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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Oxidation and Extraction of Americium(VI) from Lanthanides

Partitioning and transmutation of americium and curium has been the subject of significant research in the nuclear fuel cycle over the past two decades. Numerous approaches have been studied to separate these elements from the lanthanide elements to enable their recycle and transmutation. Americium is one of the primary long-term heat sources in used nuclear fuel, which may impact repository loading. The lanthanides are both a) neutron poisons, reducing reactor performance, if recycled, and b) can chemically interact with fuel cladding to cause early failure, if present in sufficient concentration. Chemical separation approaches for heterogeneous fuel recycle, typically utilize proven technology (PUREX or modifications to the PUREX process) to remove uranium and plutonium from the dissolved fuel (and if desired, can remove neptunium as well). Follow-on processing is then required to separate the americium and curium, or the americium alone (for target fabrication). In a homogeneous recycle approach, the bulk of the uranium is typically separated first, followed by additional processing to remove the transuranic elements as a group. Because of the chemical similarity of the americium with the lanthanides, and particularly with curium, these separate processes are difficult. Utilizing the unique valence states of americium (primarily the (VI) oxidation state), opens up new opportunities for the separation of americium for either heterogeneous recycle (enabling americium separation alone) or homogeneous recycle (separating americium together with plutonium and neptunium). The US Department of Energy Fuel Cycle Technologies program has been researching methods to oxidize americium and to extract it from lanthanides as americium(VI), preferably from molar nitric acid solutions. Early efforts identified sodium bismuthate as an effective oxidant, which enabled testing of the extraction of americium(VI) by tributyl phosphate and diamylamylphosphonate. Successful extraction of americium(VI) was demonstrated in this system, in both batch contact laboratory tests and in centrifugal contactors; however, the sodium bismuthate is a solid, and must be in excess of saturation with the solution. This creates some engineering challenges in the process. A significant effort to identify alternative oxidants has led to a number of promising approaches. Silver-catalyzed ozone, copper(III) periodate, and electrochemical oxidation of americium from the trivalent to hexavalent state have all been successfully demonstrated in laboratory experiments. These approaches would enable oxidation and extraction of americium without having to filter solids. Once the americium is oxidized, a key issue is how long it will remain in the hexavalent state. Investigations have shown that some materials of construction (e.g., tantalum) do not reduce americium as quickly as stainless steel. Also, alternative extractants, such as amides, do not appear to reduce the americium as rapidly as the phosphate or phosphonate extractants. While still early in their development, these advances in the technology offer some positive indications that a workable extraction process for the separation of americium(VI) can be realized in the near future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Economic risk analysis for the capture of a distributed energy resource using modular chemical process intensification

Recent advances in the chemical process industry have allowed for the intensification of reactors and unit operations, by enhancing heat and mass transfer or combining multiple unit operations. Process intensification can enable chemical plants to be constructed in a more compact, modular fashion, offering improvements over conventional on-site approaches to capital construction, operations and maintenance. This modular chemical process intensification (MCPI) offers several benefits over conventional stick-built (CSB) plant construction in terms of reduced footprint, reduced energy consumption, lower cost, less waste and improved safety and quality control. However, acceptance of MCPI over CSB construction practices within the chemical industry can be impeded by the uncertain risks associated with investing in new technology. Furthermore, the work here documents a case study during the development of a modular chemical plant for capturing distributed energy resources within chemical production. This MCPI approach to plant construction is contrasted with a CSB approach for producing the same chemical product. Data collection tools were developed, based on a literature review, and data was collected from the technology developer to understand the process technology. Sensitivity analysis was then conducted to analyze the business rationale for the application of MCPI over CSB across several market scenarios. It was found that MCPI would be better suited for capacities up to 150 000 metric tons per year, but that improvement in payback period was needed. Additionally, for MCPI approach to achieve acceptable payback periods, efforts are needed to reduce the cost of capital equipment and compress the schedule for ramping up modular production.

42 ENGINEERING↗
DOE OSTI2018

Causal Analysis Report for "Demolition of Historic and Yet-to-be-Determined Radar Towers at TTR Without Completing Required NEPA Process"

Two radar towers at the Tonopah Test Range (TTR), Contraves Towers 22-00 and 12-00, were torn down prior to completion of the required National Environmental Policy Act (NEPA) process. National Technology and Engineering Solutions of Sandia, LLC, (NTESS) submission of the NEPA checklist triggered a Sandia Field Office (SFO) review of the proposed work scope and was to include a required consultation between SFO and the Nevada State Historic Preservation Office (SHPO) to assess any adverse effect(s) on historic properties or contributing element(s) to a historic district and, if so, determine a resolution. Following the consultation, SFO provides approval/denial of the proposed work detailed on the submitted NEPA checklist. Contraves Tower 22-00 is a historic structure, as formally determined by the SFO in consultation with the SHPO. The historical eligibility of Contraves Tower 12-00 is yet to be determined. On February 13, 2018, NTESS notified SFO that Contraves Tower 22-00 at TTR was torn down in May 2017 prior to completion of the required the NEPA process, including consultation with the SHPO. NTESS submitted two NEPA checklists to SFO in 2016 for the removal of several structures no longer required by NTESS. The first NEPA checklist listed three historic structures (one of which was Contraves Tower 22-00) and SFO determination on whether consultation with the SHPO is necessary as well as approval/denial of the NEPA checklist is pending. The second NEPA checklist listed five non-historic structures, one of which was Contraves Tower 12-00. SFO approved the NEPA checklist covering non historic structures except for the Contraves Tower 12-00, as the Contraves Tower 12-00 requires further consultation with the SHPO by SFO. Only after completion of the consultation would SFO determine approval/denial on the remaining property cited within the NEPA checklist. In late January 2018, NTESS personnel discovered that Contraves Tower 22-00 was no longer listed in the Facility Information Management System (FIMS). Upon further investigation, NTESS personnel verified that the Contraves Tower 22-00 had been removed in May 2017. During the initial extent of condition, it was discovered that Contraves Tower 12-00 had also been torn down in May 2017 as part of this same destruction and demolition (D&D) activity. Both Contraves Towers 22-00 and 12-00) had been torn down prior to completion of the NEPA process, including consultation with the SHPO.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Physics-Informed and Data-Driven Prediction of Residual Stress in Three-Dimensional Machining

Efficient and reliable prediction of machining-induced residual stress (RS) is a key requirement for truly integrated computational materials engineering (ICME). Currently available process modeling approaches, including empirical, analytical, and numerical methodologies lack predictive power and require substantial calibration and validation data. Moreover, most model-based approaches consider only two-dimensional (2D) (i.e., orthogonal), cutting processes. Meanwhile, industrial processes such as milling, turning, and drilling are inherently three-dimensional (3D). The present work attempts to bridge the gap between 2D and 3D through careful consideration of the process physics, including geometric, kinematic, and size-effect constraints to realize robust prediction of how RS develops in 3D machining. Using a novel in-situ experimental technique and digital image correlation (DIC) to determine equivalent Hertzian contact widths, contact pressures, and friction coefficients, the proposed methodology leverages a discretized conversion algorithm that includes multi-pass shakedown effects. This paper presents a semi-analytical model to predict machining-induced RS in 3D turning operations, which are used representatively for 3D processes more generally. Rather than follow a ‘brute force’ 3D FEM approach or conduct countless experiments to train a purely data-driven machine learning algorithm, the proposed approach builds on previous 2D modeling work. Through careful consideration of the process physics, including complex geometry/kinematic considerations of 3D turning, the authors demonstrated an experimentally calibrated approach, as well as validation based on published RS data. Model predictions and previously published measurement data of RS depth profiles for turning of Inconel 718 were compared for a range of process parameters. Correlation between the proposed 3D model and validation data was found to be within the margin of experimental error for most conditions. The proposed model appears to capture the overall behavior of 3D RS depth profiles with acceptable accuracy, particularly the key metrics of near-surface stress, peak stress magnitude and location, as well as overall stress profile depth. This report presents a physics-informed, data-driven approach for efficient calibration of a 2D model for machining-induced RS through DIC analysis of in-situ characterized subsurface displacement fields.

42 ENGINEERING↗
DOE OSTI2022

Engineering Design of a Linde-BASF Advanced Post-Combustion CO 2 Capture Technology at a Linde Steam Methane Reforming H 2 Plant

Linde carried out an initial engineering design study for a Linde-BASF advanced post combustion CO 2 capture technology to be installed at a commercial-scale steam methane reforming (SMR) hydrogen plant located in the US Gulf Coast. This pre-FEED equivalent study included following: (1) basic design, including specific project scope definition and design basis, (2) basic engineering, including development of process flow diagrams and heat & material balances, (3) inside the battery limit (ISBL) equipment and systems specification, (4) balance of plant outside the battery limit (OSBL) equipment and systems specifications, (5) technology maturation plan, (6) hazard and operability (HAZOP) review, (7) environmental, health and safety (EH&S) assessment and environmental permitting analysis, (8) constructability review, (9) ISBL and OSBL EPC cost estimation, and (10) commercial-scale techno-economic analysis including capital expenditures (CAPEX) and operating expenditures (OPEX) and CO 2 capture cost estimates.

08 HYDROGEN↗
DOE OSTI2019

Advancing Turbulent Spray and Combustion Models for Compression Ignition Engine Simulations

This thesis seeks to investigate the turbulent mixing influence on spray atomization and combustion processes encountered in compression ignition diesel engines. Despite greater thermal efficiency of diesel engine than spark ignition engine, the nature of stratified air-fuel mixture and non-premixed flame gives rise to unacceptable levels of nitrogen oxides (NOx) and particulate matter (PM), thus the use of diesel engines has often been limited to heavy-duty vehicle and industrial power sources. However, recent advancement in diesel engine combustion strategies, e.g. low temperature com-bustion (LTC), has demonstrated promising pathways towards improvement in the engine-out pollutants. Therefore, particularly in the effort of computer-aided en-gine design tasks, such a new engine design concept requires more accurate modeling techniques applicable over a broader range of engine operating conditions than those of conventional engine strategies. In the notion of challenges in new engine operat-ing conditions, this thesis aims to present successful implementation of improvement in numerical modeling techniques in high-pressure spray atomization and resulting turbulent spray flame of interest. Three-dimensional Computational Fluid Dynamics (CFD) in in-cylinder turbu-lent combustion is considered an integral part of engine design progress, but rather a cost-prohibitive to apply over a broad range of engine relevant conditions. In spite of successful use of existing spray atomization modeling, prior researchers have pointed out some degree of failure in LTC targeted injection strategies. Furthermore, finite rate and strong nonlinearity of chemistry influenced by local turbulent mixing still re-main in challenges to account for in cost-efficient CFD analysis. In this context, a new attempt of hybrid spray primary breakup modeling is presented and demonstrated in successful application aimed at LTC technique. In addition, the Representative Interactive Flamelets (RIF) model with aid of multi-flamelets approach is extensively assessed in terms of predictive capability against classical combustion model. The combustion model employed in this study are fully examined in the general diesel combustion metric, e.g., ignition delay and flame lift-off length as well as newly sug-gested test metric, combustion recession. The combustion recession has been recently idenfied, but still remain largely unknown. Since the governing physics of this phe-nomenon is characterized by turbulent mixing coupled with finite rate chemistry, this can be considered as a relevant test metric for turbulent combustion models. In ad-dition, very recent experimental studies have introduced a new non-sooting diesel combustion technique by manipulating direct injection method. The ducted fuel in-jection (DFI) has thus been demonstrated with its potential of low soot emissions. Knowing that the duct equipped ahead of injector nozzle was identifed to enhance turbulent mixing, investigations of DFI combustion may prove the effectiveness of turbulece-chemistry interaction modeling. This thesis presents comprehensive under-standings of aformentioned diesel combustion techniques in terms of several important physics keywords, e.g., turbulent mixing and detailed chemistry

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

ADVANCING TURBULENT SPRAY AND COMBUSTION MODELS FOR COMPRESSION IGNITION ENGINE SIMULATIONS

This thesis seeks to investigate the turbulent mixing influence on spray atomization and combustion processes encountered in compression ignition diesel engines. Despite greater thermal efficiency of diesel engine than spark ignition engine, the nature of stratified air-fuel mixture and non-premixed flame gives rise to unacceptable levels of nitrogen oxides (NOx) and particulate matter (PM), thus the use of diesel engines has often been limited to heavy-duty vehicle and industrial power sources. However, recent advancement in diesel engine combustion strategies, e.g. low temperature combustion (LTC), has demonstrated promising pathways towards improvement in the engine-out pollutants. Therefore, particularly in the effort of computer-aided engine design tasks, such a new engine design concept requires more accurate modeling techniques applicable over a broader range of engine operating conditions than those of conventional engine strategies. In the notion of challenges in new engine operating conditions, this thesis aims to present successful implementation of improvement in numerical modeling techniques in high-pressure spray atomization and resulting turbulent spray flame of interest. Three-dimensional Computational Fluid Dynamics (CFD) in in-cylinder turbulent combustion is considered an integral part of engine design progress, but rather a cost-prohibitive to apply over a broad range of engine relevant conditions. In spite of successful use of existing spray atomization modeling, prior researchers have pointed out some degree of failure in LTC targeted injection strategies. Furthermore, finite rate and strong nonlinearity of chemistry influenced by local turbulent mixing still remain in challenges to account for in cost-efficient CFD analysis. In this context, a new attempt of hybrid spray primary breakup modeling is presented and demonstrated in successful application aimed at LTC technique. In addition, the Representative Interactive Flamelets (RIF) model with aid of multi-flamelets approach is extensively assessed in terms of predictive capability against classical combustion model. The combustion model employed in this study are fully examined in the general diesel combustion metric, e.g., ignition delay and flame lift-off length as well as newly suggested test metric, combustion recession. The combustion recession has been recently idenfied, but still remain largely unknown. Since the governing physics of this phenomenon is characterized by turbulent mixing coupled with finite rate chemistry, this can be considered as a relevant test metric for turbulent combustion models. In addition, very recent experimental studies have introduced a new non-sooting diesel combustion technique by manipulating direct injection method. The ducted fuel injection (DFI) has thus been demonstrated with its potential of low soot emissions. Knowing that the duct equipped ahead of injector nozzle was identifed to enhance turbulent mixing, investigations of DFI combustion may prove the effectiveness of turbulece-chemistry interaction modeling. This thesis presents comprehensive understandings of aformentioned diesel combustion techniques in terms of several important physics keywords, e.g., turbulent mixing and detailed chemistry.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

O'Hare Airport roadway traffic prediction via data fusion and Gaussian process regression

This study proposes an approach of leveraging information gathered from multiple traffic data sources at different resolutions to obtain approximate inference on the traffic distribution of Chicago's O'Hare Airport area. Specifically, it proposes the ingestion of traffic datasets at different resolutions to build spatiotemporal models for predicting the distribution of traffic volume on the road network. Due to its good adaptability and flexibility for spatiotemporal data, the Gaussian process (GP) regression was employed to provide short-term forecasts using data collected by loop detectors (sensors) and supplemented by telematics data. The GP regression is used to make predictions of the distribution of the proportion of sensor data traffic volume represented by the telematics data for each location of the sensors. Consequently, the fitted GP model can be used to determine the approximate traffic distribution for a testing location outside of the training points. Policymakers in the transportation sector can find the results of this work helpful for making informed decisions relating to current and future transportation conditions in the area.

42 ENGINEERING↗
DOE OSTI2014

99 Tc Process Monitoring System In-Lab Performance Characterization

A 99 Tc Process Monitoring (Tc-Mon) System has been designed and built for deployment at the recently constructed 200 West Pump & Treat (200W P&T) Plant in the 200 West Area ZP-1 Operable Unit of the Hanford Site. The plant is operated by CH2M Hill Plateau Remediation Company (CHPRC). The Tc-Mon system was created through collaboration between Pacific Northwest National Laboratory (PNNL) and Burge Environmental, Inc. The design of the new system has been optimized based on experience from an earlier field test (2011) of a prototype system at the 200W-ZP-1 Interim Pump & Treat Plant.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Probing the pH Effect on Boehmite Particles in Water Using Vacuum Ultraviolet Single-Photon Ionization Mass Spectrometry

Boehmite has been widely used in theoretical research and industry, especially for hazardous material processing. For the liquid-phase treating process, the interfacial properties of boehmite are believed to be affected by pH conditions, which change its physicochemical behavior. However, molecular-level detection on cluster ions is challenging when using bulk approaches. Herein we employ in situ vacuum ultraviolet single-photon ionization mass spectrometry (VUV SPI-MS) coupled with a vacuum-compatible microreactor system for analysis at the liquid–vacuum interface (SALVI) to investigate the solute molecular composition of boehmite under different pH conditions for the first time. The mass spectral results show that more complex clustering of solute molecules exists at the solid–liquid (s–l) interface than conventionally perceived in a “simple” aqueous solution. Besides solute ions, such as boehmite molecules and fragments, the composition and appearance energies of these newly discovered solvated cluster ions are determined by VUV SPI-MS in different pH solutions. We offer new results for the pH-dependent effect of boehmite and provide insights into a more detailed solvation mechanism at the s–l interface. By comparing the key products under different pH conditions, fundamental understanding of boehmite dissolution is revealed to assist the engineering design of waste processing and storage solutions.

SALVI↗
DOE OSTI2016

Validation metrics for turbulent plasma transport

Developing accurate models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. In modern computer science and engineering, formal verification and validation processes are used to assess model accuracy and establish confidence in the predictive capabilities of a given model. This paper provides an overview of the key guiding principles and best practices for the development of validation metrics, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. Particular emphasis is given to the importance of uncertainty quantification and its inclusion within the metrics, and the need for utilizing synthetic diagnostics to enable quantitatively meaningful comparisons between simulation and experiment. As a starting point, the structure of commonly used global transport model metrics and their limitations is reviewed. An alternate approach is then presented, which focuses upon comparisons of predicted local fluxes, fluctuations, and equilibrium gradients against observation. The utility of metrics based upon these comparisons is demonstrated by applying them to gyrokinetic predictions of turbulent transport in a variety of discharges performed on the DIII-D tokamak [J. L. Luxon, Nucl. Fusion 42, 614 (2002)], as part of a multi-year transport model validation activity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Electrochemical-assisted leaching of active materials from lithium ion batteries

The development of a circular economy for lithium-ion batteries (LIB) is essential to realize decarbonization and an electrified energy market. However, the current commercial operations that recover valuable constituents from LIBs require significant energy and reagents, which create toxic emissions and additional waste. We report an electrochemical-based method for leaching valuable metals from the active materials of mixed shredded LIBs. In this process, the use electrons, as green reagent, allows the use and regeneration of Fe 2+ in low concentrations as substitute for hydrogen peroxide as a reducing agent. Leaching in a membrane separated two-compartment electrochemical cell contributes to decrease the acid requirements as H+ can be generated electrochemically. With this design, leaching efficiencies over 96% for the active metals (Li, Co, Mn, and Ni) were demonstrated at pulp densities up to 240 g/L. Copper present in the active material is electrowon and recovered separately. Preliminary cost analyses demonstrate ca. 80% reduction in energy and chemical costs as compared to traditional hydrometallurgical routes.

25 ENERGY STORAGE↗
DOE OSTI2013

Development of Production-Intent Plug-In Hybrid Vehicle Using Advanced Lithium-Ion Battery Packs with Deployment to a Demonstration Fleet

The primary goal of this project was to speed the development of one of the first commercially available, OEM-produced plug-in hybrid electric vehicles (PHEV). The performance of the PHEV was expected to double the fuel economy of the conventional hybrid version. This vehicle program incorporated a number of advanced technologies, including advanced lithium-ion battery packs and an E85-capable flex-fuel engine. The project developed, fully integrated, and validated plug-in specific systems and controls by using GM’s Global Vehicle Development Process (GVDP) for production vehicles. Engineering Development related activities included the build of mule vehicles and integration vehicles for Phases I & II of the project. Performance data for these vehicles was shared with the U.S. Department of Energy (DOE). The deployment of many of these vehicles was restricted to internal use at GM sites or restricted to assigned GM drivers. Phase III of the project captured the first half or Alpha phase of the Engineering tasks for the development of a new thermal management design for a second generation battery module. The project spanned five years. It included six on-site technical reviews with representatives from the DOE. One unique aspect of the GM/DOE collaborative project was the involvement of the DOE throughout the OEM vehicle development process. The DOE gained an understanding of how an OEM develops vehicle efficiency and FE performance, while balancing many other vehicle performance attributes to provide customers well balanced and fuel efficient vehicles that are exciting to drive. Many vehicle content and performance trade-offs were encountered throughout the vehicle development process to achieve product cost and performance targets for both the OEM and end customer. The project team completed two sets of PHEV development vehicles with fully integrated PHEV systems. Over 50 development vehicles were built and operated for over 180,000 development miles. The team also completed four GM engineering development Buy-Off rides/milestones. The project included numerous engineering vehicle and systems development trips including extreme hot, cold and altitude exposure. The final fuel economy performance demonstrated met the objectives of the PHEV collaborative GM/DOE project. Charge depletion fuel economy of twice that of the non-PHEV model was demonstrated. The project team also designed, developed and tested a high voltage battery module concept that appears to be feasible from a manufacturability, cost and performance standpoint. The project provided important product development and knowledge as well as technological learnings and advancements that include multiple U.S. patent applications.

25 ENERGY STORAGE↗
DOE OSTI2021

The mechanics of brittle granular materials with coevolving grain size and shape

The influence of particle shape on the mechanics of sand is widely recognized, especially in mineral processing and geomechanics. However, most existing continuum theories for engineering applications do not encompass the morphology of the grains and its evolution during comminution. Similarly, the relatively few engineering models accounting for grain-scale processes tend to idealize particles as spheres, with their diameters considered as the primary and sole geometric descriptor. This paper inspires a new generation of constitutive laws for crushable granular continua with arbitrary, yet evolving, particle morphology. We explore the idea of introducing multiple grain shape descriptors into Continuum Breakage Mechanics (CBM), a theory originally designed to track changes in particle size distributions during confined comminution. We incorporate the influence of these descriptors on the elastic strain energy potential and treat them as dissipative state variables. In analogy with the original CBM, and in light of evidence from extreme fragmentation in nature, the evolution of the additional shape descriptors is postulated to converge towards an attractor. Comparisons with laboratory experiments, discrete element analyses and particle-scale fracture models illustrate the encouraging performance of the theory. The theory provides insights into the feedback among particle shape, compressive yielding and inelastic deformation in crushable granular continua. These results inspire new questions that should guide future research into crushable granular systems using particle-scale imaging and computations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Creep Behavior of a High-$\gamma^{\prime}$ Ni-Based Superalloy Fabricated via Electron Beam Melting

Additive manufacturing enables the fabrication of complex engineering components previously inaccessible through traditional processes. Nickel-base superalloys with large γ' volume fraction are typically considered non-weldable and therefore exhibit a propensity for cracking during the fusion process. These crack-prone materials, however, are of great importance in gas turbine engines due to their excellent high temperature creep resistance. In this study we investigate the creep behavior of IN738LC produced by the electron beam melting process. Here, we find that with appropriate post-build heat treatment the creep response of material oriented in the build direction exhibits deformation and rupture behavior comparable to that of conventionally cast IN738 & IN738LC. In the transverse direction properties fall below the expected cast behavior, however, we argue this is likely due to differences in grain scale and crystallographic texture. It may be possible to coarsen the grain morphology with appropriate process-parameter optimization in order to reduce the severity of intergranular fracture in the transverse direction. These results illustrate that high temperature properties exhibited by additively manufactured IN738LC are suitable for the hot section of gas turbine engines.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Data-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold

This paper introduces a surrogate modeling scheme based on Grassmannian manifold learning to be used for cost-efficient predictions of high-dimensional stochastic systems. The method exploits subspace-structured features of each solution by projecting it onto a Grassmann manifold. This point-wise linear dimensionality reduction harnesses the structural information to assess the similarity between solutions at different points in the input parameter space. The method utilizes a solution clustering approach in order to identify regions of the parameter space over which solutions are sufficiently similarly such that they can be interpolated on the Grassmannian. In this clustering, the reduced-order solutions are partitioned into disjoint clusters on the Grassmann manifold using the eigen-structure of properly defined Grassmannian kernels and, the Karcher mean of each cluster is estimated. Then, the points in each cluster are projected onto the tangent space with origin at the corresponding Karcher mean using the exponential mapping. For each cluster, a Gaussian process regression model is trained that maps the input parameters of the system to the reduced solution points of the corresponding cluster projected onto the tangent space. Using this Gaussian process model, the full-field solution can be efficiently predicted at any new point in the parameter space. In certain cases, the solution clusters will span disjoint regions of the parameter space. In such cases, for each of the solution clusters we utilize a second, density-based spatial clustering to group their corresponding input parameter points in the Euclidean space. The proposed method is applied to two numerical examples. Here, the first is a nonlinear stochastic ordinary differential equation with uncertain initial conditions where the surrogate is used to predict the time history solution. The second involves modeling of plastic deformation in a model amorphous solid using the Shear Transformation Zone theory of plasticity, where the proposed surrogate is used to predict the full strain field of a material specimen under large shear strains.

42 ENGINEERING↗
DOE OSTI2024

A crystal-plasticity-informed Gaussian Process Regression model to capture anisotropy in single crystal shape memory alloys

This work presents a machine learning (ML) framework that model the anisotropic actuation responses in a shape memory alloy. A Gaussian Process Regression (GPR) based ML model is trained on a set of different crystal orientations subjected to different actuation conditions. The training employed thermo-mechanical responses from a crystal-plasticity model that captures phase-transformation, stress-induced plasticity, and transformation-induced plasticity. Further, on training the GPR-ML model at fixed stress level for different orientations, it captured the thermo-mechanical responses accounting for the anisotropy, and predicted responses for new orientations with good accuracy. The GPR-ML model is able to capture the transformation temperature variations even when trained using multiple stress levels, and the transformation strain showed significant deviations. The developed GPR-ML model gave reasonable predictions for an unexplored sample set of orientations and loading conditions.

36 MATERIALS SCIENCE↗