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DOE OSTI2024

Applicability of 1D site response analysis to shallow sedimentary basins: A critical evaluation through physics-based 3D ground motion simulations

One-dimensional site response analysis (1D SRA) remains the standard practice in considering the effect of local soil deposits and predicting site-specific ground motions, although its range of applicability to realistic seismic wavefields is still in question. In this 1D approach, horizontal and vertical ground shaking are assumed to be induced by vertically propagating shear and compressional waves, respectively. A recent study based on analytical two-dimensional (2D) plane waves and simple point source earthquake simulations has shown two mechanistic limitations in this 1D modelling technique for general inclined seismic waves, that is, systematic over-prediction of the vertical motion and wave trapping in the 1D soil column. In this article, we evaluate in detail the applicability of this 1D modelling approach to realistic three-dimensional (3D) simulated seismic wavefields in shallow sedimentary basins. Linear-viscoelastic 1D SRA predictions using two types of input motions that are commonly used in practice—rock outcrop and in-column motions, are compared with the reference true site response results from 3D earthquake simulations in terms of various measures in the frequency and time domain. It is shown that the horizontal motion in the 3D seismic wavefield exhibits dominant shear wave propagation phenomenon, while the vertical motion is a combined effect of compressional and shear waves and can be over-predicted by the 1D approach when the incident seismic waves are inclined. Direct evidence of the wave refraction process that leads to the vertical motion over-prediction is provided. 1D SRA with in-column inputs can yield motions that have significantly longer duration compared to the true 3D site response solution due to trapped waves, casting in doubt the frequent need for increased soil damping in existing site studies to compensate for wave attenuation due to scattering alone. Sensitivity investigation on the increase of soil profile damping by a multiplier D mul shows D mul values compatible with those found in the literature for both horizontal and vertical motions. It is shown that the level of D mul optimized for a best match of the spectral acceleration is dependent on the characteristic of the input motion and a larger D mul is typically required for the vertical component. In contrast, 1D SRA with outcrop motions predicts motions with shorter significant duration due to its inability to capture the basin-edge generated surface waves. A suite of ground motion simulations was performed to assess the sensitivity of the observations to the basin geologic structure including the velocity gradient, rock-basin impedance contrast and basin depth. The analysis results show that the accuracy of the simplified 1D procedure is dependent on the wavefield composition of both the input motions and the true 3D site response solution. While the horizontal motions in shallow sedimentary basins can, to the first order, be reasonably captured by the simplified 1D approach, 1D SRA for the vertical component is in general not reliable and contributions from inclined shear waves should be accounted for in site-specific evaluation of the vertical design ground motion.

1D assumption↗

DOE OSTI2016

Modeling of inertial deposition in scaled models of rat and human nasal airways: Towards in vitro regional dosimetry in small animals

Rodents are routinely used in inhalation toxicology tests as human surrogates. However, in vitro dosimetry tests in rodent casts are still scarce due to small rodent airways and in vitro tests to quantify sub-regional dosimetry are still impractical. We hypothesized that for inertial particles whose deposition is dominated by airflow convection (Reynolds number) and particle inertia (Stokes number), the deposition should be similar among airway replicas of different scales if their Reynolds and Stokes numbers are kept the same. In this study, we aimed to (1) numerically test the hypothesis in three airway geometries: a USP induction port, a human nose model, and a Sprague-Dawley rat nose model, and (2) find the range of applicability of this hypothesis. Five variants of the USP and human nose models and three variants of the rat nose model were tested. Inhalation rates and particle sizes were scaled to match the Reynolds number and Stokes numbers. A low-Reynolds-number k–ω model was used to resolve the airflow and a Lagrangian tracking algorithm was used to simulate the particle transport and deposition. Statistical analysis of predicted doses was conducted using ANOVA. For normal inhalation rates and particle dia- meters ranging from 0.5 to 24 mm, the deposition differences between the life-size and scaled models are insignificant for all airway geometries considered (i.e., human nose, USP, and rat nose). Furthermore, the deposition patterns and exit particle profiles also look similar among scaled models. However, deposition rates and patterns start to deviate if inhalation rates are too low, or particle sizes are too large. For the rat nose, the threshold velocity was found to be 0.71 m/s and the threshold Froude number to be 50. Results of this study provide a theoretical foundation for sub-regional in vitro dosimetry tests in small animals and for interpretation of data from inter-species or intra-species with varying body sizes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Constitutive Modeling of the Flow Stress of GCr15 Continuous Casting Bloom in the Heavy Reduction Process

According to the calculation results of a 3D thermomechanical-coupled finite-element (FE) model of GCr15 bearing steel bloom during a heavy reduction (HR) process, the variation ranges in the strain rate and strain under HR were described. In addition, the hot deformation behavior of the GCr15 bearing steel was studied over the temperature range from 1023 K to 1573 K (750 °C to 1300 °C) with strain rates of 0.001, 0.01, and 0.1 s{sup −1} in single-pass thermosimulation compression experiments. To ensure the accuracy of the constitutive model, the temperature range was divided into two temperature intervals according to the fully austenitic temperature of GCr15 steel [1173 K (900 °C)]. Two sets of material parameters for the constitutive model were derived based on the true stress–strain curves of the two temperature intervals. A flow stress constitutive model was established using a revised Arrhenius-type constitutive equation, which considers the relationships among the material parameters and true strain. This equation describes dynamic softening during hot compression processes. Considering the effect of glide and climb on the deformation mechanism, the Arrhenius-type constitutive equation was modified by a physically based approach. This model is the most accurate over the temperatures ranging from 1173 K to 1573 K (900 °C to 1300 °C) under HR deformation conditions (ignoring the range from 1273 K to 1573 K (1000 °C to 1300 °C) with a strain rate of 0.1 s{sup −1}). To ensure the convergence of the FE calculation, an approximated method was used to estimate the flow stress at temperatures greater than 1573 K (1300 °C).

36 MATERIALS SCIENCE↗

DOE OSTI2018

Optimized Gating System for Steel Castings

Computer modeling using a commercially available software package was used to explore the optimization of filling systems based on the relatively new concepts of avoiding entrainment of air bubbles and oxides by avoiding surface turbulence. The test casting was based on a pattern for a traditional top poured test bar, whose cross section was a tri-lobed clover-like shape. The study illustrates clearly that the detailed design of the filling system has a major influence on the conditions for defect generation during filling. Traditional steel casting systems using the widely popular assembly of preformed refractory tubes were found to behave poorly. Systems were demonstrated which were capable of delivering highly controlled filling behavior. The latest systems to be developed employed (1) a naturally pressurized filling system and (2) the use of filters placed flush on the top of the runner to act as bubble diverters, together with (3) terminal spin traps. These novel filling systems demonstrated excellent performance in simulation, in agreement with practical experience of the capability (of the trident gate in particular) to produce, for the first time in the history of casting, defect-free castings on a routine basis.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Wellbore Microannulus Characterization and Modeling.

Subsurface geologic formations used for extracting resources such as oil and gas can subsequently be used as a storage reservoir for the common greenhouse gas CO 2 , a concept known as Carbon Capture and Storage (CCS). Pre-existing wellbores penetrate the reservoirs where supercritical CO 2 is to be injected. These wellbores can potentially be a pathway for contamination if CO 2 leaks through wellbore flaws to an overlying aquifer or the atmosphere. Characterizing wellbore integrity and providing zonal isolation by repairing these wellbore flaws is of critical importance to the long-term isolation of CO 2 and success of CCS. This research aims to characterize the microannulus region of the cement sheath-steel casing interface in terms of its compressibility and permeability. A mock-up of a wellbore system was used for lab-scale testing. Specimens, consisting of a cement sheath cast on a steel casing with microannuli, were subjected to confining pressures and casing pressures in a pressure vessel that allows simultaneous measurement of gas flow along the axis of the specimen. The flow was interpreted as the hydraulic aperture of the microannuli. Numerical models are used to analyze stress and displacement conditions along the casing-cement interface. These numerical results provide good agreement with closed-form elastic solutions. Numerical models incorporating flaws of varying dimensions along the casing-cement interface were then developed to describe the microannulus region. A joint model is used to describe the hydraulic aperture of the microannulus region, whose mechanical stiffness is altered in response to the imposed stress state across the joint interface. The aperture-stress behavior is based upon laboratory measurements of hydraulic aperture as a function of imposed stress conditions. This investigation found that microannulus permeability can satisfactorily be described by a joint model and that the constitutive model imposed in a numerical simulation can play a significant role in the solution behavior and agreement to experimental data. Recommendations for future work include an application of the joint model with a thermally active large-scale reservoir coupled with pore pressure caused by dynamic CO 2 injection and subsequent microannulus region affects.

03 NATURAL GAS↗

DOE OSTI2018

Computational Design of a Novel Medium-Carbon, Low-Alloy Steel Microalloyed with Niobium

The design of a new steel with specific properties is always challenging owing to the complex interactions of many variables. In this work, this challenge is dealt with by combining metallurgical principles with computational thermodynamics and kinetics to design a novel steel composition suitable for thermomechanical processing and induction heat treatment to achieve a hardness level in excess of 600 HV with the potential for good fracture toughness. CALPHAD-based packages for the thermodynamics and kinetics of phase transformations and diffusion, namely Thermo-Calc{sup ®} and JMatPro{sup ®}, have been combined with an interdendritic segregation tool (IDS) to optimize the contents of chromium, molybdenum and niobium in a proposed medium-carbon low-manganese steel composition. Important factors taken into account in the modeling and optimization were hardenability and as-quenched hardness, grain refinement and alloying cost. For further investigations and verification, the designed composition, i.e., in wt.% 0.40C, 0.20Si, 0.25Mn, 0.90Cr, 0.50Mo, was cast with two nominal levels of Nb: 0 and 0.012 wt.%. The results showed that an addition of Nb decreases the austenite grain size during casting and after slab reheating prior to hot rolling. Validation experiments showed that the predicted properties, i.e., hardness, hardenability and level of segregation, for the designed composition were realistic. It is also demonstrated that the applied procedure could be useful in reducing the number of experiments required for developing compositions for other new steels.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Microstructural characterization of Mg-based bulk metallic glass and nanocomposite

New magnesium-based bulk metallic glasses Mg{sub 60}Cu{sub 30}Y{sub 10} have been prepared by pressure casting. Glassy alloys were successfully annealed to become nanocomposite containing 200 nm crystallites in an amorphous matrix. The microstructure of bulk glassy alloy and nanocomposite obtained during heat treatment was examined by X-ray diffraction and scanning and high-resolution electron microscopy. Metallic glass has been also studied to explain the structural characteristics by the reverse Monte Carlo (RMC) modeling based on the diffraction data. The HRTEM images allow to indicate some medium-range order (MRO) regions about 2–3 nm in size and formation of local atomic clusters. The RMC modeling results confirmed some kinds of short range order (SRO) structures. It was found that the structure of bulk metallic glass formed by the pressure casting is homogeneous. The composite material contained very small particles in the amorphous matrix. Homogeneous glassy alloy had better corrosion resistance than a composite containing nanocrystalline particles in a glassy matrix. - Highlights: • RMC modeling demonstrates some kinds of SRO structures in Mg-based BMGs. • HRTEM indicated MRO regions about 2–3 nm and SRO regions about 0.5 nm in size. • Mg-based glassy alloys were successfully annealed to become nanocomposite material. • Crystalline particles have spherical morphology with an average diameter of 200 nm. • Glassy alloy had higher corrosion resistance than a nanocomposite sample.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Development of Novel Ferritic-Martensitic Steels with Superior Creep Properties for Power Plant Applications

A creep resistant martensitic steel, CPJ-7, was developed with an operating temperature approaching 650°C. Subsequently, another creep resistant martensitic steel, JMP, was designed with the potential to operate at, or slightly above, 650°C. This report describes the development of these alloys from early iterations of CPJ steels to the final CPJ-7 formulation as well as the more heat resistant JMP steel formulation. The design originated from computational modeling for phase stability and precipitate strengthening using fifteen constituent elements. Approximately forty heats of CPJ and ten of JMP, each weighing ~7 kg, were vacuum induction melted. A computationally optimized heat treatment schedule was developed to homogenize the ingots prior to hot forging and rolling prior to final normalization and tempering. Overall, wrought and cast versions of CPJ-7 present superior creep properties when compared to wrought and cast versions of COST alloys for steam turbine and wrought and cast versions of P91/92 for boiler applications. For instance, the Larson Miller Parameter curve for CPJ-7 at 650°C almost coincides with that of COST E at 620°C. The prolonged creep life was attributed to slowing down the process of the destabilization of the MX and M 23 C 6 precipitates at 650°C. On the other hand, the cast version of CPJ-7 also revealed superior mechanical performance, well above commercially available cast 9% Cr martensitic steel or derivatives, especially for creep life at 650°C. The casting process employed slow cooling to simulate the conditions of a thick wall full-size steam turbine casing but utilized a separate homogenization step prior to final normalization and tempering. To advance the development of CPJ-7 for commercial applications, a process was used to scale up the production of the alloy using vacuum induction melting (VIM) and electroslag remelting (ESR), which underlined the importance of melt processing control of intentionally designed minor and trace elements in these advanced alloys. Following the work on CPJ-7, the JMP steels were designed with higher Co for increased solid solution strengthening, Si for oxidation resistance and increased W (with low Mo content) for matrix strength and stability as well as solid solution strengthening. The JMP steels showed increases in creep life compared to CPJ-7 between 118 to 150% at 650°C for testing at various stresses between 138 MPa and 207 MPa. On a Larson-Miller plot, the performance of the JMP steels surpasses that of state-of-the-art MARBN and other MARBN-type steels. The influence of various elements within the composition of the alloys on the microstructure and mechanical properties are discussed. This report presents approximately 420,000 h of in-house creep testing, the equivalent of almost 50 years of cumulative creep tests.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Encoding of linear kinetic plasma problems in quantum circuits via data compression

We propose an algorithm for encoding linear kinetic plasma problems in quantum circuits. The focus is on modelling electrostatic linear waves in a one-dimensional Maxwellian electron plasma. The waves are described by the linearized Vlasov–Ampère system with a spatially localized external current that drives plasma oscillations. This system is formulated as a boundary-value problem and cast in the form of a linear vector equation Aψ = b to be solved by using the quantum signal processing algorithm. The latter requires encoding of matrix A in a quantum circuit as a sub-block of a unitary matrix. We propose how to encode A in a circuit in a compressed form and discuss how the resulting circuit scales with the problem size and the desired precision.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Resilient Observer Design for Cyber-Physical Systems with Data-Driven Measurement Pruning

Resilient observer design for Cyber-Physical Systems (CPS) in the presence of adversarial false data injection attacks (FDIA) is an active area of research. The existing state-of-the-art algorithms tend to break down as more and more knowledge of the system is built into the attack model; also as the percentage of attacked nodes increases. From the view of optimization theory, the problem is often cast as a classical error correction problem for which a theoretical limit of has been established as the maximum percentage attacked nodes for which state recovery is guaranteed. Beyond this limit, the performance of -minimization based schemes, for instance, deteriorates rapidly. Similar performance degradation occurs for other types of resilient observers beyond certain percentages of attacked nodes. In order to increase the corresponding percentage of attacked nodes for which state recoveries can be guaranteed, researchers have begun to incorporate prior information into the underlying resilient observer design framework. For the most pragmatic cases, this prior information is often obtained through a data-driven machine learning process. Existing results have shown a strong positive correlation between the maximum attacked percentages that can be tolerated and the accuracy of the data-driven model. Motivated by these results, this chapter examines the case for pruning algorithms designed to improve the Positive Prediction Value (PPV) of the resulting prior information, given stochastic uncertainty characteristics of the underlying machine learning model. Theoretical quantification of the achievable improvement is given. Simulation results show that the pruning algorithm significantly increases the maximum correctable percentage of attacked nodes, even for machine learning model whose prediction power is comparable to the random flip of a coin.

Resilient Observer, Cyber-physical Systems, Data-D↗

DOE OSTI2022

Volumetric Rendering on Wavelet-Based Adaptive Grid

Numerical modeling of physical phenomena frequently involves processes across a wide range of spatial and temporal scales. In the last two decades, the advancements in wavelet-based numerical methodologies to solve partial differential equations, combined with the unique properties of wavelet analysis to resolve localized structures of the solution on dynamically adaptive computational meshes, make it feasible to perform large-scale numerical simulations of a variety of physical systems on a dynamically adaptive computational mesh that changes both in space and time. Volumetric visualization of the solution is an essential part of scientific computing, yet the existing volumetric visualization techniques do not take full advantage of multi-resolution wavelet analysis and are not fully tailored for visualization of a compressed solution on the wavelet-based adaptive computational mesh. Our objective is to explore the alternatives for the visualization of time-dependent data on space-time varying adaptive mesh using volume rendering while capitalizing on the available sparse data representation. Two alternative formulations are explored. The first one is based on volumetric ray casting of multi-scale datasets in wavelet space. Rather than working with the wavelets at the finest possible resolution, a partial inverse wavelet transform is performed as a preprocessing step to obtain scaling functions on a uniform grid at a user-prescribed resolution. As a result, a solution in physical space is represented by a superposition of scaling functions on a coarse regular grid and wavelets on an adaptive mesh. An efficient and accurate ray casting algorithm is based just on these coarse scaling functions. Additional details are added during the ray tracing by taking an appropriate number of wavelets into account based on support overlap with the interpolation point, wavelet coefficient magnitude, and other characteristics, such as opacity accumulation (front to back ordering) and deviation from frontal viewing direction. The second approach is based on complementing of wavelet-based adaptive mesh to the traditional Adaptive Mesh Refinement (AMR) mesh. Both algorithms are illustrated and compared to the existing volume visualization software for Rayleigh-Benard thermal convection and electron density data sets in terms of rendering time and visual quality for different data compression of both wavelet-based and AMR adaptive meshes.

Vezolainen, Alexei V.↗

DOE OSTI2015

Accelerated development of Zr-containing new generation ferritic steels for advanced nuclear reactors

The mission of the Nuclear Energy Enabling Technologies (NEET) program is to develop crosscutting technologies for nuclear energy applications. Advanced structural materials with superior performance at elevated temperatures are always desired for nuclear reactors, which can improve reactor economics, safety margins, and design flexibility. They benefit not only new reactors, including advanced light water reactors (LWRs) and fast reactors such as the sodium-cooled fast reactor (SFR) that is primarily designed for management of high-level wastes, but also life extension of the existing fleet when component exchange is needed. Developing and utilizing the modern materials science tools (experimental, theoretical, and computational tools) is an important path to more efficient alloy development and process optimization. The ultimate goal of this project is, with the aid of computational modeling tools, to accelerate the development of Zr-bearing ferritic alloys that can be fabricated using conventional steelmaking methods. The new alloys are expected to have superior high-temperature creep performance and excellent radiation resistance as compared to Grade 91. The designed alloys were fabricated using arc-melting and drop-casting, followed by hot rolling and conventional heat treatments. Comprehensive experimental studies have been conducted on the developed alloys to evaluate their hardness, tensile properties, creep resistance, Charpy impact toughness, and aging resistance, as well as resistance to proton and heavy ion (Fe 2+ ) irradiation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Atomistic modeling of interface strengthening in Al-Si eutectic alloys

Al-Si cast alloys are usually composed of α-Al and Al-Si eutectic. Si flakes and Al matrix generally hold cube-on-cube orientation relationship with the primary interface (111) Al ∥(111) Si . Extensive experimental studies demonstrated that Si flakes cannot significantly improve mechanical properties of Al-Si cast alloys. We hypothesize that the weak strengthening effect associated with Si flakes might be attributed to thermomechanical properties of Al-Si interfaces besides their morphologies. To characterize Al-Si interfaces with a large lattice mismatch (> 30%), we proposed the quasi-coincident site lattice (Q-CSL) as reference lattice, and demonstrated that the Q-CSL Al-Si coherent interface has three characteristic coherent structures, one stable and low energy structure and two metastable and high energy structures. The translation vectors for the same type of coherent Q-CSL structures are consistent with three displacement shift complete (DSC) vectors. The two metastable structures can be obtained by shifting the low energy structure with three partial DSC vectors. Semi-coherent interface is composed of the low energy Q-CSL patches and three sets of interface misfit dislocations with Burgers vectors same as the DSC vectors. Atomistic simulations revealed that Al-Si interface exhibits low shear resistance. Ideal shear strength of the Q-CSL coherent interface is 110 MPa and semi-coherent interface is 20 MPa. The low shear resistance is attributed to the glide of interface misfit dislocations. Al-Si interface also exhibits low formation and migration energies of point defects. Owing to low shear strength and low formation and migration energies of point defects, interface sliding or shear readily happen under mechanical loading or during dislocation-interface interactions. Lattice dislocations can cross slip onto or climb along Al-Si interfaces. These reactions decrease the number of accumulated dislocation loops around Si flakes and promote nucleation and emission of lattice dislocations from Al-Si interfaces to matrix, consequently reduce the repulsive force on approaching dislocations and weaken Si flakes strengthening effect. In situ tension and compression tests in a scanning electron microscope reveal relatively weak strengthening effect due to Si flakes, consistent with the computed dislocation interaction with interfaces and shear behavior of interfaces.

36 MATERIALS SCIENCE↗

DOE OSTI2020

PASSAT: particle accelerator helioScopes for Slim Axion-like-particle deTection

We propose a novel method to search for axion-like particles (ALPs) at particle accelerator experiments. ALPs produced at the target via the Primakoff effect subsequently enter a region with a magnetic field, where they are converted to photons that are then detected. Dubbed Particle Accelerator helioScopes for Slim Axion-like-particle deTection (PASSAT), our proposal uses the principle of the axion helioscope but replaces ALPs produced in the Sun with those produced in a target material. Since we rely on ALP-photon conversions , our proposal probes light (slim) ALPs that are otherwise inaccessible to laboratory-based experiments which rely on ALP decay, and complements astrophysical probes that are more model-dependent. As a first application, we reinterpret existing data from the NOMAD experiment in light of PASSAT, and constrain the parameter space for ALPs lighter than $$\sim 100~\mathrm{eV}$$ ~ 100 eV and ALP-photon coupling larger than $$\sim 10^{-4}~\mathrm{GeV}^{-1}$$ ~ 10 - 4 GeV - 1 . As benchmarks of feasible low-cost experiments improving over the NOMAD limits, we study the possibility of re-using the magnets of the CAST and the proposed BabyIAXO experiments and placing them at the proposed BDF facility at CERN, together with some new detectors. We find that these realizations of PASSAT allow for a direct probe of the parameter space for ALPs lighter than $$\sim 100~\mathrm{eV}$$ ~ 100 eV and ALP-photon coupling larger than $$\sim 4\times 10^{-6}~\mathrm{GeV}^{-1}$$ ~ 4 × 10 - 6 GeV - 1 , which are regions that have not been probed yet by experiments with laboratory-produced ALPs. In contrast to other proposals aiming at detecting single or two-photon only events in hadronic beam dump environments, that rely heavily on Monte Carlo simulations, the background in our proposal can be directly measured in-situ , its suppression optimized, and the irreducible background statistically subtracted. Sensitivity evaluations with other beams will be the subject of a future paper. The measurements suggested in this paper represent an additional physics case for the BDF at CERN beyond those already proposed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

On the implementation of dislocation reactions in continuum dislocation dynamics modeling of mesoscale plasticity

The continuum dislocation dynamics framework for mesoscale plasticity is intended to capture the dislocation density evolution and the deformation of crystals when subjected to mechanical loading. It does so by solving a set of transport equations for dislocations concurrently with crystal mechanics equations, with the latter being cast in the form of an eigenstrain problem. Incorporating dislocation reactions in the dislocation transport equations is essential for making such continuum dislocation dynamics predictive. A formulation is proposed to incorporate dislocation reactions in the transport equations of the vector density-based continuum dislocation dynamics. This formulation aims to rigorously enforce dislocation line continuity using the concept of virtual dislocations that close all dislocation loops involved in cross slip, annihilation, and glissile and sessile junction reactions. The addition of virtual dislocations enables us to accurately enforce the divergence free condition upon the numerical solution of the dislocation transport equations for all slip systems individually. A set of tests were performed to illustrate the accuracy of the formulation and the solution of the transport equations within the vector density-based continuum dislocation dynamics. Comparing the results from these tests with an earlier approach in which the divergence free constraint was enforced on the total dislocation density tensor or the sum of two densities when only cross slip is considered shows that the new approach yields highly accurate results. Bulk simulations were performed for a face centered cubic crystal based on the new formulation and the results were compared with discrete dislocation dynamics predictions of the same. The microstructural features obtained from continuum dislocation dynamics were also analyzed with reference to relevant experimental observations.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Characterization of a Cast Duplex Stainless Steel with 3.0%Cu and Modeling of Precipitation Hardening

Duplex stainless steels (DSSs) are corrosion-resistant alloys extensively used in aggressive environments. Cast DSSs may be selected for pipes, valves and pumps in chemical, petrochemical and nuclear industries. The grade steel ASTM A890 1B is an example of cast DSS with 2.7-3.3%Cu addition. Copper increases the resistance to many types of corrosion, especially in non-oxidizing environments. When the copper content is higher than 2%, the steel can be precipitation-hardened. In this work, the precipitation hardening of a DSS ASTM A890 1B steel with 3.0%Cu was studied and modeled for aging temperatures in the 450-600 °C range. Copper precipitates in the ferrite phase, but remains in solid solution in the austenite. The age hardening curves were modeled by ΔH = K(t){sup n} model, where ΔH is the increase in hardness, t is the aging time, and K and n are constants to be determined. The microstructure and substructure were investigated by scanning electron and transmission electron microscopes.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Micromechanical Surrogate Machine Learning Model for Creep Deformation Modeling

Process variability during the manufacture of gas turbine engine hot section components can significantly affect the material’s resulting microstructure. In casting, for instance, geometric variation within a component (thin sections versus thick sections, radial location) influences cooling rates and the resulting grain size. The high temperature creep response is known to be sensitive to grain size owing to a diffusional creep mechanism which occurs more readily along grain boundaries. Microstructural variation correspondingly drives mechanical behavior which propagates into component scale performance uncertainty. These factors are essential when planning inspection, maintenance, and repair strategies within a reliability framework. These benefits provide opportunities to increase overall energy efficiency through refined margins. Critically, there is an opportunity to bolster existing data-driven reliability models using physics-driven process-structure-property relations. Here we present recent work establishing a framework for evaluating the probabilistic creep performance of high-temperature materials. A novel microstructure-sensitive crystal plasticity finite element model is established that captures both grain boundary and crystallographic deformation effects. The computationally expensive physics model is calibrated using a statistical approach and this high-fidelity model is subsequently used to train a computationally efficient machine learning surrogate model. The surrogate model is essential for sampling a large ensemble of simulated structure-property pair results. The ensemble data are then mined to extract salient trends to be incorporated into a microstructure-sensitive reliability model. The proposed approach represents a novel way to capture microstructure-sensitive trends from physics-based models within a modern reliability framework.

Fernandez-Zelaia, Patxi [ORNL]↗

DOE OSTI2024

Atomic Diffusivities of Yttrium, Titanium and Oxygen Calculated by Ab Initio Molecular Dynamics in Molten 316L Oxide-Dispersion-Strengthened Steel Fabricated via Additive Manufacturing

Oxide-dispersion-strengthened (ODS) steels have long been viewed as a prime solution for harsh environments. However, conventional manufacturing of ODS steels limits the final product geometry, is difficult to scale up to large components, and is expensive due to multiple highly involved, solid-state processing steps required. Additive manufacturing (AM) can directly incorporate dispersion elements (e.g., Y, Ti and O) during component fabrication, thus bypassing the need for an ODS steel supply chain, the scale-up challenges of powder processing routes, the buoyancy challenges associated with casting ODS steels, and the joining issues for net-shape component fabrication. In the AM process, the diffusion of the dispersion elements in the molten steel plays a key role in the precipitation of the oxide particles, thereby influencing the microstructure, thermal stability and high-temperature mechanical properties of the resulting ODS steels. In this work, the atomic diffusivities of Y, Ti, and O in molten 316L stainless steel (SS) as functions of temperature are determined by ab initio molecular dynamics simulations. The latest Vienna Ab initio Simulation Package (VASP) package that incorporates an on-the-fly machine learning force field for accelerated computation is used. At a constant temperature, the time-dependent coordinates of the target atoms in the molten 316L SS were analyzed in the form of mean square displacement in order to obtain diffusivity. The values of the diffusivity at multiple temperatures are then fitted to the Arrhenius form to determine the activation energy and the pre-exponential factor. Given the challenges in experimental measurement of atomic diffusivity at such high temperatures and correspondingly the lack of experimental data, this study provides important physical parameters for future modeling of the oxide precipitation kinetics during AM process.

Chemistry↗