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DOE OSTI2022

TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY2022

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) work package is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline training to provide engineers with experience in both numerical simulations and experimental methods. This work will use and provide feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development: engineering common model framework (ECMF), engineering quantification of margins and uncertainties (EQMU), test information management system (TIMS), and [WAVES] Analysis for Verified Engineering Simulation (WAVES).

42 ENGINEERING↗

DOE OSTI2020

Procedure for Creating, Reviewing, and Submitting Input Files into the Benchmark Library

Los Alamos National Laboratory (LANL) has a number of criticality benchmark input files, modeled for use with MCNP, developed and maintained by various organizations including the Nuclear Criticality Safety (NCS) Division, XCP-3, and XCP-5. The purpose of this procedure is to standardize input file creation, review, and maintenance. This procedure incorporates existing practices used by IRSN as documented in the original report and the translation from French in addition to practices used by the LANL NCS Division as documented in. The report relates to input files used for the validation of the continuous energy Monte Carlo code MCNP6 but is general enough to be extended to other codes. This report describes the procedure on how to prepare and use benchmarks (taken mainly from the ICSBEP Handbook) for the validation of calculation routes. In particular, this report describes the procedure to follow in the creation of the input files and their integration in the experimental validation databases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

TRUST Nonlinear Dynamics (ND) Report: FY22

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) work package, is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are relevant to the current and future stockpile. This work will use and provide feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development: engineering common model framework (ECMF), engineering quantification of margins and uncertainties (EQMU), and the test information management system (TIMS). Additionally, this work is being used to test a newly available framework in W-13, Weapons Analysis for Verified Engineering Simulation (WAVES).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2023

TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY23

42 ENGINEERING↗

DOE OSTI2024

Bioblendstocks to Optimize Mixing Controlled Compression Ignition (MCCI) Engines

In this project, a team of researchers from the University of Massachusetts Lowell, the University of Maine, and Mainstream Engineering developed an integrated process for the product of bioblendstocks to optimize mixing controlled compression ignition (MCCI) engines. The objective was to improve the energy density, sooting propensity, and cetane number of base diesel fuel while maintaining cold weather behavior. The process converts woody biomass (e.g. sawmill residues) into bio-oil through selective fast pyrolysis; the bio-oil is then selectively upgraded to form selectively oxygenated, minimally-branched hydrocarbons using non-noble metal catalysts in combination with metal-catalyzed hydrogenation. Advanced predictive models, in conjunction with existing property databases, and experimental testing are used to evaluate overall bioblendstock properties and their impact on base diesel fuel. An iterative, targeted upgrading approach was implemented to optimize the proposed bioblendstock’s properties. Assessment methodologies included techno-economic analysis, life-cycle assessment, property testing, and engine testing. Ultimately, the project team successfully produced a viable bioblendstock while identifying critical process points related to scale-up efforts. It was found that producing pyrolysis oils at 500 degrees C and with pine particle sizes of 1-2 mm led to bio-oil with a higher yield (of approximately 45 wt%) and rich amounts of aromatic alcohols. The resultant pyrolysis oil was then upgraded using a sequence of mild hydrotreating, followed by catalytic etherification and esterification, followed by another final mild hydrotreating to produce a blendstock containing saturated species with a limited, but non-zero, amount of oxygen. The aromatic alcohols produced by pyrolysis were especially helpful in this regard, as the resulting bicycloethers and derivatives exhibited high cetane numbers. While most bulk properties of the bioblendstock met or exceeded targeted thresholds, viscosity and cloud point notably fell outside the expected range; this could be addressed by blending limits and/or through the use of additives that are commonplace in current refinding practices. Identification of a bioblendstock that can be produced economically at scale while improving the performance and emissions characteristics of internal combustion engines positively affects the economy by boosting domestic fuel production and the environment by decreasing harmful emissions and increasing efficiency.

09 BIOMASS FUELS↗

DOE OSTI2024

TRUST Sensors in Environments: Thermocouples (SE-TC) Report Release FY24

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to the development, on-target assessment, and qualification of current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. This work uses and provides feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development.

42 ENGINEERING↗

DOE OSTI2025

TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY25

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments [1]. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline collaboration to provide engineers with experience in both numerical simulations and experimental methods. This work uses and provides feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development.

42 ENGINEERING↗

NASA NTRS1995

A design of experiments test to define critical spray cleaning parameters for Brulin 815 GD and Jettacin cleaners

Experimental design testing was conducted to identify critical parameters of an aqueous spray process intended for cleaning solid rocket motor metal components (steel and aluminum). A two-level, six-parameter, fractional factorial matrix was constructed and conducted for two cleaners, Brulin 815 GD and Diversey Jettacin. The matrix parameters included cleaner temperature and concentration, wash density, wash pressure, rinse pressure, and dishwasher type. Other spray parameters: nozzle stand-off, rinse water temperature, wash and rinse time, dry conditions, and type of rinse water (deionized) were held constant. Matrix response testing utilized discriminating bond specimens (fracture energy and tensile adhesion strength) which represent critical production bond lines. Overall, Jettacin spray cleaning was insensitive to the range of conditions tested for all parameters and exhibited bond strengths significantly above the TCA test baseline for all bond lines tested. Brulin 815 was sensitive to cleaning temperature, but produced bond strengths above the TCA test baseline even at the lower temperatures. Ultimately, the experimental design database was utilized to recommend process parameter settings for future aqueous spray cleaning characterization work.

Keen, Jill M.↗

NASA NTRS1998

Rarefied Flow

Rarefaction effects are important for hypersonic applications for a wide spectrum of conditions ranging from low-density (high altitude) situations to relatively high-density flows where the characteristic dimension is small. The present chapter concentrates on two hypersonic flow problems at flow conditions that produce a significant range of rarefaction effects: corner flow with jet interaction and blunt body flow with special emphasis on the near wake, These problems were chosen because they involve complex flow interactions that have significant implications for both spacecraft and re-entry vehicles. In an effort to clarify issues associated with these two general flow problems and to enhance their respective databases, both experimental and computational contributions were executed by an international group of researchers. In some cases, multiple data sources for both experimental and computational contributions are achieved.

James N. Moss↗

DOE OSTI2023

Deep learning of electrochemical CO 2 conversion literature reveals research trends and directions

Large-scale and openly available material science databases are mainly composed of computer simulation results rather than experimental data. Some examples include the Materials Project, Open Quantum Materials Database, and Open Catalyst 2022. Unfortunately, building large-scale experimental databases remains challenging due to the difficulties in consolidating locally distributed datasets. In this work, focusing on the catalysis literature of CO 2 reduction reactions (CO 2 RRs), we present a machine learning (ML)-based protocol for selecting highly relevant papers and extracting important experimental data. First, we report a document embedding method (Doc2Vec) for collecting papers of greatest relevance to the specific target domain, which yielded 3154 CO 2 RR-related papers from six publishers. Next, we developed named entity recognition (NER) models to extract twelve entities related to material names (catalyst, electrolyte, etc.) and catalytic performance (Faradaic efficiency, current density, etc.). Further, among several tested models, the MatBERT-based approach achieved the highest accuracy, with an average F1-score of 90.4% and an F1-score of 95.2% in a boundary relaxation evaluation scheme. The accurate and accelerated NER-based data extraction from a large volume of catalysis literature enables temporal trend analyses of the CO 2 RR catalysts, products, and performances, revealing the potentially effective material space in CO 2 RRs. While this work demonstrates the effectiveness of our ML-based text mining methods for specifically CO 2 RR literature, the methods and approach are applicable to and may be used to accelerate the development of other catalytic chemical reactions.

36 MATERIALS SCIENCE↗

NASA NTRS2009

Aerothermal Testing for Project Orion Crew Exploration Vehicle

The Project Orion Crew Exploration Vehicle aerothermodynamic experimentation strategy, as it relates to flight database development, is reviewed. Experimental data has been obtained to both validate the computational predictions utilized as part of the database and support the development of engineering models for issues not adequately addressed with computations. An outline is provided of the working groups formed to address the key deficiencies in data and knowledge for blunt reentry vehicles. The facilities utilized to address these deficiencies are reviewed, along with some of the important results obtained thus far. For smooth wall comparisons of computational convective heating predictions against experimental data from several facilities, confidence was gained with the use of algebraic turbulence model solutions as part of the database. For cavities and protuberances, experimental data is being used for screening various designs, plus providing support to the development of engineering models. With the reaction-control system testing, experimental data were acquired on the surface in combination with off-body flow visualization of the jet plumes and interactions. These results are being compared against predictions for improved understanding of aftbody thermal environments and uncertainties.

Berry, Scott A.↗

DOE OSTI2019

Hierarchical Bayesian estimation for adsorption isotherm parameter determination

Estimation of isotherm model parameters from experimental data is necessary in adsorption process modeling. To facilitate isotherm modeling, databases that store experimental data exist. Nevertheless, data inconsistency among different researchers must be resolved to find a single set of isotherm parameters from multiple data sets. Herein, we propose a hierarchical Bayesian estimation method to quantify the discrepancy by a multiplicative factor while simultaneously obtaining the probability distributions of a single set of isotherm parameters. This approach also allows us to identify outliers, which are data sets that are not in agreement with other sets. The proposed approach is demonstrated for the case of CO 2 adsorption in the metal-organic framework UiO-66.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Engagement opportunities in OECD NEA benchmark development

A myriad of opportunities is available to collaborate via international benchmark exercises and experimental data preservation activities. Many such opportunities abound under the auspices of the Nuclear Science Committee of the Organisation for Economic Co-operation and Development Nuclear Energy Agency (NEA). Key projects and activities of relevance to the development of advanced reactors design include the International Criticality Safety Benchmark Evaluation Project (ICSBEP), the International Reactor Physics Experiment Evaluation Project (IRPhEP), the International Assay Data of Spent Nuclear Fuel Database (SFCOMPO), the Shielding Integral Benchmark and Archive Database (SINBAD), and The International Experimental Thermal HYdraulicS Database (TIETHYS), and various cooperative benchmark exercises. Interested participants are encouraged to contact the leadership and secretariat of the various Technical Working Groups and Working Parties to become more engaged. This paper provides a summary of the current benchmark exercises and experimental databases available for international participation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2025

Data Science-Driven Discovery of Multimetallic Oxygen-cycle Electrocatalysts for Enhanced Energy Conversion

The overarching objective of this effort has been to combine state-of-the-art data science techniques, first principles analyses, and molecular-level characterization of electrocatalyst structure and reactivity to identify both in-situ mechanisms for degradation and transformation of electrocatalysts with highly complex catalytic structures and the impact of these transformations on catalytic activity. The primary catalysts of interest have been multielemental alloys, including high entropy alloys (HEA’s), which are characterized by a high degree of disorder and up to 20 different elements within a single nanoparticle. We have applied these strategies primarily to energy-critical oxygen cycle electrocatalytic reactions, including oxygen reduction (ORR), but we have also considered extensions to non-electrochemical chemistries such as ammonia synthesis and decomposition. We have made strong progress in the development of computational methods on both the level of machine learning methods development as well as first principles-based treatments of HEA’s, and we have leveraged these insights to propose promising HEA catalysts for the ORR. On the experimental side, we developed new HEA synthesis and characterization protocols relevant to these reactions and developed a database combining our experimental results with corresponding computational tools.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Vickers hardness prediction from machine learning methods

Abstract The search for new superhard materials is of great interest for extreme industrial applications. However, the theoretical prediction of hardness is still a challenge for the scientific community, given the difficulty of modeling plastic behavior of solids. Different hardness models have been proposed over the years. Still, they are either too complicated to use, inaccurate when extrapolating to a wide variety of solids or require coding knowledge. In this investigation, we built a successful machine learning model that implements Gradient Boosting Regressor (GBR) to predict hardness and uses the mechanical properties of a solid (bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio) as input variables. The model was trained with an experimental Vickers hardness database of 143 materials, assuring various kinds of compounds. The input properties were calculated from the theoretical elastic tensor. The Materials Project’s database was explored to search for new superhard materials, and our results are in good agreement with the experimental data available. Other alternative models to compute hardness from mechanical properties are also discussed in this work. Our results are available in a free-access easy to use online application to be further used in future studies of new materials at www.hardnesscalculator.com .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

A database of synthetic inelastic neutron scattering spectra from molecules and crystals

Abstract Inelastic neutron scattering (INS) is a powerful tool to study the vibrational dynamics in a material. The analysis and interpretation of the INS spectra, however, are often nontrivial. Unlike diffraction, for which one can quickly calculate the scattering pattern from the structure, the calculation of INS spectra from the structure involves multiple steps requiring significant experience and computational resources. To overcome this barrier, a database of INS spectra consisting of commonly seen materials will be a valuable reference, and it will also lay the foundation of advanced data-driven analysis and interpretation of INS spectra. Here we report such a database compiled for over 20,000 organic molecules and over 10,000 inorganic crystals. The INS spectra are obtained from a streamlined workflow, and the synthetic INS spectra are also verified by available experimental data. The database is expected to greatly facilitate INS data analysis, and it can also enable the utilization of advanced analytics such as data mining and machine learning. Notice: This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2001

Baseline Validation of Unstructured Grid Reynolds-Averaged Navier-Stokes Toward Flow Control

The value of the use of the Reynolds-averaged Navier-Stokes methodology for active flow control applications is assessed. An experimental flow control database exists for a NACA0015 airfoil modified at the leading edge to implement a fluidic actuator; hence, this configuration is used. Computational results are documented for the baseline wing configuration (no control) with the experimental results and assumes two-dimensional flow. The baseline wing configuration has discontinuities at the leading edge, trailing edge, and aft of midchord on the upper surface. A limited number of active flow control applications have been tested in the laboratory and in flight. These applications include dynamic stall control using a deformable leading edge, separation control for takeoff and landing flight conditions using piezoelectric devices, pulsed vortex generators, zero-net-mass oscillations, and thrust vectoring with zero-net-mass piezoelectric-driven oscillatory actuation. As yet, there is no definitive comparison with experimental data that indicates current computational capabilities can quantitatively predict the large aerodynamic performance gains achieved with active flow control in the laboratory. However, one study using the Reynolds-averaged Navier-Stokes (RANS) methodology has shown good quantitative agreement with experimental results for an isolated zero-net-mass actuator. In addition, some recent studies have used RANS to demonstrate qualitative performance gains compared with the experimental data for separation control on an airfoil. Those quantitative comparisons for both baseline and flow control cases indicated that computational results were in poor quantitative agreement with the experiments. The current research thrust will investigate the potential use of an unstructured grid RANS approach to predict aerodynamic performance for active flow control applications building on the early studies. First the computational results must quantitatively match experiments for the no-control case before proceeding to the time-dependent flow control case. This paper documents the baseline (no-control) case using an unswept airfoil configuration. The next section describes the configurations used for the computations and the experimentals. The computational approach is then described followed by results and concluding remarks.

Joslin, Ronald D.↗

NASA NTRS2002

The NASA Low-Pressure Turbine Flow Physics Program: A Review

An overview of the NASA Glenn Low-Pressure Turbine (LPT) Flow Physics Program will be presented. The flow in the LPT is unique for the gas turbine. It is characterized by low Reynolds number and high freestream turbulence intensity and is dominated by interplay of three basic mechanisms: transition, separation and wake interaction. The flow of most interest is on the suction surface, where large losses are generated due to separation. The LPT is a large, multistage, heavy, jet engine component that suffers efficiency degradation between takeoff and cruise conditions due to decrease in Reynolds number with altitude. The performance penalty is around 2 points for large commercial bypass engines and as much as 7 points for small, high cruise altitude, military engines. The gas-turbine industry is very interested in improving the performance of the LPT and in reducing its weight, part count and cost. Many improvements can be accomplished by improved airfoil design, mainly by increasing the airfoil loading that can yield reduction of airfoils and improved performance. In addition, there is a strong interest in reducing the design cycle time and cost. Key enablers of the needed improvements are computational tools that can accurately predict LPT flows. Current CFD tools in use cannot yet satisfactorily predict the unsteady, transitional and separated flow in the LPT. The main reasons are inadequate transition & turbulence models and incomplete understanding of the LPT flow physics. NASA Glenn has established its LPT program to answer these needs. The main goal of the program is to develop and assess models for unsteady CFD of LPT flows. An approach that consists of complementing and augmenting experimental and computational work elements has been adopted. The work is performed in-house and by several academic institutions, in cooperation and interaction with industry. The program was reviewed at the Minnowbrook II meeting in 1997. This review will summarize the progress that was made since and will introduce newly started projects. The LPT program is focused on three areas: acquisition of experimental and numerical databases and on modeling and computation. Priority was initially given to experiments. There are three classes of experiments: simulated LPT passages, linear cascade, both with and without wakes, and low-speed rotating rig. They are being conducted as follows: At NASA GRC on a flat surface with blade pressure distribution, at the US Naval Academy on a curved surface. The addition of wakes is studied at the University of Minnesota in a curved passage with a retractable wake generator, and at Texas A&M University in a linear cascade with continuously running wake generator. The pressure distribution of the Pratt & Whitney blade 'Pak B' is used in all these experiments. Experiments have been performed also in the GEAE Low-Speed Rotating Turbine (LSRT) rig with GE-designed airfoils. Work on numerically generated database is in progress at the University of Kentucky, using the DNS/LES code LESTool developed there. Turbulence/transition model assessment and development is performed also at the University of Kentucky, where a new intermittency transport model was developed and many experimental test cases have been numerically computed. Assessments of models using simulations of multistage LPT experiments were performed at Virginia Commonwealth University using the Corsair code. Work on suction surface separation delay, using passive and active flow-control, has also been initiated. Following the overview, Principal Investigators attending the workshop will present in detail several of the projects supported by NASA.

Ashpis, David E.↗