammonia was vented to space. Since the radiator was vented, periodic imagery of all radiator panels was taken to monitor any changes in the face sheet and inspect for other radiator anomalies. In January 2025, after years of trending and inspections, the radiator was reintegrated into the system to increase heat rejection capabilities. This paper will document the multi-year investigation that took place to determine root cause and mitigations implemented to reduce risk to the system. A summary of the data since the investigation will show rationale for reintegrating the radiator even with the damaged panel. The goal of the paper is to document the investigation for historical purposes and provide future programs with findings discovered during the investigation.

Aaron Rodriguez↗

NASA NTRS2026

ISS Radiator Face Sheet Anomaly Investigation and Return to Function

Maintaining sufficient heat rejection on the International Space Station (ISS) is critical to the function of the Low-Earth Orbit station. The External Active Thermal Control System (EATCS) rejects the excess heat generated by the US On-Orbit Segment (USOS) modules. The system uses single-phase liquid ammonia to collect the heat and reject it to six radiators (three on the Starboard side, three on the Port side). Each radiator is made up of eight panels. In September 2008, imagery of the Starboard radiators was conducted and showed one of the panels’ face sheets had peeled up from the internal honeycomb core structure. Out of an abundance of caution, the radiator was isolated from the rest of the EATCS and the ammonia was vented to space. Since the radiator was vented, periodic imagery of all radiator panels was taken to monitor any changes in the face sheet and inspect for other radiator anomalies. In January 2025, after years of trending and inspections, the radiator was reintegrated into the system to increase heat rejection capabilities. This paper will document the multi-year investigation that took place to determine root cause and mitigations implemented to reduce risk to the system. A summary of the data since the investigation will show rationale for reintegrating the radiator even with the damaged panel. The goal of the paper is to document the investigation for historical purposes and provide future programs with findings discovered during the investigation.

Aaron Rodriguez↗

NASA NTRS2010

Ares I-X Ground Diagnostic Prototype

Automating prelaunch diagnostics for launch vehicles offers three potential benefits. First, it potentially improves safety by detecting faults that might otherwise have been missed so that they can be corrected before launch. Second, it potentially reduces launch delays by more quickly diagnosing the cause of anomalies that occur during prelaunch processing. Reducing launch delays will be critical to the success of NASA's planned future missions that require in-orbit rendezvous. Third, it potentially reduces costs by reducing both launch delays and the number of people needed to monitor the prelaunch process. NASA is currently developing the Ares I launch vehicle to bring the Orion capsule and its crew of four astronauts to low-earth orbit on their way to the moon. Ares I-X will be the first unmanned test flight of Ares I. It is scheduled to launch on October 27, 2009. The Ares I-X Ground Diagnostic Prototype is a prototype ground diagnostic system that will provide anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage thrust vector control (TVC) and for the associated ground hydraulics while it is in the Vehicle Assembly Building (VAB) at John F. Kennedy Space Center (KSC) and on the launch pad. It will serve as a prototype for a future operational ground diagnostic system for Ares I. The prototype combines three existing diagnostic tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool that is commercially produced by Qualtech Systems, Inc. It uses a qualitative model of failure propagation to perform fault isolation and diagnostics. We adapted an existing TEAMS model of the TVC to use for diagnostics and developed a TEAMS model of the ground hydraulics. The second tool, Spacecraft Health Inference Engine (SHINE), is a rule-based expert system developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification. The prototype uses the outputs of SHINE as inputs to TEAMS. The third tool, the Inductive Monitoring System (IMS), is an anomaly detection tool developed at NASA Ames Research Center and is currently used to monitor the International Space Station Control Moment Gyroscopes. IMS automatically "learns" a model of historical nominal data in the form of a set of clusters and signals an alarm when new data fails to match this model. IMS offers the potential to detect faults that have not been modeled. The three tools have been integrated and deployed to Hangar AE at KSC where they interface with live data from the Ares I-X vehicle and from the ground hydraulics. The outputs of the tools are displayed on a console in Hangar AE, one of the locations from which the Ares I-X launch will be monitored. In a previous publication, we discussed how we selected the three tools based primarily on their ability to be certified for human spaceflight and described our plans for the prototype. This abstract is due October 23, 2009, and the Ares I-X launch is currently scheduled for October 27, 2009. If this abstract is accepted, then the full paper will describe how the prototype performed before the launch. It will include an analysis of the prototype's accuracy, including false-positive rates, false-negative rates, and receiver operating characteristics (ROC) curves. It will also include a description of the prototype's computational requirements, including CPU usage, main memory usage, and disk usage. If the prototype detects any faults during the prelaunch period then the paper will include a description of those faults. Similarly, if the prototype has any false alarms then the paper will describe them and will attempt to explain their causes. Also, the paper will describe the three tools and how they are used in the prototype. It will include a description of the TEAMS models of the Ares I-X first-stage TVC and associated ground hydraulics and how we adapted the TVC model for use in real-time diagnostics. It will describe the SHINE rules used for fault detection and mode identification and the software architecture that interfaces the various pieces of existing software that are part of the prototype to one another. It will describe how we selected the sensor values and commands that were used to train the IMS model and how we optimized the number of clusters in the IMS model. It will include screen shots of the graphical display that we developed in Java to display the outputs of the three tools. Because Ares I-X data was not yet available to us while we were developing the prototype, we used historical data from the Space Shuttle's Solid Rocket Booster (SRB) TVCs and the associated ground hydraulics to train IMS and to test the entire prototype. Because most of the failure modes that we modeled have never occurred in the Shuttle we inserted simulated failures into the Shuttle data. The Ares I-X first-stage TVC is very similar to the SRB TVC and we expect the data will be very similar. After the launch, we will determine how similar the data actually is and report how any differences in the data affected the diagnostic accuracy of the prototype. Finally, although we did not get the prototype certified, we designed it in a way that it could be certified and wrote a preliminary certification plan. The paper will include a brief summary of how we considered the need for certification in the design of the prototype, how we tested the prototype before deploying it to Hangar AE, and how we would propose to get it certified if it were deployed as an operational system. The paper will conclude with a description of some of the challenges we faced and some of the lessons learned in developing and deploying the prototype.

International Space Station↗

NASA NTRS1970

Prevention of Coupled Structure-Propulsion Instability (POGO) On The Space Shuttle

Many liquid-propellant rocket vehicles have experienced longitudinal vibration, nicknamed pogo after the jumping stick, due to an instability arising from interaction of the vehicle structure with the propulsion system. These vibrations can produce an intolerable environment for astronauts and equipment, can overload vehicle structure, and can lead to loss of propulsion performance. A NASA monograph concerned with the prevention of pogo is well on its way toward publication and should serve as a useful guide to design for the Space Shuttle. The paper will briefly describe the nature of the pogo phenomenon, present a summary of past instabilities, relate the possible deleterious effects of pogo, and discuss the contents of the design criteria monograph. Finally, research tasks are recommended for support of pogo development activities on the Space Shuttle.

S. Rubin↗

NASA NTRSDate not supplied

Design, Development, and Test of the Advanced Apollo Orbital Assembly System

As spaceflight moves toward commercial solutions for Crew Vehicles and Space Stations, opportunity exists to lower costs with novel designs. Probe and cone docking systems provide a lightweight, low cost, and high-performance docking solution. This work revisits the Apollo probe and cone design and modifies it for the requirements of today’s computer-controlled spacecraft. This new system is called the Advanced Apollo Orbital Assembly (APOA) system, and is intended to support satellite, cargo, and space station assembly missions. A simulation of the APOA was programmed, components were sized, and a design was created by scaling the probe to the size of an EELV Secondary Payload Adapter (ESPA) tunnel. Prototype test hardware was 3D printed using Fused Deposition Modeling (FDM) methods with Polylactic Acid (PLA) material. Testing of the APOA-ESPA was conducted at Marshall Space Flight Center’s (MSFC) Flat Floor, and a test-correlated simulation is used to evaluate a Monte-Carlo of Initial Contact Conditions (ICC’s) to establish baseline performance. The successful development, test, and correlation of the APOA-ESPA proves the design validity and increases Technology Readiness Level (TRL) from 2 to 4. This work opens the door to construction of an APOA-ESPA from flight like materials, and to develop a larger scale prototype APOA. When the full scale APOA is incorporated with the Common Berthing Mechanism (CBM), becomes the Hybrid Berthing System (HBS), which allows for berthing without a robotic arm.

Berthing↗

NASA NTRS1993

Charge-exchange erosion studies of accelerator grids in ion thrusters

A particle simulation model is developed to study the charge-exchange grid erosion in ion thrusters for both ground-based and space-based operations. Because the neutral gas downstream from the accelerator grid is different for space and ground operation conditions, the charge-exchange erosion processes are also different. Based on an assumption of now electric potential hill downstream from the ion thruster, the calculations show that the accelerator grid erosion rate for space-based operating conditions should be significantly less than experimentally observed erosion rates from the ground-based tests conducted at NASA Lewis Research Center (LeRC) and NASA Jet Propulsion Laboratory (JPL). To resolve this erosion issue completely, we believe that it is necessary to accurately measure the entire electric potential field downstream from the thruster.

Xiaohang Peng↗

NASA NTRSDate not supplied

Natural Fiber Simulations and Analysis for Composites

As the U.S. government and the aviation industry strive to achieve net-zero carbon emissions by 2050, the Sustainable Manufacturing of Aircraft (SUMAC) project, supported by the Convergent Aeronautics Solutions (CAS) program of the National Aeronautics and Space Administration (NASA), aims to develop sustainably derived thermoplastic composites and manufacturing technologies for future aviation. A multidisciplinary team of experts drives this initiative through a collective effort. The team’s key focus areas are sustainably derived thermoplastic resins, natural fiber reinforcement, composite manufacturing, structural health monitoring, computational materials modeling, and systems analysis. This presentation will give an overview of the SUMAC project. Fiber-scale microscopy analysis characterized fiber cross sections finding that hemp and flax fibers are very deformable and non-circular (circularities of 0.2 were observed), and diameters range from submicron to 20 μm. Fiber shapes range from flattened, with aspect ratios Rlong/Rshort up to 5, to round, Rlong/Rshort =1. And Fiber core perimeters, which likely drives deformability, were calculated Pcore=7 μm. Explicit-fiber yarn simulations, parameterized from single-fiber measurements, resolved and identified slack as a cause for yarn strain-hardening tensile behavior. The bonded network model of PLA, PHA and PA11 resins captures tensile behavior, and can model an infused weave. Computational models of the weave unit cells matched the pattern (including plain, twill and triaxial braid), yarn ply (1to 2), and yarn twist from optical microscopy.

thermoplastic↗

NASA NTRSDate not supplied

Natural Fiber Simulations and Analysis for Composites

As the U.S. government and the aviation industry strive to achieve net-zero carbon emissions by 2050, the Sustainable Manufacturing of Aircraft (SUMAC) project, supported by the Convergent Aeronautics Solutions (CAS) program of the National Aeronautics and Space Administration (NASA), aims to develop sustainably derived thermoplastic composites and manufacturing technologies for future aviation. A multidisciplinary team of experts drives this initiative through a collective effort. The team’s key focus areas are sustainably derived thermoplastic resins, natural fiber reinforcement, composite manufacturing, structural health monitoring, computational materials modeling, and systems analysis. This presentation will give an overview of the SUMAC project. Fiber-scale microscopy analysis characterized fiber cross sections finding that hemp and flax fibers are very deformable and non-circular (circularities of 0.2 were observed), and diameters range from submicron to 20 μm. Fiber shapes range from flattened, with aspect ratios Rlong/Rshort up to 5, to round, Rlong/Rshort =1. And Fiber core perimeters, which likely drives deformability, were calculated Pcore=7 μm. Explicit-fiber yarn simulations, parameterized from single-fiber measurements, resolved and identified slack as a cause for yarn strain-hardening tensile behavior. The bonded network model of PLA, PHA and PA11 resins captures tensile behavior, and can model an infused weave. Computational models of the weave unit cells matched the pattern (including plain, twill and triaxial braid), yarn ply (1to 2), and yarn twist from optical microscopy.

thermoplastic↗