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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Novel Lightweight, Low-Cost Heliostat for Concentrating Solar Power (SBIR Phase I Final Report)

The overall goal of this Department of Energy (DOE) SBIR Phase I project was to demonstrate the feasibility of the L.Garde, Inc. heliostat mirror facet for use in concentrated solar power applications. Prior to this Phase I project, L.Garde, Inc. developed a design for a lightweight and low cost mirror facet and successfully fabricated small scale (0.667 m 2 ) with a mirror surface flatness of 0.7 mrad. Therefore, the focus of the Phase I effort was to (1) demonstrate scalability by fabricating larger size mirrors while retaining the same mirror surface flatness, (2) demonstrate the design can withstand operating environment conditions through field testing, and (3) perform cost analysis to show the heliostat mirror facet design can meet DoE goals of < 12 kg/m2 and <$30/m 2 . During the Phase I project, L.Garde successfully fabricated large area (1.395 m 2 ) heliostat mirror facets, with a mass per unit area of 8 kg/m 2 and a cost of $29.80/m 2 . Surface flatness measurements (using contact probe technique) were performed on the mirror surface and results showed a flatness of 0.68 mrad, which were in agreement with previously fabricated small scale mirror facets. Slope error measurements was also performed on the mirror surface and results showed a slope error of 0.77 mrad which also was in agreement with previously fabricated small scale mirror facets. One large area mirror facet was subjected to a three (3) month field test. Surface flatness and slope error measurements were performed on the mirror surface after the field test and results were 0.663 mrad and 0.58 mrad respectively. The large scale heliostat mirror facets were also subjected to accelerated aging. However, during this exposure we observed failure due to the breaking of the mirror facets. Further investigation into the source of the failure showed that the mirror component alone showed signs of degradation during the same accelerated aging test. We believe that moisture ingress is occurring when subjected to high humidity, leading to buildup of water with the layers of protective paints and resulting in mirror breakage when water expands in freezing conditions. In order to mitigate or eliminate this issue, a new weatherproofing strategy may be implemented or a new mirror component may be used that is able to survive accelerated aging conditions.

14 SOLAR ENERGY↗
DOE OSTI2022

High strain rate deformation of aged TRIP Ti-10V-2Fe-3Al (wt.%) examined by in-situ synchrotron X-ray diffraction

Transformation Induced Plasticity (TRIP) is a promising avenue for tailoring the work hardening response of metastable $β$ titanium (Ti) alloys. Here we show that aged TRIP Ti-10V-2Fe-3Al (wt.%) maintains higher elongations and flow stresses as strain rate increases, if phase stability and microstructural characteristics are tuned. Low temperature aging influences the matrix $β$ phase stability by $ω$ phase precipitation, which affords a promising way to impact the TRIP effect and obtain desirable mechanical properties, ranging from high damping capacity to good strength/ductility combinations. Although TRIP is active during quasi-static and dynamic testing up to 2000 s –1 , increasing aging time and/or strain rate reduces the overall propensity for the TRIP effect and extent of transformation, which occurs rapidly just at the onset of yielding. Importantly, TRIP with $ω$ phase precipitation provides interesting alloying, microstructure, and property design strategies for engineering applications like lightweight protective structures, where high strains and the need for energy absorption are encountered.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Evaluating and modeling the effects of surface sampling factors on the recovery of organic chemical attribution signatures using the accelerated diffusion sampler and solvent extraction

In this study, an experimental design matrix was created and executed in order to test the effects of various real-world factors on the ability of the (1) accelerated diffusion sampler with solid phase micro-extraction (ADS-SPME) and (2) solvent extraction to capture organic chemical attribution signatures (CAS) from dimethyl methylphosphonate (DMMP) spiked onto painted wall board (PWB) surfaces. The DMMP CAS organic impurities sampled by ADS-SPME and solvent extraction were analyzed by gas chromatography/mass spectrometry (GC/MS). The number of detected DMMP CAS impurities and their respective GC/MS peak areas were determined as a function of DMMP stock, DMMP spiked volume, exposure time, SPME sampling time, and ADS headspace pressure. Based on the statistical analysis of experimental results, several general conclusions are made: (1) ADS-SPME with vacuum (i.e., reduced pressure) increased the amount of detected CAS impurity, as measured by GC/MS peak area, by a factor of 1.7 to 1.9 for PWB under certain experimental conditions, (2) the amount of detected CAS impurity was most influenced by spiked volume, stock, and ADS headspace pressure, (3) the ADS had no measurable effect on the number of detected DMMP impurities, that is, the ADS (with and without reduced pressure) had no practical effect on the DMMP impurity profile collected from spiked PWB, and (4) solvent extraction out performed ADS-SPME in terms of consistently capturing all or most of the targeted DMMP impurities from spiked PWB.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Roofline Analysis in the Intel® Advisor to Deliver Optimized Performance for applications on Intel® Xeon Phi™ Processor

In this session we show, in two case studies, how the roofline feature of Intel Advisor has been utilized to optimize the performance of kernels of the XGC1 and PICSAR codes in preparation for Intel Knights Landing architecture. The impact of the implemented optimizations and the benefits of using the automatic roofline feature of Intel Advisor to study performance of large applications will be presented. This demonstrates an effective optimization strategy that has enabled these science applications to achieve up to 4.6 times speed-up and prepare for future exascale architectures. # Goal/Relevance of Session The roofline model [1,2] is a powerful tool for analyzing the performance of applications with respect to the theoretical peak achievable on a given computer architecture. It allows one to graphically represent the performance of an application in terms of operational intensity, i.e. the ratio of flops performed and bytes moved from memory in order to guide optimization efforts. Given the scale and complexity of modern science applications, it can often be a tedious task for the user to perform the analysis on the level of functions or loops to identify where performance gains can be made. With new Intel tools, it is now possible to automate this task, as well as base the estimates of peak performance on measurements rather than vendor specifications. The goal of this session is to demonstrate how the roofline feature of Intel Advisor can be used to balance memory vs. computation related optimization efforts and effectively identify performance bottlenecks. A series of typical optimization techniques: cache blocking, structure refactoring, data alignment, and vectorization illustrated by the kernel cases will be addressed. # Description of the codes ## XGC1 The XGC1 code [3] is a magnetic fusion Particle-In-Cell code that uses an unstructured mesh for its Poisson solver that allows it to accurately resolve the edge plasma of a magnetic fusion device. After recent optimizations to its collision kernel [4], most of the computing time is spent in the electron push (pushe) kernel, where these optimization efforts have been focused. The kernel code scaled well with MPI+OpenMP but had almost no automatic compiler vectorization, in part due to indirect memory addresses and in part due to low trip counts of low-level loops that would be candidates for vectorization. Particle blocking and sorting have been implemented to increase trip counts of low-level loops and improve memory locality, and OpenMP directives have been added to vectorize compute-intensive loops that were identified by Advisor. The optimizations have improved the performance of the pushe kernel 2x on Haswell processors and 1.7x on KNL. The KNL node-for-node performance has been brought to within 30% of a NERSC Cori phase I Haswell node and we expect to bridge this gap by reducing the memory footprint of compute intensive routines to improve cache reuse. ## PICSAR is a Fortran/Python high-performance Particle-In-Cell library targeting at MIC architectures first designed to be coupled with the PIC code WARP for the simulation of laser-matter interaction and particle accelerators. PICSAR also contains a FORTRAN stand-alone kernel for performance studies and benchmarks. A MPI domain decomposition is used between NUMA domains and a tile decomposition (cache-blocking) handled by OpenMP has been added for shared-memory parallelism and better cache management. The so-called current deposition and field gathering steps that compose the PIC time loop constitute major hotspots that have been rewritten to enable more efficient vectorization. Particle communications between tiles and MPI domain has been merged and parallelized. All considered, these improvements provide speedups of 3.1 for order 1 and 4.6 for order 3 interpolation shape factors on KNL configured in SNC4 quadrant flat mode. Performance is similar between a node of cori phase 1 and KNL at order 1 and better on KNL by a factor 1.6 at order 3 with the considered test case (homogeneous thermal plasma).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Tailoring Microstructure and Mechanical Properties of Additively-Manufactured Ti6Al4V Using Post Processing

Additively-manufactured Ti-6Al-4V (Ti64) exhibits high strength but in some cases inferior elongation to those of conventionally manufactured materials. Post-processing of additively manufactured Ti64 components is investigated to modify the mechanical properties for specific applications while still utilizing the benefits of the additive manufacturing process. The mechanical properties and fatigue resistance of Ti64 samples made by electron beam melting were tested in the as-built state. Several heat treatments (up to 1000 °C) were performed to study their effect on the microstructure and mechanical properties. Phase content during heating was tested with high reliability by neutron diffraction at Los Alamos National Laboratory. Two different hot isostatic pressings (HIP) cycles were tested, one at low temperature (780 °C), the other is at the standard temperature (920 °C). The results show that lowering the HIP holding temperature retains the fine microstructure (~1% β phase) and the 0.2% proof stress of the as-built samples (1038 MPa), but gives rise to higher elongation (~14%) and better fatigue life. The material subjected to a higher HIP temperature had a coarser microstructure, more residual β phase (~2% difference), displayed slightly lower Vickers hardness (~15 HV10N), 0.2% proof stress (~60 MPa) and ultimate stresses (~40 MPa) than the material HIP’ed at 780 °C, but had superior elongation (~6%) and fatigue resistance. Heat treatment at 1000 °C entirely altered the microstructure (~7% β phase), yield elongation of 13.7% but decrease the 0.2% proof-stress to 927 MPa. The results of the HIP at 780 °C imply it would be beneficial to lower the standard ASTM HIP temperature for Ti6Al4V additively manufactured by electron beam melting.

36 MATERIALS SCIENCE↗
DOE OSTI2018

B2 Grain Growth Behavior of a Ti-22Al-25Nb Alloy Fabricated by Hot Pressing Sintering

Grain growth behavior of a powder metallurgy (P/M) Ti-22Al-25Nb alloy was investigated by applying a series of isothermal treatment tests over a wide range of temperatures and holding times. An isothermal treatment scheme was conducted in the B2 phase region (1070-1110 °C) and α{sub 2} + B2 phase region (1010-1050 °C) at holding times of 10, 30 min, 1, 2, and 3 h, respectively. The effects of temperature and holding time on the microstructure evolution and microhardness of the P/M Ti-22Al-25Nb alloy at elevated temperatures were evaluated using optical microscope, scanning electron microscope, x-ray diffraction, and Vickers hardness test techniques. The results revealed that the alloy’s treated microstructure was closely linked to temperature and holding time, respectively. The change law of B2 grain growth with holding time and temperature can be well interpreted by the Beck equation and Hillert equation, respectively. The B2 grain growth exponent n and activation energy Q were acquired based on experimental data in the α{sub 2} + B2 and B2 phase regions. In addition, the grain growth contour map for the P/M Ti-22Al-25Nb alloy was constructed to depict variations in B2 grain size based on holding time and temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Discovery and ramifications of incidental Magnéli phase generation and release from industrial coal-burning

Coal, as one of the most economic and abundant energy sources, remains the leading fuel for producing electricity worldwide. Yet, burning coal produces more global warming CO 2 relative to all other fossil fuels, and it is a major contributor to atmospheric particulate matter known to have a deleterious respiratory and cardiovascular impact in humans, especially in China and India. Here we have discovered that burning coal also produces large quantities of otherwise rare Magnéli phases (Ti x –1 with 4 ≤ x ≤ 9) from TiO 2 minerals naturally present in coal. This provides a new tracer for tracking solid-state emissions worldwide from industrial coal-burning. In its first toxicity testing, we have also shown that nanoscale Magnéli phases have potential toxicity pathways that are not photoactive like TiO 2 phases, but instead seem to be biologically active without photostimulation. In the future, these phases should be thoroughly tested for their toxicity in the human lung.

Yang, Yi↗
DOE OSTI2026

One Earth Energy Static and Dynamic Reservoir Modeling

This report presents the static and dynamic reservoir modeling conducted for the CarbonSAFE Phase III Illinois Storage Corridor project to assess the feasibility of commercial-scale CO 2 storage in the Mt. Simon Sandstone at the One Earth Energy (OEE) site in McLean County, Illinois. Three-dimensional geocellular models of the Mt. Simon storage complex were developed in Petrel ® by integrating petrophysical log data, core analyses, and seismic surveys from the OEE #1 stratigraphic test well and two nearby wells, with multiple model versions created as new data became available. Dynamic reservoir simulations, performed using Landmark's Nexus software, progressed through three phases (preliminary, sensitivity, and UIC Class VI permit studies) evaluating injection scenarios across varying rates, well orientations, permeability models, and multi-well configurations. Results demonstrate that commercial-scale storage is feasible: three injection wells spaced approximately one mile apart can store a total of 90 million tonnes of CO 2 over 20 years, producing a combined plume with an equivalent radius of 3.2 miles and a maximum pressure-front-defined Area of Review of 178 mi 2 at the end of injection that diminishes to 34 mi 2 after 50 years of post-injection monitoring. Sensitivity analyses indicate that a 20% change in porosity or permeability yields approximately a 7% change in AoR radius, and that perforating the high-permeability arkosic zone minimizes the pressure front compared to injection in the upper Mt. Simon Sandstone.

09 BIOMASS FUELS↗
DOE OSTI2025

Basin-Size Mapping: Prediction of Metastable Polymorph Synthesizability Across TaC–TaN Alloys

The sizes of the basins of attraction on the potential energy surface are helpful indicators in determining the experimental synthesizability of metastable phases. In principle, these basins can be controlled with changes in thermodynamic conditions such as composition, pressure, and surface energy. Herein, we use random structure sampling to computationally study how alloying smoothly perturbs basin of attraction sizes. The TaC 1-x N x pseudobinary is an ideal test system given the structural and polymorphic contrast of its parent compounds and their technological relevance as epitaxial substrates for Al 1-x Ga x N. While we find limited thermodynamic stability across all computationally observed phases, random structure sampling shows a significant composition region where the rocksalt basin dominates. As such, we predict the potential for the nonequilibrium synthesis of metastable rocksalt TaC 1-x N x alloys as substrates for Al 1-x Ga x N. At higher nitrogen concentrations, other low-energy metastable polymorphs emerge that continue to retain the hexagonal close packing suitable for III-N growth. Confidence in these trends was established through uncertainty quantification of the basin sizes and energy distributions; such analysis utilized the Beta and Dirichlet distributions. In conclusion, we also find (a) polymorph basin sizes can be rationalized in terms of energetic preferences for different coordination environments; and (b) basin sizes universally shrink with increasing nitrogen content, making the system more prone to amorphous growth.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Structure of the Fe-Mn-Si alloys submitted to γ ↔ ε thermocycling

Highlights: • The effect of thermal cycling Fe–Mn–Si alloys is studied. • In situ neutron diffraction, internal friction, DSC and TEM results are analysed. • Lattice defects accumulation both in martensitic and austenitic phases. • Microstrains in the γ and ε phases are estimated. - Abstract: The accumulation of defects and internal stresses and related changes of the direct and reverse martensitic transition (MT) on thermocycling over the phase transition in different Fe–Mn–Si alloys are investigated by in situ neutron diffraction, TEM, SEM-EBSD, DSC and mechanical spectroscopy. The temperature of direct MT in Fe-22Mn-3Si, Fe-26Mn-4Si and Fe-26Mn-7Si alloys decreases during thermal cycling, while that of the inverse MT increases, which causes a widening of the transformation hysteresis. Transmission electron microscopy shows that a large number of dislocations and stacking faults are formed in both martensitic and austenitic phases in the Fe-22Mn-3Si annealed alloy submitted to γ ↔ ε thermocycling. From in situ neutron diffraction tests on Fe-22Mn-3Si annealed alloy and classical Williamson-Hall analysis, we found that the microstrains in the ε-martensite after 1 and 12 thermocycles are roughly twice higher as compared with the austenite phase.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Detection efficiency measurement and operational tests of the X-Arapuca for the first module of DUNE far detector

The Deep Underground Neutrino Experiment (DUNE) is a dual-site experiment for long-baseline neutrino oscillation studies, able to resolve the neutrino mass hierarchy and measure δ$_{CP}$. DUNE will also have sensitivity to supernova neutrinos and to processes beyond the Standard Model, such as nucleon decay searches. The Far Detector (FD) will consist of four liquid argon TPC (17.5 kt total mass) with systems for the detection of charge and scintillation light produced by an ionization event. The charge detection system permits both calorimetry and position determination. In addition, the photon-detection system (PDS) enhances the detector capabilities for all DUNE physics drivers. The PDS of the first FD module consists of light collector modules placed in the inactive space between the innermost wire planes of the TPC anode. The light collectors, the so-called X-ARAPUCAS, are functionally a light trap that captures wavelength-shifted photons inside boxes with highly reflective internal surfaces where they are guided to Silicon Photo-multipliers (SiPM) by wavelength-shifting (WLS) bars. Functionality and operational tests of the X-ARAPUCAS to be installed in ProtoDUNE-SP phase II (FD DUNE prototype at the scale 1:20), as well as the measurement of their absolute detection efficiency is reported in this publication.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Influence of Heave Plate Topology on Reaction Force

In this study, we explore the role of heave plate topology on fluid reaction forces using three, representative shapes: a hexagonal flat plate, a hexagonal conic with an open top, and the same with a closed top that encloses a fluid mass. We force each test article sinusoidally in a quiescent tank and decompose the reaction force using forms of the Morison equation for phase-invariant and phase-dependent parameterizations. We find that a flat plate generates 5.3 % more fluid reaction force than the open conic topology, and 21.4% more than the enclosed conic. Asymmetric topologies generate asymmetric reaction forces, but the magnitude of asymmetry is limited by nearly symmetric fluid inertia forces, which dominate over drag for these test articles. Additionally, we observe asymmetric vortex dynamics for the flat plate when the Keulegan-Carpenter number is between 1 and 2, accompanied by a shift in the phase of the peak force by of the oscillation period. As a consequence of this shift, the hydrodynamic coefficients estimated from the phase-dependent Morison equation decomposition are asymmetric, suggesting that phase-dependent representations may not provide physical insight in some hydrodynamic regimes.

added mass↗
DOE OSTI2019

Information Products & Communications Materials for COR and Contractors' Meetings [Slides]

Contents include the following: 1) Large Scale CO 2 Storage in the Lower Tuscaloosa Massive Sand Formation, December 12, 2007; 2) CoalFleet Program Update and Workshops, July 26-28, 2005; 3) Regional Carbon Sequestration Partnership Annual Review Meeting, November 18, 2009; 4) SECARB U. S. Regional Partnerships from Pilot to Demonstration, November 5, 2009; 5) The SECARB Anthropogenic Test–CO 2 Capture/Transportation/Storage, August 21-23, 2012; 6) Citronelle Project–Experiences With Permitting and Regulations on CCS, August 21, 2013; 7) Partnering With Industry for Large Scale CCS Projects, August 22, 2013; 8) Plant Barry-Citronelle Field Project, August 13, 2104; 9) SECARB's Early Test at Cranfield, Mississippi; 10) SECARB Partnership Early Test at Cranfield Status, August 18-20, 2015; 11) Citronelle Project, August 18, 2015; 12) Plant Barry 25 MW Demo; 13) SECARB Phase III Citronelle Project (Anthropogenic Test) in Alabama, August 18, 2015; 14) SECARB Early Test Retrospective; 15) SECARB Anthropogenic Test Lessons Learned, August 16-18, 2016; 16) SECARB Early Test at Cranfield, August 1-3, 2017; 17) Carbon Storage and Oil and Natural Gas Technologies Review Meeting, August 1-3, 2017; 18) SECARB Partnership Early Test at Cranfield, August 13-16, 2018; 19) SECARB Anthropogenic Test Update, August 13-16, 2018; 20) SECARB Partnership Early Test at Cranfield, August 26-30, 2019; 21) SECARB (Citronelle) Phase III, August 27, 2019.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Measurements and Model Improvement: Insight into NWP Model Error Using Doppler Lidar and Other WFIP2 Measurement Systems

Abstract Doppler-lidar wind-profile measurements at three sites were used to evaluate NWP model errors from two versions of NOAA’s 3-km-grid HRRR model, to see whether updates in the latest version 4 reduced errors when compared against the original version 1. Nested (750-m grid) versions of each were also tested to see how grid spacing affected forecast skill. The measurements were part of the field phase of the Second Wind Forecasting Improvement Project (WFIP2), an 18-month deployment into central Oregon–Washington, a major wind-energy-producing region. This study focuses on errors in simulating marine intrusions, a summertime, 600–800-m-deep, regional sea-breeze flow found to generate large errors. HRRR errors proved to be complex and site dependent. The most prominent error resulted from a premature drop in modeled marine-intrusion wind speeds after local midnight, when lidar-measured winds of greater than 8 m s −1 persisted through the next morning. These large negative errors were offset at low levels by positive errors due to excessive mixing, complicating the interpretation of model “improvement,” such that the updates to the full-scale versions produced mixed results, sometimes enhancing but sometimes degrading model skill. Nesting consistently improved model performance, with version 1’s nest producing the smallest errors overall. HRRR’s ability to represent the stages of sea-breeze forcing was evaluated using radiation budget, surface-energy balance, and near-surface temperature measurements available during WFIP2. The significant site-to-site differences in model error and the complex nature of these errors mean that field-measurement campaigns having dense arrays of profiling sensors are necessary to properly diagnose and characterize model errors, as part of a systematic approach to NWP model improvement. Significance Statement Dramatic increases in NWP model skill will be required over the coming decades. This paper describes the role of major deployments of accurate profiling sensors in achieving that goal and presents an example from the Second Wind Forecast Improvement Program (WFIP2). Wind-profile data from scanning Doppler lidars were used to evaluate two versions of HRRR, the original and an updated version, and nested versions of each. This study focuses on the ability of updated HRRR versions to improve upon predicting a regional sea-breeze flow, which was found to generate large errors by the original HRRR. Updates to the full-scale HRRR versions produced mixed results, but the finer-mesh versions consistently reduced model errors.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

High Temperature Additive Architectures for 65% Efficiency (Final Report)

GE Power (GEP) proposed a development program that targets advanced high temperature additive components that contribute towards the DOE’s goal for advanced gas turbines that are capable of 65%, or greater, efficiency in combined cycle application. GEP proposed to leverage state-of-the-art additive manufacturing to develop novel and innovative component airfoil and end wall architectures that provide cooling flow savings while maintaining the component durability expected in today’s gas turbines. The objective of this program was to develop advanced component designs and architectures enabled by additive manufacturing, and the materials systems and additive manufacturing technology required for these designs. This Phase I program leveraged existing design and analysis knowledge and techniques for additive materials and methods and utilized extensive analytical evaluations to develop and refine designs for advanced turbine hot gas path (HGP) components. The design will be the basis for development and testing in a potential Phase II program. The goal of this Phase I program was to establish a feasible conceptual design for advanced additive turbine hot section components along with a technology maturation plan involving testing to address risk areas and needed validation. It was approached through two primary elements: 1) conceptual design and analysis of wall architectures, advanced airfoil cooling concepts, and advanced system-level concepts, and 2) investigation of additive modalities and associated materials systems. The Phase I program has concluded with the down-select of a primary design concept for a potential Phase II program.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Temperature dependence of magnetic anisotropy and magnetoelasticity from classical spin-lattice calculations

Here we present a classical molecular-spin dynamics (MSD) methodology that enables accurate computations of the temperature dependence of the magnetocrystalline anisotropy as well as magnetoelastic properties of magnetic materials. The nonmagnetic interactions are accounted for by a spectral neighbor analysis potential (SNAP) machine-learned interatomic potential, whereas the magnetoelastic contributions are accounted for using a combination of an extended Heisenberg Hamiltonian and a Néel pair interaction model, representing both the exchange interaction and spin-orbit-coupling effects, respectively. All magnetoelastic potential components are parameterized using a combination of first-principles and experimental data. Our framework is applied to the α phase of iron. Initial testing of our MSD model is done using a 0 K parametrization of the Néel interaction model. After this, we examine how individual Néel parameters impact the $B$ 1 and $B$ 2 magnetostrictive coefficients using a moment-independent δ sensitivity analysis. The results from this study are then used to initialize a genetic algorithm optimization which explores the Néel parameter phase space and tries to minimize the error in the B 1 and B 2 magnetostrictive coefficients in the range of 0–1200 K. Our results show that while both the 0 K and genetic algorithm optimized parametrization provide good experimental agreement for $B$ 1 and $B$ 2 , only the genetic algorithm optimized results can capture the second peak in the $B$ 1 magnetostrictive coefficient which occurs near approximately 800 K.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗