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DOE OSTI2022

DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification

With increased adoption of supervised deep learning methods for work with cosmological survey data, the assessment of data perturbation effects (that can naturally occur in the data processing and analysis pipelines) and the development of methods that increase model robustness are increasingly important. In the context of morphological classification of galaxies, we study the effects of perturbations in imaging data. In particular, we examine the consequences of using neural networks when training on baseline data and testing on perturbed data. We consider perturbations associated with two primary sources: (a) increased observational noise as represented by higher levels of Poisson noise and (b) data processing noise incurred by steps such as image compression or telescope errors as represented by one-pixel adversarial attacks. We also test the efficacy of domain adaptation techniques in mitigating the perturbation-driven errors. We use classification accuracy, latent space visualizations, and latent space distance to assess model robustness in the face of these perturbations. For deep learning models without domain adaptation, we find that processing pixel-level errors easily flip the classification into an incorrect class and that higher observational noise makes the model trained on low-noise data unable to classify galaxy morphologies. On the other hand, we show that training with domain adaptation improves model robustness and mitigates the effects of these perturbations, improving the classification accuracy up to 23% on data with higher observational noise. Domain adaptation also increases up to a factor of ${\approx}2.3$ the latent space distance between the baseline and the incorrectly classified one-pixel perturbed image, making the model more robust to inadvertent perturbations. Successful development and implementation of methods that increase model robustness in astronomical survey pipelines will help pave the way for many more uses of deep learning for astronomy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Quantum mechanical static dipole polarizabilities in the QM7b and AlphaML showcase databases

While density functional theory (DFT) is often an accurate and efficient methodology for evaluating molecular properties such as energies and multipole moments, this approach often yields larger errors for response properties such as the dipole polarizability (α), which describes the tendency of a molecule to form an induced dipole moment in the presence of an electric field. In this work, we provide static α tensors (and other molecular properties such as total energy components, dipole and quadrupole moments, etc.) computed using quantum chemical (QC) and DFT methodologies for all 7,211 molecules in the QM7b database. We also provide the same quantities for the 52 molecules in the AlphaML showcase database, which includes the DNA/RNA nucleobases, uncharged amino acids, several open-chain and cyclic carbohydrates, five popular pharmaceutical molecules, and 23 isomers of C 8 H n . All QC calculations were performed using linear-response coupled-cluster theory including single and double excitations (LR-CCSD), a sophisticated approach for electron correlation, and the d-aug-cc-pVDZ basis set to mitigate basis set incompleteness error. DFT calculations employed the B3LYP and SCAN0 hybrid functionals, in conjunction with d-aug-cc-pVDZ (B3LYP and SCAN0) and d-aug-cc-pVTZ (B3LYP).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Numerical discreteness errors in multispecies cosmological N -body simulations

ABSTRACT We present a detailed analysis of numerical discreteness errors in two-species, gravity-only, cosmological simulations using the density power spectrum as a diagnostic probe. In a simple set-up where both species are initialized with the same total matter transfer function, biased growth of power forms on small scales when the solver force resolution is finer than the mean interparticle separation. The artificial bias is more severe when individual density and velocity transfer functions are applied. In particular, significant large-scale offsets in power are measured between simulations with conventional offset grid initial conditions when compared against converged high-resolution results where the force resolution scale is matched to the interparticle separation. These offsets persist even when the cosmology is chosen so that the two particle species have the same mass, indicating that the error is sourced from discreteness in the total matter field as opposed to unequal particle mass. We further investigate two mitigation strategies to address discreteness errors: the frozen potential method and softened interspecies short-range forces. The former evolves particles under the approximately ‘frozen’ total matter potential in linear theory at early times, while the latter filters cross-species gravitational interactions on small scales in low-density regions. By modelling closer to the continuum limit, both mitigation strategies demonstrate considerable reductions in large-scale power spectrum offsets.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Improving the real-time probabilistic channel flood forecasting by incorporating the uncertainty of inflow using the particle filter

An accurate and reliable real-time flood forecast is crucial for mitigating flood disasters. The errors associated with the inflow boundary forcing data are considered as an important source of uncertainties in hydraulic model. In this paper, a real-time probabilistic channel flood forecasting model is developed with a novel function to incorporate the uncertainty of the forcing inflow. This new approach couples a hydraulic model with the particle filter (PF) data assimilation algorithm, a sequential Bayesian Monte Carlo method. The stage observations at hydrological stations are assimilated at each time step to update the model states in order to improve the next time step’s forecasting. This new approach is tested against a real flood event occurred in the upper Yangtze River. As compared with the open loop simulations, the evaluations of model performance with several deterministic and probabilistic metrics indicate that the accuracy of the ensemble mean prediction and the reliability of the uncertainty quantification are improved pronouncedly as a result of the PF assimilation. Further assessment of the prediction results at different lead times shows that the improvement of model performance deteriorates with the increase of the lead time due to the gradual diminishing of the updating effect for the initial conditions. Based on the analyses of the number of particles and the assimilation frequency, we find that the optimal number of particles can be determined by balancing the model performance and the computation cost, while a high assimilation frequency is preferred to incorporate the emerging observations to update the model states to match the real conditions.

Channel flood forecasting, probabilistic forecast,↗

DOE OSTI2015

Impact of numerics on the predictive capabilities of reacting flow LES

Combustors in modern aerospace propulsion systems are highly optimized devices and further enhancements to their performance will require advanced predictive modeling techniques. The LES approach has potential to be such a technique, but demonstration of its true predictive capability remains a challenge. In this paper, a methodical study is performed to assess the impact of numerical error on the predictive capabilities of LES and to distinguish it from error arising from physical modeling. Four codes are employed to simulate the bluff body stabilized flame experiment of Volvo Flygmotor AB. The physical models (governing equations and sub-grid models) are kept identical between the codes so that the physical modeling error is the same. For the same reason, computational grids are also kept identical since the sub-grid models are grid dependent. Results indicate that all codes produce a very similar solution for the non-reacting flow in terms of large scale unsteady vortex shedding behavior, mean profiles and second order turbulence statistics, on a suitably refined grid. This solution is also very close to the experimentally observed behavior of the flow. In contrast, for the reacting case, solutions from the various codes exhibit significant differences when analyzed under the same metrics and with similar or even finer grid resolution than that used for the non-reacting case. These differences are large enough to change the macroscopic behavior of the flow, e.g. some codes predict symmetric vortex shedding while others predict asymmetric shedding and some codes show strong recirculation zones while others show stagnant regions behind the bluff body. It is also shown that none of the solutions truly predicts the experimentally observed flow. Given that the physical sub-grid models and computational grids are the same in all the simulations, the inconsistency between results points to a significant impact of numerical methods and, hence, numerical error. The need for mitigation of this impact is highlighted, along with the need for metrics detailing how LES should be applied to reacting flows. It is suggested that both of these issues should be the focus of future work.

Energy & Fuels↗

DOE OSTI2014

On bias of kinetic temperature measurements in complex plasmas

The kinetic temperature in complex plasmas is often measured using particle tracking velocimetry. Here, we introduce a criterion which minimizes the probability of faulty tracking of particles with normally distributed random displacements in consecutive frames. Faulty particle tracking results in a measurement bias of the deduced velocity distribution function and hence the deduced kinetic temperature. For particles with a normal velocity distribution function, mistracking biases the obtained velocity distribution function towards small velocities at the expense of large velocities, i.e., the inferred velocity distribution is more peaked and its tail is less pronounced. The kinetic temperature is therefore systematically underestimated in measurements. We give a prescription to mitigate this type of error.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Photoelectron spectra of early 3 d -transition metal dioxide molecular anions from GW calculations

Photoelectron spectra of early 3 d -transition metal dioxide anions, Sc O 2 - , Ti O 2 - , V O 2 - , Cr O 2 - , and Mn O 2 - , are calculated using semilocal and hybrid density functional theory (DFT) and many-body perturbation theory within the GW approximation using one-shot perturbative and eigenvalue self-consistent formalisms. Different levels of theory are compared with each other and with available photoelectron spectra. We show that one-shot GW with a PBE0 starting point ( G 0 W 0 @PBE0) consistently provides very good agreement for all experimentally measured binding energies (within 0.1 eV–0.2 eV or less). We attribute this to the success of PBE0 in mitigating self-interaction error and providing good quasiparticle wave functions, which renders a first-order perturbative GW correction effective. One-shot GW calculations with a Perdew–Burke–Ernzerhof (PBE) starting point do poorly in predicting electron removal energies by underbinding orbitals with typical errors near 1.5 eV. A higher exact exchange amount of 50% in the DFT starting point of one-shot GW does not provide very good agreement with experiment by overbinding orbitals with typical errors near 0.5 eV. While not as accurate as G 0 W 0 @PBE0, the G -only eigenvalue self-consistent GW scheme with W fixed to the PBE level provides a reasonably predictive level of theory (typical errors near 0.3 eV) to describe photoelectron spectra of these 3 d -transition metal dioxide anions. Adding eigenvalue self-consistency also in W , on the other hand, worsens the agreement with experiment overall. Overall, our findings on the performance of various GW methods are discussed in the context of our previous studies on other transition metal oxide molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Overview of NSTX Upgrade initial results and modelling highlights

The National Spherical Torus Experiment (NSTX) has undergone a major upgrade, and the NSTX Upgrade (NSTX-U) Project was completed in the summer of 2015. NSTX-U first plasma was subsequently achieved, diagnostic and control systems have been commissioned, the H-mode accessed, magnetic error fields identified and mitigated, and the first physics research campaign carried out. During ten run weeks of operation, NSTX-U surpassed NSTX record pulse-durations and toroidal fields (TF), and high-performance ~1 MA H-mode plasmas comparable to the best of NSTX have been sustained near and slightly above the n = 1 no-wall stability limit and with H-mode confinement multiplier H 98y,2 above 1. Transport and turbulence studies in L-mode plasmas have identified the coexistence of at least two ion-gyro-scale turbulent micro-instabilities near the same radial location but propagating in opposite (i.e. ion and electron diamagnetic) directions. These modes have the characteristics of ion-temperature gradient and micro-tearing modes, respectively, and the role of these modes in contributing to thermal transport is under active investigation. The new second more tangential neutral beam injection was observed to significantly modify the stability of two types of Alfven eigenmodes. Improvements in offline disruption forecasting were made in the areas of identification of rotating MHD modes and other macroscopic instabilities using the disruption event characterization and forecasting code. Finally, the materials analysis and particle probe was utilized on NSTX-U for the first time and enabled assessments of the correlation between boronized wall conditions and plasma performance. These and other highlights from the first run campaign of NSTX-U are described.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Fast Sideband Control of a Multimode Cavity Memory with Weak Dispersive Coupling to a Transmon

Mitigating ancilla-mediated error channels is a critical challenge in controlling high-quality superconducting cavities using circuit quantum electrodynamics (cQED). We address this by weakening the dispersive coupling while demonstrating fast, high-fidelity multimode control through transmon-mediated sideband interactions. We implement transmon-cavity SWAP gates with speeds up to 30 times larger than the bare dispersive coupling. Combined with transmon rotations, this enables universal state preparation in a single mode, though achieving unitary gates and extending control to multiple modes remains a challenge. In this work, we overcome this limitation by introducing two control strategies: (i) a shelving technique that stores populations in sideband-transparent states, and (ii) a method that exploits the dispersive shift to implement photon-number-selective transmon-cavity SWAP gates. We use these protocols to prepare Fock and binomial code states across any of the ten modes of a multimode cavity with millisecond coherence times—serving as a multimode quantum memory. We demonstrate unitaries that encode and decode an arbitrary qubit state from the transmon into corresponding vacuum and Fock state superpositions, as well as entangled NOON states of cavity mode pairs—a scheme extendable to arbitrary multimode Fock encodings in the cavity modes. Furthermore, we implement a new binomial encoding gate that converts arbitrary transmon superpositions into binomial code states in any cavity mode at a rate exceeding the dispersive shifts in our system, achieving an average post-selected state fidelity of 96.3% in a 4 μ⁢s gate time. By using precalibrated transmon and sideband pulses, our work demonstrates multimode control with significantly reduced calibration overhead, enabling efficient unitary operations using sideband interactions in multimode cQED systems.

Huang, Jordan [Rutgers Univ., Piscataway, NJ (Unit↗

DOE OSTI2013

Investigation of various energy deposition kernel refinements for the convolution/superposition method

Purpose: Several simplifications used in clinical implementations of the convolution/superposition (C/S) method, specifically, density scaling of water kernels for heterogeneous media and use of a single polyenergetic kernel, lead to dose calculation inaccuracies. Although these weaknesses of the C/S method are known, it is not well known which of these simplifications has the largest effect on dose calculation accuracy in clinical situations. The purpose of this study was to generate and characterize high-resolution, polyenergetic, and material-specific energy deposition kernels (EDKs), as well as to investigate the dosimetric impact of implementing spatially variant polyenergetic and material-specific kernels in a collapsed cone C/S algorithm.Methods: High-resolution, monoenergetic water EDKs and various material-specific EDKs were simulated using the EGSnrc Monte Carlo code. Polyenergetic kernels, reflecting the primary spectrum of a clinical 6 MV photon beam at different locations in a water phantom, were calculated for different depths, field sizes, and off-axis distances. To investigate the dosimetric impact of implementing spatially variant polyenergetic kernels, depth dose curves in water were calculated using two different implementations of the collapsed cone C/S method. The first method uses a single polyenergetic kernel, while the second method fully takes into account spectral changes in the convolution calculation. To investigate the dosimetric impact of implementing material-specific kernels, depth dose curves were calculated for a simplified titanium implant geometry using both a traditional C/S implementation that performs density scaling of water kernels and a novel implementation using material-specific kernels.Results: For our high-resolution kernels, we found good agreement with the Mackie et al. kernels, with some differences near the interaction site for low photon energies (<500 keV). For our spatially variant polyenergetic kernels, we found that depth was the most dominant factor affecting the pattern of energy deposition; however, the effects of field size and off-axis distance were not negligible. For the material-specific kernels, we found that as the density of the material increased, more energy was deposited laterally by charged particles, as opposed to in the forward direction. Thus, density scaling of water kernels becomes a worse approximation as the density and the effective atomic number of the material differ more from water. Implementation of spatially variant, polyenergetic kernels increased the percent depth dose value at 25 cm depth by 2.1%–5.8% depending on the field size, while implementation of titanium kernels gave 4.9% higher dose upstream of the metal cavity (i.e., higher backscatter dose) and 8.2% lower dose downstream of the cavity.Conclusions: Of the various kernel refinements investigated, inclusion of depth-dependent and metal-specific kernels into the C/S method has the greatest potential to improve dose calculation accuracy. Implementation of spatially variant polyenergetic kernels resulted in a harder depth dose curve and thus has the potential to affect beam modeling parameters obtained in the commissioning process. For metal implants, the C/S algorithms generally underestimate the dose upstream and overestimate the dose downstream of the implant. Implementation of a metal-specific kernel mitigated both of these errors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2017

Overview of NSTX Upgrade Initial Results and Modelling Highlights

The National Spherical Torus Experiment (NSTX) has undergone a major upgrade, and the NSTX Upgrade (NSTX-U) Project was completed in the summer of 2015. NSTX-U first plasma was subsequently achieved, diagnostic and control systems have been commissioned, H-Mode accessed, magnetic error fields identified and mitigated, and the first physics research campaign carried out. During 10 run weeks of operation, NSTX-U surpassed NSTX-record pulse-durations and toroidal fields, and high-performance ~1MA H-mode plasmas comparable to the best of NSTX have been sustained near and slightly above the n=1 no-wall stability limit and with H-mode confinement multiplier H98y2 above 1. Transport and turbulence studies in L-mode plasmas have identified the coexistence of at least two ion-gyro-scale turbulent micro-instabilities near the same radial location but propagating in opposite (i.e. ion and electron diamagnetic) directions. These modes have the characteristics of ion-temperature gradient and micro-tearing modes, respectively, and the role of these modes in contributing to thermal transport is under active investigation. The new second more tangential neutral beam injection was observed to significantly modify the stability of two types of Alfven Eigenmodes. Improvements in offline disruption forecasting were made in the areas of identification of rotating MHD modes and other macroscopic instabilities using the Disruption Event Characterization and Forecasting (DECAF) code. Lastly, the Materials Analysis and Particle Probe (MAPP) was utilized on NSTX-U for the first time and enabled assessments of the correlation between boronized wall conditions and plasma performance. These and other highlights from the first run campaign of NSTX-U are described.

Alfven Eigenmodes↗

DOE OSTI2012

An Analysis of Source Tilting and Sub-cell Opacity Sampling for IMC [Slides]

Implicit Monte Carlo (IMC) is a stochastic method for solving the radiative transfer equations for multiphysics application with the material in local thermodynamic equilibrium. The IMC method employs a fictitious scattering term that is computed from an implicit discretization of the material temperature equation. Unfortunately, the original histogram representation of the temperature and opacity with respect to the spatial domain leads to nonphysically fast propagation of radiation waves through optically thick material. In the past, heuristic source tilting schemes have been used to mitigate the numerical teleportation error of the radiation particles in IMC that cause this overly rapid radiation wave propagation. While improving the material temperature profile throughout the time duration, these tilting schemes alone do not generally alleviate the teleportation error to suitable levels. Another means of potentially reducing teleportation error in IMC is implementing continuous sub-cell opacities based on sub-cell temperature profiles. We present here an analysis of source tilting and continuous sub-cell opacity sampling applied to various discretizations of the temperature equation. Through this analysis, we demonstrate that applying both heuristics does not necessarily yield more accurate results if the discretization of the material equation is inconsistent with the Monte Carlo sub-cell transport.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2012

Computer-Based Procedures for Field Workers in Nuclear Power Plants: Development of a Model of Procedure Usage and Identification of Requirements

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2012

Model of Procedure Usage – Results from a Qualitative Study to Inform Design of Computer-Based Procedures

The nuclear industry is constantly trying to find ways to decrease the human error rate, especially the human errors associated with procedure use. As a step toward the goal of improving procedure use performance, researchers, together with the nuclear industry, have been looking at replacing the current paper-based procedures with computer-based procedure systems. The concept of computer-based procedures is not new by any means; however most research has focused on procedures used in the main control room. Procedures reviewed in these efforts are mainly emergency operating procedures and normal operating procedures. Based on lessons learned for these previous efforts we are now exploring a more unknown application for computer based procedures - field procedures, i.e. procedures used by nuclear equipment operators and maintenance technicians. The Idaho National Laboratory, the Institute for Energy Technology, and participants from the U.S. commercial nuclear industry are collaborating in an applied research effort with the objective of developing requirements and specifications for a computer-based procedure system to be used by field operators. The goal is to identify the types of human errors that can be mitigated by using computer-based procedures and how to best design the computer-based procedures to do this. The underlying philosophy in the research effort is “Stop – Start – Continue”, i.e. what features from the use of paper-based procedures should we not incorporate (Stop), what should we keep (Continue), and what new features or work processes should be added (Start). One step in identifying the Stop – Start – Continue was to conduct a baseline study where affordances related to the current usage of paper-based procedures were identified. The purpose of the study was to develop a model of paper based procedure use which will help to identify desirable features for computer based procedure prototypes. Affordances such as note taking, markups, sharing procedures between fellow coworkers, the use of multiple procedures at once, etc. were considered. The model describes which affordances associated with paper based procedures should be transferred to computer-based procedures as well as what features should not be incorporated. The model also provides a means to identify what new features not present in paper based procedures need to be added to the computer-based procedures to further enhance performance. The next step is to use the requirements and specifications to develop concepts and prototypes of computer-based procedures. User tests and other data collection efforts will be conducted to ensure that the real issues with field procedures and their usage are being addressed and solved in the best manner possible. This paper describes the baseline study, the construction of the model of procedure use, and the requirements and specifications for computer-based procedures that were developed based on the model. It also addresses how the model and the insights gained from it were used to develop concepts and prototypes for computer based procedures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Simplifying the Tracking of Waste Disposal Inventories: Process Improvement for Rapid Data Interpretation and Reduced Errors - 16143

Tracking the inventory of low-level radioactive waste at an operating disposal facility offers unique challenges. At the Savannah River Site's Saltstone Disposal Facility (SDF) the inventory used in Performance Assessment modeling is determined based on radionuclide concentrations from the aqueous waste in a feed tank and the volume of the waste that is transferred from the feed tank to the Saltstone Production Facility (SPF). These inputs are reported quarterly. As such, the disposal inventories are also updated quarterly; however, due to decay and ingrowth, the inventory values for some radionuclides can be misrepresented if the data is not tracked appropriately. Additionally, it is not feasible to analyze the feed tank samples for every possible radionuclide; therefore, a series of adjustments are necessary to estimate the concentrations of radionuclides that are not explicitly measured but still pose a potential dose risk. Prior to 2015, the SDF disposal inventories were updated using a series of spreadsheets that required users to perform a significant number of steps (including manually transferring data back and forth between a separate decay and ingrowth calculation software). Despite this labor intensive approach, the process only provided single point-in-time results. With multiple steps, minimal automation, and limited result data, this approach to inventory tracking was not ideal and minor mistakes were often identified during the equally cumbersome review process. As a process improvement, the simplified SDF Waste Inventory Disposed Estimator (SDF-WIDE) Model was developed using GoldSim software. The software allows users to identify specific dates to define the duration of the simulation, from the beginning of operations until the time of future facility closure, and provides graphical interfaces for displaying data over time. Further, GoldSim's Contaminant Transport Module is used to perform the decay and ingrowth calculations, making the model completely self-contained (i.e., there is no need to transfer intermediate data back and forth between different programs). GoldSim also includes model 'versioning' features that significantly reduce the time needed to perform the appropriate quality assurance reviews as required for each quarterly inventory update. By transitioning from the complex spreadsheets to the simplified SDFWIDE model, the time needed to perform updates to the SDF inventory has been reduced from days to hours, the risk of making human errors has been greatly mitigated, and users are able to quickly observe trends in the data over time. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

LSTM-Based Data Integration to Improve Snow Water Equivalent Prediction and Diagnose Error Sources

Accurate prediction of snow water equivalent (SWE) can be valuable for water resource managers. Recently, deep learning methods such as long short-term memory (LSTM) have exhibited high accuracy in simulating hydrologic variables and can integrate lagged observations to improve prediction, but their benefits were not clear for SWE simulations. Here we tested an LSTM network with data integration (DI) for SWE in the western United States to integrate 30-day-lagged or 7-day-lagged observations of either SWE or satellite-observed snow cover fraction (SCF) to improve future predictions. SCF proved beneficial only for shallow-snow sites during snowmelt, while lagged SWE integration significantly improved prediction accuracy for both shallow- and deep-snow sites. The median Nash–Sutcliffe model efficiency coefficient (NSE) in temporal testing improved from 0.92 to 0.97 with 30-day-lagged SWE integration, and root-mean-square error (RMSE) and the difference between estimated and observed peak SWE values d max were reduced by 41% and 57%, respectively. DI effectively mitigated accumulated model and forcing errors that would otherwise be persistent. Moreover, by applying DI to different observations (30-day-lagged, 7-day-lagged), we revealed the spatial distribution of errors with different persistent lengths. For example, integrating 30-day-lagged SWE was ineffective for ephemeral snow sites in the southwestern United States, but significantly reduced monthly-scale biases for regions with stable seasonal snowpack such as high-elevation sites in California. These biases are likely attributable to large interannual variability in snowfall or site-specific snow redistribution patterns that can accumulate to impactful levels over time for nonephemeral sites. These results set up benchmark levels and provide guidance for future model improvement strategies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Implicit Monte Carlo with a linear discontinuous finite element material solution and piecewise non-constant opacity

Here, the non-linear thermal radiative-transfer equations can be solved in various ways. One popular way is the Fleck and Cummings Implicit Monte Carlo (IMC) method. The IMC method was originally formulated with piecewise-constant material properties. For domains with a coarse spatial grid and large temperature gradients, an error known as numerical teleportation may cause artificially non-causal energy propagation and consequently an inaccurate material temperature. Source tilting is a technique to reduce teleportation error by constructing sub-spatial-cell (or sub-cell) emission profiles from which IMC particles are sampled. Several source tilting schemes exist, but some allow teleportation error to persist. We examine the effect of source tilting in problems with a temperature-dependent opacity. Within each cell, the opacity is evaluated continuously from a temperature profile implied by the source tilt. For IMC, this is a new approach to modeling the opacity. We find that applying both source tilting along with a source tilt-dependent opacity can introduce another dominant error that overly inhibits thermal wavefronts. We show that we can mitigate both teleportation and under-propagation errors if we discretize the temperature equation with a linear discontinuous (LD) trial space. Our method is for opacities ~ 1/T 3 , but we formulate and test a slight extension for opacities ~ 1/T 3.5 , where T is temperature. We find our method avoids errors that can be incurred by IMC with continuous source tilt constructions and piecewise-constant material temperature updates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2013

Detection and Correction of Silent Data Corruption for Large-Scale High-Performance Computing

Faults have become the norm rather than the exception for high-end computing on clusters with 10s/100s of thousands of cores. Exacerbating this situation, some of these faults remain undetected, manifesting themselves as silent errors that corrupt memory while applications continue to operate and report incorrect results. This paper studies the potential for redundancy to both detect and correct soft errors in MPI message-passing applications. Our study investigates the challenges inherent to detecting soft errors within MPI application while providing transparent MPI redundancy. By assuming a model wherein corruption in application data manifests itself by producing differing MPI message data between replicas, we study the best suited protocols for detecting and correcting MPI data that is the result of corruption. To experimentally validate our proposed detection and correction protocols, we introduce RedMPI, an MPI library which resides in the MPI profiling layer. RedMPI is capable of both online detection and correction of soft errors that occur in MPI applications without requiring any modifications to the application source by utilizing either double or triple redundancy. Our results indicate that our most efficient consistency protocol can successfully protect applications experiencing even high rates of silent data corruption with runtime overheads between 0% and 30% as compared to unprotected applications without redundancy. Using our fault injector within RedMPI, we observe that even a single soft error can have profound effects on running applications, causing a cascading pattern of corruption in most cases causes that spreads to all other processes. RedMPI's protection has been shown to successfully mitigate the effects of soft errors while allowing applications to complete with correct results even in the face of errors.

Fiala, David J↗