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At least 307 records · Page 17

Experimental clean combustor program: Phase 3: Turbulence measurement addendum

Airflow turbulence parameters were measured in the high pressure, high temperature flow stream leaving the compressor of an operating gas turbine engine. A water cooled hot film turbulence probe was used to determine the turbulence intensity and length scale in the compressor exit flow stream of the CF6-50 engine. Data were obtained only at idle operating conditions. At engine power levels above idle conditions, durability problems and erratic data readings were encountered with the turbulence measurement probes. Turbulence measurements were made at three radial immersions at a point 15.5 cm downstream of the compressor outlet guide vanes in the compressor exit diffuser. The passage height at this point is 5.54 cm. Data reduction was accomplished with a time-data fast Fourier transform (FFT) system. This system finds the power spectral density distribution (PSD) of a large number of data samples using a direct Fourier transform algorithm and finds the autocorrelation parameter for these data by doing an FFT analysis of the PSD curves for a series of time delay intervals.

Taylor, J. R.↗

Inspection error and its adverse effects - A model with implications for practitioners

Inspection error has clearly been shown to have adverse effects upon the results desired from a quality assurance sampling plan. These effects upon performance measures have been well documented from a statistical point of view. However, little work has been presented to convince the QC manager of the unfavorable cost consequences resulting from inspection error. This paper develops a very general, yet easily used, mathematical cost model. The basic format of the well-known Guthrie-Johns model is used. However, it is modified as required to assess the effects of attributes sampling errors of the first and second kind. The economic results, under different yet realistic conditions, will no doubt be of interest to QC practitioners who face similar problems daily. Sampling inspection plans are optimized to minimize economic losses due to inspection error. Unfortunately, any error at all results in some economic loss which cannot be compensated for by sampling plan design; however, improvements over plans which neglect the presence of inspection error are possible. Implications for human performance betterment programs are apparent, as are trade-offs between sampling plan modification and inspection and training improvements economics.

Collins, R. D., Jr.↗

Advanced Material Developments with Laser Engineered Net Shaping

The Laser Engineered Net Shaping (LENS(Trademark)) process is a new technology to fabricate three-dimensional metallic components directly from CAD solid models. It directly fabricates metal hardware by injecting the metal powder of choice into the focal point of a 700W Nd:Yag laser as it traces the perimeter and fills of a part. The Rapid Prototype Laboratory at Marshall Space Flight Center is currently operating a OPTOMEC 750 LENS machine in evaluation experiments involving integration of this technology into various manufacturing processes associated with aerospace applications. This paper will cover our research finding about properties of samples created from Inconel 718 & SS316 using this process versus the same materials in cast & wrought conditions.

Williams, Glenn A.↗

Sub-pilot-scale Production of High-Value Products from U.S. Coals

Investigators from the University of Utah, University of Wyoming and Marshall University pursued a program to study the conversion of raw coal to high-value products of carbon fiber and silicon carbide. Team members also developed an initial framework for a data portal that can incorporate laboratory data on coal processing and product quality, and also work with tools for machine learning for data analysis, data visualization and economic assessment. Experimental R&D efforts focused on the conversion of raw coal to coal tar and other byproducts, and the resulting tar intermediates were upgraded to form anisotropic and isotropic pitch materials. These pitch materials were produced from coal using both thermal (pyrolysis) and chemical (mild solvolysis liquefaction) decomposition of raw coal. Four different coals were studied: Utah bituminous coal (Sufco), Wyoming PRB coal (Black Thunder), Illinois bituminous coal (Illinois #6), and West Virginia bituminous coal (Flying Eagle). Both metallurgical-grade coking coals and lower-grade steam coals were investigated, and controlled secondary gas-phase reactions were used during a two-stage pyrolysis process to induce cracking and condensation reactions among the pyrolytic tar species. This approach successfully improved the performance of the lower grade coals for yielding pitch materials, with properties more consistent with a commercial-grade pitch that had previously demonstrated success for quality carbon fiber production. The use of waste plastic materials was also studied, to help improve physical and chemical characteristics of the intermediate tars and final pitch product; in particular, for lowering the pitch softening point to an acceptable level for melt spinning carbon fiber. Mild solvolysis liquefaction was also used as a method for producing pitch for carbon fiber production. As expected, significantly higher pitch yields were obtained using this approach, and waste plastic materials were also successfully used to reduce pitch softening point to an acceptable level. The plastic materials were also utilized to create a solvent for the mild solvolysis process, and this plastic-derived solvent was shown to provide results consistent with more expensive commercial chemical solvents, and could thus avoid the need for costly recovery and recycle of a liquefaction solvent. Additional experimental R&D focused on the production of silicon carbide (β-SiC) from the residual char byproduct from pitch production, and also on the production of carbon fiber from the anisotropic pitch. SiC was successfully synthesized using a mixture of residual char and sandstone at a ratio of 1:1. Reaction temperature and residence time were optimized and yielded a product purity of 81%. For carbon fiber production, the most successful pitch samples were obtained from the mild solvolysis liquefaction approach, combined with the use of a plastic (HDPE)-derived solvent. Fiber properties improved over time as laboratory fiber production methodologies improved, and final yields of carbon fiber were obtained with a diameter of 12.14 ± 1.10 um, Modulus of 173.73 ± 15.25 GPa, and Tensile Strength of 1.04 ± 0.10 GPa. A proof-of-concept Modern Community Research Data Portal (MCRDP) was developed and deployed for coal and coal-derived pitch characterization, with the full support of (i) remote web-based access, (ii) distributed analysis, (iii) interactive visualization and exploration, (iv) shared and long-term data access, (v) advanced query capabilities and (vi) real-time collaboration. The Coal to Products Data Portal “coaltoproducts.org” provides researchers with space to store and share data within a project, tools for analyzing and understanding data for scientific investigation, and the ability to publish data to the broader community for reproducibility. The portal leverages the Material Commons 2.0 (MC) platform developed by the Center for PRedictive Integrated Structural Materials Science (PRISMS) of the University of Michigan, to achieve long-term longevity of data collections and, more importantly, collaborative science. A number of data visualization tools were also assessed and implemented for interrogating the experimental and modeling data. The machine learning portion of this project analyzed datasets from two different coal conversion processes performed on a diverse set of coal samples from both the coal pyrolysis experiments and the solvent liquefaction experiments. The work was initiated by exploring standard regression models on the pyrolysis data, aiming to understand the impact of sample characteristics and processing conditions on key product metrics. Over the course of the project, the focus expanded to include a variety of machine learning tools, delving into both supervised and unsupervised learning methods. Models tested on the pyrolysis data included linear, ridge, lasso, elastic-net, Gaussian process, random forest regression, and AutoSklearn, and the approach was continually refined to enhance predictive accuracy and model interpretability. Similar techniques were applied to the liquefaction data with an additional focus on feature engineering. Along with mesophase content, additional outputs of interest were the pitch yield, softening point, and QI content. Insights derived from these analyses are crucial in determining the factors influencing the quality and yield of coal-derived products. As the work progressed, the research evolved from foundational model comparisons to analyses of random forests, decision paths, and feature importance scores. A thorough market analysis was performed to examine the prospects of coal-based carbon fibers. The best opportunities for coal come from its lower and more stable price relative to petroleum, particularly for subbituminous coals, which is the primary advantage that a coal refinery may have over a petroleum refinery. Before a commercial CTP production facility can be modeled, however, several things need to be understood regarding the nature of the would-be coal refinery. These include the technology to be deployed, the size of facility, the volume(s) of co-product(s), and the waste and emissions profile of the plant. The volume of co-products and waste may be substantial and will require separate market analysis to ensure viability. In the near-term, the importance of coal tar pitch, in the form of carbon pitch, to the aluminum and steel industries is likely to overshadow the alternative use of this material as an input for carbon fiber. The importance of steel and aluminum in building materials, and the need for carbon materials in their manufacturing, will ensure that demand for these products remains for the long run. In addition, carbon fiber may also be the best substitute for steel and aluminum well into the future. While society will eventually be able to shift production of much of its electricity needs to renewables, it will not be able to shift away from fossil fuels for production of high-strength construction and vehicular materials. Demand for carbon fiber is expected to increase quickly, but the volume of carbon fiber and the amount of coal that would be needed to produce even a sizeable share of this market may still be relatively small compared to current coal production. Thus, other coal-based products like graphene, graphite, carbon foams, resins, and carbon-based building products will play important roles in sustaining coal production as coal-fired power generation continues to decline.

01 COAL, LIGNITE, AND PEAT↗

Nanoscale Mass Spectrometry Multimodal Imaging via Tip-Enhanced Photothermal Desorption

Materials ranging from adhesives, pharmaceuticals, lubricants, and personal care products are traditionally studied using macroscopic characterization techniques. However, their functionality is in reality defined by details of chemical organization on often noncrystalline matter with characteristic length scales on the order of microns to nanometers. Additionally, these materials are traditionally difficult to analyze using standard vacuum-based approaches that provide nanoscale chemical characterization due to their volatile and beam-sensitive nature. Therefore, approaches that operate under ambient conditions need to be developed that allow probing of nanoscale chemical phenomena and correlated functionality. Here, we demonstrate a tool for probing and visualizing local chemical environments and correlating them to material structure and functionality using advanced multimodal chemical imaging on a combined atomic force microscopy (AFM) and mass spectrometry (MS) system using tip-enhanced photothermal desorption with atmospheric pressure chemical ionization (APCI). We demonstrate enhanced performance metrics of the technique for correlated imaging and point sampling and illustrate the applicability for the analysis of trace chemicals on a human hair, additives in adhesives on paper, and pharmaceuticals samples notoriously difficult to analyze in a vacuum environment. Overall, this approach of correlating local chemical environments to structure and functionality is key to advancing research in many fields ranging from biology, to medicine, to material science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Speed of sound in methane under conditions of planetary interiors

We present direct observations of acoustic waves in warm dense matter. We analyze wave-number- and energy-resolved x-ray spectra taken from warm dense methane created by laser heating a cryogenic liquid jet. X-ray diffraction and inelastic free-electron scattering yield sample conditions of 0.3 ± 0.1 eV and 0.8 ± 0.1 g/ cm − 3 , corresponding to a pressure of ∼ 13 GPa. Inelastic x-ray scattering was used to observe the collective oscillations of the ions. With a highly improved energy resolution of ∼ 50 meV, we could clearly distinguish the Brillouin peaks from the quasielastic Rayleigh feature. Data at different wave numbers were utilized to derive a sound speed of 5.9 ± 0.5 km/s, marking a high-temperature data point for methane and demonstrating consistency with Birch's law in this parameter regime. Published by the American Physical Society 2024

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Aerothermodynamic Analysis of Stardust Sample Return Capsule with Coupled Radiation and Ablation

An aerothermodynamic analysis of the forebody aeroshell of the Stardust Sample Return Capsule is carried out by using the axisymmetric viscous shock-layer equations with and without fully coupled radiation and ablation. Formulation of the viscous shock-layer equations with shoulder radius as the length scale and implementation of the Vigneron pressure condition allow resolution of the flowfield over the shoulder. With a predominantly supersonic outflow over the shoulder, a globally iterated solution or viscous shock-layer equations can be obtained. The stagnation-point results are obtained along a specified trajectory, whereas detailed calculations along the body are provided at the peak-heating point. The equilibrium calculations with ablation injection are the focus of the present study because of the lack of a general chemical nonequilibrium analysis that accounts for both surface and flowfield effect. The equilibrium calculations also provide a simple way to conserve surface (and flowfield) elemental composition for the current small ablation injection rates, where the surface elemental composition is a mixture of freestream and ablator elements. Therefore, the coupled laminar and turbulent flow solutions with radiation and ablation are obtained by using the equilibrium flow chemistry, whereas a nonequilibrium chemistry model is used for solutions without ablation and turbulence. Various computed results are compared with those obtained by the other researchers.

Gupta, Roop N.↗

A Scintillation Counter System Design To Detect Antiproton Annihilation using the High Performance Antiproton Trap(HiPAT)

The High Performance Antiproton Trap (HiPAT), a system designed to hold up to l0(exp 12) charge particles with a storage half-life of approximately 18 days, is a tool to support basic antimatter research. NASA's interest stems from the energy density represented by the annihilation of matter with antimatter, 10(exp 2)MJ/g. The HiPAT is configured with a Penning-Malmberg style electromagnetic confinement region with field strengths up to 4 Tesla, and 20kV. To date a series of normal matter experiments, using positive and negative ions, have been performed evaluating the designs performance prior to operations with antiprotons. The primary methods of detecting and monitoring stored normal matter ions and antiprotons within the trap includes a destructive extraction technique that makes use of a micro channel plate (MCP) device and a non-destractive radio frequency scheme tuned to key particle frequencies. However, an independent means of detecting stored antiprotons is possible by making use of the actual annihilation products as a unique indicator. The immediate yield of the annihilation event includes photons and pie mesons, emanating spherically from the point of annihilation. To "count" these events, a hardware system of scintillators, discriminators, coincident meters and multi channel scalars (MCS) have been configured to surround much of the HiPAT. Signal coincidence with voting logic is an essential part of this system, necessary to weed out the single cosmic ray events from the multi-particle annihilation shower. This system can be operated in a variety of modes accommodating various conditions. The first is a low-speed sampling interval that monitors the background loss or "evaporation" rate of antiprotons held in the trap during long storage periods; provides an independent method of validating particle lifetimes. The second is a high-speed sample rate accumulating information on a microseconds time-scale; useful when trapped antiparticles are extracted against a target, providing an indication of quantity. This paper details the layout of this system, setup of the hardware components around HiPAT, and applicable checkouts using normal matter radioactive sources.

Martin, James J.↗

Demonstrating resonant ultrasound spectroscopy as a viable technique to characterize thermally conditioned high explosive materials

We present results of resonant ultrasound spectroscopy (RUS) measurements applied to granular high explosive materials at different bulk pressing densities and degree of thermal conditioning. The material chosen in this study is a ubiquitously used explosive material known as pentaerythritol tetranitrate (PETN), which is used commercially in civil and defense applications both as a binderized plastic bonded explosive material and an unbinderized neat material. However, changes in granular PETN bulk elastic properties due to thermal conditioning, which could have implications for better understanding environmental aging-related effects, have not been well studied even though it is believed that elasticity may play an important role in explosive material initiation mechanisms. Furthermore, monitoring elastic property changes in granular explosive pressings has not yet been demonstrated using RUS, which is an appealing non-destructive characterization tool that requires only dry point contact with the explosive material. To this end, we report the first study using RUS to quantify the elastic properties of binderized and neat PETN pressings as well as to quantify changes in elastic properties as a function of both thermal conditioning and bulk pressing density. Elastic stiffness coefficients, sometimes more commonly referred to as elastic constants, calculated from the RUS measurements on the different PETN-based materials show a significant increase for the post-conditioned samples compared to the pre-conditioned samples. This trend of increasing elastic properties with thermal conditioning was consistent for different density pressings, different thermal exposure conditions, and even different neat PETN pressings of differing average crystal sizes and/or specific surface areas.

36 MATERIALS SCIENCE↗

Abundance matching analysis of the emission-line galaxy sample in the extended Baryon Oscillation Spectroscopic Survey

We present the measurements of the small-scale clustering for the emission-line galaxy (ELG) sample from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) in the Sloan Digital Sky Survey IV (SDSS-IV). We use conditional abundance matching method to interpret the clustering measurements from 0.34 to 70 h -1 Mpc. In order to account for the correlation between properties of ELGs and their environment, we add a secondary connection between star formation rate of ELGs and halo accretion rate. Three parameters are introduced to model the ELG [O II ] luminosity and to mimic the target selection of eBOSS ELGs. The parameters in our models are optimized using Markov Chain Monte Carlo (MCMC) method. We find that by conditionally matching star formation rate of galaxies and the halo accretion rate, we are able to reproduce the eBOSS ELG small-scale clustering within 1σ error level. Our best-fitting model shows that the eBOSS ELG sample only consists of ~ 12 per cent of all star-forming galaxies, and the satellite fraction of eBOSS ELG sample is 19.3 per cent. We show that the effect of assembly bias is ~ 20 per cent on the two-point correlation function and ~ 5 per cent on the void probability function at scale of r ~ 20 h -1 Mpc.

79 ASTRONOMY AND ASTROPHYSICS↗

Solid-State Joining of Magnesium Sheet to High-Strength Steel

Increasing the use of lightweight materials and implementing enabling manufacturing technologies are the two primary paths toward automotive weight reduction. In many situations, the ability to substitute light weight material requires a need to attach and join light weight material to existing steel substructures requiring dissimilar joining technologies. Dissimilar joining methods currently available in cost range for high volume automotive manufacturing face multiple challenges. The problem is exacerbated in the case of Magnesium alloy to steel joints because of their highly dissimilar nature and lack of mutual miscibility. Additionally, Magnesium’s poor room temperature ductility complicates the use of point fastening technologies. Two emerging solid-state joining technologies Friction Stir assisted Scribe welding (FaST) and Ultrasonic Welding (USW) that employ large amount of plastic deformation at the interface were used to investigate, develop, and understand dissimilar joints between Magnesium Alloy to DP590 Steel. Various process responses including interface temperatures, process forces, strain fields were captured during the development of the welding process. Variety of welded samples were tested and characterized to understand the relationship between welding conditions and joints microstructure and mechanical properties.

36 MATERIALS SCIENCE↗

The Scientific Case for Sample Return from a Primitive Near-Earth Asteroid

This paper is predicated on the recent experimental findings that the smallest structural ferromagnesiosilica entities in collected chondritic aggregate interplanetary dust particles (IDPs) have a predictable metastable eutectic composition. Kinetically controlled gas to solid condensation of MgFe-SiO-O2-H2 vapors does NOT produce stoichiometric crystalline solids (i.e. minerals) such as predicted by equilibrium condensation models but instead yields amorphous solids that are chemically ordered at metastable eutectics in the binary phase diagrams. Therefore these condensed dust grains will have a considerable amount of 'internal free energy' that will make them highly responsive to changes in their environments. Their inherent high energy-content 'buys' time and energy for mineralogical modification and chemical readjustment in response to changing environmental conditions. The activation energy barrier for reactions in metastable eutectic solids will be lower than for crystalline solids. As a result the reactions can take place at much lower temperatures and on much shorter time scales. That is, they will also occur much earlier in the evolution of a parent body wherein heat-producing sources may either be immature or inefficient. The ensuing reaction chains from metastable equilibrium to full thermodynamic equilibration with the local environment will be a chaotic 'Ostwald cascade' but from a well defined starting point to a predictable end result. Here we will discuss the implications of metastable eutectic dust as we see them for dust properties in icy and ice-free parent bodies wherein circumstellar dust is still recognizable because of the primitive nature of these parent bodies. We point to potential engineering constraints on sample acquisition and storage during Earth transit. Among the scientific goals of a primitive Near Earth Asteroid (NEA) sample return mission will be verification of the nature of dust forming and modification processes during hierarchical accretion in the earliest protoplanets. We propose sampling an infrared P- or D-class NEA or an object showing cometary activity such as 2201 Oljato that could be an asteroid or evolved comet. Additional information is contained in the original extended abstract.

Rietmeijer, Frans J. M.↗

Maximizing Science Return from Future Rodent Experiments on the International Space Station (ISS): Tissue Preservation

To better understand how mammals adapt to long duration habitation in space, a system for performing rodent experiments on the ISS is under development; Rodent Research-1 is the first flight and will include validation of both on-orbit animal support and tissue preservation. To evaluate plans for on-orbit sample dissection and preservation, we simulated conditions for euthanasia, tissue dissection, and prolonged sample storage on the ISS, and we also developed methods for post-flight dissection and recovery of high quality RNA from multiple tissues following prolonged storage in situ for future science. Mouse livers and spleens were harvested under conditions that simulated nominal, on-orbit euthanasia and dissection operations including storage at -80 C for 4 months. The RNA recovered was of high quality (RNA Integrity Number, RIN(is) greater than 8) and quantity, and the liver enzyme contents and activities (catalase, glutathione reductase, GAPDH) were similar to positive controls, which were collected under standard laboratory conditions. We also assessed the impact of possible delayed on-orbit dissection scenarios (off-nominal) by dissecting and preserving the spleen (RNAlater) and liver (fast-freezing) at various time points post-euthanasia (from 5 min up to 105 min). The RNA recovered was of high quality (spleen, RIN (is) greater than 8; liver, RIN (is) greater than 6) and liver enzyme activities were similar to positive controls at all time points, although an apparent decline in select enzyme activities was evident at the latest time (105 min). Additionally, various tissues were harvested from either intact or partially dissected, frozen carcasses after storage for approximately 2 months; most of the tissues (brain, heart, kidney, eye, adrenal glands and muscle) were of acceptable RNA quality for science return, whereas some tissues (small intestine, bone marrow and bones) were not. These data demonstrate: 1) The protocols developed for future flight experiments will support science return despite delayed preservation post-euthanasia or prolonged storage, and 2) Many additional tissues for gene expression analysis can be obtained by dissection following prolonged storage of the tissue in situ at -80 C. These findings have relevance both to high value, ground-based experiments when sample collection capability is severely constrained, and to all future spaceflight experiments that entail on-orbit sample recovery by the ISS crew.

tissues↗

Rapid prediction of fuel research octane number and octane sensitivity using the AFIDA constant-volume combustion chamber

Current research octane number (RON) and motor octane number (MON) gasoline performance characterization techniques use dated, complex engine testing methodology and limit researchers’ ability to easily characterize small volumes of experimental fuels. A novel methodology is presented that correlates measured ignition delay (ID) time to RON in an Advanced Fuel Ignition Delay Analyzer (AFIDA) constant-volume combustion chamber device at a single pressure/temperature condition, with an r2 of 0.99 and standard error (SE) of 1.0. The correlation of the slope of the ID time between two additional temperature points to octane sensitivity (S) produces an r2 of 0.97 and SE of 0.69; however, fuels with S>12 are indistinguishable. These results are based on methodology calibration using 31 primary and toluene reference fuels containing 0%-40% ethanol with RON values ranging from 85 to 113. Validation of these methods using a 102-sample fuel matrix spanning an array of base fuels and additive chemistry designed to test the robust applicability of the method, along with pump gasoline and high-octane surrogate blend samples, demonstrates an r2 of 0.94 and SE of 1.3 for the RON correlation over all samples, whereas the equivalent S correlation produces an r2 of 0.78 and SE of 1.2 by excluding two additives, 3-pentanone and diisobutylene, which displayed poor S correlation results. This novel AFIDA analysis method can be performed in 1 h and with 40 mL of fuel, offering significant improvements in time and volume requirements over traditional techniques.

33 ADVANCED PROPULSION SYSTEMS↗

Multiobjective Constrained Symbolic Regression for Predictive Modeling of Material Creep Behavior

When creep testing is repeated on samples of the same alloy under the same parametric conditions (i.e., stress and temperature), the resulting strain/time curves can vary from each other considerably as shown in Figure 1 [1]. The time required to creep test a material to rupture can extend to the order of years. Because of this, a numerical model that can quickly analyze the incomplete results of an ongoing experiment to predict 1) the incomplete portion of the strain/time curve leading up to the rupture point and 2) the rupture point itself would be of great utility to the materials community. Such a model has the potential to save 1) the time required to finish running the experiment to rupture 2) the associated monetary cost of finishing said experiment. Furthermore, it would be advantageous if the predictive model could give a parametric function modeling strain/time curves for material scientists to investigate the impact of the temperature and stress parameters on the resulting creep behavior. This work introduces a piecewise symbolic regression algorithm to predict the remainder of the strain/time curve. Preliminary results show good model performance.

36 MATERIALS SCIENCE↗

Advanced Materials & Manufacturing Technology (AMMT): Process understanding for qualifying LPBF 316H SS

Investigations were conducted in fiscal years (FY) 2023 and 2024 to gather relevant data sets addressing challenges related to qualifying 316H stainless steel (SS) for use in future nuclear reactors. This work was a collaborative effort involving researchers from Idaho National Laboratory (INL), Argonne National Laboratory (ANL), and Oak Ridge National Laboratory (ORNL). Key outcomes included: • Development of process-structure-property data sets to better understand the relationships between manufacturing processes, material structure, and performance characteristics. • Establishment of an in-situ monitoring system to link these various data sets together. • Detailed characterization of the raw material feedstock to further strengthen the understanding of process-structure and process-property relationships. Building on this foundation, in FY25 there was interest in exploring the behavior of additively manufactured 316H SS under different test conditions to support the overall material qualification process. Los Alamos National Laboratory (LANL) was tasked with providing specimen samples to the collaborating labs, who then conducted a round-robin study examining factors like selective heat treatment, low-cycle fatigue (LCF), and tensile-creep (T-C) properties. Additionally, high-temperature differential scanning calorimetry (DSC) was performed by LANL to better understand how the material's thermal characteristics change as it is heated up to the melting point. This provided a more comprehensive understanding of the material's behavior. The combined results from these investigations could potentially be used to support the inclusion of 316H stainless steel in Section III, Division 5 of the relevant codes and standards, allowing its use in future nuclear reactor applications.

36 MATERIALS SCIENCE↗

High-Throughput Nanoindentation Mapping of Additively Manufactured T91 Steel

Here, this work aims to adapt nanoindentation mapping combined with a k-means algorithm as a high-throughput technique to study the nano-scale spatial changes in mechanical properties for a heterogeneous material. This technique can also classify the individual data points based on their properties. Hundreds to thousands of indents were performed on additively manufactured T91 at room temperature, 300°C, 400°C, and 500°C across a square area with a side length of 120 μm to 400 μm. From this data, the hardness and reduced modulus at each point could be calculated and mapped. Using k-means clustering, we were able to arrange the data into three or four clusters corresponding roughly to the ferritic and martensitic phases as well as one or two intermediate clusters sampling both the phases. The hardness of these two phases appears to be quite stable as a function of temperature. Nanoindentation mapping and the k-means algorithm can therefore be used to rapidly assess the feasibility of heterogeneous materials under extreme conditions, such as nuclear reactor steels.

36 MATERIALS SCIENCE↗

Data-Driven Protection Software to classify fault locations by protective zone in distribution systems with high PV penetration

The software contains (a) the source codes to generate Point-on-Wave (PoW) transient data for any feeder model in Alternative Transient Program (ATP) format. Codes provide options to change different steady state settings, including the loading condition and PV capacity and transient state setting like faults type, location and initiation time (b) data post-processing source code to converted data from native format to COMTRADE, csv, HDF5 (c) Docker container to train CNN to classify fault locations by protective zone. The container takes dataset and other training parameters (sampling rate, training epochs, batch size etc) as input to train CNN. The container writes back the trained CNN model, training and testing metrics and plots to the local workstation

Ramesh, Meghana↗