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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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NASA NTRS1989

First incremental buy for Increment 2 of the Space Transportation System (STS)

Thiokol manufactured and delivered 9 flight motors to KSC on schedule. All test flights were successful. All spent SRMs were recovered. Design, development, manufacture, and delivery of required transportation, handling, and checkout equipment to MSFC and to KSC were completed on schedule. All items of data required by DPD 400 were prepared and delivered as directed. In the system requirements and analysis area, the point of departure from Buy 1 to the operational phase was developed in significant detail with a complete set of transition documentation available. The documentation prepared during the Buy 1 program was maintained and updated where required. The following flight support activities should be continued through other production programs: as-built materials usage tracking on all flight hardware; mass properties reporting for all flight hardware until sample size is large enough to verify that the weight limit requirements were met; ballistic predictions and postflight performance assessments for all production flights; and recovered SRM hardware inspection and anomaly identification. In the safety, reliability, and quality assurance area, activities accomplished were assurance oriented in nature and specifically formulated to prevent problems and hardware failures. The flight program to date has adequately demonstrated the success of this assurance approach. The attention focused on details of design, analysis, manufacture, and inspection to assure the production of high-quality hardware has resulted in the absence of flight failures. The few anomalies which did occur were evaluated, design or manufacturing changes incorporated, and corrective actions taken to preclude recurrence.

Source record↗

DOE OSTI2025

Novel Preprocessing Techniques for Enhancing Flowability of Miscanthus

Purpose-grown energy crops possess significant potential as promising feedstocks for biofuel and biochemical production. However, similar to other biomass feedstocks, their utilization has been hindered by handling and feeding challenges such as clogging and segregation, which prevent biorefineries from operating at full capacity. These challenges arise primarily due to particle attributes including irregular shape, high flexibility, and high compressibility, leading to interlocking, high compaction, and significant friction under stress consolidation. To enhance operational reliability, it is crucial to focus on preprocessing techniques to address these issues, alongside accurately characterizing the mechanical and physical properties and flow performance of these feedstocks. This study investigates novel preprocessing techniques, including pelletization and torrefaction, to fundamentally alter these particle attributes and improve flowability. Miscanthus, an herbaceous energy crop, was the primary focus of this study. Samples were processed using a Forest Concepts Crumbler rotary shear system and an oscillating multi-stack screen bed to achieve two nominal (baseline) particle sizes: 6mm and 2mm. The study evaluated the efficiency and energy consumption of size reduction, revealing that while 2mm particles required more energy, they exhibited better flowability and higher yield strength compared to 6mm particles. Shear and compression tests assessed the material's shear strength, internal friction, and elastic modulus, while wedge-shaped hopper tests measured the critical arching distance and mass flow rate. The results provide valuable insights into the mechanical properties and processing efficiency of Miscanthus, contributing to the development of a preprocessing framework that enhances energy efficiency and material flowability in bioenergy production. However, further preprocessing and development are required to optimize this framework fully.

09 - BIOMASS FUELS↗

NASA NTRS1961

An Automatic Terminal Guidance System for Rendezvous with a Satellite

This study includes a consideration of the design philosophy for an automatic terminal guidance system, a derivation of guidance equations required, and an outline of the general type of instrumentation necessary to provide the essential information. A control system for a sample vehicle is analyzed. A representative case, rendezvous with a satellite in circular orbit at 400 nautical miles, was examined. Terminal-stage nominal burning times of 200 and 400 seconds were used. For the 200-second case, initial errors in circumferential displacement of +/- 25,000 feet, in radial displacement of 7,000 to -9,000 feet, and in lateral displacement of +/- 20,000 feet were within the capabilities of the system. Velocity errors of 300 to -400 ft/sec in the circumferential direction, 180 to -200 ft/sec in the radial direction, and velocity offsets of at least 20 (+/- 800 ft/sec) in the lateral direction could also be handled. The 400-second case was capable of correcting larger errors, but limits were not determined. The dependence of required characteristic velocity on initial errors was determined and it was found that increases over the nominal terminal-stage characteristic velocity of the order of 15 percent covered most of the previously mentioned in-plane errors. The requirements were more severe for cases with lateral velocity offsets. A simplified set of guidance equations was tested and produced only slight variations in performance. Overall velocity requirements and mass ratios were determined for terminal-stage burning times of 100, 200, 300, and 400 seconds and for a range of transfer angles by using exact calculations for the terminal stage and an impulsive launching velocity. These results indicated that the shortest burning time consistent with the launch guidance errors expected gave the best mass ratio.

Carney, Terrance M.↗

DOE OSTI2024

Efficient mapping between void shapes and stress fields using Deep Convolutional Neural Networks with sparse data

Establishing fast and accurate structure-to-property relationships is an important component in the design and discovery of advanced materials. Physics-based simulation models like the finite element method (FEM) are often used to predict deformation, stress, and strain fields as a function of material microstructure in material and structural systems. Such models may be computationally expensive and time intensive if the underlying physics of the system is complex. This limits their application to solve inverse design problems and identify structures that maximize performance. In such scenarios, surrogate models are employed to make the forward mapping computationally efficient to evaluate. However, the high dimensionality of the input microstructure and the output field of interest often renders such surrogate models inefficient, especially when dealing with sparse data. Deep convolutional neural network (CNN) based surrogate models have shown great promise in handling such high-dimensional problems. In this paper, a single ellipsoidal void structure under a uniaxial tensile load represented by a linear elastic, high-dimensional and expensive-to-query, FEM model. We consider two deep CNN architectures, a modified convolutional autoencoder framework with a fully connected bottleneck and a UNet CNN, and compare their accuracy in predicting the von Mises stress field for any given input void shape in the FEM model. Additionally, a sensitivity analysis study is performed using the two approaches, where the variation in the prediction accuracy on unseen test data is studied through numerical experiments by varying the number of training samples from 20 to 100.

surrogate modeling; convolutional neural networks;↗

NASA NTRS2009

Self-Supervised Learning of Terrain Traversability from Proprioceptive Sensors

Robust and reliable autonomous navigation in unstructured, off-road terrain is a critical element in making unmanned ground vehicles a reality. Existing approaches tend to rely on evaluating the traversability of terrain based on fixed parameters obtained via testing in specific environments. This results in a system that handles the terrain well that it trained in, but is unable to process terrain outside its test parameters. An adaptive system does not take the place of training, but supplements it. Whereas training imprints certain environments, an adaptive system would imprint terrain elements and the interactions amongst them, and allow the vehicle to build a map of local elements using proprioceptive sensors. Such sensors can include velocity, wheel slippage, bumper hits, and accelerometers. Data obtained by the sensors can be compared to observations from ranging sensors such as cameras and LADAR (laser detection and ranging) in order to adapt to any kind of terrain. In this way, it could sample its surroundings not only to create a map of clear space, but also of what kind of space it is and its composition. By having a set of building blocks consisting of terrain features, a vehicle can adapt to terrain that it has never seen before, and thus be robust to a changing environment. New observations could be added to its library, enabling it to infer terrain types that it wasn't trained on. This would be very useful in alien environments, where many of the physical features are known, but some are not. For example, a seemingly flat, hard plain could actually be soft sand, and the vehicle would sense the sand and avoid it automatically.

Bajracharya, Max↗

NASA NTRS2025

Single Integrated Flux Files to Account for Spacecraft Attitude Motion in Meteoroid Risk Assessments Using the NASA MEM3 and Bumper Codes

Spacecraft meteoroid risk assessments can be performed using NASA’s Meteoroid Engineering Model 3 (MEM3) and the Bumper risk assessment code. The MEM3 meteoroid flux is highly directional in heliocentric space. To represent the directionality, MEM3 outputs the flux in commonly used coordinate frames. For example, if a spacecraft attitude is fixed in the orbital tangential frame, a single Bumper run using the MEM3 flux file in the body-fixed frame can be performed. Cases exist in which the spacecraft does not remain fixed in one of these frames during a mission. This could be handled by performing a series of Bumper runs at points along the trajectory. For each trajectory point, the spacecraft has to be rotated into the frame in which the MEM3 flux file is defined. Another option presented here is to generate a single integrated flux (SIF) file. A SIF file is an average over a trajectory of the time varying MEM3 flux files rotated from their native frame into the spacecraft bus frame. A SIF file enables accounting for spacecraft rotation (coupled with flux variation over the trajectory) in a single Bumper run. An example of an application of SIF files is the meteoroid risk assessment for the Mars Sample Return (MSR) campaign Capture Containment and Return System (CCRS). This report discusses how SIF files were generated for the CCRS risk assessment and presents metrics on the accuracy of the impinging fluence that is generated when using the files. The results show a maximum difference per element in a finite element model within 1 percent for seven of the eight examined cases, with the outlier being less than 2 percent. The results also show that the maximum standard deviation of differences across all elements is within 0.275 percent. The maximum difference in the total fluence across all the elements is 0.0463 percent. The maximum difference in the mean fluence across all the elements is 0.0407 percent.

Meteoroids↗

NASA NTRS2002

Following the water, the new program for Mars exploration

In the wake of the loss of Mars Climate Orbiter and Mars Polar Lander in late 1999, NASA embarked on a major review of the failures and subsequently restructured all aspects of what was then called the Mars Surveyor Program--now renamed the Mars Exploration Program. This paper presents the process and results of this reexamination and defines a new approach which we have called "Program System Engineering". Emphasis is given to the scientific, technological, and programmatic strategies that were used to shape the new Program. A scientific approach known as "follow the water" is described, as is an exploration strategy we have called "seek--in situ--sample". An overview of the mission queue from continuing Mars Global Surveyor through a possible Mars Sample Return Mission launch in 2011 is provided. In addition, key proposed international collaborations, especially those between NASA, CNES and ASI are outlined, as is an approach for a robust telecommunications infrastructure. c2002 Published by Elsevier Science Ltd.

Water↗

DOE OSTI2025

An implementation of neural simulation-based inference for parameter estimation in ATLAS

Neural simulation-based inference (NSBI) is a powerful class of machine-learning-based methods for statistical inference that naturally handles high-dimensional parameter estimation without the need to bin data into low-dimensional summary histograms. Such methods are promising for a range of measurements, including at the Large Hadron Collider, where no single observable may be optimal to scan over the entire theoretical phase space under consideration, or where binning data into histograms could result in a loss of sensitivity. This work develops a NSBI framework for statistical inference, using neural networks to estimate probability density ratios, which enables the application to a full-scale analysis. It incorporates a large number of systematic uncertainties, quantifies the uncertainty due to the finite number of events in training samples, develops a method to construct confidence intervals, and demonstrates a series of intermediate diagnostic checks that can be performed to validate the robustness of the method. As an example, the power and feasibility of the method are assessed on simulated data for a simplified version of an off-shell Higgs boson couplings measurement in the four-lepton final states. This approach represents an extension to the standard statistical methodology used by the experiments at the Large Hadron Collider, and can benefit many physics analyses.

frequentist statistics↗

NASA NTRS2003

Infrared Database for Process Support Materials

Process support materials' compatibility with cleaning processes is critical to ensure final hardware cleanliness and that performance requirements are met. Previous discovery of potential contaminants in process materials shows the need for incoming materials testing and establishment of a process materials database. The Contamination Control Team of the Materials, Processes, and Manufacturing (MP&M) Department at Marshall Space Flight Center (MSFC) has initiated the development of such an infrared (IR) database, called the MSFC Process Materials IR database, of the common process support materials used at MSFC. These process support materials include solvents, wiper cloths, gloves, bagging materials, etc. Testing includes evaluation of the potential of gloves, wiper cloths, and other items to transfer contamination to handled articles in the absence of solvent exposure, and the potential for solvent exposure to induce material degradation. This Technical Memorandum (TM) summarizes the initial testing completed through December 2002. It is anticipated that additional testing will be conducted with updates provided in future TMs.Materials were analyzed using two different IR techniques: (1) Dry transference and (2) liquid extraction testing. The first of these techniques utilized the Nicolet Magna 750 IR spectrometer outfitted with a horizontal attenuated total reflectance (HATR) crystal accessory. The region from 650 to 4,000 wave numbers was analyzed, and 50 scans were performed per IR spectrum. A dry transference test was conducted by applying each sample with hand pressure to the HATR crystal to first obtain a spectrum of the parent material. The material was then removed from the HATR crystal and analyzed to determine the presence of any residues. If volatile, liquid samples were examined both prior to and following evaporation.The second technique was to perform an extraction test with each sample in five different solvents.Once the scans were complete for both the dry transference and the extraction tests, the residue from each scan was interpreted.

Bennett, K. E.↗

NASA NTRS2010

Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Verification

This paper is focused on applying Monte Carlo simulation to probabilistic launch vehicle design and requirements verification. The approaches developed in this paper can be applied to other complex design efforts as well. Typically the verification must show that requirement "x" is met for at least "y" % of cases, with, say, 10% consumer risk or 90% confidence. Two particular aspects of making these runs for requirements verification will be explored in this paper. First, there are several types of uncertainties that should be handled in different ways, depending on when they become known (or not). The paper describes how to handle different types of uncertainties and how to develop vehicle models that can be used to examine their characteristics. This includes items that are not known exactly during the design phase but that will be known for each assembled vehicle (can be used to determine the payload capability and overall behavior of that vehicle), other items that become known before or on flight day (can be used for flight day trajectory design and go/no go decision), and items that remain unknown on flight day. Second, this paper explains a method (order statistics) for determining whether certain probabilistic requirements are met or not and enables the user to determine how many Monte Carlo samples are required. Order statistics is not new, but may not be known in general to the GN&C community. The methods also apply to determining the design values of parameters of interest in driving the vehicle design. The paper briefly discusses when it is desirable to fit a distribution to the experimental Monte Carlo results rather than using order statistics.

Hanson, John M.↗

NASA NTRS2003

Planetary protection and the search for life beneath the surface of Mars

The search for traces of extinct and extant life on Mars will be extended to beneath the surface of the planet. Current data from Mars missions suggesting the presence of liquid water early in Mars' history and mathematical modeling of the fate of water on Mars imply that liquid water may exist deep beneath the surface of Mars. This leads to the hypothesis that life may exist deep beneath the Martian surface. One possible scenario to look for life on Mars involves a series of unmanned missions culminating with a manned mission drilling deep into the Martian subsurface (approximately 3Km), collecting samples, and conducting preliminary analyses to select samples for return to earth. This mission must address both forward and back contamination issues, and falls under planetary protection category V. Planetary protection issues to be addressed include provisions stating that the inevitable deposition of earth microbes by humans should be minimized and localized, and that earth microbes and organic material must not contaminate the Martian subsurface. This requires that the drilling equipment be sterilized prior to use. Further, the collection, containment and retrieval of the sample must be conducted such that the crew is protected and that any materials returning to earth are contained (i.e., physically and biologically isolated) and the chain of connection with Mars is broken. c2002 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

NASA Discipline Exobiology↗

DOE OSTI2025

Risk Assessment in a Chemical Laboratory Following an Explosive Incident Involving a Novel Diazonium Compound: Retrospective Analysis and Lessons Learned

Diazonium compounds are synthetically useful in the production of dyes and textiles, however they are highly explosive under dry conditions. Explosion prevention becomes more difficult when new diazonium compounds are synthesized, because while some syntheses include a counterion to increase their stability, this is not always a reliable method to prevent an explosive incident. Due to the uncertainty surrounding the explosiveness of different diazonium compounds, it is important to understand how to safely clean up after an incident and how to determine when it is safe to return a laboratory to typical operational use, particularly when the incident involves a novel compound where a standard does not exist for instrument calibration. Here, an explosive event is discussed involving the synthesis of 4-bromo-benzenediazonium-2-carboxylate. Following the explosive incident and 3-step cleanup, which involved a precautionary neutralization step, samples were collected from the fume hood where the incident occurred. Because the incident involved an unstable, novel compound that is not commercially available and was deemed unsafe to resynthesize for instrument calibration, we assessed the risk of further explosion by analyzing for the stable decomposition products. Mass spectrometry analysis confirmed that the residue in the fume hood contained 5-bromosalicylic acid, a decomposition product of 4-bromo-benzenediazonium-2-carboxylate. Samples were taken from multiple points in the fume hood and analyzed to estimate the spatial distribution of the decomposition product. Based on this analysis, we inferred that the primary decomposition product was far more abundant than residual energetic, indicating the energetic had been consumed or neutralized to a trace quantity where the risk of further explosion was low. Furthermore, the steps presented here─specifically, initial neutralization and then analyzing the spatial distribution of expected decomposition products to assess risk when a novel explosive material is detonated in a confined space─were our approach to assess further risk following an explosion due to a novel diazonium compound without the need for any further handling or resynthesis of the energetic. Here, we present our approach and critically analyze these steps by discussing retrospective lessons learned and alternative analytical approaches.

Computer simulations↗

NASA NTRS2020

Dynamic Modeling, Simulation, and Analysis of Orbiting Sample Capture for Potential Mars Sample Return

The current notional architecture for the Mars Sample Return (MSR) campaign would require autonomous on-orbit rendezvous and capture of a sample container after it has been delivered to Mars orbit by a preceding MSR mission. As part of the complete orbital payload known as the Capture, Contain, and Return System (CCRS), a concept has been developed for autonomously sensing and capturing this Orbiting Sample (OS) container. The concept, comprised of a capture mechanism and multiple optical break-beam arrays, would detect and enclose the OS into CCRS, and engage a dust-tight seal to prevent the escape of the OS or other unsterilized particles. A challenging goal for the system is to close the lid prior to the OS coming into physical contact after entering CCRS in order to reduce the risk of unsterilized Mars particles on the surface of the OS from contaminating the outside of the spacecraft. The mechanical and sensor performance requirements were driven by the broader architecture of CCRS, OS rendezvous parameters, and Planetary Protection requirements regarding the interaction and handling of the OS. The mechanism and break-beam array concepts were designed accordingly, and kinematic simulations of the mechanism’s behavior, combined with a Monte-Carlo simulation of OS rendezvous/collision behaviors and corresponding breakbeam sensor responses verify compliance.

Ishigo, Alyssa↗

NASA NTRS2003

Sensory characterization of a ready-to-eat sweetpotato breakfast cereal by descriptive analysis

The sweetpotato [Ipomoea batatas (L.) Lam], an important industry in the United States, has been selected as a candidate crop to be grown on future long-duration space missions by NASA. Raw sweetpotato roots were processed into flour, which was used to formulate ready-to-eat breakfast cereal (RTEBC). Twelve trained panelists evaluated the sensory attributes of the extruded RTEBC using descriptive analysis. The samples were significantly different (P<0.05) for all attributes. Twelve perceived sensory attributes, which could be used to differentiate the appearance, texture, and flavor of sweetpotato RTEBC, were described. The data could be used to optimize the RTEBC and for designing studies to test its consumer acceptance.

NASA Discipline Life Support Systems↗

NASA NTRS2021

Trend Detection of Atmospheric Time Series: Incorporating Appropriate Uncertainty Estimates and Handling Extreme Events

This paper is aimed at atmospheric scientists without formal training in statistical theory. Its goal is to, 1) provide a critical review of the rationale for trend analysis of the time series typically encountered in the field of atmospheric chemistry; 2) describe a range of trend-detection methods; and 3) demonstrate effective means of conveying the results to a general audience. Trend detections in atmospheric chemical composition data are often challenged by a variety of sources of uncertainty, which often behave differently to other environmental phenomena such as temperature, precipitation rate, or stream flow, and may require specific methods depending on the science questions to be addressed. Some sources of uncertainty can be explicitly included in the model specification, such as autocorrelation and seasonality, but some inherent uncertainties are difficult to quantify, such as data heterogeneity and measurement uncertainty due to the combined effect of short- and long-term natural variability, instrumental stability, and aggregation of data from sparse sampling frequency. Failure to account for these uncertainties might result in an inappropriate inference of the trends and their estimation errors. On the other hand, the variation in extreme events might be interesting for different scientific questions, for example, the frequency of extremely high surface ozone events and their relevance to human health. In this study we aim to, 1) review trend detection methods for addressing different levels of data complexity in different chemical species; 2) demonstrate that the incorporation of scientifically interpretable covariates can outperform pure numerical curve fitting techniques in terms of uncertainty reduction and improved predictability; 3) illustrate the study of trends based on extreme quantiles that can provide insight beyond standard mean or median based trend estimates; and 4) present an advanced method of quantifying regional trends based on the inter-site correlations of multi-site data. All demonstrations are based on time series of observed trace gases relevant to atmospheric chemistry, but the methods can be applied to other environmental data sets.

Trace gas↗

DOE OSTI2024

Hyper‐Local Temperature Prediction Using Detailed Urban Climate Informatics

The accurate modeling of urban microclimate is a challenging task given the high surface heterogeneity of urban land cover and the vertical structure of street morphology. Recent years have witnessed significant efforts in numerical modeling and data collection of the urban environment. Nonetheless, it is difficult for the physical‐based models to fully utilize the high‐resolution data under the constraints of computing resources. The advancement in machine learning (ML) techniques offers the computational strength to handle the massive volume of data. In this study, we proposed a modeling framework that uses ML approach to estimate point‐scale street‐level air temperature from the urban‐resolving meso‐scale climate model and a suite of hyper‐resolution urban geospatial data sets, including three‐dimensional urban morphology, parcel‐level land use inventory, and weather observations from a sensor network. We implemented this approach in the City of Chicago as a case study to demonstrate the capability of the framework. The proposed approach vastly improves the resolution of temperature predictions in cities, which will help the city with walkability, drivability, and heat‐related behavioral studies. Moreover, we tested the model's reliability on out‐of‐sample locations to investigate the modeling uncertainties and the application potentials to the other areas. This study aims to gain insights into next‐gen urban climate modeling and guide the observation efforts in cities to build the strength for the holistic understanding of urban microclimate dynamics.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Higher Order Modeling In the BEM/FEM Hybrid Formulation

Hybrid formulations using low order curl-conforming bases to represent the total electric field within a finite element region and low order divergence-conforming bases to represent equivalent electric and magnetic currents on the boundary are well known. However, higher-order divergence and curl-conforming bases have been shown to provide significant benefits in convergence rates and accuracy when employed in strictly integral equation and strictly finite element formulations. In this paper, a hybrid electric field formulation employing higher order bases is presented. The paper addresses benefits and issues associated with using higher order divergence-and curl-conforming bases in the hybrid finite element/boundary element electric field formulation. The method of singularity subtraction may be used to compute the self terms of the boundary integral when the bases are of low order. But this method becomes laborious and requires great care when the divergence conforming bases are of higher order. In order to handle these singularities simply and accurately, a generalized Gaussian quadrature method is employed in which the expansion functions account for the singularity. In preliminary tests of the higher order hybrid formulation, the equivalent electric current induced by scattering of a plane wave from a square dielectric cylinder is examined. Accurate results are obtained using only a two-triangle mesh when the current basis is of order 4 or 5. Additional results are presented comparing the error obtained using higher order bases to that obtained using lower order bases when the number of unknowns is approximately equal. Also, convergence rates obtained with higher order bases are compared to those obtained with lower order bases for selected sample problems.

Fink, Patrick W.↗

DOE OSTI2025

Storage-Induced Collapse of Lignin Macromolecular Structure and Its Impacts on the Biorefinery

Lignin plays a vital role in the economics of biorefineries, serving as a source of process energy and a feedstock for sustainable fuels and chemical production. While understanding lignin’s chemical composition is crucial, emerging evidence suggests that a more comprehensive understanding of its macromolecular structure is critical to explaining its complex behavior in the biorefinery. This study investigated the partial collapse of the lignin network in corn stover feedstock after harvest and storage as a result of the microbial digestion of hemicellulose. Fluorescence microscopy was used to detect the collapse of lignin in terms of lignin’s inter-molecular interaction and the re-orientation of lignin’s chromophores, by the changes in lignin’s fluorescence lifetime, anisotropy, and the number of effective emitters. With minimal sample perturbation, our in-situ microscopic results revealed lignin's coil-globule transition phenomena, which was only previously predicted by molecular dynamics modeling extracted lignin in solvent. This collapse of lignin macromolecular structure was confirmed by results from NMR, IR, Raman, and powder X-ray diffraction. We also investigated the impact of this storage-induced collapse on the downstream biorefinery processes. Our study revealed that the two major approaches for lignin valorization in the lignin-first biorefinery model, namely monomer extraction and milled wood lignin extraction, were negatively impacted by the lignin collapse. As changes during storage are a source of feedstock variability, our study highlights the importance of understanding the effect of feedstock handling on biorefinery operations and economics.

09 BIOMASS FUELS↗