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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Parameter Calibration for Johnson Cook and Preston-Tonks-Wallace Material Strength Models with Uncertainty Quantification

In this study we perform a Bayesian calibration of the parameters in the Johnson Cook (JC) material strength model, with uncertainty, using experiments with for a range of low and medium strain rates. For the parameter calibration, we used a variational Bayesian approach with experimental data from Hopkinson bar and quasi-static tests done on Oxygen Free High Conductivity (OFHC) copper. The estimated parameter values matched well with experimental data for a modest range of strain rates and temperatures. Through this method, we also recovered uncertainty and correlation information for the estimated parameter values. We also compared our results to a calibration of parameters in the Preston-Tonks-Wallace (PTW) material strength model, using the same variational Bayesian method. The parameters estimated for both models provided good agreement with the experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A surprising proliferation of detwinning in β -tin at extreme loading rates

Integrating data from dynamic compression experiments of condensed matter across three national laboratories has led to insight and quantitative calibration of materials strength over decades of loading rate. For many materials, a single strength model (such as PTW) is sufficient to capture the flow-stress strain rate relationship which is monotonic. Here, we show here that β -tin, a tetragonal metal, exhibits dramatic deviations from this behavior. Naive fitting to a single PTW model is insufficient to capture the behavior; indeed, such resulting inferred flow stress versus strain exhibits a non-monotonic behavior. We suggest a resolution to this by proposing that in β -tin there are important Bauschinger effects arising from favorable conditions for twinning and detwinning. A simple yield surface model when paired with PTW hardening captures the experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Elastic Bayesian Model Calibration

Functional data are ubiquitous in scientific modeling. For instance, quantities of interest are modeled as functions of time, space, energy, density, etc. Uncertainty quantification methods for computer models with functional response have resulted in tools for emulation, sensitivity analysis, and calibration that are widely used. However, many of these tools do not perform well when the computer model’s parameters control both the amplitude variation of the functional output and its alignment (or phase variation). This paper introduces a framework for Bayesian model calibration when the model responses are misaligned functional data. The approach generates two types of data out of the misaligned functional responses: (1) aligned functions so that the amplitude variation is isolated and (2) warping functions that isolate the phase variation. These two types of data are created for the computer simulation data (both of which may be emulated) and the experimental data. The calibration approach uses both types so that it seeks to match both the amplitude and phase of the experimental data. The framework is careful to respect constraints that arise, especially when modeling phase variation, and is framed in a way that it can be done with readily available calibration software. In conclusion, we demonstrate the techniques on two simulated data examples and on two dynamic material science problems: a strength model calibration using flyer plate experiments and an equation of state model calibration using experiments performed on the Sandia National Laboratories’ Z-machine.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Bayesian calibration of strength model parameters from Taylor impact data

Materials strength plays a key role in determining the mechanical response of engineered structures. As such, accurate strength models are crucial in simulations involving complex loading conditions, particularly when deformation in the plastic regime is deemed important. In this work, a Gaussian process based surrogate for a finite element simulation of a Taylor impact test is developed and used for Bayesian calibration of the Preston–Tonks–Wallace strength model. Here, the surrogate model is shown to closely approximate the salient features of the Taylor cylinder deformation and is validated against simulation output before being used in the strength model calibration routine. The results show that Taylor impact test data can be used in the calibration of constitutive equations through the use of a combination of data science techniques, namely Gaussian processes and Bayesian inference.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Characterization of Tri-lab β-Tin (Sn)

This report documents details of the microstructure and mechanical properties of -tin (Sn), that is used in the Tri-lab (Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), Sandia National Laboratories (SNL)) collaboration project on Multi-phase Tin Strength. We report microstructural features detailing the crystallographic texture and grain morphology of as-received -tin from electron back scatter diffraction (EBSD). Temperature and strain rate dependent mechanical behavior was investigated by multiple compression tests at temperatures of 200K to 400K and strain rates of 0.0001 /s to 100 /s. Tri-lab tin showed significant temperature and strain rate dependent strength with no significant plastic anisotropy. A sample to sample material variation was observed from duplicate compression tests and texture measurements. Compression data was used to calibrate model parameters for temperature and rate dependent strength models, Johnson-Cook (JC), Zerilli-Armstrong (ZA) and Preston-Tonks-Wallace (PTW) strength models.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A better understanding of the mechanics of borehole breakout utilizing a finite strain gradient-enhanced micropolar continuum model

Borehole breakout denotes the failure in rock mass subjected to drilling, caused by stress concentrations exceeding the material strength. Depending on the material properties, the preexisting in situ stress state, and the borehole dimensions, different types of borehole breakout, such as spiral-shaped breakout or v-shaped breakout, are distinguished in the literature. In the present work, we address the influence of the material properties on the predicted borehole breakout mode in a comprehensive finite element study. To this end, herein we employ a gradient-enhanced micropolar damage-plasticity model based on the Mohr–Coulomb strength criterion, formulated in the finite strain regime, which is calibrated based on experimental results from plane strain compression tests on Red Wildmoor sandstone. In the numerical study, the influence of the in situ stress state, the material friction angle, plastic dilation, post peak residual strength, and the inherent material length scale parameters are investigated. Thereby, we demonstrate that depending on the material parameters, substantially different failure modes, characterized by strongly localized shear bands or diffuse failure zones, are predicted. It is shown that in particular the brittleness of the material in the post peak regime has a major influence on the predicted breakout type. Moreover, a statistical validation of the results is obtained by considering different random field distributions of the initial material strength.

58 GEOSCIENCES↗
DOE OSTI2021

Geodyn Material Library: Pseudocap models for dry porous tocks

This report describes the second edition of the Pseudocap Strength models for porous rocks implemented in GEODYN material library. The first model was developed in 2007 and calibrated for concrete. Then, the model parameters were calibrated based on triaxial tests reported for limestones and sandstones of various porosities. In these models some key parameters were chosen as functions of the reference porosity,Φ. Since then multiple modifications were implemented in the model, therefore, it has been recalibrated for some common porous materials such as limestones, sandstones, alluvium, tuffs and granite. Two types of models are described in this repot. The first type (called Pseudocap Model or PM) is for rocks from a specific location. Parameters were calibrated for several specific geologic materials. The second type (called Generic Pseudocap Model or GPM) is useful for the sites where only basic information (rock type, porosity) is available. Generic models include built-in correlations between porosities and other mechanical properties observed for certain rock types. The models of both types were validated by comparing not only to quasi-static triaxial tests for these materials but also to shock Hugoniot data and spherical explosion data for some materials. All models were derived in the frame of isotropic plasticity. They are designed to be used in explicit finite element/difference codes. Tangent stiffness tensor is not provided but can be calculated numerically for the model to be used in implicit finite element codes. For an isotropic material the stress can be decomposed into volumetric and deviatoric parts. The volumetric part is modeled using an Equation of state (EOS) which calculates the pressure and the bulk sound speed as functions of the internal specific energy and density. Here a simple, Mie-Gruneisen EOS is presented, but tabulated EOS (LEOS) provided by the library can be used as well. The stress is limited by the yield surface which depends on three invariants of the stress tensor and specific internal energy. In addition, to capture the strain-rate dependence a simple multiplier is used for the yield surface which depends on the equivalent plastic strain rate. The failure surface (the ultimate yield, Y f , defined later) is chosen in the Hoek-Brown form, commonly used in rock mechanics. It includes measurable parameters such as Unconfined Compressive Strength (UCS) as well as scale parameters characterizing the quality of the rock such as GSI (Geologic Strength Index). Thus, even though the model is calibrated for small samples it offers a way to extrapolate the strength to the field scale using geological characterization of the rock mass. The model captures effects of brittle-ductile transition in rocks by introducing a cap multiplier to the yield function. The rate of dilatancy (bulking) is proportional to the slope of the yield surface affected by the cap. Therefore, it takes place only at low confinements when the pressure is less than the brittle-ductile transition pressure, P BD . On the contrary, the porous compaction takes place at pressures higher than P BD . The cap moves as the porosity is compacted or new porosity is generated due to dilatancy. The porous compaction is modeled using an evolution equation which includes deviatoric stress so that the onset of compaction corresponds to the cap surface. The model captures effects of shear-enhanced compaction which is an important for porous rocks. Section 2 describes the modeling framework and Section 3 presents the model calibration procedure. Section 4 compares experimental data for various rocks versus model predictions. The model parameters used for this comparison are given in Appendix. The files with material constants are available with the latest GEODYN material library distribution.

58 GEOSCIENCES↗
DOE OSTI2021

Discrete-Direct Model Calibration and Uncertainty Propagation Method Confirmed on Multi-Parameter Plasticity Model Calibrated to Sparse Random Field Data

A discrete direct (DD) model calibration and uncertainty propagation approach is explained and demonstrated on a 4-parameter Johnson-Cook (J-C) strain-rate dependent material strength model for an aluminum alloy. The methodology's performance is characterized in many trials involving four random realizations of strain-rate dependent material-test data curves per trial, drawn from a large synthetic population. The J-C model is calibrated to particular combinations of the data curves to obtain calibration parameter sets which are then propagated to “Can Crush” structural model predictions to produce samples of predicted response variability. These are processed with appropriate sparse-sample uncertainty quantification (UQ) methods to estimate various statistics of response with an appropriate level of conservatism. This is tested on 16 output quantities (von Mises stresses and equivalent plastic strains) and it is shown that important statistics of the true variabilities of the 16 quantities are bounded with a high success rate that is reasonably predictable and controllable. The DD approach has several advantages over other calibration-UQ approaches like Bayesian inference for capturing and utilizing the information obtained from typically small numbers of replicate experiments in model calibration situations—especially when sparse replicate functional data are involved like force–displacement curves from material tests. The DD methodology is straightforward and efficient for calibration and propagation problems involving aleatory and epistemic uncertainties in calibration experiments, models, and procedures.

42 ENGINEERING↗
DOE OSTI2023

Neural network-based single material beam-hardening correction for X-ray CT in Additive Manufacturing

Beam-hardening (BH) artifacts are ubiquitous in X-ray CT scans of dense metal additively manufactured (AM) parts. While linearization approaches are useful for correcting beam-hardened data from single material objects, they either require a calibration scan or detailed system and material composition information. In this paper, we introduce a neural network-based, material-agnostic method to correct beam-hardening artifacts. We train a neural network to map the acquired beam-hardened projection values and the corresponding estimated thickness of the part based on an initial segmentation to beam-hardening related parameters, which can be used to compute the coefficients of a linearizing correction polynomial. A key strength of our approach is that, once the network is trained, it can be used for correcting beam hardening from a variety of materials without any calibration scans or detailed system and material composition information. Furthermore, our method is robust to errors in the estimated thickness due to the typical challenge of obtaining an accurate initial segmentation from reconstructions impacted by BH artifacts. We demonstrate the utility of our method to obtain high-quality CT reconstructions from a collection of AM parts -- suppressing cupping and streaking artifacts

Rahman, Obaid↗
DOE OSTI2020

An analytical expression for temperature in a thermodynamically consistent model with a Mie-Gruneisen equation for pressure

The objective of this paper is to develop an analytical expression for temperature in a thermodynamically consistent model with a Mie-Gruneisen equation for pressure. This expression for the temperature is obtained for both constant and variable specific heat models and can be used in common models for the material yield strength that include thermal softening due to increase in temperature. Additionally, the material parameters in the model can easily be calibrated to match known experimental data and the model has been used to determine the value of the shock pressure at the onset of melting during shock loading.

42 ENGINEERING↗
DOE OSTI2021

A practical extension of the recursive multi-fidelity model for the emulation of hole closure experiments

We report in regimes of high strain rate, the strength of materials often cannot be measured directly in experiments. Instead, the strength is inferred based on an experimental observable, such as a change in shape, that is matched by simulations supported by a known strength model. In hole closure experiments, the rate and degree to which a central hole in a plate of material closes during a dynamic loading event are used to infer material strength parameters. Due to the complexity of the experiment, many computationally expensive, three-dimensional simulations are necessary to train an emulator for calibration or other analyses. These simulations can be run at multiple grid resolutions, where dense grids are slower but more accurate. In an effort to reduce the computational cost, a combination of simulations with different resolutions can be combined to develop an accurate emulator within a limited training time. We explore the novel design and construction of an appropriate functional recursive multi-fidelity emulator of a strength model for tantalum in hole closure experiments that can be applied to arbitrarily large training data. Hence, by formulating a multi-fidelity model to employ low-fidelity simulations, we were able to reduce the error of our emulator by approximately 81% with only an approximately 1.6% increase in computing resource utilization.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Inference of strength and phase transition kinetics in dynamically-compressed tin

Dynamic compression experiments in condensed matter are of interest in part because they provide opportunities to examine material response under extreme conditions; however, the inference of material behavior from dynamic experiments is challenging in the presence of phase transitions exhibiting kinetic processes. Demonstrating an approach to quantitative interpretation of such dynamic experiments, here we present a Bayesian model calibration of strength and phase transformation parameters to data drawn from pulsed power and gas gun shot experiments. The posterior predictions of the Bayesian model capture the experimental measurements and account for the various uncertainties in the experimental configurations. This holistic approach to model calibration utilizing multiple types of experimental data identifies important cross correlations among kinetics, strength, and the phase boundary. Improved insight into potential sources of current model form error is provided by comparing the differences between calibrations against different subsets of the experimental data.

42 ENGINEERING↗
DOE OSTI2022

Yield strength of CeO 2 measured from static compression in a radial diamond anvil cell

Cerium oxide (ceria, CeO 2 ) is frequently used as a standard in applications such as synchrotron and x-ray free electron lasers for calibrating x-ray wavelengths and offers the potential for understanding the high pressure properties and deformation mechanisms in a wide range of similar face centered cubic (fcc) materials. In this study, the pressure dependence of the strength of ceria was investigated up to 38 GPa using angle dispersive x-ray diffraction in a radial geometry in a diamond anvil cell. In this experiment, the difference in the stress along the axis of compression and perpendicular to the direction of compression can be determined, giving a quantity known as the differential stress. It was found that the differential stress (t), a measure of the lower bound for yield strength, initially increases rapidly from 0.35 ± 0.06 GPa to 2.2 ± 0.4 GPa at pressures of 1.8 and 3.8 GPa, respectively. Above 4 GPa, t increases more slowly to 13.8 ± 2.6 GPa at a pressure of 38 GPa. The changes in the preferred orientation (texture) of CeO 2 with pressure were also measured, allowing for the determination of active deformation mechanisms using an elasto-viscoplastic self-consistent model (EVPSC). It was found that as pressure increased, the [001] direction had a slight preferred orientation along the axis of compression. Our EVPSC model of experimental fiber (cylindrically symmetric) textures and lattice strains were most consistent with dominant slip activity along ${111}$ $\langle$$1\bar10$$\rangle$.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Reduced scale stripline platform to extend accessible pressures on the Z machine: Shockless compression of platinum to 650 GPa

Reaching astrophysically relevant high energy density (HED) material states in the laboratory is an ongoing effort at multiple experimental facilities. We have developed a new dynamic compression platform for the Z Pulsed Power Facility that allows for sample sizes 100s of [Formula: see text]m in thickness that accommodate multiple grains in order to fully capture bulk properties, such as material strength. A pair of experiments compressed platinum (Pt) to HED conditions and conventional inverse Lagrangian analysis as well as a recent Bayesian calibration technique were used to determine the principal isentrope to 650 GPa with density uncertainties of <2%. These low uncertainties are calculated for single sample experiments, presenting the possibility of even smaller experimental uncertainties with multiple samples the platform allows. Our new platform extends the accessible Pt ramp pressures achievable on the Z machine to over 80% of the pressure recently achieved using the National Ignition Facility planar Hohlraum platform. This new capability, the next generation evolution of the stripline platform, was made possible by advancements in both our understanding of the Z pulsed power driver and our overall magnetohydrodynamic modeling capabilities.

Porwitzky, Andrew↗
DOE OSTI2023

252 Cf yield calibration method for nuclear material accountancy and safeguards practitioners

Californium-252 is an isotope commonly encapsulated as a physically small but strong spontaneous fission neutron source for applications in industry, academia, and research. Within the nuclear safeguards community, a well-characterized 252 Cf source is often used as an accessible alternative for plutonium in calibrations measurements, which require the absolute source strength. Current methods of source strength quantification can provide an accurate estimate, approximately 1% uncertainty under optimal conditions, but are typically costly and time consuming. An alternative method was developed to determine 252 Cf source strength using passive neutron correlation counting (PNCC). The PNCC method enables institutions and facilities to perform 252 Cf source calibration measurements in-house using detection systems that are common within the nuclear safeguards community. This novel method was previously successfully demonstrated using neutron multiplicity well counters. However, the previous evaluation utilized detection systems with high neutron detection efficiencies, greater than 60%. The purpose of the current study is to extend the previous evaluation and demonstrate the feasibility of the PNCC 252 Cf calibration method for suite of coincidence counters with lower neutron detection efficiencies, between 15% and 35%, which are more commonly encountered in the field, as well as to provide a step-by-step guide to using the method. The neutron source used in this evaluation was previously certified by the National Institutes of Science and Technology (NIST), which provides a reference for the accuracy of the PNCC method. In conclusion, the present source yield calculations demonstrate excellent agreement with a NIST calibration technique and achieve a standard uncertainty below the target 1%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Strength of porous α-SiO 2 in a shock loaded environment: Calibration via Richtmyer–Meshkov instability and validation via Mach lens

The strength of brittle porous media is of concern in numerous applications, for example, earth penetration, crater formation, and blast loading. Thus, it is of importance to possess techniques that allow for constitutive model calibration within the laboratory setting. The goal of the current work is to demonstrate an experimental technique allowing for strength assessment of porous media subjected to shock loading, which can be implemented into pressure-dependent yield surfaces within numerical simulation schemes. As a case study, the deviatoric response of distended α-SiO 2 has been captured in a tamped Richtmyer–Meshkov instability (RMI) environment at a pressure regime of 4–10 GPa. Hydrocode simulations were used to interpret RMI experimental data, and a resulting pressure-dependent yield surface akin to the often employed modified Drucker–Prager model was calibrated. Simulations indicate that the resulting jet length generated by the RMI is sensitive to the porous media strength, thereby providing a feasible experimental platform capable of capturing the pressurized granular deviatoric response. Furthermore, in efforts to validate the RMI-calibrated strength model, a set of Mach-lens experiments was performed and simulated with the calibrated pressure-dependent yield surface. Excellent agreement between the resulting Mach-lens length in experiment and simulation provides additional confidence to the RMI yield-surface calibration scheme.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Comprehensive Studies on Hot Compaction and Vibration-Assisted Compaction Tests of Aluminum Powder

Abstract Aluminum powder compaction was studied using both test and simulation. Cold compaction, hot compaction, and vibration-assisted (cold) compaction tests were conducted to achieve different density ratios. First, the hot compaction test (at 300 °C, compression pressure 140 MPa) improved about 6% compared with cold compaction under the same compression pressure. Second, although the relative density ratio does not obviously improve at a vibration-assisted (cold) compaction, the strength of the specimens made under vibration loading is much better than those of cold compaction. Additionally, finite element models with well-calibrated Drucker–Prager Cap (DPC) material constitutive model were built in abaqus/standard to simulate the powder compaction process. The results of the finite element model have very good correlations with test results up to the tested range, and this finite element model further predicts the loading conditions needed to achieve the higher density ratios. Two exponential equations of the predicted density ratio were obtained by combining the test data and the simulation results. A new analytical solution was developed to predict the axial pressure versus the density ratio for the powder compaction according to DPC material model. The results between the analytical solution and the simulation model have a very good match.

Engineering↗