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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 271 records · Page 15

Probabilistic learning and updating of a digital twin for composite material systems

This paper presents an approach for characterizing and estimating statistical dependence between a large number of observables in a composite material system. Conditional regression is carried out using the estimated joint density function, permitting a systematic exploration of interdependence between fine scale and coarse observables that can be used for both prognosis and design of complex material systems. An example demonstrates the integration of experimental data with a computational database. The statistical approach is based on the probabilistic learning on manifolds recently developed by the authors. This approach leverages intrinsic structure detected through diffusion on graphs with projected stochastic differential equations to generate samples constrained to that structure.

42 ENGINEERING↗

CALPHAD Uncertainty Quantification and TDBX

CALPHAD uncertainty quantification (UQ) is the foundation of materials design with quantified confidence. We report a framework and software packages to enable CALPHAD UQ assessment and calculation using commercial CALPHAD software (Thermo-Calc). This Bayesian inference framework is coupled with a Markov chain Monte Carlo algorithm to establish uncertainty traces with a given thermodynamic database file (TDB) and corresponding experimental data points. This general framework is demonstrated with the Ni–Cr binary system. The algorithm is firstly validated on synthetic data with known ground truth. Then it is applied to real experimental data to generate posterior traces. We develop a file format named TDBX, which provides a single source of truth by combining the original TDB content and the traces for each assessed Gibbs energy parameter. CALPHAD UQ calculations are performed based on the TDBX file, from which uncertainties for phase boundaries, enthalpy curves, and solidification range are collected as examples of basic design parameters. This TDBX file with corresponding scripts are made open-source. Finally, the combination of CALPHAD UQ assessments and calculations connected by TDBX supports uncertainty-assisted modeling, enabling the integrated application of modern design with uncertainty methodologies to computational materials design.

36 MATERIALS SCIENCE↗

Augmentation of MS/MS Libraries with Spectral Interpolation for Improved Identification

Tandem mass spectrometry (MS/MS) is a primary tool for identification of small molecules and metabolites where resultant spectra are most commonly identified by matching them with spectra in MS/MS reference libraries. The high degree of variability in MS/MS spectrum acquisition techniques and parameters creates a significant challenge for building standardized reference libraries. Here we present a method to improve the usefulness of existing MS/MS libraries by augmenting available experimental spectra datasets with statistically interpolated spectra at unreported collision energies. We find that highly accurate spectral approximations can be interpolated from as few as three experimental spectra and that the interpolated spectra will be consistent with true spectra gathered from the same instrument as the experimental spectra. Supplementing existing spectral databases with interpolated spectra yields consistent improvements to identification accuracy on a range of instruments and precursor types. Applying this method yields significant improvements (~10% more spectra correctly identified) on large datasets (2,000 - 10,000 spectra), indicating this is a quick yet adept tool for improving spectral matching in situations where available reference libraries are not yet sufficient. We also find improvements of matching spectra across instrument types (between an Agilent Q-TOF and an Orbitrap Elite), at high collision energies (50 - 90 eV), and with smaller datasets available through MassBank.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

First-Principles-Based Study of the Decomposition of Phenol and Hydroquinone on Pt(111) Combined with Quantitative Information from XPS Spectra to Address the Impact of Coverage and Number of Hydroxyl Functional Groups

A combined first-principles-based and experimental X-ray photoelectron spectroscopy approach was used to investigate the thermal decomposition of two model biofuel compounds, phenol and hydroquinone, on Pt(111) at both low and high coverages. The DFT-based approach yields adsorption geometries and energies, activation barriers and core-level binding energy shifts for C 1s and O 1s. Increasing the coverage in the theoretical model leads to slight shifts in core-level binding energies─toward higher values for C 1s and lower values for O 1s. It also alters the energy profiles of the decomposition reaction pathway, resulting in weaker adsorption energies and changes in both reaction and activation barriers. At low temperatures, we observe a multilayer for phenol and hydroquinone upon adsorption, with desorption occurring at 200 and 270 K, respectively. Following desorption of the multilayer, decomposition proceeds via initial O–H bond scission, followed by two parallel pathways involving either C–H or C–C bond scission, whereby in the case of phenol C–H bond scission occurs first. Here, we further provide characteristic core level binding energies by theoretical calculations that are subsequently used in experimental analyses, establishing a reference database for key spectra of phenolic functionalities applicable to a range of catalytic reactions.

09 BIOMASS FUELS↗

BLINK enables ultrafast tandem mass spectrometry cosine similarity scoring

Metabolomics has a long history of using cosine similarity to match experimental tandem mass spectra to databases for compound identification. Here we introduce the Blur-and-Link (BLINK) approach for scoring cosine similarity. By bypassing fragment alignment and simultaneously scoring all pairs of spectra using sparse matrix operations, BLINK is over 3000 times faster than MatchMS, a widely used loop-based alignment and scoring implementation. Using a similarity cutoff of 0.7, BLINK and MatchMS had practically equivalent identification agreement, and greater than 99% of their scores and matching ion counts were identical. This performance improvement can enable calculations to be performed that would typically be limited by time and available computational resources.

47 OTHER INSTRUMENTATION↗

Size distribution of polycyclic aromatic hydrocarbons in space: an old new light on the 11.2/3.3 μm intensity ratio

The intensity ratio of the 11.2/3.3 μm emission bands is considered to be a reliable tracer of the size distribution of polycyclic aromatic hydrocarbons (PAHs) in the interstellar medium (ISM). This paper describes the validation of the calculated intrinsic infrared (IR) spectra of PAHs that underlie the interpretation of the observed ratio. The comparison of harmonic calculations from the NASA Ames PAH IR spectroscopic database to gas-phase experimental absorption IR spectra reveals a consistent underestimation of the 11.2/3.3 μm intensity ratio by 34%. IR spectra based on higher level anharmonic calculations, on the other hand, are in very good agreement with the experiments. While there are indications that the 11.2/3.3 μm ratio increases systematically for PAHs in the relevant size range when using a larger basis set, it is unfortunately not yet possible to reliably calculate anharmonic spectra for large PAHs. Based on these considerations, we have adjusted the intrinsic ratio of these modes and incorporated this in an interstellar PAH emission model. This corrected model implies that typical PAH sizes in reflection nebulae such as NGC 7023 – previously inferred to be in the range of 50 to 70 carbon atoms per PAH are actually in the range of 40 to 55 carbon atoms. The higher limit of this range is close to the size of the C 60 fullerene (also detected in reflection nebulae), which would be in line with the hypothesis that, under appropriate conditions, large PAHs are converted into the more stable fullerenes in the ISM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deep learning-based predictive models for laser direct drive at the Omega Laser Facility

The rich and complex physics of inertial confinement fusion provides a unique and challenging space for high-fidelity first-principles modeling. Consequently, simulation codes that are used to design experiments are computationally expensive and lack the predictive capability required for extensive parameter exploration in search of a high-performing design for laser direct drive. In this article, we present two deep-learning-based predictive models intended to address these difficulties. The first model (TL DNN) acts as a fast emulator of simulations as well as experiments at the Omega Laser Facility. This model is trained on a simulation database and subsequently calibrated on experimental data using transfer learning. To facilitate the development of this model, an autoencoder is developed to reduce the dimensionality of the input space by compressing the laser pulse input. The model predicts key experimental scalar observables of Omega experiments with high accuracy and minimal computational cost. This deep neural net enables rapid exploration of a high-dimensional input parameter space for an optimal implosion design. The second model (DNN SM+) aims to extend the statistical modeling work of Lees et al. [Phys. Rev. Lett. 127, 105001 (2021)], by increasing the complexity of the model space and allowing for coupling between degradation terms. Since the model capacity of DNN SM+ is higher than the model of Lees et al., DNN SM+ can potentially provide an improvement in predictive capability, and we use this model to provide insight into complicated degradation dependencies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Ascent Aerodynamic Pressure Distributions on WB001

To support the reusable launch vehicle concept study, the aerodynamic data and surface pressure for WB001 were predicted using three computational fluid dynamic (CFD) codes at several flow conditions between code to code and code to aerodynamic database as well as available experimental data. A set of particular solutions have been selected and recommended for use in preliminary conceptual designs. These computational fluid dynamic (CFD) results have also been provided to the structure group for wing loading analysis.

Vu, B.↗

Protein Crystal Growth

In order to rapidly and efficiently grow crystals, tools were needed to automatically identify and analyze the growing process of protein crystals. To meet this need, Diversified Scientific, Inc. (DSI), with the support of a Small Business Innovation Research (SBIR) contract from NASA s Marshall Space Flight Center, developed CrystalScore(trademark), the first automated image acquisition, analysis, and archiving system designed specifically for the macromolecular crystal growing community. It offers automated hardware control, image and data archiving, image processing, a searchable database, and surface plotting of experimental data. CrystalScore is currently being used by numerous pharmaceutical companies and academic and nonprofit research centers. DSI, located in Birmingham, Alabama, was awarded the patent Method for acquiring, storing, and analyzing crystal images on March 4, 2003. Another DSI product made possible by Marshall SBIR funding is VaporPro(trademark), a unique, comprehensive system that allows for the automated control of vapor diffusion for crystallization experiments.

Source record↗

Fluorescence Visualization of Hypersonic Flow Past Triangular and Rectangular Boundary-layer Trips

Planar laser-induced fluorescence (PLIF) flow visualization has been used to investigate the hypersonic flow of air over surface protrusions that are sized to force laminar-to-turbulent boundary layer transition. These trips were selected to simulate protruding Space Shuttle Orbiter heat shield gap-filler material. Experiments were performed in the NASA Langley Research Center 31-Inch Mach 10 Air Wind Tunnel, which is an electrically-heated, blowdown facility. Two-mm high by 8-mm wide triangular and rectangular trips were attached to a flat plate and were oriented at an angle of 45 degrees with respect to the oncoming flow. Upstream of these trips, nitric oxide (NO) was seeded into the boundary layer. PLIF visualization of this NO allowed observation of both laminar and turbulent boundary layer flow downstream of the trips for varying flow conditions as the flat plate angle of attack was varied. By varying the angle of attack, the Mach number above the boundary layer was varied between 4.2 and 9.8, according to analytical oblique-shock calculations. Computational Fluid Dynamics (CFD) simulations of the flowfield with a laminar boundary layer were also performed to better understand the flow environment. The PLIF images of the tripped boundary layer flow were compared to a case with no trip for which the flow remained laminar over the entire angle-of-attack range studied. Qualitative agreement is found between the present observed transition measurements and a previous experimental roughness-induced transition database determined by other means, which is used by the shuttle return-to-flight program.

Danehy, Paul M.↗

Pion Nucleon Scattering in BCHPT Combined with 1/Nc Expansion

Pion nucleon scattering has played a crucial role in advancing our understanding of the low-energy regime of strong interactions. This dissertation presents the development of a new theoretical framework that combines Baryon Chiral Perturbation Theory (BChPT) with the 1/Nc Expansion to analyze pion nucleon scattering. The resulting effective Lagrangian incorporates both chiral and spin-flavor symmetries. Scattering amplitudes are calculated up to the one-loop level (NNLO), which includes four tree-level Feynman diagrams and 45 non-zero loop diagrams. The effective Lagrangian is renormalized at the one-loop level. With spin-3/2 baryons naturally included, the framework demonstrates strong convergence at higher energies. The NNLO pion nucleon scattering amplitude shows good agreement with experimental data from the SAID database. This novel approach, BChPT combined with 1/Nc Expansion, demonstrates substantial predictive power at higher energies where other low-energy theories fall short, achieving the goals of this combined framework. The contribution from loop diagrams is essential for achieving good agreement with the data, highlighting the importance of conducting the calculation up to NNLO. Extracted values for physically measurable quantities agree reasonably well with independently extracted values, underscoring the robustness of the theory.

Jayakodige, Dulitha [Hampton Univ., Hampton, VA (U↗

Design Evolution and Performance Characterization of the GTX Air-Breathing Launch Vehicle Inlet

The design and analysis of a second version of the inlet for the GTX rocket-based combine-cycle launch vehicle is discussed. The previous design did not achieve its predicted performance levels due to excessive turning of low-momentum comer flows and local over-contraction due to asymmetric end-walls. This design attempts to remove these problems by reducing the spike half-angle to 10- from 12-degrees and by implementing true plane of symmetry end-walls. Axisymmetric Reynolds-Averaged Navier-Stokes simulations using both perfect gas and real gas, finite rate chemistry, assumptions were performed to aid in the design process and to create a comprehensive database of inlet performance. The inlet design, which operates over the entire air-breathing Mach number range from 0 to 12, and the performance database are presented. The performance database, for use in cycle analysis, includes predictions of mass capture, pressure recovery, throat Mach number, drag force, and heat load, for the entire Mach range. Results of the computations are compared with experimental data to validate the performance database.

DeBonis, J. R.↗

Shuttle Damage/Repair from the Perspective of Hypersonic Boundary Layer Transition - Experimental Results

An overview is provided of the experimental wind tunnel program conducted at the NASA Langley Research Center Aerothermodynamics Laboratory in support of an agency-wide effort to prepare the Shuttle Orbiter for Return-to-Flight. The effect of an isolated protuberance and an isolated rectangular cavity on hypersonic boundary layer transition onset on the windward surface of the Shuttle Orbiter has been experimentally characterized. These experimental studies were initiated to provide a protuberance and cavity effects database for developing hypersonic transition criteria to support on-orbit disposition of thermal protection system damage or repair. In addition, a synergistic experimental investigation was undertaken to assess the impact of an isolated mass-flow entrainment source (simulating pyrolysis/outgassing from a proposed tile repair material) on boundary layer transition. A brief review of the relevant literature regarding hypersonic boundary layer transition induced from cavities and localized mass addition from ablation is presented. Boundary layer transition results were obtained using 0.0075-scale Orbiter models with simulated tile damage (rectangular cavities) of varying length, width, and depth and simulated tile damage or repair (protuberances) of varying height. Cavity and mass addition effects were assessed at a fixed location (x/L = 0.3) along the model centerline in a region of near zero pressure gradient. Cavity length-to-depth ratio was systematically varied from 2.5 to 17.7 and length-to-width ratio of 1 to 8.5. Cavity depth-to-local boundary layer thickness ranged from 0.5 to 4.8. Protuberances were located at several sites along the centerline and port/starboard attachment lines along the chine and wing leading edge. Protuberance height-to-boundary layer thickness was varied from approximately 0.2 to 1.1. Global heat transfer images and heating distributions of the Orbiter windward surface using phosphor thermography were used to infer the state of the boundary layer (laminar, transitional, or turbulent). Test parametrics include angles-of-attack of 30 deg and 40 deg, sideslip angle of 0 deg, freestream Reynolds numbers from 0.02x106 to 7.3x106 per foot, edge-to-wall temperature ratio from 0.4 to 0.8, and normal shock density ratios of approximately 5.3, 6.0, and 12 in Mach 6 air, Mach 10 air, and Mach 6 CF4, respectively. Testing to simulate the effects of ablation from a proposed tile repair concept indicated that transition was not a concern. The experimental protuberance and cavity databases highlighted in this report were used to formulate boundary layer transition correlations that were an integral part of an analytical process to disposition observed Orbiter TPS damage during STS- 114.

Horvath, Thomas J.↗

Computational Thermochemistry of Jet Fuels and Rocket Propellants

The design of new high-energy density molecules as candidates for jet and rocket fuels is an important goal of modern chemical thermodynamics. The NASA Glenn Research Center is home to a database of thermodynamic data for over 2000 compounds related to this goal, in the form of least-squares fits of heat capacities, enthalpies, and entropies as functions of temperature over the range of 300 - 6000 K. The chemical equilibrium with applications (CEA) program written and maintained by researchers at NASA Glenn over the last fifty years, makes use of this database for modeling the performance of potential rocket propellants. During its long history, the NASA Glenn database has been developed based on experimental results and data published in the scientific literature such as the standard JANAF tables. The recent development of efficient computational techniques based on quantum chemical methods provides an alternative source of information for expansion of such databases. For example, it is now possible to model dissociation or combustion reactions of small molecules to high accuracy using techniques such as coupled cluster theory or density functional theory. Unfortunately, the current applicability of reliable computational models is limited to relatively small molecules containing only around a dozen (non-hydrogen) atoms. We propose to extend the applicability of coupled cluster theory- often referred to as the 'gold standard' of quantum chemical methods- to molecules containing 30-50 non-hydrogen atoms. The centerpiece of this work is the concept of local correlation, in which the description of the electron interactions- known as electron correlation effects- are reduced to only their most important localized components. Such an advance has the potential to greatly expand the current reach of computational thermochemistry and thus to have a significant impact on the theoretical study of jet and rocket propellants.

Crawford, T. Daniel↗

Initial demonstration of automated fuel performance modeling with 1977 EBR-II metallic fuel pins using BISON code with FIPD and IMIS databases

Using the BISON fuel performance code, simulations were conducted using an automated process to read initial and operating conditions from the Fuels Irradiation and Physics Database (FIPD) and Integral Fast Reactor materials information system (IMIS) database, which contains metallic fuel data from the Experimental Breeder Reactor-II (EBR-II). This work demonstrates use of an integrated framework to access the vast majority of EBR-II experimental fuel pin data to support rapid development of fuel performance models for next-generation metallic fuel systems. With this capability, validation for fuel qualification can be performed rapidly. Between IMIS and FIPD, there is enough information to conduct 1977 unique EBR-II metallic fuel pin histories from 24 different experiments, at varying levels of detail between the two databases. Each of these histories includes a high-resolution power history, flux history, coolant channel flow rates, and coolant channel temperatures. Fission gas release (FGR), cumulative damage fraction (CDF), fuel axial swelling, cladding profilometry, and burnup were all simulated in BISON. The results were compared to post-irradiation examination (PIE) results for the initial demonstration of automated BISON modeling. BISON simulations conducted with IMIS and FIPD were in rough agreement with PIE measurements and calculations. Cladding profilometry, FGR, and fuel axial swelling were found to be in rough agreement with PIE measurements, depending on the physics used within the BISON input files. Here, the mechanical contact solver chosen was found to significantly impact axial fuel swelling and cladding strain predictions. CDF values were assessed to see whether pin failure may have been predicted (CDF ≥ 1). This work suggests that continued development of an automated tool for BISON should focus on inclusion of the Fast Flux Test Facility (FFTF) experimental data for a larger database for metallic fuel, improved physical models to better capture fuel performance, such as fuel-cladding interactions, and a more detailed comparison with available PIE data to further the BISON model development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Predicting oxidation damage of ultra high-temperature carbide ceramics in extreme environments using machine learning

Determining the oxidation resistance of UHTC carbides in extreme environments is challenging theoretically and experimentally due to the high dimensional complexity of influencing variables and intricate testing setups. Herein we demonstrate the use of machine learning (ML) models trained with experimental literature data to predict the oxide thickness of UHTC carbides exposed to air based on composition, mean grain size, relative densification, holding time, and temperature. A multi-dimensional database with 76 occurrences is created containing experimental results of Hf, Zr, and Ta carbides plus additives. In this study, the preprocessed database is then used to train ML models to predict their oxidation behavior. The trained model predicts the oxidation damage in the form of an average oxide thickness in UHTC carbides with a Mean Absolute Error (MAE) of ±65.45 μm for samples in the testing set that developed thicknesses up to 1000 μm. The model successfully predicted oxidation damage for a recession rate lower than 60 μm/min. It is noticed that the ensemble method MAE is increased to ±134.34 μm while forecasting the oxidation of samples with a recession rate higher than the threshold. The unprecedented approach is a novel way to predict the damage through the oxidation of carbide compounds before processing for a smarter design with room for improvement.

36 MATERIALS SCIENCE↗

Trust Not Verify? The Critical Need for Data Curation Standards in Materials Informatics

The importance of data curation has been recognized in multiple areas of research; however, the discussion of this important issue is only beginning to emerge in materials science. In this Perspective, we highlight the benefits of using the standardized data curation protocols in materials science and discuss current gaps in accurate and reproducible data reporting using case studies drawn from high-impact materials science papers and well-known databases such as the Crystallography Open Database (COD) and the Cambridge Structural Database (CSD). We argue that both experimental and computational materials scientists need to embrace a culture of rigorous data curation as part of modern research data management. We propose a sample data curation pipeline for materials chemistry and illustrate its use by creating two new materials chemistry databases. Here, we hope that this perspective will serve to catalyze further discussion and promote the continuous development of rigorous data curation practices within the materials science research community. We posit that adherence to best practices of data curation will promote and enhance the reliability, reproducibility, and integrity of materials research and enable the development of reliable AI and machine learning models that critically depend on the use of quality data.

Chemical structure↗

Privacy Preserving Federated Learning for Advanced Scientific Ecosystems

We present a framework to provide privacy preserving (PP) federating learning (FL) across multiple computational and experimental facilities. This work joins the compute capabilities of National Energy Research Scientific Computing Center (NERSC) and Oak Ridge National Laboratory Research Cloud (ORC) with simulated experimental data, such as those produced at the SLAC National Accelerator Laboratory and Spallation Neutron Source (SNS). We describe the software infrastructure developed to provide privacy for computational and experimental networks. We developed algorithmic privacy across the federated system by embedding database security, computation, and communication into the federation architecture, utilizing scientific tools developed by the experimental community.

Archibald, Rick [ORNL] (ORCID:0000000245389780)↗