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At least 217 records · Page 12

Hanford Waste Treatment Plant LAB Facility Stack Effluent Monitoring: Sampling Probe Location Qualification Evaluation

The Waste Treatment Plant laboratory (LAB) facility stack monitor locations were qualified using scale model stacks to mitigate the risk of identifying that sampling locations do not meet the qualification criteria on the full-scale stack. As required by the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-1999 standard, the scale model and its sampling location were geometrically similar to the actual stack, and the Reynolds numbers for both the actual and model stacks were >10,000. An additional criterion is that the product of the hydraulic diameter and mean velocity (DV) of the full-scale stack must be between 1/6 DV and 6 DV of the scale model stack tests. Verification tests of the LAB stacks were performed at normal operating conditions. The minimum 1/6 DV value, along with the maximum 6 DV value from the scale model testing, determines the range of conditions for which the full-scale stack may be operated and remain in compliance with the stack verification criterion. A practical range for the full-scale stack qualification uses the average DV through 6 DV from the scale model tests to compute the corresponding flow rates. Table S1 lists the operating flow rates along with the average and maximum qualified stack flow rates for each of the LAB facility stacks. For each stack, the operating flow is below the maximum qualified stack flow, which means that the scale model test results are acceptable for stack qualification. The remaining criteria for the stack verification to be considered valid involve the flow angle and velocity uniformity results. First, the flow angle at the full-scale stack must be ≤20°. Second, the velocity uniformity at the full-scale stack must be ≤20% coefficient of variance (COV). Finally, the velocity uniformity results for the actual and scale model stack tests must agree within 5% COV. These criteria were met through the full-scale stack tests at the LAB facility. Flow angle results were primarily less than 10°, except for the LB-C2 Fan A results, which were an average of 13.7°; all flow angle results were within the ≤20° criterion. The velocity uniformity results for each test condition averaged between 1.5 and 4.1% COV, which were all within the range of the target percent coefficient of variation values from the scale model tests. Based on these stack verification test results, the three LAB filtered exhaust stack sampling locations meet the qualification criteria provided in the ANSI/HPS N13.1-1999 standard for all fan operating configurations. This includes single-fan as well as dual-fan operations for LB-C2, each of the dual-fan operating conditions for LB-S1, and each single-fan operating condition for LB-S2. Further changes to the system configuration or operating conditions that are outside the bounds described in this report may require additional tests or analyses to determine compliance with the standard.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Simulation of ENSO Teleconnections to Precipitation Extremes over the United States in the High-Resolution Version of E3SM

Abstract We evaluate the simulated teleconnection of El Niño–Southern Oscillation (ENSO) to winter season precipitation extremes over the United States in a long (98 years) 1950 control high-resolution version (HR; 25-km nominal atmosphere model horizontal resolution) of the U.S. Department of Energy’s (DOE) Energy Exascale Earth System Model version 1 (E3SMv1). The model bias and spatial pattern of ENSO teleconnections to mean and extreme precipitation in HR overall are similar to the low-resolution model’s (LR; 110 km) historical simulation (four-member ensemble, 1925–59). However, over the southeastern United States (SE-U.S.), HR produces stronger El Niño–associated extremes, reducing LR’s model bias. Both LR and HR produce weaker than observed increase in storm track activity during El Niño events there, but HR improves the ENSO-associated variability of moisture transport over SE-U.S. During El Niño, stronger vertical velocities in HR produce stronger large-scale precipitation, causing larger latent heating of the troposphere that pulls in more moisture from the Gulf of Mexico into the SE-U.S. This positive feedback also contributes to the stronger mean and extreme precipitation response in HR. Over the Pacific Northwest, LR’s bias of stronger than observed La Niña associated extremes is amplified in HR. Both models simulate stronger than observed moisture transport from the Pacific Ocean into the region during La Niña years. The amplified HR bias there is due to stronger orographically driven vertical updrafts that create stronger large-scale precipitation, despite weaker La Niña–induced storm track activity. Significance Statement New high-resolution Earth system models (ESMs) solve mathematical equations of fluid flow at much smaller spatial scales than prevalent ESMs, and thus are prohibitively expensive to compute. However, they can be useful for simulating accurate details of regional climate extremes that are driven by naturally occurring climate oscillations like El Niño–Southern Oscillation (ENSO). Here, we evaluate the simulation of ENSO-driven precipitation extremes over the United States in the high-resolution version of the U.S. Department of Energy’s new Energy Exascale Earth System Model version 1. We find that the high-resolution model improves upon its low-resolution counterpart over the southeastern United States by producing a better transport of moisture into the region from the Gulf of Mexico during El Niño. Over the U.S. Pacific Northwest, the high-resolution model simulates the atmospheric flow in more detail over the complex mountainous terrain. However, it also brings in more moisture from the Pacific Ocean just like the low-resolution model. This causes it to produce precipitation extremes during La Niña years there that are stronger than that observed in the real world.

54 ENVIRONMENTAL SCIENCES↗

EXPRES. I. HD 3651 as an Ideal RV Benchmark

The next generation of exoplanet-hunting spectrographs should deliver up to an order of magnitude improvement in radial velocity (RV) precision over the standard 1 m s{sup −1} state-of-the-art spectrographs. This advance is critical for enabling the detection of Earth-mass planets around Sun-like stars. New calibration techniques such as laser frequency combs and stabilized etalons ensure that the instrumental stability is well characterized. However, additional sources of error include stellar noise, undetected short-period planets, and telluric contamination. To understand and ultimately mitigate error sources, the contributing terms in the error budget must be isolated to the greatest extent possible. Here, we introduce a new high-cadence RV program, the Extreme Precision Spectrograph (EXPRES) 100 Earths Survey, which aims to identify rocky planets around bright, nearby G and K dwarfs. We also present a benchmark case: the 62 day orbit of a Saturn-mass planet orbiting the chromospherically quiet star, HD 3651. The combination of high eccentricity (0.6) and a moderately long orbital period ensures significant dynamical clearing of any inner planets. Our Keplerian model for this planetary orbit has a residual rms of 58 cm s{sup −1} over a ∼6 month time baseline. By eliminating significant contributors to the RV error budget, HD 3651 serves as a standard for evaluating the long-term precision of extreme precision RV programs.

79 ASTRONOMY AND ASTROPHYSICS↗

Mesh-Sequenced Realizations for Evaluation of Subgrid-Scale Models for Turbulent Combustion

This paper develops a new approach for analysis of subgrid closures for turbulent combustion as modeled using direct quadrature (finite-rate chemistry) techniques. The approach, termed multiresolution analysis through mesh-sequenced realizations (MRA-MSR), conducts simultaneous, constrained large-eddy simulations on a set of hierarchically coarsened meshes. Furthermore, the availability of underlying fine-mesh (subgrid) data corresponding to coarse-mesh locations allows a clearer assessment of the effects of unresolved fluctuations on apparent reactivity. A key to MRA-MSR is the correlation of eddy structures at coarser mesh levels, which is facilitated by the transfer of filtered fine-mesh velocity information. A seven-mesh MRA-MSR hierarchy using three resolution levels is applied to one of the Sydney bluff-body stabilized methane–hydrogen flames. Analysis of the simultaneously evolved data at different resolution levels reveals several interesting trends. First, at high Damköhler numbers, there is clear evidence of attenuation of apparent reactivity due to the effects of unresolved fluctuations. Secondly, single-point, single-time filtered density functions of a normalized subgrid Damköhler number show a characteristic beta probability density function (PDF) form and display evidence of scale similarity. Interrogation of the MRA-MSR database also shows that the recently-proposed least-squares minimization (LSM) turbulence–chemistry interaction model can account for the observed diminishment in reactivity at high Damköhler numbers but cannot reduce scatter significantly. A new form of the LSM model, which makes use of the normalized subgrid Damköhler number beta PDF distribution, performs slightly better than the original model, illustrating the potential of MRA-MSR both in assessing existing closure concepts and in developing new ones.

42 ENGINEERING↗

Transient solute drag and strain aging of dislocations

The transient drag force exerted by mobile solutes on a moving dislocation is computed using continuum theory. These mobile solutes form so-called Cottrell atmospheres around dislocations during static and dynamic strain aging. We evaluate the evolution of the drag force exerted by the atmosphere under two velocity time-histories: impulsive acceleration to a chosen velocity and a constant acceleration rate. A particular focus is on the conditions under which the stationary limit assumed by theories of dynamic strain aging is obeyed. According to our results, two conditions—one on the dislocation velocity and one on the acceleration rate—must be satisfied for the stationary limit to hold. Using the Orowan relation and a line tension model, we obtain estimates for the temperature, stress, strain rate, and dislocation density regimes where the stationary limit is valid, and compare these results with experiments for a few material systems.

36 MATERIALS SCIENCE↗

Inflation alternative via the gravitational field of a singularity

Abstract We explore the scenario that the observable Universe emerged from the vicinity of a negative mass ring singularity, and all content of the Universe travels at the same group velocity close to the speed of light on a geodesic trajectory along the axis of rotation of the singularity. In appropriate coordinate parametrization and evaluated on the trajectory, we find that the metric tensor in the vicinity of the trajectory exhibits a conformal scale factor a ( η ) with contraction and subsequent expansion properties that solve the horizon problem. We then introduce a static flow of gravitating radiation along the trajectory (perturbatively with respect to the mass scale of the singularity) to model a homogeneous radiation dominated Universe. Solving the Einstein field equations with a physically motivated ansatz of metric perturbation then reveals that the effective conformal scale factor indeed grows asymptotically with the same power law as expected in a conventional radiation dominated Universe.

Astronomy & Astrophysics↗

High-Fidelity Energy Deposition Ignition Model Coupled with Flame Propagation Models at Engine-like Flow Conditions

With the heightened pressure on car manufacturers to increase the efficiency and reduce the carbon emissions of their fleets, more challenging engine operation has become a viable option. Highly dilute, boosted, and stratified charge, among others, promise engine efficiency gains and emissions reductions. At such demanding engine conditions, the spark-ignition process is a key factor for the flame initiation propagation and the combustion event. From a computational standpoint, there exist multiple spark-ignition models that perform well under conventional conditions but are not truly predictive under strenuous engine operation modes, where the underlying physics needs to be expanded. In this paper, a hybrid Lagrangian-Eulerian spark-ignition (LESI) model is coupled with different turbulence models, grid sizes, and combustion models. The ignition model, previously developed, relies on coupling Eulerian energy deposition with a Lagrangian particle evolution of the spark channel, at every time-step. The spark channel is attached to the electrodes and allowed to elongate at a speed derived from the flow velocity. The LESI model is used to simulate spark ignition in a nonquiescent crossflow environment at engine-like conditions, using converge commercial computational fluid dynamics (CFD) solver. The results highlight the consistency, robustness, and versatility of the model in a range of engine-like setups, from typical with Reynolds-averaged Navier-Stokes (RANS) and a larger grid size to high fidelity with large-eddy simulation (LES) and a finer grid size. The flame kernel growth is then evaluated against Schlieren images from an optical constant volume ignition chamber with a focus on the performance of flame propagation models, such as G-equation and thickened flame model, versus the baseline well-stirred reactor model. Finally, future development details are discussed.

Advanced ignition modeling↗

Experimental and Kinetic Modeling Study of Laminar Burning Velocities of Cyclopentanone and Its Binary Mixtures with Ethanol and n-Propanol

Cyclopentanone is a promising biofuel that can enable more efficient engine operation and increase the fuel economy of the light duty fleet over current and planned technology developments. While the ignition of cyclopentanone has been investigated in detail, more studies on the laminar burning velocities of cyclopentanone are called for. In this work, the laminar burning velocities of cyclopentanone (C 5 H 8 O) have been measured using the heat flux and spherical flame methods at 1 atm, equivalence ratios from 0.7 to 1.6, and initial temperatures of 328, 353, and 428 K. To further investigate the relationship between the molecular structure and laminar burning velocity, identical experiments were also performed for binary mixtures of cyclopentanone with ethanol and n-propanol at 1:1 (mol). The consistency between the experimental data sets obtained in this work and literature data sets has been evaluated. Here, a recently published mechanism of cyclopentanone was used for simulation after adopting the submechanism of n-propanol. Good agreement has been seen between experimental and simulated results for all flames. To qualitatively explain the characteristics of the laminar burning velocity of cyclopentanone and the differences with those of ethanol and n-propanol, sensitivity analysis and reaction pathway analysis have been performed to compare the chemistry of the fuels under flame conditions, which revealed how the molecular structure of cyclopentanone could affect its laminar burning velocity. Compared to ethanol and n-propanol, cyclopentanone does not have primary carbon atoms in its molecule, leading to lower production of methyl radicals. Meanwhile, the carbonyl group in the cyclopentanone molecule is mostly released as CO in the decomposition of multiple intermediates accompanied by the production of unsaturated C 2 and C 4 species, especially C 2 H 4 and C 2 H 3 . Both features contribute to the high laminar burning velocity of cyclopentanone.

09 BIOMASS FUELS↗

Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments

In this paper, we developed a machine learning-based Bayesian approach to inversely quantify and reduce the uncertainties of multiphase computational fluid dynamics (MCFD) simulations for bubbly flows. The proposed approach is supported by high-resolution two-phase flow measurements, including those by double-sensor conductivity probes, high-speed imaging, and particle image velocimetry. Local distributions of key physical quantities of interest (QoIs), including the void fraction and phasic velocities, are obtained to support the Bayesian inference. In the process, the epistemic uncertainties of the closure relations are inversely quantified while the aleatory uncertainties from stochastic fluctuations of the system are evaluated based on experimental uncertainty analysis. The combined uncertainties are then propagated through the MCFD solver to obtain uncertainties of the QoIs, based on which probability-boxes are constructed for validation. The proposed approach relies on three machine learning methods: feedforward neural networks and principal component analysis for surrogate modeling, and Gaussian processes for model form uncertainty modeling. The whole process is implemented within the framework of an open-source deep learning library PyTorch with graphics processing unit (GPU) acceleration, thus ensuring the efficiency of the computation. The results demonstrate that with the support of high-resolution data, the uncertainties of MCFD simulations can be significantly reduced. The proposed approach has the potential for other applications that involve numerical models with empirical parameters.

42 ENGINEERING↗

Wintertime Supraglacial Lake Drainage Cascade Triggers Large‐Scale Ice Flow Response in Greenland

Surface melt forces summertime ice-flow accelerations on glaciers and ice sheets. Here, we show that large meltwater-forced accelerations also occur during wintertime in Greenland. We document supraglacial lakes (SGLs) draining in cascades at unusually high elevation, causing an expansive flow acceleration over a ~5,200 km 2 region during winter. The three-component interferometric surface velocity field and decomposition modeling reveal the underlying flood propagation with unprecedented detail as it traveled over 160 km from the drainage site to the margin, providing novel constraints on subglacial water pathways, drainage morphology, and links with basal sliding. The triggering SGLs continuously grew over 40 years and suddenly released decades of stored meltwater, demonstrating surface melting can impact dynamics well beyond melt production. We show these events are likely common and thus their cumulative impact on dynamics should be further evaluated.

54 ENVIRONMENTAL SCIENCES↗

The Influence of the Instantaneous Collapse of Tailings Pond on Downstream Facilities

To evaluate the evolutionary processes guiding the formation of the tailings‐water mixtures produced by the instantaneous collapse of tailings ponds and the influence of these on downstream facilities, a 2D simulation model with reasonable boundary and working conditions derived from actual engineering practice was built in this study, and the relationship between dam‐break elevation and impact on downstream facilities was also analyzed to determine the relevant mechanism of influence. Computational results indicated that lowering the dam‐break elevation caused the maximum velocity and flooding depth, along with the flooded area at monitoring points, to gradually increase. The occurrence times of maximum velocity and flooding depth were also gradually moved forward as the breaking elevation was reduced; this effect is directly related to the increase in the total potential energy at the lower break elevations. Further simulations of sand‐prevent dams with different heights located downstream from a tailings pond were carried out to identify methods for mitigating the impact of dam failure. The results revealed that increasing the height of the sand‐prevent dam reduced the production of tailings mixtures. Based on the results, the construction of a sand‐prevent dam with a crest elevation equal to that of the starter dam was recommended.

Wang, Sha (ORCID:0000000324875445)↗

Computational fluid dynamics analysis of char conversion in Sandia’s pressurized entrained flow reactor

Design and analysis of practical reactors utilizing solid feedstocks rely on reaction rate parameters that are typically generated in lab-scale reactors. Evaluation of the reaction rate information often relies on assumptions of uniform temperature, velocity, and species distributions in the reactor, in lieu of detailed measurements that provide local information. This assumption might be a source of substantial error, since reactor designs can impose significant inhomogeneities, leading to data misinterpretation. Spatially resolved reactor simulations help understand the key processes within the reactor and support the identification of severe variations of temperature, velocity, and species distributions. In this work, Sandia’s pressurized entrained flow reactor is modeled to identify inhomogeneities in the reaction zone. Tracer particles are tracked through the reactor to estimate the residence times and burnout ratio of introduced coal char particles in gasifying environments. The results reveal a complex mixing environment for the cool gas and particles entering the reactor along the centerline and the main high-speed hot gas reactor flow. Furthermore, the computational fluid dynamics (CFD) results show that flow asymmetries are introduced through the use of a horizontal gas pre-heating section that connects to the vertical reactor tube. Computed particle temperatures and residence times in the reactor differ substantially from the idealized plug flow conditions typically evoked in interpreting experimental measurements. Furthermore, experimental measurements and CFD analysis of heat flow through porous refractory insulation suggest that for the investigated conditions (1350 °C, <20 atm), the thermal conductivity of the insulation does not increase substantially with increasing pressure.

47 OTHER INSTRUMENTATION↗

Vorticity screening by dense layers

We investigate variable density layers in the presence of vortices, by analogy to line charges in the presence of a dielectric slab. We adapt solutions for dielectric layers from the literature to the variable density fluid case, obtaining exact hypergeometric expressions for flow velocities induced everywhere by a vortex in the vicinity of a finite-thickness slab of different densities. The dimensionless Atwood number, which appears naturally in other variable density phenomena, such as the Rayleigh–Taylor instability, reappears here as the natural ordering parameter for the influence of the slab, which acts primarily to screen the influence of vorticity across the slab to a lower effective circulation. The solution takes the form of scaling correction factors that might be applied to computational models or evaluated directly. Extensions, where vorticity is localized within the dense layer itself and amplified outside of it, are considered, as well as some speculative applications such as inertial confinement fusion capsule designs.

42 ENGINEERING↗

Deep Learning for Full Waveform Inversion of Elastic Active-Source Seismic Data to Estimate P-Wave Velocity Models

Seismic imaging methods are critical for Global Security and Energy & Homeland Security missions and activities that rely on subsurface characterization, but traditional methods remain computationally expensive and require significant labor hours and expertise to execute. Within the past few years, machine learning (ML), namely deep learning (DL), has been used to develop data-driven end-to-end full waveform inversion (FWI) methods to estimate 2D P-wave velocity (Vp) models in a fraction of the time as conventional FWI. These methods, however, are trained on simplistic acoustic wave seismic data and Vp models that are not realistic nor representative of real-world observations, leaving a large gap between the state-of-the-art and deployable, feasible, and practical DL FWI methods. Here, we generate a synthetic active-source, 3D, elastic wave seismic data set and a variety of Vp models with realistic geologic structure for training DL FWI methods. We evaluate six different methods that have performed well for acoustic DL FWI or medical imaging tasks using our more realistic dataset. We find that these six trained models do not match the performance of published acoustic end-to-end DL FWI methods, indicating more training data may be needed, physics may need to be incorporated to achieve good accuracy at the sacrifice of the end-to-end advantage, and/or novel methods need to be developed to enable end-to-end DL FWI methods to perform well for real-world seismic data.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Hanford Waste Treatment Plant Low Activity Waste Facility Stack Effluent Monitoring - Sampling Probe Location Qualification Evaluation

The Hanford Tank Waste Treatment and Immobilization Plant low activity waste (LAW) facility stack monitor locations were qualified using scale model stacks to mitigate the risk of identifying that sampling locations do not meet the qualification criteria on the full-scale stack. As required by the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-1999 standard, the scale model and its sampling location were geometrically similar to the actual stack and the Reynolds numbers for both the actual and model stacks were >10,000. An additional criterion is that the product of the hydraulic diameter and mean velocity (DV) of the full-scale stack must be between 1/6 DV and 6 DV of the scale model stack tests. Verification tests of the LAW stacks were performed at normal operating conditions. The minimum 1/6 DV value, along with the maximum 6 DV value from the scale model testing determines the range of conditions for which the full-scale stack may be operated and remain in compliance with the stack verification criterion. Based on these DV values, the corresponding stack flow rates for each of the LAW stacks are 815–55,758 scfm for LV-S1, 980–112,078 scfm for LV-S2, 264–22,901 scfm for LV-S3, and 981–79,832 scfm for LV-C2. The remaining criteria for the stack verification to be considered valid involve the flow angle and velocity uniformity results. First, the flow angle at the full-scale stack must be =20°. Second, the velocity uniformity at the full-scale stack must be =20% coefficient of variance (COV). Finally, the velocity uniformity results for the actual and scale model stack tests must agree within 5% COV. These criteria were met through the full-scale stack tests at the LAW facility. Flow angle results were primarily less than 10°, except for one LV-S2 Fan A result, which was 13.2°; all flow angle results were within the =20° criterion. The velocity uniformity results for each test condition ranged between 1.5 COV and 9.2% COV, which were all within the range of the target % COV values from the scale model tests. Based on these stack verification test results, the four LAW filtered exhaust stack sampling locations meet the qualification criteria provided in the ANSI/HPS N13.1-1999 standard for all fan operating configurations. This includes single-fan operating conditions for LV-S1 and LV-S2, dual-fan operations for LV-S3 at both the continuous air monitor and record sampler locations, and both the single-fan as well as the dual-fan operations for LV-C2. Further changes to the system configuration or operating conditions that are outside the bounds described in this report may require additional tests or analyses to determine compliance with the standard.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Hanford Waste Treatment Plant Low Activity Waste Facility Stack Effluent Monitoring: Sampling Probe Location Qualification Evaluation (Rev.1)

The Hanford Tank Waste Treatment and Immobilization Plant Low Activity Waste (LAW) facility stack monitor locations were qualified using scale model stacks to mitigate the risk of discovering that sampling locations do not meet the qualification criteria on the full-scale stacks. As required by the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-1999 standard, the scale model and its sampling location were geometrically similar to the actual stack and the Reynolds numbers for both the actual and model stacks were >10,000. An additional criterion is that the product of the hydraulic diameter and mean velocity (DV) of the full-scale stack must be between 1/6 DV and 6 DV of the scale model stack tests. Verification tests of the LAW stacks were performed at normal operating conditions. The minimum 1/6 DV value, along with the maximum 6 DV value from the scale model testing, determines the range of stack flow rates for which the full-scale stack may be operated and remain in compliance with the stack verification criterion. For this analysis, the range of qualified flow rates listed is conservatively based on the average DV through 6 DV for LV-S1, LV-S2, and LV-C2, and 1/3 DV to 3 DV for LV-S3. Table S1 lists the operating flow rates along with the conservative lower and upper qualified stack flow rates for each of the LAW facility stacks. For each stack, the operating flow is below the upper qualified stack.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Evaluation of Two-Dimensional to One-Dimensional Site Response for Idaho National Laboratory

We perform two-dimensional (2D) site response analyses accounting for spatial variability of soil properties and subsurface geometry of the Eastern Snake River Plane (ESRP), and quantify their effects on ground surface motion relative to one-dimensional (1D) site response analyses at the Idaho National Laboratory (INL). We first present the development of random field idealizations of the repeated basalt lava flows, heterogeneously inter-layered with sediments, from seismic velocity data collected over four decades in the ESRP. Using realizations of the stochastic fields mapped on 2D deterministic finite element models, we perform 2D viscoelastic and equivalent-linear wave propagation simulations, and quantify the mean and variance of site response aggravation factors, defined as the response spectral ratio of 2D to 1D analyses on the ground surface. Results are shown to be insensitive to the constitutive material behavior considered here, for strains induced by rock outcrop peak ground acceleration (PGA) as high as 0.7g: viscoelastic and equivalent-linear analyses predict peak mean 2D/1D aggravation factor 1.05 at period T=0.075 sec (i.e. the 2D response spectrum is 5% higher than the corresponding 1D at that period, on average), which corresponds to the wavelength of the horizontal correlation length of the random field (50m). For periods longer than the fundamental period of the site (here, T 1 =0.3125 sec), the propagating wavelengths are too long to be affected by the 1D site response and the aggravation factor becomes equal to 1. The standard deviation of the natural logarithms of the 2D/1D aggravation factors is ~0.15 for periods shorter than the fundamental period of the site, and decays thereafter at a steady rate.

58 GEOSCIENCES↗

Solidification modes during additive manufacturing of steel revealed by high-speed X-ray diffraction

Solidification during fusion-based additive manufacturing (AM) is characterized by high solidification velocities and large thermal gradients, two factors that control the solidification mode of metals and alloys. Using two synchrotron-based, in situ setups, we perform high-speed X-ray diffraction measurements to investigate the impact of the solidification velocities and thermal gradients on the solidification mode of a hot-work tool steel over a wide range of thermal conditions of relevance to AM of metals. The solidification mode of primary δ-ferrite is observed at a cooling rate of 2.12x10 4 K/s, and at a higher cooling rate of 1.5x10 6 K/s, δ-ferrite is sup-pressed, and primary austenite is observed. The experimental thermal conditions are evaluated and linked to a Kurz-Giovanola-Trivedi (KGT) based solidification model. The modelling results show that the predictions from the multicomponent KGT model agree with the experimental observations. This work highlights the role of in situ XRD measurements for a fundamental understanding of the microstructure evolution during AM and for vali-dation of computational thermodynamics and kinetics models, facilitating parameter and alloy development for AM processes.

36 MATERIALS SCIENCE↗