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NASA Glenn Electrified Aircraft Propulsion (EAP) Presentation Outline: High-Voltage, High-Power EAP - Standards and Regulations - Safety and Certification - High Power Density, High-Efficiency Electric Machines and Drives - Thermal Management - Fault Management - Superconducting Electric Machines - Materials Research - Modeling Tools - Advanced Controls
Vacancy-mediated diffusion barriers in 316 stainless steel have been systematically calculated using density functional theory to provide essential parameters for mesoscale microstructure evolution models. A statistical sampling approach employing 210 nudged elastic band calculations across multiple special quasi-random structures captures the effects of local chemical environments in this concentrated alloy. The computational methodology addresses challenges specific to chemically disordered systems, including proper magnetic treatment throughout multi-step calculations and validation against experimental structural properties. The calculated activation barriers reveal clear species-dependent diffusion behavior with the hierarchy Ni >> Fe ˜ Cr >> Mo. Nickel exhibits the highest barriers (0.74–1.31 eV, mean 1.045 eV), confirming its role as the slowest-diffusing major component. Iron and chromium show similar moderate barriers averaging 0.587 eV and 0.522 eV, respectively. Remarkably, molybdenum demonstrates exceptionally low barriers (0.12–0.28 eV, mean 0.194 eV), suggesting much higher mobility than previously recognized and potentially significant implications for precipitation kinetics and microstructure evolution. The barrier ranges remain consistent across different 316 SS compositions, supporting parameter transferability for modeling applications. The overall mean barrier of 0.64 eV provides a practical approximation for phase field simulations, while species-specific values enable detailed treatments of diffusion-controlled processes. This systematic approach establishes a validated framework for generating diffusion parameters in other concentrated alloys where experimental data are limited, while providing the first systematic set of species-specific barriers for predictive modeling of 316 stainless steel microstructure evolution.
Purpose: Municipal Solid Waste (MSW) is a potentially valuable sustainable feedstock for fuel and chemical production due to its carbon-rich content and low cost. This study aims to assess the material handling properties of paperand plastic-rich MSW feedstocks to mitigate equipment failure and processing downtime. Methods: The material handling properties of crumbled MSW feedstocks were measured using apowder rheometer with mass flow hopper calculations to assess handling performance. Inverse gas chromatography was use to measure the surface energy differences between feedstocks. Electron microscopy and Raman spectroscopy was used to evaluate microscale features that may contribute to material handling differences. Results: Plastic and paper rich feedstocks crumbled to a nominal 2 mm particle size were observed to have similar flow and handling characteristics with reasonable hopper outlets. 2 mm plastic rich crumbles, with their higher bulk density, exhibited superior flow performance. By contrast, 4 mm material required significantly larger hopper outlets, indicating poor flowability. Paper rich and 4 mm plastic rich samples displayed broad particle size distributions, which contributed to particle interlocking, jamming, and other flow issues. Electron microscopy revealed that plastic rich samples were significantly smoother, enhancing their flowability compared to the rougher, paper rich materials. Conclusions: This study establishes critical material handling baselines for processing MSW as a viable feedstock for fuel and chemical production. The findings highlight the importance of optimizing particle size and feedstock composition to improve flowability and handling performance.
Report describes fabrication of graphite-fiber/copper-matrix composite plates, measurements of thermal conductivities of plates at temperatures from ambient to 1,073 K, and measurements of thermal expansions of plates from ambient temperature to 1,050 K. Composites promising lightweight, high-thermal-conductivity materials proposed for use in heat exchangers and other heat-transfer components of power systems in spacecraft and hypersonic aircraft. Graphite/copper also of interest as model composite material.
The Near Earth Asteroid (NEA) Scout is a solar sail mission whose objective is to scout at least one Near Earth Asteroid to help prepare for human missions to Near Earth Asteroids. NEA Scout will launch as a secondary payload on the first SLS-Orion mission. NEA Scout will perform a small trim maneuver shortly after deploy from the spent SLS upper stage using a cold gas propulsion system, but from that point on will depend entirely on the solar sail for thrust. As such, it is important to accurately characterize the thrust of the sail in order to achieve mission success. Additionally, the solar sail creates a relatively large solar disturbance torque that must be mitigated. For early mission design studies a flat plate model of the solar sail with a fixed center of pressure was adequate, but as mission concepts and the sail design matured, greater fidelity was required. Here we discuss the progress to a three-dimensional sail model that includes the effects of tension and thermal deformation that has been derived from a large structural Finite Element Model (FEM) developed by the Langley Research Center. We have found that the deformed sail membrane affects torque relatively much more than thrust; a flat plate model could potentially model thrust well enough to close mission design studies, but a three-dimensional solar sail is essential to control system design. The three-dimensional solar sail model revealed that thermal deformations of unshielded booms would create unacceptably large solar disturbance torques. The original large FEM model was used in control and mission simulations, but was resulted in simulations with prohibitive run times. This led us to adapt the Generalized Sail Model (GSM) of Rios-Reyes. A design reference sail model has been baselined for NEA Scout and has been used to design the mission and control system for the sailcraft. Additionally, since NEA Scout uses reaction wheels for attitude pointing and control, the solar torque model is essentially to successfully design the NEA Scout momentum management control system. We have also updated the estimate of diffusivity used for the aluminized sail material based on optical testing of wrinkled sail material. The model presented here represents the current state of the art of NASA's ability to model solar sail thrust and torque.
Micromechanics-based modeling of composite material behaviors requires an accurate assessment of the constituent properties and behaviors. For the specific case of continuous-fiber-reinforced metal matrix composites (MMC's) manufactured from a foil/fiber/foil process, much emphasis has been placed on characterizing foil-based matrix materials that have been fabricated in the same way as the composite. Such materials are believed to yield mechanical properties and behaviors that are representative of the matrix constituent within the composite (in situ matrix). Therefore, these materials are desired for micromechanics modeling input. Unfortunately, such foils are extremely expensive to fabricate and procure because of the labor-intensive rolling process needed to produce them. As a potential solution to this problem that would maintain appropriately representative in situ properties, the matrix constituent could be characterized with sheet-based materials, which are considerably less expensive to manufacture than foils, are more readily procured, and result in fewer plies to obtain a desired panel thickness. The critical question is, however, does the consolidated sheet material exhibit the same properties and behaviors as do the consolidated foils? Researchers at NASA Lewis Research Center's Life Prediction Branch completed a detailed experimental investigation to answer this question for three titanium alloys commonly used in metal matrix composite form.
Accurate and efficient constitutive modeling remains a cornerstone issue for solid mechanics analysis. Over the years, the LAMÉ advanced material model library has grown to address this challenge by implementing models capable of describing material systems spanning soft polymers to stiff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco)plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options an
The Mars Science Laboratory (MSL) was protected during its atmospheric entry by an instrumented heatshield using NASA's Phenolic Impregnated Carbon Ablator (PICA) material [1]. PICA is a lightweight carbon fiber/polymeric resin material that offers outstanding performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of material response and atmospheric entry. MEDLI recorded, among other things, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP) [2]. The objective of this work is to showcase and analyze the coupling between the material response and the aerothermal environment. As shown in Figure 1, the workflow is divided into the following steps. First, the aerothermal properties are computed in the Data Parallel Line Relaxation (DPLR) code [3] and used with the Nonequilibrium air radiation (NEQAIR) program [8] to compute radiative heating. Second, the thermal response inside the material is computed in the Porous material Analysis Toolbox based on OpenFOAM (PATO) [4,5,6] using a fixed blowing correction parameter. Third, the pyrolysis gases computed in PATO are used as inputs to a blowing boundary condition within DPLR. Fourth, the new environment properties from DPLR are used in NEQAIR to provide an updated solution, then both the updated aerothermal environment and radiative heating are used in PATO without blowing correction. The third and fourth steps are then repeated until convergence in surface temperature is obtained. Convergence in the radiative heating is generally achieved before surface temperature, at which point the radiative heating is no longer updated. Char mass loss rates are forced to zero to produce a non-receding surface condition. For early time points in the trajectory, where flow around the MSL aeroshell is rarefied, the Direct Simulation Monte Carlo (DSMC) code, SPARTA [7], is used to compute the aerothermal environment. Iteration between PATO and SPARTA is not performed due to the computational cost of DSMC simulations. Preliminary results of the coupling between PATO and DPLR for the MSL heatshield atmospheric entry model are presented in Figures 2-4 at 65 seconds after entry interface. Figure 2 shows the surface temperature results from an uncoupled simulation in PATO with the blowing correction parameter applied (left) along with the coupled surface temperature after iteration (right). Figure 3 shows the surface temperature along the centerline from windward to leeward for easier comparison. Figure 4 shows the coupled and uncoupled pyrolysis gas blowing rate. Mars 2020 used a similar heatshield consisting of PICA for thermal protection during entry, descent, and landing. In preparation for Mars 2020 post-flight analysis, the predictive material response capability is benchmarked against flight data from MEDLI. This work represents an important milestone toward the development of validated predictive capabilities for designing thermal protection systems for planetary probes.
A model was developed to generate quantitative estimates of the risk associated with the release of graphite fibers during fires involving commercial aircraft constructed with graphite fiber composite materials. The model was used to estimate the risk associated with accidents at several U.S. airports. These results were then combined to provide an estimate of the total risk to the nation.
The space environment is detrimental to the exterior of the spacecraft and imposes stringent requirements on spacecraft materials. Space materials are often expected to perform for 15-20 years in the harsh space environment without significant degradation of their optical, electrical, mechanical and thermal properties. Further, as commercial activities increase in the space domain, development of predictive capability for material evolution is critical for agile adaption of novel materials. Therefore, it is very important to understand the effects of the space environments on the spacecraft materials. The Materials on the International Space Station Experiment Flight Facility (MISSE-FF) has flown numerous material samples to investigate the effect of LEO space weather exposure on the performance and durability of materials and devices. We are manifest on the MISSE-16 mission, scheduled to launch in June 2022, to fly fifteen novel and well-characterized materials in the LEO environment for a duration of six months. Changes in spectral reflectivity will be measured in real time throughout the mission with an RGB/IR camera. These time-resolved data will function as a "space-truth" reference for our team's ongoing laboratory-based space weather-material interaction experiments. Correlation of the MISSE-16 data with extensive ground testing of duplicate samples under simulated space weather conditions will enable development of fundamental chemical models for material degradation. This paper discusses preliminary results from the ground test campaign to collect the RGB/IR images for pristine and damaged materials and the development of machine learning algorithms to extract reflectance spectra from the color images.
The space environment is detrimental to the exterior of the spacecraft and imposes stringent requirements on spacecraft materials. Space materials are often expected to perform for 15-20 years in the harsh space environment without significant degradation of their optical, electrical, mechanical and thermal properties. Further, as commercial activities increase in the space domain, development of predictive capability for material evolution is critical for agile adaption of novel materials. Therefore, it is very important to understand the effects of the space environments on the spacecraft materials. The Materials on the International Space Station Experiment Flight Facility (MISSE-FF) has flown numerous material samples to investigate the effect of LEO space weather exposure on the performance and durability of materials and devices. We are manifest on the MISSE-16 mission, scheduled to launch in June 2022, to fly fifteen novel and well-characterized materials in the LEO environment for a duration of six months. Changes in spectral reflectivity will be measured in real time throughout the mission with an RGB/IR camera. These time-resolved data will function as a "space-truth" reference for our team's ongoing laboratory-based space weather-material interaction experiments. Correlation of the MISSE-16 data with extensive ground testing of duplicate samples under simulated space weather conditions will enable development of fundamental chemical models for material degradation. This paper discusses preliminary results from the ground test campaign to collect the RGB/IR images for pristine and damaged materials and the development of machine learning algorithms to extract reflectance spectra from the color images.
RSRM nozzle liner components have been analyzed and tested to explore the occurrence of anomalous material performance known as pocketing erosion. Primary physical factors that contribute to pocketing seem to include the geometric permeability, which governs pore pressure magnitudes and hence load, and carbon fiber high temperature tensile strength, which defines a material limiting capability. The study reports on the results of a coupled thermostructural finite element analysis of Carbon Cloth Phenolic (CCP) material tested at the Laser Hardened Material Evaluation Laboratory (the LHMEL facility). Modeled test configurations will be limited to the special case of where temperature gradients are oriented perpendicular to the composite material ply angle. Analyses were conducted using a transient, one-dimensional flow/thermal finite element code that models pore pressure and temperature distributions and in an explicitly coupled formulation, passes this information to a 2-dimensional finite element structural model for determination of the stress/deformation behavior of the orthotropic fiber/matrix CCP. Pore pressures are generated by thermal decomposition of the phenolic resin which evolve as a multi-component gas phase which is partially trapped in the porous microstructure of the composite. The nature of resultant pressures are described by using the Darcy relationships which have been modified to permit a multi-specie mass and momentum balance including water vapor condensation. Solution to the conjugate flow/thermal equations were performed using the SINDA code. Of particular importance to this problem was the implementation of a char and deformation state dependent (geometric) permeability as describing a first order interaction between the flow/thermal and structural models. Material property models are used to characterize the solid phase mechanical stiffness and failure. Structural calculations were performed using the ABAQUS code. Iterations were made between the two codes involving the dependent variables temperature, pressure and across-ply strain level. Model results comparisons are made for three different surface heat rates and dependent variable sensitivities discussed for the various cases.
Atomic disorder can strongly influence material properties such as charge transport, optical response, and catalytic activity. However, efficiently modeling these disorder effects remains challenging for first-principles methods due to the cost of sampling large configurational spaces and computing complex physical quantities. Recent advances of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. In this work, we present a general machine-learning-assisted computational framework that integrates equivariant GNNs with Monte Carlo simulations to compute the thermodynamic and ensemble-averaged functional properties of disordered materials. Using the surface-termination-disordered MXene monolayer Ti 3 C 2 T 2–x as a representative system, we find that electrical conductivity exhibits an emergent peak near the order–disorder phase transition temperature due to the interplay between electron scattering and doping. In contrast, optical conductivity remains largely insensitive to local atomic disorder and reflects the global surface chemical composition. These results highlight the role of atomic disorder in affecting material properties and demonstrate the potential of our approach for statistically modeling disorder effects in a wide range of materials such as high-entropy alloys and spin liquids.
Coupled fluid-material response analyses of arc-jet wedge ablation tests conducted in a NASA Ames arc-jet facility are considered. These tests were conducted using blunt wedge models placed in a free jet downstream of the 6-inch diameter conical nozzle in the Ames 60-MW Interaction Heating Facility. The fluid analysis includes computational Navier-Stokes simulations of the nonequilibrium flowfield in the facility nozzle and test box as well as the flowfield over the models. The material response analysis includes simulation of two-dimensional surface ablation and internal heat conduction, thermal decomposition, and pyrolysis gas flow. For ablating test articles undergoing shape change, the material response and fluid analyses are coupled in order to calculate the time dependent surface heating and pressure distributions that result from shape change. The ablating material used in these arc-jet tests was Phenolic Impregnated Carbon Ablator. Effects of the test article shape change on fluid and material response simulations are demonstrated, and computational predictions of surface recession, shape change, and in-depth temperatures are compared with the experimental measurements.
In computing the response of an ablating thermal protection system during atmospheric entry, the aerothermal environment and material response are generally computed separately with a blowing correction term in the material response model to account for the blowing of char and pyrolysis gases. In this work, we apply a coupled approach in which pyrolysis blowing gases, computed in the PATO material response code, are used with a blowing boundary condition in the DPLR hypersonic CFD code. This leads to an iterative method in which blowing products from PATO are input into DPLR to update surface heating estimates. The full iterative method, with the addition of radiative heating estimates using the NEQAIR radiation solver, is shown in Fig. 1. The method is demonstrated on a sphere case with the environment and material properties based on the Mars Science Laboratory entry. Future work includes utilizing this method in computing full 3D material response during the Mars 2020 entry.
The Mars Science Laboratory (MSL) was protected during its atmospheric entry by an instrumented heat-shield using NASA's Phenolic Impregnated Carbon Ablator (PICA) material. PICA is a lightweight carbon fiber/polymeric resin material that offers out-standing performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of material response and atmospheric entry. MEDLI recorded, among other things, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP). The objective of this work is to showcase and analyze the coupling between the material response and the aerothermal environment. As shown in Figure 1, the workflow is divided into the following steps. First, the aerothermal properties are computed in the Data Parallel Line Relaxation (DPLR) code [3] and used with the Nonequilibrium air radiation (NEQAIR) program [8] to compute radiative heating. Second, the thermal response inside the material is computed in the Porous material Analysis Toolbox based on Open-FOAM (PATO) using a fixed blowing correction parameter. Third, the pyrolysis gases computed in PATO are used as inputs to a blowing boundary condition within DPLR. Fourth, the new environment properties from DPLR are used in NEQAIR to provide an updated solution, then both the updated aerothermal environment and radiative heating are used in PATO without blowing correction. The third and fourth steps are then repeated until convergence in surface temperature is obtained. Convergence in the radiative heating is generally achieved before surface temperature, at which point the radiative heating is no longer updated. Char mass loss rates are forced to zero to produce a non-receding surface condition. For early time points in the trajectory, where flow around the MSL aeroshell is rarefied, the Direct Simulation Monte Carlo (DSMC) code, SPARTA, is used to compute the aerothermal environment. Iteration between PATO and SPARTA is not performed due to the computational cost of DSMC simulations. Preliminary results of the coupling between PATO and DPLR for the MSL heatshield atmospheric entry model are presented in Figures 2-4 at 65 seconds after entry interface. Figure 2 shows the surface temperature results from an uncoupled simulation in PATO with the blowing correction parameter applied (left) along with the coupled surface temperature after iteration (right). Figure 3 shows the surface temperature along the centerline from windward to leeward for easier comparison. Figure 4 shows the coupled and uncoupled pyrolysis gas blowing rate. Mars 2020 used a similar heatshield consisting of PICA for thermal protection during entry, descent, and landing. In preparation for Mars 2020 post-flight analysis, the predictive material response capability is benchmarked against flight data from MEDLI. This work represents an important milestone toward the development of validated predictive capabilities for designing thermal protection systems for planetary probes.
A plastic waste upcycling value chain model has been applied to assess the potential of processing packaging waste in Spain using thermo-chemical technologies to produce low-density polyethylene (LDPE) and polypropylene (PP), which are highly valuable materials. The model projects an annual profit of 120.6 M$\$$/yr, with a capital investment of 789.3 M$\$$, generating 3285 jobs and contributing 65.5 M$\$$/yr to Spain’s economy. The achieved circularity rate of the waste processing infrastructure exceeds 40 %, incorporating recycled HDPE and PET. Despite these advantages, regulatory gaps and market hesitancy toward recycled materials due to quality concerns hinder adoption. Additionally, economies of scale remain underutilized in Spain due to lower plastic waste collection levels compared to countries such as the United States. This network, while less profitable, is environmentally superior, yielding upcycled products with a Global Warming Potential 20–35 % lower than their virgin, fossil-fuel counterparts, confirming this as a viable and sustainable alternative.
The study of conductive oxides has gained momentum within the photonics community due to their unique linear and nonlinear optical properties. Despite recent experiments reporting on high harmonic generation from thin films, the optical/electronic behavior of these compounds at the nanoscale is still not fully understood due to the lack of a suitable theoretical model. In the present work, aluminum zinc oxide is excited near its epsilon-near-zero crossing point using incident femtosecond pulses having peak power densities in the 1 TW cm −2 range. A relatively efficient frequency up-conversion including even and odd harmonics up to the seventh order is observed. A hydrodynamic-Maxwell theoretical approach is adopted, capable of simultaneously taking into account linear and nonlinear dispersions, nonlocal effects, surface, magnetic, and bulk nonlinearities in a spectral region that spans over two and a half octaves from the UV to the NIR region. The study enables a deeper understanding of the fundamental material parameters regulating optical nonlinearities, providing important insights to engineer this class of materials for applications in sensing, ultra-fast physics, and spectroscopy.