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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Exhaust Simulation Testing of a Hypersonic Airbreathing Model at Transonic Speeds

An experimental study was performed to examine jet-effects for an airframe-integrated, scramjet-rocket combined-cycle vehicle configuration at transonic test conditions. This investigation was performed by testing an existing exhaust simulation wind tunnel model, known as Model 5B, in the NASA Langley 16-Ft. Transonic Tunnel. Tests were conducted at freestream Mach numbers from 0.7 to 1.2, at angles of attack from 2 to +14 degrees, and at up to seven nozzle static pressure ratio values for a set of horizontal-tail and body-flap deflections. The model aftbody, horizontal tails, and body flaps were extensively pressure instrumented to provide an understanding of jet-effects and control-surface/plume interactions, as well as for the development of analytical methodologies and calibration of computational fluid dynamic codes to predict this type of flow phenomenon. At all transonic test conditions examined, the exhaust flow at the exit of the internal nozzle was over-expanded, generating an exhaust plume that turned toward the aftbody. Pressure contour plots for the aftbody of Model 5B are presented for freestream transonic Mach numbers of 0.70, 0.95, and 1.20. These pressure data, along with shadowgraph images, indicated the impingement of an internal plume shock and at least one reflected shock onto the aftbody for all transonic conditions tested. These results also provided evidence of the highly three-dimensional nature of the aftbody exhaust flowfield. Parametric testing showed that angle-of-attack, static nozzle pressure ratio, and freestream Mach number all affected the exhaust-plume size, exhaust-flowfield shock structure, and the aftbody-pressure distribution, with Mach number having the largest effect. Integration of the aftbody pressure data showed large variations in the pitching moment throughout the transonic regime.

Huebner, Lawrence D.↗
NASA NTRS2003

The Madden-Julian Oscillation and its Impact on Northern Hemisphere Weather Predictability during Wintertime

The Madden-Julian Oscillation (MJO) is known as the dominant mode of tropical intraseasonal variability and has an important role in the coupled-atmosphere system. This study used twin numerical model experiments to investigate the influence of the MJO activity on weather predictability in the midlatitudes of the Northern Hemisphere during boreal winter. The National Aeronautics and Space Administration (NASA) Goddard laboratory for the Atmospheres (GLA) general circulation model was first used in a 10-yr simulation with fixed climatological SSTs to generate a validation data set as well as to select initial conditions for active MJO periods and Null cases. Two perturbation numerical experiments were performed for the 75 cases selected [(4 MJO phases + Null phase) _ 15 initial conditions in each]. For each alternative initial condition, the model was integrated for 90 days. Mean anomaly correlations in the midlatitudes of the Northern Hemisphere (2O deg N_60 deg.N) and standardized root-mean-square errors were computed to validate forecasts and control run. The analyses of 500-hPa geopotential height, 200-hPa Streamfunction and 850-hPa zonal wind component systematically show larger predictability during periods of active MJO as opposed to quiescent episodes of the oscillation.

Jones, Charles↗
NASA NTRS1999

Low-Frequency Oscillations and Transport Processes Induced by Multiscale Transverse Structures in the Polar Wind Outflow: A Three-Dimensional Simulation

Multiscale transverse structures in the magnetic-field-aligned flows have been frequently observed in the auroral region by FAST and Freja satellites. A number of multiscale processes, such as broadband low-frequency oscillations and various cross-field transport effects are well correlated with these structures. To study these effects, we have used our three-dimensional multifluid model with multiscale transverse inhomogeneities in the initial velocity profile. Self-consistent-frequency mode driven by local transverse gradients in the generation of the low field-aligned ion flow and associated transport processes were simulated. Effects of particle interaction with the self-consistent time-dependent three-dimensional wave potential have been modeled using a distribution of test particles. For typical polar wind conditions it has been found that even large-scale (approximately 50 - 100 km) transverse inhomogeneities in the flow can generate low-frequency oscillations that lead to significant flow modifications, cross-field particle diffusion, and other transport effects. It has also been shown that even small-amplitude (approximately 10 - 20%) short-scale (approximately 10 km) modulations of the original large-scale flow profile significantly increases low-frequency mode generation and associated cross-field transport, not only at the local spatial scales imposed by the modulations but also on global scales. Note that this wave-induced cross-field transport is not included in any of the global numerical models of the ionosphere, ionosphere-thermosphere, or ionosphere-polar wind. The simulation results indicate that the wave-induced cross-field transport not only affects the ion outflow rates but also leads to a significant broadening of particle phase-space distribution and transverse particle diffusion.

Ganguli, Supriya B.↗
NASA NTRS2018

Mid-Fidelity Computational Fluid Dynamics Analysis of the Elytron 4S UAV Concept

The Elytron 4S Unmanned Aerial Vehicle (UAV) Concept was developed to combine the advantages of fixed- and rotary-wing technology. The 4S Concept is a box-wing configuration with rotors mounted on a centrally located tiltwing. The UAV is intended to be capable of both conventional takeoff and landing (CTOL) and vertical takeoff and landing (VTOL), and is envisioned to excel in UAV performance because of the combined efficiency of fixed-wing aircraft and the hover and VTOL capabilities of regular drones or quadcopters. A mid-fidelity Unsteady Reynolds-Averaged Navier-Stokes (URANS) approach using Rotorcraft CFD (RotCFD) is performed to analyze and characterize the performance of the aircraft. The flow field is coupled with a rotor model based on blade-element momentum theory to model the 4S UAV rotors. Turbulence is modeled using a realizable k- turbulence model with special wall function. The code is used to generate aerodynamic forces and moments on the body at cruise conditions, and during VTOL. The results and their uncertainties are characterized, and an angle- of-attack and sideslip sweep are computed, both with and without rotors on. Simulations are compared with the wind tunnel tests in the 7- by 10-Foot U.S. Army Wind Tunnel at NASA Ames Research Center, performed in 2017. Results show promising comparison with experimental data, despite a late change in rotor size and rudder size of the physical model that cause the expected deviations from the simulation. A slight change in the net thrust value, when rotors are modeled, is observed because of the rotor diameter increase on the physical model. A noticeable difference in the directional stability was observed because of the increased rudder surface and added strakes. These changes were implemented to improve on the design as simulated, which is observed in the results. The simulation results paved the way to the first successful flight of the UAV Concept.

Koning, Witold J. K.↗
NASA NTRS2014

Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

This paper presents recent thermal model results of the Advanced Stirling Radioisotope Generator (ASRG). The three-dimensional (3D) ASRG thermal power model was built using the Thermal Desktop(trademark) thermal analyzer. The model was correlated with ASRG engineering unit test data and ASRG flight unit predictions from Lockheed Martin's (LM's) I-deas(trademark) TMG thermal model. The auxiliary cooling system (ACS) of the ASRG is also included in the ASRG thermal model. The ACS is designed to remove waste heat from the ASRG so that it can be used to heat spacecraft components. The performance of the ACS is reported under nominal conditions and during a Venus flyby scenario. The results for the nominal case are validated with data from Lockheed Martin. Transient thermal analysis results of ASRG for a Venus flyby with a representative trajectory are also presented. In addition, model results of an ASRG mounted on a Cassini-like spacecraft with a sunshade are presented to show a way to mitigate the high temperatures of a Venus flyby. It was predicted that the sunshade can lower the temperature of the ASRG alternator by 20 C for the representative Venus flyby trajectory. The 3D model also was modified to predict generator performance after a single Advanced Stirling Convertor failure. The geometry of the Microtherm HT insulation block on the outboard side was modified to match deformation and shrinkage observed during testing of a prototypic ASRG test fixture by LM. Test conditions and test data were used to correlate the model by adjusting the thermal conductivity of the deformed insulation to match the post-heat-dump steady state temperatures. Results for these conditions showed that the performance of the still-functioning inboard ACS was unaffected.

radioisotope power system↗
NASA NTRS1993

Modelling the Shuttle Remote Manipulator System: Another flexible model

High fidelity elastic system modeling algorithms are discussed. The particular system studied is the Space Shuttle Remote Manipulator System (RMS) undergoing full articulated motion. The model incorporates flexibility via a methodology the author has been developing. The technique is based in variational principles, so rigorous boundary condition generation and weak formulations for the associated partial differential equations are realized, yet the analyst need not integrate by parts. The methodology is formulated using vector-dyad notation with minimal use of tensor notation, therefore the technique is believed to be affable to practicing engineers. The objectives of this work are as follows: (1) determine the efficacy of the modeling method; and (2) determine if the method affords an analyst advantages in the overall modeling and simulation task. Generated out of necessity were Mathematica algorithms that quasi-automate the modeling procedure and simulation development. The project was divided into sections as follows: (1) model development of a simplified manipulator; (2) model development of the full-freedom RMS including a flexible movable base on a six degree of freedom orbiter (a rigid-body is attached to the manipulator end-effector); (3) simulation development for item 2; and (4) comparison to the currently used model of the flexible RMS in the Structures and Mechanics Division of NASA JSC. At the time of the writing of this report, items 3 and 4 above were not complete.

Barhorst, Alan A.↗
NASA NTRS2018

Turbulent Aeroheating Measurements on a 7-deg Half-Angle Sphere-Cone in a High-Enthalpy CO2 Expansion Tunnel

A database of heating and pressure measurements on a 7-deg half-angle cone in a highenthalpy expansion tunnel in CO2 has been generated to support development and validation of computational models to be employed in the design of future Mars missions. Laminar, transitional, and turbulent simulations were performed at the test conditions for comparisons with the data. Close agreement was obtained for both fully-laminar and fully turbulent conditions. For the remaining transitional/turbulent conditions, agreement to within, or slightly more than, the estimated experimental uncertainty was demonstrated. The influence of transition intermittency and transition length models on predicted heating levels was demonstrated, as were differences in turbulent heating predictions generated using various algebraic, one-equation, and two-equation turbulence models. These comparisons provide some measure of confidence in turbulent simulation capabilities; however, because the data were not obtained on a relevant entry vehicle geometry, it is not possible to fully quantify computational uncertainties for the definition of Mars mission aerothermodynamic environments at this time

Brian R Hollis↗
NASA NTRS2013

Sensitivity of the Atmospheric Response to Warm Pool El Nino Events to Modeled SSTs and Future Climate Forcings

Warm pool El Nino (WPEN) events are characterized by positive sea surface temperature (SST) anomalies in the central equatorial Pacific. Under present-day climate conditions, WPEN events generate poleward propagating wavetrains and enhance midlatitude planetary wave activity, weakening the stratospheric polar vortices. The late 21st century extratropical atmospheric response to WPEN events is investigated using the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM), version 2. GEOSCCM simulations are forced by projected late 21st century concentrations of greenhouse gases (GHGs) and ozone-depleting substances (ODSs) and by SSTs and sea ice concentrations from an existing ocean-atmosphere simulation. Despite known ocean-atmosphere model biases, the prescribed SST fields represent a best estimate of the structure of late 21st century WPEN events. The future Arctic vortex response is qualitatively similar to that observed in recent decades but is weaker in late winter. This response reflects the weaker SST forcing in the Nino 3.4 region and subsequently weaker Northern Hemisphere tropospheric teleconnections. The Antarctic stratosphere does not respond to WPEN events in a future climate, reflecting a change in tropospheric teleconnections: The meridional wavetrain weakens while a more zonal wavetrain originates near Australia. Sensitivity simulations show that a strong poleward wavetrain response to WPEN requires a strengthening and southeastward extension of the South Pacific Convergence Zone; this feature is not captured by the late 21st century modeled SSTs. Expected future increases in GHGs and decreases in ODSs do not affect the polar stratospheric responses to WPEN.

stratosphere↗
NASA NTRS2009

Predicting Pilot Performance in Off-Nominal Conditions: A Meta-Analysis and Model Validation

Pilot response to off-nominal (very rare) events represents a critical component to understanding the safety of next generation airspace technology and procedures. We describe a meta-analysis designed to integrate the existing data regarding pilot accuracy of detecting rare, unexpected events such as runway incursions in realistic flight simulations. Thirty-five studies were identified and pilot responses were categorized by expectancy, event location, and whether the pilot was flying with a highway-in-the-sky display. All three dichotomies produced large, significant effects on event miss rate. A model of human attention and noticing, N-SEEV, was then used to predict event noticing performance as a function of event salience and expectancy, and retinal eccentricity. Eccentricity is predicted from steady state scanning by the SEEV model of attention allocation. The model was used to predict miss rates for the expectancy, location and highway-in-the-sky (HITS) effects identified in the meta-analysis. The correlation between model-predicted results and data from the meta-analysis was 0.72.

Wickens, C.D.↗
NASA NTRS2024

A Feasibility Study of 4-D Tomography of Soft X-ray Magnetosheath Emissivities Using Multi-Spacecraft Measurements

Upcoming heliophysics missions utilize state-of-the-art wide field-of-view (FOV) imaging technology to measure and investigate the space plasma environment on a global scale. At Earth, remote sensing of soft X-ray emissions, which are generated via the charge exchange interaction between heavy solar wind ions and exospheric neutral atoms, is a promising means to investigate the global magnetosheath structure, its response to varying solar wind conditions, and the spatiotemporal properties of the dayside magnetic reconnection. Data analysis techniques such as optical tomography can provide additional structural and time-varying information from the observed target and thus enhance the mission’s scientific return. In this work, we simulate multiple and simultaneous observations of the dayside magnetosphere using soft X-ray imagers located at long-distance vantage points to reconstruct the time-dependent, three-dimensional (3-D) structure of the magnetosheath using a dynamic tomographic approach. The OpenGCCM MHD model is used to simulate the time-varying response of the magnetosheath to solar wind conditions and, subsequently, generate synthetic soft X-ray images from multiple spacecraft vantage points separated along a common orbit. A detailed analysis is then performed to identify the nominal set of spacecraft that produces the highest fidelity tomographic reconstruction of the magnetopause. This work aims to (i) demonstrate, for the first time, the use of dynamic tomography to retrieve the time-varying magnetosheath structure and (ii) identify a nominal mission design for multi-spacecraft configurations aiming for optical tomography.

3-D/4_d tomography↗
NASA NTRS1979

Simulations of the monthly mean atmosphere for February 1976 with the GISS model

Three monthly mean simulations of the global atmosphere were computed for February 1976 with the GISS model from observed initial conditions on the first day of the month. In a replication experiment, two of these computations generated slightly different monthly mean states, apparently due to the schedule of interruptions on the computer. The root-mean-square errors of replication over the Northern Hemisphere were found to be about 2 mb, 20 m and 1 K for sea level pressure, 500 mb height and 850 mb temperature, respectively. The monthly mean 500 mb forecast results for February 1976 over the Northern Hemisphere are consistent with those from earlier GISS model experiments and again indicate some predictive skill at that level. Use of the observed monthly mean sea surface temperature (SST) field for February 1976 in place of the climatological SST field for February resulted in slightly improved simulations over the globe and Northern Hemisphere,

Spar, J.↗
NASA NTRS2020

INVESTIGATING THE FEASIBILITY AND STABILITY FOR MODELING ACOUSTIC WAVE SCATTERING USING A TIME-DOMAIN BOUNDARY INTEGRAL EQUATION WITH IMPEDANCE BOUNDARY CONDITION

Reducing aircraft noise is a major objective in the field of computational aeroacoustics. When designing next generation quiet and environmentally friendly aircraft, it is important to be able to accurately and efficiently predict the acoustic scattering by an aircraft body from a given noise source. Acoustic liners are an effective tool for aircraft noise reduction and are characterized by a frequency-dependent impedance. Converted into the time-domain using Fourier transforms, an impedance boundary condition can be used to simulate the acoustic wave scattering by geometric bodies treated with acoustic liners. This work considers using either an impedance or an admittance (inverse of impedance) boundary condition to allow for acoustic scattering problems to be modeled with geometries consisting of both un-lined and lined surfaces. Three acoustic liner models are discussed: the Extended Helmholtz Resonator Model, the Three-Parameter Impedance Model, and the Broadband Impedance Model. In both the Helmholtz and Three-Parameter models, liner impedance is specified at a given frequency, whereas the Broadband model allows for the investigation of multiple frequencies simultaneously. The impedance and admittance boundary conditions for acoustic liners are derived for each model and coupled with a time-domain boundary integral equation. The scattering solution is obtained iteratively using a boundary element method with constant spatial and third-order temporal basis functions. Time-domain boundary integral equations are unfortunately prone to numerical instabilities due to resonant frequencies resulting from non-trivial solutions in the interior domain. When reformulated with the Burton-Miller method, the instabilities are eliminated. Using a Burton-Miller reformulation, the stability of the boundary element method assuming a liner boundary condition is assessed using eigenvalue analysis. The stability of each liner model is discussed, and it is shown that the Three-Parameter and Broadband models are sufficient for modeling an acoustic liner on the surface of scattering bodies. The Helmholtz model demonstrates strict limitations for stability, whereas the Three-Parameter and Broadband models are stable for most cases. Also included in this work is an assessment of the spatial accuracy of the time-domain boundary element method with respect to the surface element basis functions, as well as a performance study of the numerical algorithm.

computational mathematics↗
DOE OSTI2024

Creep and Creep Fracture Modeling with Surrogate Creep Models and the Extended Finite Element Method

Alloy components in advanced nuclear reactors will be subjected to environmental conditions that could include high temperatures, irradiation, and exposure to corrosive salts. These conditions could lead to the formation of crack-like defects, which could grow over time in a mechanism known as creep crack growth (CCG). Predicting growth rates of these defects is important for assessing the safe operating life of advanced reactors. This project documents progress toward developing and testing next-generation data-driven constitutive models for deformation creep. It also documents the application of the extended finite element method in conjunction with surrogate creep models to predict CCG parameters under a variety of conditions. These important incremental developments contribute to the longer-term objective of developing microstructure-aware constitutive models that can be used for predicting creep deformation and CCG at the component scale with improved accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Automated Gold Nanorod Spectral Morphology Analysis Pipeline

The development of a colloidal synthesis procedure to produce nanomaterials with high shape and size purity is often a time-consuming, iterative process. This is often due to quantitative uncertainties in the required reaction conditions and the time, resources, and expertise intensive characterization methods required for quantitative determination of nanomaterial size and shape. Absorption spectroscopy is often the easiest method for colloidal nanomaterial characterization. However, due to the lack of a reliable method to extract nanoparticle shapes from absorption spectroscopy, it is generally treated as a more qualitative measure for metal nanoparticles. This work demonstrates a gold nanorod (AuNR) spectral morphology analysis tool, called AuNR-SMA, which is a fast and accurate method to extract quantitative structural information from colloidal AuNR absorption spectra. To demonstrate the practical utility of this model, we apply it to three distinct applications. First, we demonstrate this model's utility as an automated analysis tool in a high-throughput AuNR synthesis procedure by generating quantitative size information from optical spectra. Second, we use the predictions generated by this model to train a machine learning model to predict the resulting AuNR size distributions under specified reaction conditions. Third, we apply this model to spectra extracted from the literature where no size distributions are reported and impute unreported quantitative information on AuNR synthesis. This approach can potentially be extended to any other nanocrystal system where absorption spectra are size dependent, and accurate numerical simulation of absorption spectra is possible. In addition, this pipeline could be integrated into automated synthesis apparatuses to provide interpretable data from simple measurements, help explore the synthesis science of nanoparticles in a rational manner, or facilitate closed-loop workflows.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials Using MALAMUTE

Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy, aims to develop and qualify additively-manufactured materials for nuclear applications. The key challenges to these efforts are the microstructural variabilities observed on the AM products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-through-put experimental and modeling techniques to accelerate the qualification efforts. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the AM process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture the microstructural variabilities is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning modeling capabilities to develop a digital twin for AM that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation for AM materials. The melting and subsequent solidification that occurs during the AM process is a complex phenomenon that requires multiscale multiphysics analysis. Idaho National Laboratory’s (INL) Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for AM materials in an efficient, reliable, and cost-effective way. This work package focuses on understanding the role of process variabilities on the various microstructural characteristics of the AM materials. Microstructures unique to AM materials, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. In fiscal year (FY) 24, we significantly advanced upon our work in the last fiscal year, both on physics-based and ML models. The alloy solidification model available in MOOSE has been extended to incorporate the thermodynamic properties and free energy relevant to 316SS. The model demonstrates the Cr segregation that occurs during solidifcation. It is demonstrated that rate of solidification and solute segregation is primarily influence by the cooling rate dictating the level of freezing. This work captures the microstructural variabilities at the subgrain level that are often missing in the part-scale models. With an aim to connect the microstructural evolution model to realistic process conditions, a reduced order model is developed for predicting the thermal conditions around meltpool from high-fidelity process simulations. Furthermore, machine learning approach is used to accelerate the temperature prediction during the AM process. In the following years, MALAMUTE will be used to connect different aspects of the models and quantitatively predict the microstructural evolution. The developed ML-based surrogate model will consider the process conditions as the input to predict the microstructural features in a cost-effective way. The generated microstructures can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work help identify the key microstructural features at the subgrain level that are significant in property/performance prediction of the AM products. This work will provide inputs to the large-scale process variability models to reevaluate and validate assumptions/simplifications made in the part-scale models. Furthermore, through active learning this work will help identify the data need from both modeling and experimental sides for development of a robust digital twin for AM.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Performance Comparison Between NiH2 Dry Sinter and Slurry Electrode Cells

The electrical and thermal performance of dry sinter and slurry process electrode cells manufactured for the Hubble Space Telescope (HST) batteries have been characterized for a matrix of operating conditions over the temperature range from 14 to 86 F at various charge control levels. The dry sinter process electrode cells tested are similar to the onboard HST NiH2 cells. The slurry process electrode cells were developed to be less susceptible to electrode expansion and impedance changes with life. Both cell types were impregnated by the aqueous electrochemical process. Test conditions included standard capacity tests and electrical cycling using 96-minute cycling regimens incorporating gr depth-of-discharge (DOD) cycles. The dry sinter process electrodes have higher operating capacities to 1.20V/cell, but both electrode types have similar heat dissipation for the conditions tested. The results of the testing included cyclic heat generation during a typical 96-minute cycle, operating capacity data vs. cutoff voltage to generate a temperature-compensated voltage curve, and voltage characteristics suitable to develop a voltage prediction model. Analysis of data shows differences in the discharge voltage plateaus operating conditions evaluated. This is the basis for recommended changes in the battery charge control.

Armantrout, J. D.↗
DOE OSTI2025

Policy support and technology development trajectory for renewable natural gas in the U.S.

Renewable natural gas (RNG) is a clean alternative to fossil natural gas, which can be used as transportation fuel, among other applications. This study projects the development trajectory of RNG and evaluates its impacts on the future U.S. transportation market using a hybrid computable general equilibrium model. This analysis considers various factors and uncertainties affecting RNG production, such as technology development, market conditions, competition with other advanced biofuels, and national and state policies. In 2050, RNG production will grow to 2.7 billion gallons (10 billion liters), mostly from swine manure, under current policy provisions. This will lead to a reduction in greenhouse gas (GHG) emissions by 58.56 million metric tonne of CO 2e in 2050. Analysis of different technology cases finds RNG from animal manure to be predominant, while RNG from corn stover and cellulosic ethanol are less competitive. Furthermore, a high mandatory target of 1 billion gallons will drive RNG production higher by 8–18 %, while an extended 2 nd -generation biofuel production tax credit will mostly increase cellulosic ethanol production. The model also finds RNG production being affected by uncertainties in market conditions, such as GDP growth, fossil fuel prices, and oil and gas supply.

Biomethane↗
NASA NTRS2017

Optimization Routine for Generating Medical Kits for Spaceflight Using the Integrated Medical Model

The Integrated Medical Model (IMM) is a MATLAB model that provides probabilistic assessment of the medical risk associated with human spaceflight missions.Different simulations or profiles can be run in which input conditions regarding both mission characteristics and crew characteristics may vary. For each simulation, the IMM records the total medical events that occur and “treats” each event with resources drawn from import scripts. IMM outputs include Total Medical Events (TME), Crew Health Index (CHI), probability of Evacuation (pEVAC), and probability of Loss of Crew Life (pLOCL).The Crew Health Index is determined by the amount of quality time lost (QTL). Previously, an optimization code was implemented in order to efficiently generate medical kits. The kits were optimized to have the greatest benefit possible, given amass and/or volume constraint. A 6-crew, 14-day lunar mission was chosen for the simulation and run through the IMM for 100,000 trials. A built-in MATLAB solver, mixed-integer linear programming, was used for the optimization routine. Kits were generated in 10% increments ranging from 10%-100% of the benefit constraints. Conditions wheremass alone was minimized, volume alone was minimized, and where mass and volume were minimizedjointly were tested.

Medical Kit↗