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Results for “Yield Prediction”

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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Using machine-learning to understand complex microstructural effects on the mechanical behavior of Ti-6Al-4V alloys

Structural materials properties are highly dependent on their microstructure. Their microstructure is in turn affected by multiple fabrication and thermo-mechanical treatment parameters, all of which conform a highly-dimensional parametric space with often hidden correlations that are difficult to extract by experimentation alone. This is particularly true for alloys of the dual-phase Ti-6Al-4V family, with their greatly complex and rich microstructures, which combine several intrinsic length scales associated with multiple grain and subgrain structures, grains with different crystal lattices (α and β phases), and complex chemistry. In this paper we use a comprehensive set of machine learning techniques to develop predictive tools relating the yield strength and hardening rate of these alloys to a set of input parameters covering extensive ranges. The data generator is a finite-element crystal plasticity model for polycrystal deformation that takes into account slip anisotropy and employs standard dislocation evolution models for the α and β phases of Ti-based alloys. Our dataset includes over two thousand independent simulations and is used to train the machine learning models, which are then used to establish correlations between microstructural parameters and the alloys’ mechanical response. Our results point to the most influential parameters affecting yield strength and hardening rate, information that can then be used to guide experimental synthesis and characterization efforts to save time and resources.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High-throughput screening tools facilitate calculation of a combined exposure-bioactivity index for chemicals with endocrine activity

High-throughput and computational tools provide a new opportunity to calculate combined bioactivity of exposure to diverse chemicals acting through a common mechanism. We used high throughput in vitro bioactivity data and exposure predictions from the U.S. EPA’s Toxicity and Exposure Forecaster (ToxCast and ExpoCast) to estimate combined estrogen receptor (ER) agonist activity of non-pharmaceutical chemical exposures for the general U.S. population. High-throughput toxicokinetic (HTTK) data provide conversion factors that relate bioactive concentrations measured in vitro (µM), to predicted population geometric mean exposure rates (mg/kg/day). These data were available for 22 chemicals with ER agonist activity and were estimated for other ER bioactive chemicals based on the geometric mean of HTTK values across chemicals. For each chemical, ER bioactivity across ToxCast assays was compared to predicted population geometric mean exposure at different levels of in vitro potency and model certainty. Dose additivity was assumed in calculating a Combined Exposure-Bioactivity Index (CEBI), the sum of exposure/bioactivity ratios. Combined estrogen bioactivity was also calculated in terms of the percent maximum bioactivity of chemical mixtures in human plasma using a concentration-addition model. Estimated CEBIs vary greatly depending on assumptions used for exposure and bioactivity. In general, CEBI values were <1 when using median of the estimated general population chemical intake rates, while CEBI were ≥1 when using the upper 95th confidence bound for those same intake rates for all chemicals. Concentration-addition model predictions of mixture bioactivity yield comparable results. Based on current in vitro bioactivity data, HTTK methods, and exposure models, combined exposure scenarios sufficient to influence estrogen bioactivity in the general population cannot be ruled out. Future improvements in screening methods and computational models could reduce uncertainty and better inform the potential combined effects of estrogenic chemicals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Trajectory Shaper: A Solution for Disrupted Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) can effectively reduce energy consumption, alleviate traffic congestion, and enhance safety. However, communication-related constraints and uncooperative vehicle users can disrupt CACC during real-world operations, significantly undermining the putative benefits of CACC. To alleviate the negative impacts of disrupted CACC, this study develops the trajectory shaper (TS) methods as backup solutions for two scenarios: (i) communication between vehicles is infeasible, and vehicles execute adaptive cruise control (ACC) using local sensor measurements; (ii) follower vehicles reject forming a cooperative platoon and execute their local distributed controllers using the information attained via communication. When communication is infeasible, a distributed TS is devised on each vehicle to modify the sensor measurements, enabling safe and efficient ACC operations. When communication is available but uncooperative agents are involved, the lead vehicle of the platoon executes a centralized TS to modify the information shared with uncooperative agents, achieving optimal platoon-level performance. The centralized and distributed TSs are implemented based on the model predictive control algorithms to yield optimal modifications on input information. Robustness is also factored to tackle model uncertainties during TS operations to ensure safety and efficiency. Numerical experiments validate the control performance of the proposed TSs.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗
DOE OSTI2020

Single crystal yield criterion for chromium based on atomistic studies of isolated 1/2[111] screw dislocations

Using the recently developed Bond Order Potential for Cr, we investigate the mobility of isolated 1/2[111] screw dislocations under stress at 0 K. These studies provide the dependence of the critical resolved shear stress (i.e., the Peierls stress) on the orientation of the maximum resolved shear stress plane and on the shear stress perpendicular to the slip direction. Similar studies are made for loading in tension and compression to show that the onset of yielding in Cr single crystals can be described using a combination of the shear stresses parallel and perpendicular to the slip direction. Based on these results, we develop a single crystal yield criterion for Cr that includes all non-Schmid contributions to the Peierls stress. This criterion is used to predict the shape of the yield surface and compare it with the regular Tresca's hexagon arising from the Schmid law. For all directions of uniaxial load, the criterion is used to quantify the character and magnitude of the tension-compression asymmetry.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multiscale formulation of frictional contact mechanics at the pore scale

Direct numerical simulation (DNS) yields the highest fidelity predictions of mechanical deformation at the pore scale, but is prohibitively expensive for analyzing large or many samples. Discrete element methods (DEM) are an efficient alternative, but are limited to granular media and incapable of estimating or controlling prediction errors. We present a pore-level multiscale method (PLMM) that approximates DNS efficiently and with controllable accuracy. We focus on the linear elastic response of a consolidated geologic porous medium with arbitrary microstructure, heterogeneous mineralogy, containing cracks or defects. PLMM decomposes the solid phase into non-overlapping subdomains, on which local basis functions are constructed. The bases are then coupled with a global interface problem that accounts for slip or stick contact conditions between the subdomains. PLMM produces an initial, but accurate, approximation to DNS that can be iteratively improved. It is amenable to parallelism and allows for different mesh, models, and physics in each subdomain. An algebraic interpretation of PLMM as a preconditioner is also presented to allow non-intrusive implementation into existing solvers. Lastly, this work extends previous developments of PLMM in fluid dynamics to solid mechanics and enables future extensions towards modeling coupled flow and mechanics problems.

42 ENGINEERING↗
DOE OSTI2020

Durability test of a flowing-water target for isotope harvesting

A high intensity proton irradiation was performed with the flowing-water isotope harvesting target at the University of Wisconsin-Madison Cyclotron Laboratory to measure the rate of degradation of the target shell during irradiation conditions. The beam reached an intensity of 34 µA by the end of the irradiation and covered an area of 0.7 cm 2 on the target. Radiolysis products, such as H 2 O 2 , H 2 , and O 2 , were measured in the bulk water of the system and found to be present at much lower levels than predicted by literature escape yields. Radionuclides formed in the target shell were measured in the system water as a radiotracer for target degradation. Using a simple, beam intensity dependent model, a corrosion rate of 1.5E-6 μm/(μA*s) was found to match the measured radiotracer activities at various points in the irradiation. Furthermore, this rate was used to extrapolate the lifetime of future isotope harvesting targets at the NSCL and FRIB, using the areal power density of different ion beams to scale the corrosion rate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Probing the low-temperature chemistry of methyl hexanoate: Insights from oxygenate intermediates

Understanding the combustion of methyl esters is crucial to elucidate kinetic pathways and predict combustion parameters, soot yields, and fuel performance of biodiesel, however most kinetic studies of methyl esters have focused on smaller, surrogate model esters. Methyl hexanoate is a larger methyl ester approaching the chain length of methyl esters found in biodiesel and has not received as much research attention as other smaller esters. The purpose of this work is to present the first atmospheric pressure combustion data of methyl hexanoate, CH 3 CH 2 CH 2 CH 2 CH 2 COOCH 3 . Mixtures of 2% methyl hexanoate in O 2 and N 2 are studied using a plug flow reactor at atmospheric pressure, wall temperatures from 573 to 973 K, residence times from roughly 1-2 s., and fuel equivalence ratios of 1, 1.5, and 2. Exhaust gases are analyzed by a gas chromatograph-mass spectrometer system and species mole fractions are presented. Here, the literature model shows satisfactory agreement with the experimental species profiles and improvements for future mechanistic studies are suggested. In particular, this work proposes new unimolecular decomposition pathways of methyl hexanoate to form methanol or methyl acetate. Furthermore, the experiment detected three unsaturated esters that are direct products of the low temperature oxidation chemistry and it provides more insight into branching ratios for the formation of methyl hexanoate radicals and for the decomposition of hydroperoxyalkyl radicals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

ReaxFF Parameter Set for Boron Clusters and Icosahedral Boron Crystals: Comparison with Density Functional Theory and Machine-Learning Potentials

Icosahedral boron materials, which include regular icosahedra of 12 boron atoms have gained increasing attention due to their potential applications as superhard materials, semiconductors, and energy storage media. However, the synthesis of high quality crystals of these materials has been a major barrier to the development of these applications. To enable computational prediction of synthesis conditions yielding high-quality icosahedral boron crystals, herein we tested and refined a set of ReaxFF parameters for the nucleation and growth of such crystals. We focused on matching the relative energies of small boron clusters obtained by density functional theory since such small clusters and similar motifs are likely present in crystal nuclei and at the interface of growing crystals. Using a training set of B 80 clusters, including a low-energy core–shell structure containing a B 12 icosahedron core and a high-energy single-shell structure produced in preliminary ReaxFF simulations, the ReaxFF parameter set was refined to better reproduce energies calculated by density functional theory (DFT). Among existing ReaxFF parameter sets and the machine-learning interatomic potentials MACE-MP-0, MACE-MP-0b3, MACE-MPA-0, PFP v7.0.0, and SevenNet-MF-ompa, only our new parameter set and PFP v7.0.0 correctly ranked these B 80 clusters. This refinement led to improved agreement with DFT for a test set of 58 clusters consisting of 8–103 boron atoms. Furthermore, our refined parameter set yielded greater local icosahedral structure than the previously existing ReaxFF parameter set for larger scale simulations of crystallization from supercooled liquid boron. Additionally, simulations of solid boron in contact with molten nickel using our refined ReaxFF parameters yielded a boron solubility value that agrees moderately well with experimental expectations, while the previous boron parameters gave a value that was much too low.

boron↗
DOE OSTI2026

Regio- and Stereoselective Lactone Polymerization: Divergent Effect of Catalyst Modification and Monomer Structure

Selective ring-opening polymerization (ROP) of chiral lactones enables access to biodegradable polyesters with precisely controlled microstructures. Here, combined DFT modeling and experimental validation elucidate how fine-tuning of enantiopure SalBinam aluminum catalysts (through introduction of bromine atoms and tert-butyl groups, respectively, in ortho- and para-positions) modulates regio- and stereocontrol in the ROP of methyl glycolide (MeG) and lactide (LA). Computations reveal that regioselectivity in MeG polymerization arises mainly from steric repulsion, with a small contribution from weak stabilizing C-H···Br interactions that favor ring-opening at the glycolic site, consistent with the experimentally enhanced regioselectivity for (R)-MeG. In contrast, the same steric congestion at the ligand’s ortho positions destabilizes the key transition states in rac-LA polymerization, reducing the calculated stereoselectivity. Experiments confirm the predicted loss of stereocontrol, yielding nearly atactic PLA under standard conditions. Extension of the computational framework to rac-MeG polymerization promoted by racemic catalyst identified a low-barrier, stepwise polymer chain exchange pathway that rationalizes the experimentally observed syndiotacticity of poly(lactic-co-glycolic acid).

DFT calculations↗
DOE OSTI2021

Atomic-scale homogeneous plastic flow beyond near-theoretical yield stress in a metallic glass

Abstract The onset of yielding and the related atomic-scale plastic flow behavior of bulk metallic glasses at room temperature have not been fully understood due to the difficulty in performing the atomic-scale plastic deformation experiments needed to gain direct insight into the underlying fundamental deformation mechanisms. Here we overcome these limitations by combining a unique sample preparation method with atomic force microscopy-based indentation, which allows study of the yield stress, onset of yielding, and atomic-scale plastic flow of a platinum-based bulk metallic glass in volumes containing as little as approximately 1000 atoms. Yield stresses markedly higher than in conventional nanoindentation testing were observed, surpassing predictions from current models that relate yield stress to tested volumes; subsequent flow was then established to be homogeneous without exhibiting collective shear localization or loading rate dependence. Overall, variations in glass properties due to fluctuations of free volume are found to be much smaller than previously suggested.

Yu, Jiaxin↗
DOE OSTI2024

Classifying topology in photonic crystal slabs with radiative environments

Abstract In the recent years, photonic Chern materials have attracted substantial interest as they feature topological edge states that are robust against disorder, promising to realize defect-agnostic integrated photonic crystal slab devices. However, the out-of-plane radiative losses in those photonic Chern slabs has been previously neglected, yielding limited accuracy for predictions of these systems’ topological protection. Here, we develop a general framework for measuring the topological protection in photonic systems, such as in photonic crystal slabs, while accounting for in-plane and out-of-plane radiative losses. Our approach relies on the spectral localizer that combines the position and Hamiltonian matrices of the system to draw a real-picture of the system’s topology. This operator-based approach to topology allows us to use an effective Hamiltonian directly derived from the full-wave Maxwell equations after discretization via finite-elements method (FEM), resulting in the full account of all the system’s physical processes. As the spectral FEM-localizer is constructed solely from FEM discretization of the system’s master equation, the proposed framework is applicable to any physical system and is compatible with commonly used FEM software. Moving forward, we anticipate the generality of the method to aid in the topological classification of a broad range of complex physical systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Altering the solubility of metal–organic polyhedra via pendant functionalization of Cp 3 Zr 3 O(OH) 3 nodes

Here, the chemistry of zirconium-based metal-organic polyhedra (ZrMOPs) is often limited by their poor solubilities. Despite their attractive features—including high yielding and facile syntheses, predictable topologies, high stability, and tunability—problematic solubilities have caused ZrMOPs to be under-studied and under-applied. Although these cages have been synthesized with a wide variety of carboxylate-based bridging ligands, we explored a new method for ZrMOP functionalization via node-modification, which we hypothesized could influence solubility. Herein, we report ZrMOPs with benzyl-, vinylbenzyl-, and trifluoromethylbenzyl-pendant groups decorating cyclopentadienyl moieties. The series was characterized by 1 H/ 19 F NMR, high-resolution mass spectrometry, infrared spectroscopy, and single-crystal X-ray diffraction. The effects of node functionalities on ZrMOP solubility were quantified using inductively coupled plasma mass spectrometry. Substitution caused a decrease in water solubility, but for certain organic solvents, e.g. DMF, solubility could be enhanced by ~20×, from 16 μM for the unfunctionalized cage to 310 μM for the vinylbenzyl- and trifluoromethylbenzyl-cages.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The dynamics, mixing, and thermonuclear burn of compressed foams with varied gas fills

Inertial confinement fusion (ICF) implosions involve highly coupled physics and complex hydrodynamics that are challenging to model computationally. Due to the sensitivity of such implosions to small features, detailed simulations require accurate accounting of the geometry and dimensionality of the initial conditions, including capsule defects and engineering features such as fill tubes used to insert gas into the capsule, yet this is computationally prohibitive. It is therefore difficult to evaluate whether discrepancies between the simulation and experiment arise from inadequate fidelity to the capsule geometry and drive conditions, uncertainties in physical data used by simulations, or inadequate physics. We present results from detailed high-resolution three-dimensional simulations of ICF implosions performed as part of the MARBLE campaign on the National Ignition Facility [Albright et al., Phys. Plasmas 29, 022702 (2022)]. These experiments are foam-filled separated-reactant experiments, where deuterons reside in the foam and tritons reside in the capsule gas fill and deuterium–tritium (DT) fusion reactions only occur in the presence of mixing between these materials. Material mixing in these experiments is primarily seeded by shock interaction with the complex geometry of the foam and gas fill, which induces the Richtmyer–Meshkov instability. We compare results for experiments with two different gas fills (ArT and HT), which lead to significant differences in the hydrodynamic and thermodynamic developments of the materials in the implosion. Our simulation results show generally good agreement with experiments and demonstrate a substantial impact of hydrodynamic flows on measured ion temperatures. The results suggest that viscosity, which was not included in our simulations, is the most important unmodeled physics and qualitatively explains the few discrepancies between the simulation and experiment. The results also suggest that the hydrodynamic treatment of shocks is inadequate to predict the heating and yield produced during shock flash, when the shock converges at the center of the implosion. Alternatively, underestimation of the level of radiative preheat from the shock front could explain many of the differences between the experiment and simulation. Nevertheless, simulations are able to reproduce many experimental observables within the level of experimental reproducibility, including most yields, time-resolved X-ray self-emission images, and an increase in burn-weighted ion temperature and neutron down-scattered ratio in the line of sight that includes a jet seeded by the glue spot that joins capsule hemispheres.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Low-energy 23 Al β-delayed proton decay and 22 Na destruction in novae

The radionuclide 22 Na is a target of γ-ray astronomy searches, predicted to be produced during thermonuclear runaways driving classical novae. The 22 Na (p, γ) 23 Mg reaction is the main destruction channel of 22 Na during a nova, hence, its rate is needed to accurately predict the 22 Na yield. However, experimental determinations of the resonance strengths have led to inconsistent results. In this Rapid Communication, we report a measurement of the branching ratios of the 23 Al β-delayed protons as a probe of the key 204-keV (center-of-mass) 22 Na (p, γ) 23 Mg resonance strength. We report a factor of 5 lower branching ratio compared to the most recent literature value. The variation in 22 Na yield due to nuclear data inconsistencies was assessed using a series of hydrodynamic nova outburst simulations and has increased to a factor of 3.8, corresponding to a factor of ≈ 2 uncertainty in the maximum detectability distance. Finally, this is the first reported scientific measurement using the Gaseous Detector with Germanium Tagging system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Applications of a Rayleigh-Taylor model to direct-drive laser fusion

Here, this paper presents a simple physics-based model for the interpretation of key metrics in laser direct drive. The only input parameters required are target scale, in-flight aspect ratio, and beam-to-target radius, and the importance of each has been quantified with a tailored set of cryogenic implosion experiments. These analyses lead to compact and accurate predictions of the fusion yield and areal density as a function of hydrodynamic stability, and suggest new ways to take advantage of direct drive. To provide examples, we will discuss how the inferred mix width behaves relative to theory, then show how it could be exploited to perform a direct drive implosion with a Lawson metric or Χ no α of 0.24 ± 0.02—using a novel parameter space at high velocities and beam radii on the OMEGA laser—that projects to ignition at a laser energy ≤2.0 MJ.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Performance Evaluation and Loss Modeling of WBG Devices based on a Novel Double-Pulse Test Method for Current Source Inverter

Careful measurements of the power device characteristics are necessary to accurately estimate a power converter's losses and efficiency. The conventional double-pulse test (DPT) circuit is a well-known method to implement this laboratory characterization of power devices and power modules. However, the switching characteristics of a power device depend on the power electronics circuit in which it is connected as well as the power circuit's physical layout, in addition to the device's internal structure. Hence, the conventional DPT circuit configuration, which is tailored for a standard voltage-source inverter (VSI), is not well-suited for a current-source inverter (CSI). This paper demonstrates a previously-proposed CSI-based DPT measurement technique that is appropriate for normal CSI operation. The characteristics of SiC MOSFETs and series-connected SiC Schottky diodes used in a CSI are measured using this improved technique while taking temperature effects into account to yield more accurate loss predictions. The CSI losses, including the switching and conduction losses of SiC MOSFETs and SiC Schottky diodes, have been modeled using this approach. The total CSI losses and efficiency have been estimated based on the CSI DPT results and loss models.

42 ENGINEERING↗
DOE OSTI2022

Multi-Fidelity Learning for Distribution System Voltage Probabilistic Analysis with High Penetration of PVs

This paper proposes a multi-fidelity learning approach for distribution voltage probabilistic analysis with high penetration of PVs. Unlike the existing machine learning-based approaches that require a large number of high fidelity data to achieve satisfactory results, our approach strategically leverage massive low fidelity data from inaccurate model simulations and limited high fidelity historical data. The key idea is to use low-fidelity data to establish an initial model and then the high-fidelity data to calibrate and correct the constructed low-fidelity model. This allows us to fuse low- and high-fidelity data, yielding a high fidelity prediction model. Results obtained from a realistic feeder in US with 80% penetration of PVs show that the proposed approach can achieve a similar accuracy to the one with a large number of high fidelity data. This significantly highlights the advantages of the proposed method as compared to existing data-hungry machine learning methods. Different levels of fidelity data and their impacts are also investigated.

distribution system↗
DOE OSTI2026

Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs

Dirichlet-to-Neumann maps enable the coupling of multiphysics simulations across computational subdomains by ensuring continuity of state variables and fluxes at artificial interfaces. We present a novel method for learning Dirichlet-to-Neumann maps on graphs using Gaussian processes, specifically for problems where the data obey a conservation law arising from an underlying partial differential equation. Our approach combines discrete exterior calculus and nonlinear optimal recovery to infer relationships between vertex and edge values. This framework yields data-driven predictions with uncertainty quantification across the entire graph, even when observations are limited to a subset of vertices and edges. By minimizing the reproducing kernel Hilbert space norm while penalizing kernel complexity through maximum likelihood estimation, our method ensures that the resulting surrogate strictly enforces conservation laws without overfitting. We demonstrate our method on two representative applications: subsurface flow in fracture networks and arterial blood flow. Finally, the results demonstrate that the method maintains high accuracy and well-calibrated uncertainty estimates even under severe data scarcity, highlighting its potential for scientific applications where limited data and reliable uncertainty quantification are critical.

Dirichlet-to-Neumann map↗