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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Towards Quantifying and Correlating RTV Intumescence to Entry-Relevant Conditions

Room Temperature Vulcanizing silicone (RTV) is a high-temperature adhesive used as a gap-filler between Thermal Protection System (TPS) tiles for heatshields on numerous missions. It is also adopted to bond instrumentation plugs of temperature and pressure sensors into heatshield’s tiles. While RTV has been traditionally assumed to be a non-porous and non-ablating material, numerous experiments have shown that RTV pyrolyzes and becomes highly porous as it is heated. Experimental data has also shown heating rate-dependent swelling (or intumescence) and shrinking of RTV, these volume changes may cause roughness-induced boundary layer transition. Outgassing and surface oxide formation of RTV upon decomposition also occur, which can be sources of contamination of heat shield sensors. This combination of detrimental effects motivates a critical need to develop a high-fidelity model for RTV ablation. As a first critical step in RTV modeling, a comprehensive material properties database for RTV was collected that account for the lack of data in properties such as pyrolysis char yield, shape change, virgin and char porosity. The next step is to quantify the volume change of RTV as a function of temperature. While this was done in previous campaigns, limited data was collected which showed a possible heating rate dependent intumescent behavior. To further understand the intumescence phenomenon of RTV, numerous dedicated experiments were performed at Beamline 8.3.2 of the Advanced Light Source, where RTV samples were heated while X-ray scans were taken in situ. Micro-Computed Tomography scans were taken in situ for low heating rates (≤ 60 °C/min), whereas continuous radiography scans were taken for higher heating rates (≤ 1500 ºC/min). Unconstrained samples and samples constrained in different holders (quartz, graphite, FiberForm and PICA) were tested to determine the change in intumescence due to confinement. Using deep learning techniques, the tomographies and radiographies are segmented to obtain volume change, porosity, pore size distributions and connectivity. From the results obtained, modifications to the previous RTV intumescence model are proposed, along with preliminary comparisons to testing RTV at high-enthalpy facilities.

RTV↗
NASA NTRSDate not supplied

Thermostructural Testing of PICA-D for NASA Planetary Science Missions

Phenolic Impregnated Carbon Ablator–Domestic (PICA‑D) has been selected as the heatshield thermal protection system (TPS) material for two upcoming NASA planetary science missions: the Dragonfly mission to Titan and the Mars Sample Retrieval Lander (SRL). Early testing revealed differences between PICA‑D and heritage PICA, particularly in in‑plane (IP) tensile stiffness and thermal expansion. Thermostructural analyses using Finite Element Method (FEM) tools subsequently predicted the potential for IP compressive failure in the near‑surface layers of PICA‑D under both Dragonfly and SRL flight environments. Over the past three years, the Dragonfly and SRL teams have carried out an extensive thermostructural qualification campaign to address these concerns and validate PICA‑D for flight. This effort began with a comprehensive mechanical property characterization program at Kratos test laboratories, which significantly improved understanding of PICA‑D mechanical behavior and increased the fidelity of FEM predictions. The teams also conducted six large‑scale test entries at the National Solar Thermal Test Facility (NSTTF) solar tower, exposing PICA‑D articles—including gap fillers and representative design features or flaws—to combined thermal and mechanical loads. The talk will summarize key findings from these mechanical and thermostructural test campaigns and present the current status of PICA‑D qualification for NASA’s planetary science missions.

TPS↗
DOE OSTI2021

Subsampling and DNA pooling can increase gains through genomic selection in switchgrass

Genomic selection (GS) can accelerate breeding cycles in perennial crops such as the bioenergy grass switchgrass (Panicum virgatum L.). The sequencing costs of GS can be reduced by pooling DNA samples in the training population (TP), only sequencing TP phenotypic outliers, or pooling candidate population (CP) samples. These strategies were simulated for two traits (spring vigor and anthesis date) in three breeding populations. Sequencing only the outlier 50% of the TP phenotype distribution resulted in a penalty of <5% of the predictive ability, measured using cross-validation. Predictive ability also decreased when sequencing progressively fewer TP DNA pools, but TPs constructed from only two phenotypically contrasting DNA samples retained a mean of >80% predictive ability relative to individual TP sequencing. Novel group testing methods allowed greater than one CP individual to be screened per sequenced DNA sample but resulted in a predictive ability penalty. To determine the impact of reduced sequencing, genetic gain was calculated for seven GS scenarios with variable sequencing budgets. Reduced TP sequencing and most CP pooling methods were superior to individual sequence-based GS when sequencing resources were restricted (2,000 DNA samples per 5-yr cycle). Only one scenario was superior to individual sequencing when sequencing budgets were large (8,000 DNA samples per 5-yr cycle). This study highlights multiple routes for reduced sequencing costs in GS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation

Abstract We consider the problem of learning the level set for which a noisy black-box function exceeds a given threshold. To efficiently reconstruct the level set, we investigate Gaussian process (GP) metamodels. Our focus is on strongly stochastic simulators, in particular with heavy-tailed simulation noise and low signal-to-noise ratio. To guard against noise misspecification, we assess the performance of three variants: (i) GPs with Student- t observations; (ii) Student- t processes (TPs); and (iii) classification GPs modeling the sign of the response. In conjunction with these metamodels, we analyze several acquisition functions for guiding the sequential experimental designs, extending existing stepwise uncertainty reduction criteria to the stochastic contour-finding context. This also motivates our development of (approximate) updating formulas to efficiently compute such acquisition functions. Our schemes are benchmarked by using a variety of synthetic experiments in 1–6 dimensions. We also consider an application of level set estimation for determining the optimal exercise policy of Bermudan options in finance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Enhanced flexibility and thermal conductivity of HfC decorated carbon nanofiber mats

Future-generation spacecraft components allude discovery of novel materials that can withstand extreme environments (>2000 °C). The combined effect of ultra-high temperature ceramics (UHTCs) and carbon fibers (C f ) can satisfy the demanding requirements of aerospace applications. A novel, hybrid, and flexible hafnium carbide (HfC)-decorated carbon nanofiber (C nf ) mat was fabricated via electrospinning. Enhanced thermal stability of the flexible HfC decorated C nf over C nf can be elucidated from the 20-fold increment in thermal conductivity and the onset of degradation at higher temperatures (840 °C). Successful integration of multi-layered sandwich lattice using in-housed fabricated HfC decorated C nf showed retention of the fibrous structure even after extreme spark plasma sintering (SPS) process at 1850 °C. Fabricating a similar multi-layered structure using procured C f was unsuccessful due to bundled agglomeration and micron-sized fibers. High-load indentation suggests that HfC decorated C nf interlayer is stronger (~2.3 times) than the parent UHTC with no cracking at the interface. Compared with the HfC matrix, the indentation-damaged area at the interface reduced up to ~56% due to toughening mechanisms such as C nf , fiber pull-out and bridging. The synthesized HfC decorated Cnf mat is proposed as an ultra-thin filler material for joining similar or dissimilar UHTCs while maintaining similar chemistry and better mechanical integrity at the interface. Furthermore, the findings insinuate a new paradigm in designing hybrid and flexible ceramic-containing materials for thermal protection systems (TPS) of future-generation spacecraft components that can mitigate failure in extreme environments (>2000 °C).

36 MATERIALS SCIENCE↗
DOE OSTI2022

Pendant Group Modifications Provide Graft Copolymer Silicones with Exceptionally Broad Thermomechanical Properties

Graft copolymers offer a versatile platform for the design of self-assembling materials; however, simple strategies for precisely and independently controlling the thermomechanical and morphological properties of graft copolymers remain elusive. Here, using a library of 92 polynorbornene-graft-polydimethylsiloxane (PDMS) copolymers, we discover a versatile backbone-pendant sequence-control strategy that addresses this challenge. Small structural variations of pendant groups, e.g., cyclohexyl versus n-hexyl, of small-molecule comonomers have dramatic impacts on order-to-disorder transitions, glass transitions, mechanical properties, and morphologies of statistical and block silicone-based graft copolymers, providing an exceptionally broad palette of designable materials properties. For example, statistical graft copolymers with high PDMS volume fractions yielded unbridged body-centered cubic morphologies that behaved as soft plastic crystals. By contrast, lamellae-forming graft copolymers provided robust, yet reprocessable silicone thermoplastics (TPs) with transition temperatures spanning over 160 °C and elastic moduli as high as 150 MPa despite being both unentangled and un-cross-linked. Altogether, this study reveals a new pendant-group-mediated self-assembly strategy that simplifies graft copolymer synthesis and enables access to a diverse family of silicone-based materials, setting the stage for the broader development of self-assembling materials with tailored performance specifications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Standard Characterization Techniques for Inorganic Phase Change Materials

Salt hydrates are promising candidates for phase change materials (PCMs) because of their low cost and high energy storage capacity. However, practical applications of salt hydrate based PCMs are limited due to their poor thermal cycling performance caused by phase separation and supercooling. Various techniques, including differential scanning calorimetry (DSC) and transient plane source (TPS) have been used to characterize salt hydrate based PCMs but may not provide full understanding of the degradation mechanism. In this manuscript, salt hydrate and graphite composites are prepared. Temperature history (T-History) method and X-ray diffraction (XRD) are utilized for measuring melting temperature, energy storage, and latent heat degradation of the PCM composites. Highlighting the importance of each technique and how each technique plays an important role in analyzing salt hydrates performance accurately. Temperature history, and X-ray diffraction are also used in conjunction to precisely predict the cause of degradation in salt hydrate PCMs with thermal cycling, as in most literatures the cause of degradation in salt hydrate are attributed to phase segregation, supercooling, and change in stichometry water concentration without any scientific validation.

Kumar, Navin↗
DOE OSTI2025

Machine Learning-Based Extreme Data Reduction for Prompt Supernova Pointing at DUNE

One of the goals of the Deep Underground Neutrino Experiment (DUNE) is to use the massive underground liquid argon time projection chamber (LArTPC) detectors at its far site for multimessenger astronomy (MMA), in the detection of neutrinos from core-collapse supernovae (SNe). Its current baseline trigger strategy detects activity in the detector that is consistent with supernova (SN) neutrinos and saves the raw data for further offline analysis but provides no prompt pointing information crucial for optical follow-ups by other observatories. This approach is based on the assumption that prompt pointing determination using raw data is computationally prohibitive. In this article, we demonstrate a proof-of-concept based on applying extreme data reduction on the buffered SN data in the DUNE data acquisition (DAQ) system’s front-end computers using a machine learning (ML) workflow. This reduces the data by ~5 orders of magnitude, allowing a full track reconstruction to be carried out quickly on a single server. The total time to perform the ML-based data reduction and the full track reconstruction is less than the time to transfer the SN data back to Fermilab or a high-performance computing (HPC) center. This shows that prompt processing of raw SN data is possible and, in fact, trivial once the data have been reduced to reject radiological backgrounds, paving the way to a high-quality SN pointing trigger that is based on fully reconstructed data instead of trigger primitives (TPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Supporting information for Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

In this work, we use few-shot learning to segment the body and vein architecture of P. trichocarpa leaves from high-resolution scans obtained in the UC Davis common garden. Leaf and vein segmentation are formulated as separate tasks, in which convolutional neural networks (CNNs) are used to iteratively expand partial segmentations until reaching stopping criteria. Our leaf and vein segmentation approaches use just 50 and 8 manually traced images for training, respectively, and are applied to a set of 2,634 top and bottom leaf scans. We show that both methods achieve high segmentation accuracy, in some cases exceeding even human-level segmentation. The leaf and vein segmentations are subsequently used to extract 68 morphological traits using traditional open-source image processing tools, which are validated using real-world physical measurements. For a biological perspective, we perform a genome-wide association study using the vein density trait to discover novel genetic architectures associated with multiple physiological processes relating to leaf development and function. In addition to sharing all of the few-shot learning code (see https://github.com/jlager/few-shot-leaf-segmentation), we are releasing all images, manual segmentations, model predictions, 68 extracted leaf phenotypes, and a new set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes. The data folder includes all images, ground truth segmentations, predicted segmentations, and extracted leaf traits. All images encode the sample ID in the file name by indicating the treatment, block, row, position, and leaf side, respectively. For example, the file, C_1_1_2_bot.jpeg, indicates the control treatment, block 1, row 1, position 2, and the bottom side of the leaf. Tabulated results include position IDs as well as the corresponding genotype IDs. The images folder includes the 2,906 high-resolution leaf scans taken in the field. The leaf_masks folder includes 50 ground truth segmentations used for training the leaf tracing algorithm. The leaf_preds folder includes the 2,906 predicted segmentations from the leaf tracing algorithm. The vein_masks folder includes 8 ground truth segmentations used for training the vein growing algorithm. The vein_preds folder includes the 1,453 predicted segmentations from the vein growing algorithm. The vein_probs folder includes the 1,453 predicted probability maps from the vein growing algorithm before thresholding. The genomes folder includes the set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes with a README file detailing the steps taken. The results folder includes: (i) raw values of the 68 predicted leaf traits in digital_traits.tsv, (ii) manually measured values of petiole length and width in manual_traits.tsv, (iii) thin plate spline (TPS) adjusted values of the vein density trait in vein_density_tps_adj.tsv, (iv) best linear unbiased prediction (BLUP) adjusted values of the vein density trait in vein_density_blups.tsv, and (v) GWAS results for the vein density trait, including chromosome positions and corresponding P values, in gwas_results.csv.

09 BIOMASS FUELS↗
DOE OSTI2022

Metal-Tipped and Electrochemically Wired Semiconductor Nanocrystals: Modular Constructs for Directed Charge Transfer

In our 2017 proposal to the Solar Photochemistry division of DOE/BES/Office of Science we targeted the creation, characterization and integratation of new II-IV semiconductor heterostructured nanomaterials into ultra-thin film (tethered) nanocrystalline arrays on transparent metal oxide (TCO) supports. Materials were to include CdSe quantum dots (QDs), asymmetric CdSe@CdS tetrapods (TPs) and CdSe@CdS nanorods (NRs), into unique photoelectrochemical platforms. The ultimate goal was to tether these new nanomaterials to either electron- or hole-selective oxide interlayers that would afford vectoral photo-induced charge transfer and ultimately formation of molecular products such as H 2 . This was an ambitious set of goals but integrated well with our previous work in this general area.

14 SOLAR ENERGY↗
DOE OSTI2021

Analysis Report documenting the Assessment of the Solubility of Lead, EDTA and other Organic Ligands in non-Sulfide systems performed under TP 08-02 and under TP 20-01

The objective of this report is to accept or reject the hypothesis that the experiments conducted under TP 08-02 Revision 0 (Ismail et al., 2008) were affected by CO 2 (g) intrusion and sample contamination. The test of the hypothesis is accomplished by comparing the experimental data collected under the protocols of TP 08-02 Revision O and TP 20-01 Revision O (Kirkes and Zhang, 2020). The protocols of TP 20-01 Revision 0 minimize the possibilities of CO 2 (g) intrusion and sample contamination. The experimental data sets obtained under both TPs will be assessed statistically to see if they are identical or not.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Path Sampling for Rare Events Boosted by Machine Learning

The study by Jung et al. introduced Artificial Intelligence for Molecular Mechanism Discovery (AIMMD), a novel sampling algorithm that integrates machine learning to enhance the efficiency of transition path sampling (TPS). By enabling on-the-fly estimation of the committor probability and simultaneously deriving a human-interpretable reaction coordinate, AIMMD offers a robust framework for elucidating the mechanistic pathways of complex molecular processes. Here, this commentary provides a discussion and critical analysis of the core AIMMD framework, explores its recent extensions, and offers an assessment of the method’s potential impact and limitations.

Minh, Porhouy [Univ. of Minnesota, Minneapolis, MN↗
DOE OSTI2023

Maize Terpene Synthase 8 (ZmTPS8) Contributes to a Complex Blend of Fungal-Elicited Antibiotics

In maize (Zea mays), fungal-elicited immune responses include the accumulation of terpene synthase (TPS) and cytochrome P450 monooxygenases (CYP) enzymes resulting in complex antibiotic arrays of sesquiterpenoids and diterpenoids, including α/β-selinene derivatives, zealexins, kauralexins and dolabralexins. To uncover additional antibiotic families, we conducted metabolic profiling of elicited stem tissues in mapping populations, which included B73 × M162W recombinant inbred lines and the Goodman diversity panel. Five candidate sesquiterpenoids associated with a chromosome 1 locus spanning the location of ZmTPS27 and ZmTPS8. Heterologous enzyme co-expression studies of ZmTPS27 in Nicotiana benthamiana resulted in geraniol production while ZmTPS8 yielded α-copaene, δ-cadinene and sesquiterpene alcohols consistent with epi-cubebol, cubebol, copan-3-ol and copaborneol matching the association mapping efforts. ZmTPS8 is an established multiproduct α-copaene synthase; however, ZmTPS8-derived sesquiterpene alcohols are rarely encountered in maize tissues. A genome wide association study further linked an unknown sesquiterpene acid to ZmTPS8 and combined ZmTPS8-ZmCYP71Z19 heterologous enzyme co-expression studies yielded the same product. To consider defensive roles for ZmTPS8, in vitro bioassays with cubebol demonstrated significant antifungal activity against both Fusarium graminearum and Aspergillus parasiticus. As a genetically variable biochemical trait, ZmTPS8 contributes to the cocktail of terpenoid antibiotics present following complex interactions between wounding and fungal elicitation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1971

Preliminary vibration design and test criteria considerations for the space shuttle

This paper presents some Marshall Space Flight Center preliminary vibration design and test criteria considerations for the space shuttle. The discussion is primarily concerned with the formulation of vibration criteria for the design and testing of the equipment installations on the shuttle. A recommended criteria format is presented with a discussion of when the vibration environment has to be considered in design and testing. A semiempirical method of predicting the vibration criteria for the shuttle from vibroacoustic structural data banks is presented. Some preliminary vibration criteria predictions are presented for the orbiter and booster equipment bays and for the main shuttle engine. A research testing program to determine the vibroacoustic transfer through a typical shuttle thermal protection system (TPS) panel configuration is described.

Harry J. Bandgren↗