SCALE Activities in FY22 [Slides]
This lecture touches on SCALE activities in the fiscal year of 2022. Discussion includes updates to scale.ornl.gov and the scale 6.3 online manual. Additionally, practical tools for rapid analysis are highlighted.
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This lecture touches on SCALE activities in the fiscal year of 2022. Discussion includes updates to scale.ornl.gov and the scale 6.3 online manual. Additionally, practical tools for rapid analysis are highlighted.
Near-photospheric flow fields on the Sun are deduced using two independent methods applied to the same time series of velocity images observed by SOI-MDI on SOHO. Differences in travel times between f modes entering and leaving each pixel measured using time-distance helioseismology are used to determine sites of supergranular outflows. Alternatively, correlation tracking analysis of mesogranular scales of motion applied to the same time series is used to deduce the near-surface flow field. These two approaches provide the means to assess the patterns and evolution of horizontal flows on supergranular scales even near disk center, which is not feasible with direct line-of-sight Doppler measurements. We find that the locations of the supergranular outflows seen in flow fields generated from correlation tracking coincide well with the locations of the outflows determined from the time-distance analysis, with a mean correlation coefficient after smoothing of bar-r(sub s) = 0.840. Near-surface velocity field measurements can used to study the evolution of the supergranular network, as merging and splitting events are observed to occur in these images. The data consist of one 2048-minute time series of high-resolution (0.6" pixels) line-of-sight velocity images taken by MDI on 1997 January 16-18 at a cadence of one minute.
The Grizzly software application is being developed under the Light Water Reactor Sustainability (LWRS) program to address aging and material degradation issues that could potentially become an obstacle to life extension of nuclear power plants beyond 60 years of operation. Grizzly is based on INL’s MOOSE multiphysics simulation environment, and can simultaneously solve a variety of tightly coupled physics equations, and is thus a very powerful and flexible tool with a wide range of potential applications. Grizzly, the development of which was begun during fiscal year (FY) 2012, is intended to address degradation in a variety of critical structures. The reactor pressure vessel (RPV) was chosen for an initial application of this software. Because it fulfills the critical roles of housing the reactor core and providing a barrier to the release of coolant, the RPV is clearly one of the most safety-critical components of a nuclear power plant. In addition, because of its cost, size and location in the plant, replacement of this component would be prohibitively expensive, so failure of the RPV to meet acceptance criteria would likely result in the shutting down of a nuclear power plant. The current practice used to perform engineering evaluations of the susceptibility of RPVs to fracture is to use the ASME Master Fracture Toughness Curve (ASME Code Case N-631 Section III). This is used in conjunction with empirically based models that describe the evolution of this curve due to embrittlement in terms of a transition temperature shift. These models are based on an extensive database of surveillance coupons that have been irradiated in operating nuclear power plants, but this data is limited to the lifetime of the current reactor fleet. This is an important limitation when considering life extension beyond 60 years. The currently available data cannot be extrapolated with confidence further out in time because there is a potential for additional damage mechanisms (i.e. late blooming phases) to become active later in life beyond the current operational experience. To develop a tool that can eventually serve a role in decision-making, it is clear that research and development must be perfomed at multiple scales. At the engineering scale, a multiphysics analysis code that can capture the thermomechanical response of the RPV under accident conditions, including detailed fracture mechanics evaluations of flaws with arbitrary geometry and orientation, is needed to assess whether the fracture toughness, as defined by the master curve, including the effects of embrittlement, is exceeded. At the atomistic scale, the fundamental mechanisms of degradation need to be understood, including the effects of that degradation on the relevant material properties. In addition, there is a need to better understand the mechanisms leading to the transition from ductile to brittle fracture through improved continuum mechanics modeling at the fracture coupon scale. Work is currently being conducted at all of these levels with the goal of creating a usable engineering tool informed by lower length-scale modeling. This report summarizes progress made in these efforts during FY 2013.
ABSTRACT We evaluate the consistency between lensing and clustering based on measurements from Baryon Oscillation Spectroscopic Survey combined with galaxy–galaxy lensing from Dark Energy Survey (DES) Year 3, Hyper Suprime-Cam Subaru Strategic Program (HSC) Year 1, and Kilo-Degree Survey (KiDS)-1000. We find good agreement between these lensing data sets. We model the observations using the Dark Emulator and fit the data at two fixed cosmologies: Planck (S8 = 0.83), and a Lensing cosmology (S8 = 0.76). For a joint analysis limited to large scales, we find that both cosmologies provide an acceptable fit to the data. Full utilization of the higher signal-to-noise small-scale measurements is hindered by uncertainty in the impact of baryon feedback and assembly bias, which we account for with a reasoned theoretical error budget. We incorporate a systematic inconsistency parameter for each redshift bin, A, that decouples the lensing and clustering. With a wide range of scales, we find different results for the consistency between the two cosmologies. Limiting the analysis to the bins for which the impact of the lens sample selection is expected to be minimal, for the Lensing cosmology, the measurements are consistent with A = 1; A = 0.91 ± 0.04 (A = 0.97 ± 0.06) using DES+KiDS (HSC). For the Planck case, we find a discrepancy: A = 0.79 ± 0.03 (A = 0.84 ± 0.05) using DES+KiDS (HSC). We demonstrate that a kinematic Sunyaev–Zeldovich-based estimate for baryonic effects alleviates some of the discrepancy in the Planck cosmology. This analysis demonstrates the statistical power of small-scale measurements; however, caution is still warranted given modelling uncertainties and foreground sample selection effects.
With current semiconductor technology reaching its physical limits, special-purpose hardware has emerged as an option to tackle specific computing-intensive challenges. Optimization in the form of solving quadratic unconstrained binary optimization problems, or equivalently Ising spin glasses, has been the focus of several new dedicated hardware platforms. These platforms come in many different flavors, from highly-efficient hardware implementations on digital-logic of established algorithms to proposals of analog hardware implementing new algorithms. In this work, we use a mapping of a specific class of linear equations whose solutions can be found efficiently, to a hard constraint satisfaction problem (three-regular three-XORSAT, or an Ising spin glass) with a 'golf-course' shaped energy landscape, to benchmark several of these different approaches. We perform a scaling and prefactor analysis of the performance of Fujitsu's digital annealer unit (DAU), the D-Wave advantage quantum annealer, a virtual MemComputing machine, Toshiba's simulated bifurcation machine (SBM), the SATonGPU algorithm from Bernaschi et al, and our implementation of parallel tempering. We identify the SATonGPU and DAU as currently having the smallest scaling exponent for this benchmark, with SATonGPU having a small scaling advantage and in addition having by far the smallest prefactor thanks to its use of massive parallelism. Furthermore, our work provides an objective assessment and a snapshot of the promise and limitations of dedicated optimization hardware relative to a particular class of optimization problems.
The problem of wavenumber selection for fully nonlinear, small-wavelength Goertler vortices in a curved channel flow is considered. These types of Goertler vortices were first considered by Hall & Lakin (1988) for an external boundary layer flow. They proved particularly amenable to asymptotic description, it was possible to consider vortices large enough so that the mean flow correction driven by them is as large as the basic state, and this prompted the authors to consider them in a curved channel flow as an initial application of the phase-equation approach to Goertler vortices. This involves the assumption that the phase variable of these Goertler vortices varies on slow spanwise and time scales, then an analysis of both inside and outside the core region, to which vortex activity is restricted, leads to a system of partial differential equations which can be solved numerically for the wavenumber. The authors consider in particular the effect on the wavenumber of the outer channel wall varying on the same slow spanwise scale as the phase variable.
The analysis of data recorded by the Voyager 2 spacecraft indicates the presence of large-scale fluctuations in the solar wind ram pressure on the time scale of tens of days. The amplitude of the fluctuations is highly variable but often lies within a factor of 5 to 10 change from an average or mean value of the ram pressure. Since the spacecraft has presumably not encountered the termination shock yet, these fluctuations should eventually interact with the shock and thereby play a role in determining the shock location. Numerical solutions of the time-dependent gasdynamic equations are used to simulate the response of the termination shock to fluctuations in the solar wind ram pressure comparable to those observed. The primary result of this study is that the maximum shock excursion due to the fluctuations is of the order of 1 AU, which is much smaller than that predicted by other studies. Additional simulations show that the limited movement is due to the fact that the time scale for the termination shock response is substantially larger than the time scale of the fluctuations. It is also shown that the heliopause acts as a barrier for the fluctuations and confines them to the heliosphere.
The analysis of data recorded by the Voyager 2 spacecraft indicates the presence of large-scale fluctuations in the solar wind ram pressure on the time scale of tens of days. The amplitude of the fluctuations is highly variable but often lies within a factor of 5 to 10 change from an average or mean value of the ram pressure. Since the spacecraft has presumably not encountered the termination shock yet, these fluctuations should eventually interact with the shock and thereby play a role in determining the shock location. Numerical solutions of the time-dependent gas dynamic equations are used to simulate the response of the termination shock to fluctuations in the solar wind ram pressure comparable to those observed. The primary result of this study is that the maximum shock excursion due to the fluctuations is of the order of 1 AU, which is much smaller than that predicted by other studies. Additional simulations show that the limited movement is due to the fact that the time scale for the termination shock response is substantially larger than the time scale of the fluctuations. It is also shown that the heliopause acts as a barrier for the fluctuations and confines them to the heliosphere.
Abstract Analyses of fault attributes have contributed to unraveling fault growth processes in diverse tectonic settings. By integrating such analysis at the scale of a fault population, we propose to investigate the characteristics of a rift that has evolved up to a stage typical of a continent‐ocean transition. We address this problem by considering Dabbahu‐Manda‐Hararo (DMH) rift segment (Central Afar, Ethiopia), recognized for being in a late rifting stage. We quantify fault azimuth, length, and throw attributes for 668 normal faults. Along DMH rift, the mean fault density is 0.87 ± 0.7 km/km 2 and the median tectonic strain ranges from 1.8% to 3.1% assuming a fault dip of 60° and 45°, respectively. Maximum tectonic strain (>10%) is found where the rift azimuth changes. Along‐rift variations in fault azimuth, length, and scaling relationships suggest a different stage of rifting in the northern part of the rift. We show that this difference can be attributed to the influence of the Dabbahu volcano located at the northern tip of the rift, which captured the propagating Manda‐Hararo rift in the last ~100 kyr. The morpho‐tectonic analysis reveals numerous common features with slow‐spreading ridge segments, such as the Lucky Strike segment located along the Mid‐Atlantic ridge (segment length, spreading rate, associated magmatic system) but also with intermediate and fast ones (axial valley, fault throws, and diking). This study reveals that a rift at the continent‐ocean transition may be characterized by a transient and evolutionary behavior that shares features with oceanic ridges from slow‐ to fast‐spreading rates.
Successful development of a large-scale microalgae-based biofuels industry requires comprehensive analysis and understanding of the feedstock supply chain—from facility siting and design through processing and upgrading of the feedstock to a fuel product. The evolution from pilot-scale production facilities to energy-scale operations presents many multi-disciplinary challenges, including a sustainable supply of water and nutrients, operational and infrastructure logistics, and economic competitiveness with petroleum-based fuels. These challenges are partially addressed by applying the Integrated Assessment Framework (IAF) – an integrated multi-scale modeling, analysis, and data management suite – to address key issues in developing and operating an open-pond microalgae production facility. This is done by analyzing how variability and uncertainty over space and through time affect feedstock production rates, and determining the site-specific “optimum” facility scale to minimize capital and operational expenses. This approach explicitly and systematically assesses the interdependence of biofuel production potential, associated resource requirements, and production system design trade-offs. To provide a baseline analysis, the IAF was applied in this paper to a set of sites in the southeastern U.S. with the potential to cumulatively produce 5 billion gallons per year. Finally, the results indicate costs can be reduced by scaling downstream processing capabilities to fit site-specific growing conditions, available and economically viable resources, and specific microalgal strains.
This work presents novel multiscale spatial data analytics using Ripley's K-function, as a measure of spatial interaction, to study one-dimensional arrangement of fractures. Fracture spatial arrangements are classified into clustered, anticlustered, or indistinguishable from random by testing statistical significance of the calculated Ripley's K-function. Characterizations of fracture arrangements are performed as a function of length scale and position. Analysis of the K-function along the study interval identifies where fracture clustering and anticlustering occur. Here, a simulation technique is also introduced here to statistically reconstruct spatial arrangements and to generate fracture realizations that are spatially similar to the fractures observed in the field. With this simulation technique, one can also fill spatial gaps in fracture measurements where data are absent, unreliable, or unused. Synthetic as well as field-measured 1D fracture datasets are used for testing and demonstration. Methods introduced in this work can be readily applied to fracture datasets observed in outcrops, borehole image logs, and cores.
This paper investigates the extreme wet bulb temperatures (TWs) in China, with a focus on understanding the relative contributions of temperature and moisture to the extremes. Analysis of station observations shows that daily extreme temperatures (T), specific humidity (q) and TWs generally co-occur in southeastern China while extreme TW and T rarely overlap in the arid and semi-arid North and Northwest China. Overall, q contributes more than T to extreme TWs, especially in North and Northwest China. Based on the relative contributions of q and T, regional extreme TW events are classified as q-dominated and T-dominated, respectively, to study their large-scale environment. Cluster analysis of global reanalysis data shows that extreme TWs are generally accompanied by increased surface air temperature and humidity, concomitant with anomalous high-pressure and notable water vapor flux convergence. However, important differences are also seen in the large-scale environment during q-dominated and T-dominated extreme TWs. During q-dominated extreme TWs, the large-scale environment favors convection, as indicated by ascending motions, decreased downward solar radiation (DSR) as well as increased precipitable water and near surface relative humidity. In contrast, during T-dominated extreme TWs, convection is inhibited by the large-scale environment that features descending motion and increased DSR, decreased precipitable water as well as decreased relative humidity. Consistent with the contrasting environments, we demonstrate that T-dominated extreme TWs tend to last longer than q-dominated extremes. Given the significant role of moisture in extreme TWs, more research is needed to understand its impacts on heat stress now and in the future.
Pressurized Water Reactor (PWR) burnup credit validation is demonstrated using the benchmarks for quantifying fuel reactivity decrements, published as 'Benchmarks for Quantifying Fuel Reactivity Depletion Uncertainty,' EPRI Report 1022909 (August 2011). This demonstration uses the depletion module TRITON available in the SCALE 6.1 code system followed by criticality calculations using KENO-Va. The difference between the predicted depletion reactivity and the benchmark's depletion reactivity is a bias for the criticality calculations. The uncertainty in the benchmarks is the depletion reactivity uncertainty. This depletion bias and uncertainty is used with the bias and uncertainty from fresh UO{sub 2} critical experiments to determine the criticality safety limits on the neutron multiplication factor, k{sub eff}. The analysis shows that SCALE 6.1 with the ENDF/B-VII 238-group cross section library supports the use of a depletion bias of only 0.0015 in delta k if cooling is ignored and 0.0025 if cooling is credited. The uncertainty in the depletion bias is 0.0064. Reliance on the ENDF/B V cross section library produces much larger disagreement with the benchmarks. The analysis covers numerous combinations of depletion and criticality options. In all cases, the historical uncertainty of 5% of the delta k of depletion ('Kopp memo') was shown to be conservative for fuel with more than 30 GWD/MTU burnup. Since this historically assumed burnup uncertainty is not a function of burnup, the Kopp memo's recommended bias and uncertainty may be exceeded at low burnups, but its absolute magnitude is small. (authors)
Clathrate hydrates are solid crystalline structures most commonly formed from solutions that have nucleated to form a mixed solid composed of water and gas. Understanding the mechanism of clathrate hydrate nucleation is essential to grasp the fundamental chemistry of these complex structures and their applications. Molecular dynamics (MD) simulation is an ideal method to study nucleation at the molecular level because the size of the critical nucleus and formation rate occur on the nano scale. Moreover, various analysis methods for nucleation have been developed through MD to analyze nucleation. In particular, the mean first-passage time (MFPT) and survival probability (SP) methods have proven to be effective in procuring the nucleation rate and critical nucleus size for monatomic systems. This study assesses the MFPT and SP methods, previously used for monatomic systems, when applied to analyzing clathrate hydrate nucleation. Because clathrate hydrate nucleation is relatively difficult to observe in MD simulations (due to its high free energy barrier), these methods have yet to be applied to clathrate hydrate systems. In this study, we have analyzed the nucleation rate and critical nucleus size of methane hydrate using MFPT and SP methods from data generated by MD simulations at 255 K and 50 MPa. MFPT was modified for clathrate hydrate from the original version by adding the maximum likelihood estimate and growth effect term. The nucleation rates were calculated by MFPT and SP methods and are within 5%; the critical nucleus size estimated by the MFPT method was 50% higher, than values obtained through other more rigorous but computationally expensive estimates. These methods can also be extended to the analysis of other clathrate hydrates.
Lithium supply chains remain heavily concentrated in hard rock and brine resources, creating significant supply risks. Geothermal brines represent an underutilized alternative, yet commercial progress is hindered by the absence of facility-scale cost assessments. Here, we present a techno-economic analysis of large-scale lithium extraction from Salton Sea geothermal brines, drawing on primary company disclosures, process patents, and brine resource modeling. Caused by varying lithium and impurity concentrations, brine dilution over time, and process configurations (e.g., production via carbonation and conversion vs. electrolysis), we find that large-scale production costs may reach ~10,000 United States dollars per ton, but increase up to 22,000 United States dollars per ton with higher certainty of brine modeling, raising concerns about economic competitiveness to conventional low-cost sources. Finally, a project feasibility-focused scenario analyses shows that leveraging brine pre-treatment by-product sales could lower long-term lithium break-even prices by ~5,000 United States dollars per ton, whereas capital cost optimization of 20% could further reduce lithium break-even prices by 10%.
This dataset accompanies the report "Potential Availability of and Supply Curves for Low-Cost, Dispatch-Constrained Electricity", which provides initial estimates of the quantity and availability of the potential low-cost, dispatch-constrained electricity (LDE) resource in the United States under scenarios with high variable renewable energy (VRE) penetrations. The analysis also estimates supply curves that can be used in subsequent analysis of the opportunity to use the LDE. The estimated LDE resource could be used for various applications that value low-cost electricity and can operate at reduced capacity factors, including electrolytic hydrogen production and carbon capture. The analysis accompanying this dataset was performed in 2018-2019 to support an analysis of "The Technical and Economic Potential of the H2@Scale Concept within the United States" ( https://www.nlr.gov/docs/fy21osti/77610.pdf ). This dataset includes the quantity of estimated LDE resource for each hour of the year in 2050, aggregated to both the national level and the ReEDS balancing area level. As described in the accompanying report, the ReEDS model was used to project the evolution of the power sector over time. Links to the mapping of ReEDS balancing areas to states and ReEDS balancing area shape files are provided. This dataset also includes the report figure data.
Here, a model developed to represent the progress of erosion damage in liquid-metal spallation target vessels was modified to incorporate the effect of gas injection on the erosion rate. The liquid mercury target system for the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory now operates with helium gas injection to reduce target vessel fatigue stress and cavitation-induced erosion damage. Erosion damage is a primary degradation phenomenon affecting the service life of SNS target vessels, and cavitation mitigation techniques, such as small-bubble gas injection, have been implemented to reduce damage and extend target lifetimes. Erosion depths in samples removed from SNS targets after operation were measured using laser line scanning. These measurements confirmed that gas injection reduced erosion damage. However, quantifying the damage reduction due to gas injection was complicated by variations in lifetime, power, and gas injection rates between different targets. In this study, the operating power and gas injection rate of targets were incorporated into an erosion damage prediction model to quantify their effects on erosion damage reduction. Values of a power scaling factor, β, were calculated by comparing modeled with measured erosion damage. These values indicate that the use of gas injection at the SNS reduced damage to a level equivalent to operating targets without gas injection at 35–47% of the actual beam power. To account for the gas injection effect on the cavitation damage, a simple exponential form based on analysis of the scaling factor β was developed to incorporate the gas rate history with a scaling factor γ in the erosion damage modeling.
A spherical blast wave generated by a sudden release of a sphere of compressed gas is an important model problem to understand blast phenomena such as volcanic eruptions and explosive detonations. The resulting explosion flow physics, such as the instability at the gas contact discontinuity and the interaction between the shock wave and the gas contact, are dictated by the initial pressure and sound-speed ratios between the compressed gas and the ambience. Since the initial pressure and sound-speed ratios vary over a wide range in practical applications, it is of interest to investigate the scaling laws and similarity solutions for the spherical symmetric explosion flow. In the present study, numerical simulation of a spherical blast wave is performed. A long-term length scale that incorporates the initial charge radius and the initial pressure ratio is introduced. The trajectories of the main shock normalized by the long-term length scale for a wide range of parameters collapse after a short transition time, indicating an asymptotic similarity solution exists for the far field in the long term. With the assistance of this similarity solution, the full evolution of the main shock can be obtained semi-analytically. For near-field features, i.e. the gas contact and the secondary shock wave, only semi-similarity solutions are observed, which depend on the initial sound-speed ratio but not the initial pressure ratio. The gas contact and the secondary shock share the same scaling relations. Asymptotic analysis is performed to obtain the short-term dynamics of the gas contact, including the gas contact acceleration and the Atwood number, which are the key parameters determining the Rayleigh–Taylor instability development at the gas contact. The asymptotic contact radius as $t\rightarrow \infty$ is also obtained, which is found to be well represented by the long-term length scale and thus only depends on the initial pressure ratio. A simple model of an oscillating bubble is employed to explain the scaling relation of the asymptotic gas contact radius.