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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 253 records · Page 14

Progressive collapse analysis of stiffened panel structure with consideration of actual welding distortion and residual stresses

To date, inclusion of welding distortion and residual stresses in determining the strength of marine structures is based on empirical formulations due to welding complexity. In this study, a more feasible numerical model was developed from the perspective of inherent strain theory. The accuracy of this simplified numerical model was confirmed by transient thermo-elastic–plastic finite element analysis using a novel dynamic mesh refining and iterative substructure method which is 50 times faster than conventional finite element method. Welding distortion by the two numerical approaches was validated with experimental measurement. The collapse analyses indicated that the inherent strain model predicted a compressive strength and load-displacement curve with high accuracy, as validated by the transient thermo-mechanical model. The global stiffness and the ultimate strength of the welded structure would be overestimated by about 22% if no welding effects were considered. The proposed computation procedure for determining the ultimate strength of welded structures is accurate, simple, and practical and enables improvement of ultimate strength through optimization of welding joint design to reduce the welding residual stress and distortion.

Huang, Hui↗

Multichannel Deconvolution of Vibrational Shock Signals: An Inverse Filtering Approach

When transporting critical systems of national security interest, out-of-the ordinary, impulsive events that can potentially be undetected and affect overall system performance are of great concern. Impulsive events that can occur are essentially pulse-like, transient signals of short duration that evolve from various phenomena. Here the event can be created by either the dropping of a test object, the system, subjecting it to a compact high-energy blow or being struck unintentionally during transit resulting in potential damage. The intensity and location of the strike can cause an inoperability condition that is unacceptable in a national security environment. Therefore, it is essential to detect, classify and localize damage of any test object subjected to an impulsive-event. This effort was targeted to evaluate the vibrational response of test objects that are subjected to “transport” shocks and roadway vibrations during shipping and handling. Any potential damage that could be inflicted during transportation must not only be detected, but also be evaluated to determine the operational readiness of a test object before and after transport. This event is a critical task that must be addressed as part of the Lawrence Livermore National Laboratory (LLNL) national security mission. The estimation of excitation signals from noisy data is termed the deconvolution problem in the signal processing literature. The deconvolution problem is based on recovering the input excitation signal from a system characterized by its impulse response sequence. Using this model of the system, an “inverse” representation or filter is developed to remove the system from the measured data and recover the input. Deconvolution techniques have existed for a long-time; however, transient deconvolution presents a few uncommon problems, since the signal has a finite-length time duration resulting in a limited amount of data containing information about the excitation process. The transient is wideband in the frequency domain relative to any measurement sensor implying that the smaller bandwidth sensor system “filters” the excitation eliminating some of its essential information for recovery. This fact, coupled with the filtering effect of the test object itself makes this excitation recovery (deconvolution) problem a challenge for signal processing.

42 ENGINEERING↗

Experimental and computational studies of load ratio effect on fatigue crack growth rates in Alloy 709 at elevated temperatures

Abstract Experimental testing and finite element simulations of fatigue crack growth were performed in austenitic 20Cr‐25Ni (Alloy 709) steel at different load ratios and elevated temperatures. The experimental tests were performed using compact tension specimens, and crack growth rates were measured at stress intensity factors ranging between 5 and 35 MPa√m. Fractographic analysis using scanning electron microscopy indicated crack surface roughness and secondary cracking depending on testing temperature and load ratio. Finite element simulations of fatigue crack growth were performed to compute plasticity‐induced crack opening loads and predict crack growth rates. Predictions of fatigue crack growth rates using finite element simulations were performed using the computed crack‐tip opening loads, and they are shown to match well the experimental measurements.

Engineering↗

Modeling the viscoplastic behavior of a semicrystalline polymer

In this study, a complex constitutive relation is identified using inverse modeling with the nominal mechanical response as sole experimental input. The methodology is illustrated for a semicrystalline thermoplastic in the presence of strain localization at finite deformations. The experimental database includes cylindrical tensile bars, compression pins and round notched bars loaded at strain rates spanning up to five decades and temperatures below and above T g . The data is organized into a calibration set and a validation set. The response of tensile specimens is determined using finite element analyses and a two-phase constitutive relation for semicrystalline polymers that accounts for temperature- and rate-sensitive plastic flow, pressure-sensitivity, small-strain softening and large-strain orientational hardening of the amorphous phase, along with the evolution of crystallinity. The large number of constitutive parameters is identified using an optimization tool coupled with the finite element solver and the calibration set from experiments. The methodology is shown to be successful in predicting the response of round notched bars and replicating the effects of temperature and strain rate on the severity of necking in tensile bars. The proposed model identification strategy is both simple and effective in comparison with other elaborate methods that attempt to access intrinsic behavior directly from high-fidelity experimental measurements.

36 MATERIALS SCIENCE↗

Combined ambient vibration and surface displacement measurements for improved progressive failure monitoring at a toppling rock slab in Utah, USA

Seismic resonance and surface displacement measurements can be implemented in tandem to improve landslide characterization and progressive failure monitoring. Crack aperture data are frequently used in rock slope stability monitoring and often exhibit recognizable trends prior to failure, such as accelerated crack opening. Alternatively, ambient resonance data offer multiple parameters including modal frequencies, damping, and polarization that can be monitored alongside crack aperture and may respond differently to environmental forcings and complex failure evolution. We analyzed data from continuous ambient vibration monitoring and concomitant crack aperture measurements at the Courthouse Mesa instability, a large toppling sandstone slab in Utah, USA. Three years of data revealed crack aperture increases of 2–4 mm/year with no clearly detectable irreversible changes in modal parameters, including frequency. Annually, frequency and displacement varied by 29% and 19% of the mean, respectively, with average and maximum daily frequency fluctuations of 6.5% and 16%, respectively. These reversible cyclic changes were primarily temperature-driven, but annually, frequency was in-phase with temperature whereas crack aperture lagged temperature changes by ~37 days. Polarization and damping also varied seasonally but were less strongly correlated with temperature. Conceptual 3D finite element modeling demonstrated consistent frequency decreases associated with crack propagation but variable changes in crack aperture measured at a single point; i.e., crack propagation did not always result in increased crack opening but always generated a resonance frequency decrease. Taken together, our data suggest a possible thermal wedging-ratcheting mechanism at the Courthouse Mesa instability, where annual thermoelastic crack closure is impeded by debris infill but the absence of downward crack propagation during the monitoring period is evidenced by no permanent resonance frequency changes. Our study demonstrates that combined seismic resonance and crack aperture data provide an improved description of rock slope instability behavior, supporting refined characterization and monitoring of changes accompanying progressive failure.

58 GEOSCIENCES↗

A practical approach to calculating magnetic Johnson noise for precision measurements

Magnetic Johnson noise is an important consideration for many applications involving precision magnetometry, and its significance will only increase in the future with improvements in measurement sensitivity. The fluctuation–dissipation theorem can be utilized to derive analytic expressions for magnetic Johnson noise in certain situations, but when used in conjunction with finite element analysis tools, the combined approach is particularly powerful as it provides a practical means to calculate the magnetic Johnson noise arising from conductors of arbitrary geometry and permeability. In this paper, we demonstrate this method to be one of the most comprehensive approaches presently available to calculate thermal magnetic noise. In particular, its applicability is shown to not be limited to cases where the noise is evaluated at a point in space but also can be expanded to include cases where the magnetic field detector has a more general shape, such as a finite-size loop, a gradiometer, or a detector that consists of a polarized atomic species trapped in a volume. Furthermore, some physics insights gained through studies made using this method are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Higgs Boson Spookiness: Probing Quantum Nonlocality with Spacetime-Resolved $H\rightarrowτ^+τ^-$ Decays

We demonstrate that a future precision $ee$ Higgs factory would be able to perform a spacetime-resolved test of quantum nonlocality in Higgs boson decays. In simulated $ee\rightarrow ZH \rightarrow (μμ)(ττ)$ events at $\sqrt{s}=240$ GeV, we reconstruct $τ$ lepton decay vertices and measure spin correlations as a function of the spacetime interval between the two $τ$ decays. Such a measurement would be able to test Bell-inequality-violating correlations for spacelike-separated decays, enabling direct exclusion of superluminal, finite-speed entanglement signaling theories. With 0.75 ab$^{-1}$ of integrated luminosity, entanglement signal propagation speeds below $\approx2c$ can be excluded at 95$\%$ CL. Signals establishing any spin correlation can be excluded for speeds below $\approx9c$. This constitutes the first proposed spacetime-resolved measurement of electroweak quantum entanglement at a particle collider and demonstrates a unique capability of future Higgs factories.

FOS: Physical sciences↗

Full-field quantitative visualization of shock-driven pore collapse and failure modes in PMMA

The dynamic collapse of pores under shock loading is thought to be directly related to hot spot generation and material failure, which is critical to the performance of porous energetic and structural materials. However, the shock compression response of porous materials at the local, individual pore scale is not well understood. This study examines, quantitatively, the collapse phenomenon of a single spherical void in PMMA at shock stresses ranging from 0.4 to 1.0 GPa. Using a newly developed internal digital image correlation technique in conjunction with plate impact experiments, full-field quantitative deformation measurements are conducted in the material surrounding the collapsing pore for the first time. The experimental results reveal two failure mode transitions as shock stress is increased: (i) the first in situ evidence of shear localization via adiabatic shear banding and (ii) dynamic fracture initiation at the pore surface. Numerical simulations using thermo-viscoplastic dynamic finite element analysis provide insights into the formation of adiabatic shear bands (ASBs) and stresses at which failure mode transitions occur. Further numerical and theoretical modeling indicates the dynamic fracture to occur along the weakened material inside an adiabatic shear band. Finally, analysis of the evolution of pore asymmetry and models for ASB spacing elucidate the mechanisms for the shear band initiation sites, and elastostatic theory explains the experimentally observed ASB and fracture paths based on the directions of maximum shear.

42 ENGINEERING↗

Gunn threshold voltage characterization in GaAs devices with wedge-shaped tapering

Here, we fabricate gallium arsenide-based devices with a wedge-shaped tapering region connected to a rectangular-shaped region and measure the threshold voltage required to trigger the Gunn effect. The threshold voltage reduction is attributed to the focusing of the electric field toward the narrower end of the device and is effective when the device has a steep enough tapering. We also model the electric field profile for the tapered devices using an intuitive graphical approach and the finite element method and provide estimates for the threshold voltages of tapered devices. Finally, we compare the estimates to the measured values and provide possible reasons for the discrepancies. We believe the capability of threshold voltage reduction with the wedge-shaped tapering design could be useful in device applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A contextual sensor system for non-intrusive machine status and energy monitoring

Event-driven contexts in manufacturing occur pervasively as a result of interactions among involved entities such as machines, workers, materials, and environment. One of the primary tasks in smart manufacturing is to derive a context-aware system conveniently incorporating worker knowledge for generating timely actionable intelligence for workers on factory floor and supervisors to respond. In this paper, we propose to design a human-and-machine interaction recognition framework by using a causality concept to collect contextual data for classifications of normal and abnormal machine operations. The causes and effects are between workers and machines for this initial research. To apply the causality to recognize worker interactions, initially a reliable way to identify the states of machines is necessary. The proposed contextual sensor system, consisting of a power meter for measuring machine operation conditions, a visual camera for capturing worker and machine interactions via a finite state machine model, and an algorithm for determining power signatures of individual components via energy disaggregation is implemented on semiconductor fabrication machines (manual or PLC controlled) each with multiple components. The experiment results demonstrate its context extraction capability such as components states and their corresponding energy usage in real time as well as its ability to identify anomalous operation conditions.

47 OTHER INSTRUMENTATION↗

Nanochannel electrodes facilitating interfacial transport for PEM water electrolysis

Proton-exchange membrane water electrolyzers (PEMWEs) are a promising technology for green hydrogen production; however, interfacial transport behaviors are poorly understood, hindering device performance and longevity. Here, we first utilized finite-gap electrolyzer to demonstrate the possibility of proton transfer through water in PEMWEs. The measured high-frequency resistances (HFRs) exhibit a linear trend with increasing gap distance, where extrapolation shows a lower value compared with HFRs in regular zero-gap electrolyzers, indicating that ohmic resistance could be further reduced. We introduce nanochannels to facilitate mass transport, as evidenced by both liquid-fed and vapor-fed electrolysis. Nanochannel electrodes achieve a voltage reduction of 190 mV at 9 A·cm –2 compared with the Ir-PTEs without nanochannels. Furthermore, nanochannel electrodes show negligible degradation through 100,000 accelerated-stress tests and over 2,000 h of operation at 1.8 A·cm –2 with a decay rate of 11.66 μV·h –1 . These results provide new insights into localized transport dynamics for PEMWEs and highlight the significance of interfacial engineering for electrochemical devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting Failure Using Deep Learning SAND Report

Accurate prediction of ductile failure is critical to Sandia’s NW mission, but the models are computationally heavy. The costs of including high-fidelity physics and mechanics that are germane to the failure mechanisms are often too burdensome for analysts either because of the person-hours it requires to input them or because of the additional computational time, or both. In an effort to deliver analysts a tool for representing these phenomena with minimal impact to their existing workflow, our project sought to develop modern data-driven methods that would add microstructural information to business-as-usual calculations and expedite failure predictions. The goal is a tool that receives as input a structural model with stress and strain fields, as well as a machine-learned model, and output predictions of structural response in time, including failure. As such, our project spent substantial time performing high-fidelity, three-dimensional experiments to elucidate materials mechanisms of void nucleation and evolution. We developed crystal-plasticity finite-element models from the experimental observations to enrich the findings with fields not readily measured. We developed engineering length-scale simulations of replicated test specimens to understand how the engineering fields evolve in the presence of fine-scale defects. Finally, we developed deep learning convolutional neural networks, and graph-based neural networks to encode the findings of the experiments and simulations and make forward predictions in time for structural performance. This project demonstrated the power of data-driven methods for model development, which have the potential to vastly increase both the accuracy and speed of failure predictions. These benefits and the methods necessary to develop them are highlighted in this report. However, many challenges remain to implementing these in real applications, and these are discussed along with potential methods for overcoming them.

97 MATHEMATICS AND COMPUTING↗

Elasto-viscoplastic fast Fourier transform modeling framework for assessing microstructural effects on stress intensity factors characterizing fracture toughness

A large-strain elasto-viscoplastic fast Fourier transform (LS-EVPFFT) model with non-periodic (NP) velocity-based boundary conditions is adapted to simulate the sensitivity of stress intensity factors on microstructure for 304L stainless steel. The material was characterized via electron backscattered diffraction (EBSD) serial-sectioning to obtain a measured 3-D microstructural cell to perform simulations. The NP-LS-EVPFFT model, including the simulation setup and boundary conditions, was verified using a crystal plasticity finite element (CPFE) model. To this end, the generation of meshes of notched specimens was developed, which involved creating Python scripts for mesh “cutting” in Abaqus, and Sculpt scripts in Cubit for meshing of the measured microstructural cell processed with DREAM.3D. The complexity of the mesh preparation highlighted the advantages of the FFT-based model, which circumvents the mesh generation process. Given the efficiency of the FFT-based model, statistical distribution of stress intensity factors in function of crystal orientation at the crack tip, grain structure, and crystallographic texture surrounding the crack tip were predicted. Further, the distributions reveal about 10% variation of stress intensity factors with microstructure with the most significant sensitivity found to be the crystal orientation at the crack tip. The methodology developed in this work is discussed as a practical simulation tool for predicting the sensitivity of stress intensity factors on microstructural variability in metallic materials.

36 MATERIALS SCIENCE↗

Comparison of three state-of-the-art crystal plasticity based deformation twinning models for magnesium alloys

In magnesium alloys, deformation twinning and its interactions with dislocation slip are responsible for a sigmoidal shape stress–strain behavior and an asymmetrical tension–compression yield strength in magnesium alloys. The sensitivity of twinning to the underlying microstructure renders the crystal plasticity method the most commonly adopted modeling approach for magnesium-twinning. This paper compares three state-of-the-art crystal plasticity-based twinning models from the literature, namely the elastic-viscoplastic self-consistent twinning-detwinning (EVPSC-TDT) model, crystal plasticity finite element model based on enhanced predominate twin reorientation approach (CPFE-ePTR), and the crystal plasticity finite element model based on “discrete twinning” approach (CPFE-DT). A polycrystalline microstructure is simulated with all three methods to compare the resulting stress–strain curves and lattice strains to those from the experimentally measured data. All three methods showed the capability of capturing the experimental results with different levels of accuracy. Additionally, the EVPSC-TDT method avoids solving the finite element matrices and showed the highest computational efficiency. The CPFE-ePTR model shows a higher accuracy in capturing the lattice strain. The CPFE-DT relies on high-resolution finite element mesh and is much slower than the other two methods, but it captured the local deformation concentration and stress reversal phenomena near the twin band, which was not possible with the other two methods. Based on the comparison, guidance for the selection of the appropriate model based on the specific modeling target is provided in this paper.

36 MATERIALS SCIENCE↗

Magnetic-Field Diffusion Effects in Beam Position Monitors III: Application to DARHT-II Beam Data

Beam position monitors (BPMs) provide time-resolved measurements of the current and centroid position of high-current electron beams in linear induction accelerators (LIAs). One of the types of detectors used in BPMs is the B-dot loop, which generates a signal from the EMF due to the time varying magnetic flux through the loop. If some of the boundaries of the loop are composed of thick metal walls with finite conductivity, the resulting signal must be corrected for the magnetic field diffusion into the metal. The theoretically predicted flux due to diffusion is in remarkable agreement with experimental measurements. Although accurate BPM measurements of beam current require correction of magnetic field diffusion, accurate measurement of beam position requires no correction. In this note, we present experimental validation of current and position results from a prototype detector employing finite conductivity sensing areas, based on experiments on the DARHT-II LIA.

43 PARTICLE ACCELERATORS↗

Iterative Stress Reconstruction Algorithm to Estimate Three-Dimensional Residual Stress Fields in Manufactured Components

Residual stress (RS) significantly impacts the mechanical performance of components. Measurement of RS often provides incomplete data in terms of components of stress and spatial density. Employing such fields in finite element simulations results in significant modification of the field to achieve equilibrium and compatibility among strains. To overcome this, an iterative stress reconstruction algorithm (ISRA) is developed to estimate 3D RS fields that satisfy equilibrium, are stress component-wise complete, and represent the characterized data sampled. An Al 7075-T651 plate and an additively manufactured (AM) A36 steel wall are considered for RS reconstruction using measurement data from the literature. A maximum variation of ~2.5 MPa in the Al plate, and ~10 MPa in the steel wall are observed between the reconstructed and measured stresses. Furthermore, unknown stress components emerge and reach significant magnitudes (upto ~2.3 MPa in the Al plate and ~45 MPa in the AM wall) during ISRA. Indeed, it is found that minor errors in measurement or data processing are eliminated through the physical requirements during ISRA. Employing a reconstructed RS field is hence not just more accurate given its compatibility, but it additionally corrects for minor errors in measurement. Furthermore, it is found that spatially dense measurement data result in convergence with fewer iterations. Finally, although ISRA yields a nonunique solution dependent on boundary conditions, measurement errors, fitting errors, and mesh density, it accommodates for uncertainties and inaccuracies in measurement, as opposed to failing to reach a physically realistic converged solution.

42 ENGINEERING↗

Revisiting excitation gaps in the fractional quantum Hall effect

Recent systematic measurements of the quantum well width dependence of the excitation gaps of fractional quantum Hall states in high mobility samples open the possibility of a better quantitative understanding of this important issue. Here we present what we believe to be accurate theoretical gaps including the effects of finite width and Landau level (LL) mixing. While theory captures the width dependence, there still remains a deviation between the calculated and the measured gaps, presumably caused by disorder. It is customary to model the experimental gaps of the n/(2n ± 1) states as Δ n/(2n+1) = Ce 2 /[(2n ± 1)ϵl]-Γ, where ϵ is the dielectric constant of the background semiconductor and l is the magnetic length; the first term is interpreted as the cyclotron energy of composite fermions and Γ as a disorder-induced broadening of composite-fermion LLs. Fitting the gaps for various fractional quantum Hall states, we find that Γ can be nonzero even in the absence of disorder.

36 MATERIALS SCIENCE↗

Simulation of a TRISO MiniFuel irradiation experiment with data-informed uncertainty quantification

An irradiation experiment using tristructural isotropic (TRISO) fuel particles and the miniature fuel (MiniFuel) irradiation vehicle was performed in Oak Ridge National Laboratory’s High Flux Isotope Reactor (HFIR) to support development of the Kairos Power fluoride salt–cooled, high-temperature reactor (KP-FHR). Here, this paper describes modeling predictions of temperatures and fuel burnup for the as-built experiment. An uncertainty quantification (UQ) analysis was performed to determine the effect of TRISO particle volume and position on the temperature predictions at various fuel heat generation rates (HGRs). This UQ study utilized fuel kernel position and volume measurements previously collected using X-ray computed tomography (XCT) techniques and Monte Carlo sampling methods to generate fuel compact cases that were then analyzed using a finite element thermal model. The UQ analysis indicated that uncertainty in calculated temperatures caused by varying TRISO particle arrangement is relatively small, even at high fuel HGR. Final predictions of particle temperatures throughout the irradiation are shown to be relevant to KP-FHR normal and off-normal operating conditions and to previous TRISO irradiation experiments. The combination of XCT with UQ analyses will inform post-irradiation examination (PIE) of the irradiated fuel compacts, and these analyses can be used to develop fuel performance models for coated particle fuel forms. Both PIE of separate-effects irradiation data and enhanced fuel performance modeling support accelerated qualification of TRISO fuels for a broad range of advanced reactor applications. The novel approach demonstrated here of measuring TRISO particle configurations with XCT methods and generating representative fuel compacts for finite element modeling and UQ analysis could be leveraged by the broader particle fuel community in the development of other TRISO fuel experiments in which these variables may have a significant impact on key outcomes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗