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DOE OSTI2014

Comprehensive Detection of Genes Causing a Phenotype Using Phenotype Sequencing and Pathway Analysis

Discovering all the genetic causes of a phenotype is an important goal in functional genomics. We combine an experimental design for detecting independent genetic causes of a phenotype with a high-throughput sequencing analysis that maximizes sensitivity for comprehensively identifying them. Testing this approach on a set of 24 mutant strains generated for a metabolic phenotype with many known genetic causes, we show that this pathway-based phenotype sequencing analysis greatly improves sensitivity of detection compared with previous methods, and reveals a wide range of pathways that can cause this phenotype. We demonstrate our approach on a metabolic re-engineering phenotype, the PEP/OAA metabolic node in E. coli, which is crucial to a substantial number of metabolic pathways and under renewed interest for biofuel research. Out of 2157 mutations in these strains, pathway-phenoseq discriminated just five gene groups (12 genes) as statistically significant causes of the phenotype. Experimentally, these five gene groups, and the next two high-scoring pathway-phenoseq groups, either have a clear connection to the PEP metabolite level or offer an alternative path of producing oxaloacetate (OAA), and thus clearly explain the phenotype. These high-scoring gene groups also show strong evidence of positive selection pressure, compared with strictly neutral selection in the rest of the genome.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Energy Distribution of Pickup Ions at the Solar Wind Termination Shock

In-situ measurements taken by the Voyager 2 spacecraft suggest that the solar wind termination shock is significantly affected by the presence of pickup ions that are produced in the inner heliosphere due to charge exchange between interstellar neutrals and the solar wind ions. We use a fully kinetic particle-in-cell method to self-consistently simulate the shock with all physical properties available from Voyager 2 . We have performed a set of simulations with varying velocity distribution functions for the pickup ions, since it was not determined by Voyager's measurements. We show that the measurements suggest that the pickup ions upstream of the shock are more energetic than generally believed. If their velocity distribution function assumes a filled-shell shape in the wind frame, the maximum cutoff speed for the pickup ions should be $≳$650 km s -1 in order to reproduce the measurements, which is almost twice the local wind speed. We suggest that pickup ions upstream of the shock are energized by adiabatic compression of the solar wind plasma as well as due to an enhanced level of turbulence in a broad foreshock region.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Structure Perception in 3D Point Clouds: Preprint

Understanding human perception is critical to the design of ef- fective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the liter- ature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projec- tions of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rota- tion, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under ro- tation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns per- ceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.

data analysis↗

DOE OSTI2024

Exploration of signal processing methods for superconducting magnet and quench data

Quenching is the phenomenon of a superconducting magnetic material carrying current transitioning into a regular conducting material. This may cause severe and irreparable damage to the superconductor due to Joule heating. The Magnet Department at Fermi National Accelerator Laboratory (FNAL) has acquired experimental data through quench antenna arrays that are recorded when the quench is detected. These data are in terms of voltage signals that are sampled at 100kHz for several minutes. There are multiple channels and each channel provides a data set of more than 20 million observations, while there is one channel, called the trigger channel which shows the time when quench is detected. Despite some advancements that were made including machine learning, data complexity still shadows the progress. In this work, we studied a multi-resolution analysis of the quench antenna data through the Haar wavelet transform. In particular, we applied the maximally overlapped discrete w avelet transform (MODWT) of a suitable level L to the given data and then projected it onto the wavelet basis. This decomposes a given signal (Original data) $x ϵ \mathbb{R}^N$ into $L + 1$ subspaces of $\mathbb{R}^N$. One of the subspaces called the approximation, captures the trend of the signal, and the others, called the details, capture the fluctuations at different frequency bands. This decomposition provides a clear trend of the data at a suitable level and also various activities (spikes) are seen in the details of the decomposition at every level. These spikes might reveal some information about the quench under investigation but in any case, give information about magnet behavior. Also, this decomposition is seen to be very useful in removing noise present in the data due to the source or mechanism of the experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2016

SU-D-BRC-02: Application of Six Sigma Approach to Improve the Efficiency of Patient-Specific QA in Proton Therapy

Purpose: To show how the Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) can be used for improving and optimizing the efficiency of patient-specific QA process by designing site-specific range tolerances. Methods: The Six Sigma tools (process flow diagram, cause and effect, capability analysis, Pareto chart, and control chart) were utilized to determine the steps that need focus for improving the patient-specific QA process. The patient-specific range QA plans were selected according to 7 treatment site groups, a total of 1437 cases. The process capability index, Cpm was used to guide the tolerance design of patient site-specific range. We also analyzed the financial impact of this project. Results: Our results suggested that the patient range measurements were non-capable at the current tolerance level of ±1 mm in clinical proton plans. The optimized tolerances were calculated for treatment sites. Control charts for the patient QA time were constructed to compare QA time before and after the new tolerances were implemented. It is found that overall processing time was decreased by 24.3% after establishing new site-specific range tolerances. The QA failure for whole process in proton therapy would lead up to a 46% increase in total cost. This result can also predict how costs are affected by changes in adopting the tolerance design. Conclusion: We often believe that the quality and performance of proton therapy can easily be improved by merely tightening some or all of its tolerance requirements. This can become costly, however, and it is not necessarily a guarantee of better performance. The tolerance design is not a task to be undertaken without careful thought. The Six Sigma DMAIC can be used to improve the QA process by setting optimized tolerances. When tolerance design is optimized, the quality is reasonably balanced with time and cost demands.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-R-54: CT-Texture Based Early Tumor Treatment Response Assessment During Radiation Therapy Delivery: Small Cell Versus Non-Small Cell Lung Cancers

Purpose: Tumor treatment response may potentially be assessed during radiation therapy (RT) by analyzing changes in CT-textures. We investigated the different early RT-responses between small cell (SCLC) and non-small cell lung cancer (NSCLC) as assessed by CT-texture. Methods: Daily diagnostic-quality CT acquired during routine CT-guided RT using a CT-on-Rails for 13-NSCLC and 5-SCLC patients were analyzed. These patient had ages ranging from 45–78 and 38–63 years, respectively, for NSCLC and SCLC groups, and tumor-stages ranging from T2-T4, and were treated with either RT or chemotherapy and RT with 45–66Gy/ 20–34 fractions. Gross-tumor volume (GTV) contour was generated on each daily CT by populating GTV contour from simulation to daily CTs with manual editing if necessary. CT-texture parameters, such as Hounsfield Unit (HU) histogram, mean HU, skewness, kurtosis, entropy, and short-run high-gray level emphasis (SRHGLE), were calculated in GTV from each daily CT-set using an in house software tool. Difference in changes of these texture parameters during RT between NSCLC and SCLC was analyzed and compared with GTV volume changes. Results: Radiation-induced changes in CT-texture were different between SCLC and NSCLC. Average changes from first to the last fractions for NSCLC and SCLC in GTV were 28±10(12–44) and 30±15(11–47) HU (mean HU reduction), 12.7% and 18.3% (entropy), 50% and 55% (SRHGLE), 19% and 22% (kurtosis), and 5.2% and 22% (skewness), respectively. Good correlation in kurtosis changes and GTV was seen (R{sup 2}=0.8923) for SCLC, but not for NSCLC (R{sup 2}=0.4748). SCLC had better correlations between GTV volume reduction and entropy (SCLC R{sup 2}=0.847; NSCLC R{sup 2}=0.6485), skewness (SCLC R{sup 2}=0.935; NSCLC R{sup 2}=0.7666), or SRHGLE (SCLC R{sup 2}=0.9619; NSCLC R{sup 2}=0.787). Conclusion: NSCLC and SCLC exhibited different early RT-responses as assessed by CT-texture changes during RT-delivery. The observed larger changes in various CT-texture parameters for SCLC indicate that SCLC may respond to RT more rapid than NSCLC.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

flowVS: channel-specific variance stabilization in flow cytometry

Abstract Background Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances. Results We present a variance-stabilization algorithm, called flowVS, that removes the mean-variance correlations from cell populations identified in each fluorescence channel. flowVS transforms each channel from all samples of a data set by the inverse hyperbolic sine (asinh) transformation. For each channel, the parameters of the transformation are optimally selected by Bartlett’s likelihood-ratio test so that the populations attain homogeneous variances. The optimum parameters are then used to transform the corresponding channels in every sample. flowVS is therefore an explicit variance-stabilization method that stabilizes within-population variances in each channel by evaluating the homoskedasticity of clusters with a likelihood-ratio test. With two publicly available datasets, we show that flowVS removes the mean-variance dependence from raw FC data and makes the within-population variance relatively homogeneous. We demonstrate that alternative transformation techniques such as flowTrans, flowScape, logicle, and FCSTrans might not stabilize variance. Besides flow cytometry, flowVS can also be applied to stabilize variance in microarray data. With a publicly available data set we demonstrate that flowVS performs as well as the VSN software, a state-of-the-art approach developed for microarrays. Conclusions The homogeneity of variance in cell populations across FC samples is desirable when extracting features uniformly and comparing cell populations with different levels of marker expressions. The newly developed flowVS algorithm solves the variance-stabilization problem in FC and microarrays by optimally transforming data with the help of Bartlett’s likelihood-ratio test. On two publicly available FC datasets, flowVS stabilizes within-population variances more evenly than the available transformation and normalization techniques. flowVS-based variance stabilization can help in performing comparison and alignment of phenotypically identical cell populations across different samples. flowVS and the datasets used in this paper are publicly available in Bioconductor.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Streamflow measurements from four sites on the Tuolumne River in Yosemite National Park from Water Years 2002 to 2021

Regions with remote and complex terrain experience spatially varying streamflow patterns, but are often poorly sampled due to difficult access. This data package includes streamflow measurements collected using low-visibility and low-impact installations at four sites on the Tuolumne River in Yosemite National Park, for water years 2002 to 2021. The resulting data set offers a unique opportunity to explore hydrologic processes in complex terrain.This data package contains half-hourly recordings of unvented pressure, vented pressure, and water temperature are measured and used to estimate discharge and stage height. Discharge flags provide insight into data anomalies. This dataset is formatted in accordance with ESS-Dive's Hydrologic Monitoring and File Level Metadata Formats. It contains the following files:1) Folder containing four csv files of time series streamflow measurements (unvented pressure, vented pressure, estimated discharge, water temperature, stage height, and discharge flag) from four locations on the Tuolumne River2) Data dictionary (dd.csv) containing units, definitions, human readable column names, and data type for all column headers throughout the dataset3) File-level metadata (FLMD.csv) containing metadata for files contained in the dataset4) Installation methods (InstallationMethods.csv) containing metadata on sensor installation

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Syntrophic interactions and mechanisms underpinning anaerobic methane oxidation: targeted metaproteogenomics, single-cell protein detection and quantitative isotope imaging of microbial consortia

Syntrophy and mutualism play a central role in carbon and nutrient cycling by microorganisms. Yet, our ability to effectively study symbionts in culture has been hindered by the inherent interdependence of syntrophic associations, their dynamic behavior, and their frequent existence at thermodynamic limits. Now solutions to these challenges are emerging in the form of new methodologies. Developing strategies that establish links between the identity of microorganisms and their metabolic potential, as well as techniques that can probe metabolic networks on a scale that captures individual molecule exchange and processing, is at the forefront of microbial ecology. Understanding the interactions between microorganisms on this level, at a resolution previously intractable, will lead to our greater understanding of carbon turnover and microbial community resilience to environmental perturbations. In this project, we studied an enigmatic syntrophic association between uncultured methane-oxidizing archaea and sulfate-reducing bacteria. This environmental archaeal-bacterial partnership represents a globally important sink for methane in anoxic environments. The specific goals of this project were organized into 3 major tasks designed to address questions relating to the ecophysiology of these syntrophic organisms under changing environmental conditions (e.g. different electron acceptors and nutrients), primarily through the development of microanalytical imaging methods which enable the visualization of the spatial distribution of the partners within aggregates, consumption and exchange of isotopically labeled substrates, and expression of targeted proteins identified via metaproteomics. The advanced tool set developed here to collect, correlate, and analyze these high resolution image and isotope-based datasets from methane-oxidizing consortia has the potential to be widely applicable for studying and modeling patterns of activity and interactions across a broad range of spatially structured microbial partnerships, including other syntrophic associations, microbial mats, biofilms, and plant-microbe or animal-microbe symbioses in nature.

03 NATURAL GAS↗

DOE OSTI2022

The Mira–Titan Universe – IV. High-precision power spectrum emulation

Modern cosmological surveys are delivering data sets characterized by unprecedented quality and statistical completeness; this trend is expected to continue in the future as new ground- and space-based surveys come online. In order to maximally extract cosmological information from these observations, matching theoretical predictions are needed. At low redshifts, the surveys probe the non-linear regime of structure formation where cosmological simulations are the primary means of obtaining the required information. The computational cost of sufficiently resolved large-volume simulations makes it prohibitive to run very large ensembles. Nevertheless, precision emulators built on a tractable number of high-quality simulations can be used to build very fast prediction schemes to enable a variety of cosmological inference studies. We have recently introduced the Mira–Titan Universe simulation suite designed to construct emulators for a range of cosmological probes. This gravity-only set of simulations covers the standard six cosmological parameters {ω m , ω b , σ 8 , $h, n_s, w_0$} and, in addition, includes massive neutrinos and a dynamical dark energy equation of state {ω ν , $w_a$}. In this paper, we present the final emulator for the matter power spectrum based on 111 cosmological simulations, each covering a (2.1 Gpc) 3 volume and evolving 3200 3 particles. In this work, an additional set of 1776 lower resolution simulations and TimeRG perturbation theory results for the power spectrum are used to cover scales straddling the linear to mildly non-linear regimes (maximum wavenumber $\textit{k}$ = 5 Mpc –1 ). The emulator provides predictions at the 2–3 percent level of accuracy over a wide range of cosmological parameters and is publicly released as part of this paper.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Multilayer Divide-Expand-Consolidate Coupled-Cluster Method: Demonstrative Calculations of the Adsorption Energy of Carbon Dioxide in the Mg-MOF-74 Metal–Organic Framework

The implementation and evaluation of a multilayer extension of the divide-expand-consolidate (DEC) scheme within the LSDalton program is presented. The DEC scheme is a linear-scaling, fragmentation-based local coupled-cluster (CC) method that provides a means of overcoming the scaling wall associated with canonical CC electronic structure calculations on large molecular systems. Taking advantage of the local nature of correlation effects, the correlation energy for the full molecule is calculated from a set of independent fragments using localized molecular orbitals. However, when only a small subsystem of a larger system is of interest, for example, adsorption sites or catalytically active sites, the majority of the computational time may be spent evaluating the correlation energy of fragments which have little effect on the properties in the area of interest (AOI). The multilayer DEC (ML-DEC) scheme addresses this by taking advantage of the independent nature of the fragments in order to evaluate the correlation energy of various regions of the system at different levels of theory. Regions far from the AOI are evaluated at lower (cheaper) levels of theory such as Hartree–Fock (HF) or Møller–Plesset second-order perturbation theory (MP2), while the area immediately surrounding the AOI is treated with a higher level CC model. Through the ML-DEC scheme, the computational cost of CC calculations on these types of systems can be significantly reduced while maintaining the accuracy of higher-level calculations. Results from HF/RI-MP2 and RI-MP2/CCSD ML-DEC calculations of the binding energy of a fatty acid dimer are presented. We find that the ML-DEC scheme is capable of reproducing DEC energy differences at a target level of theory, provided that the region treated at the target level of theory is chosen to be sufficiently large. Time-to-solution is found to be significantly reduced, particularly in the RI-MP2/CCSD calculations. Finally, the ML-DEC scheme is applied to the calculation of CO 2 adsorption in a Mg-MOF-74 channel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Resilient Control of Networked Microgrids Using Vertical Federated Reinforcement Learning: Designs and Real-Time Test-Bed Validations

Improving system-level resiliency of networked microgrids against adversarial cyber-attacks is an important aspect in the current regime of increased inverter-based resources (IBRs). To achieve that, this paper contributes in designing a hierarchical control layer, in conjunction with the existing control layers, resilient to adversarial attack signals. Considering model complexities, unknown dynamical behaviors of IBRs, and privacy issues regarding data sharing in multi-party-owned microgrids, designing such a control layer is non-trivial. Here, to tackle these issues, a novel federated reinforcement learning (Fed-RL) method is proposed. To grasp the interconnected dynamics of networked microgrids, the paper develops Federated Soft Actor-Critic (FedSAC) algorithm following the vertical structure of implementing Fed-RL. Next, utilizing the OpenAI Gym interface, we built a custom set-up in GridLAB-D/HELICS co-simulation platform, named Resilient RL Co-simulation (ResRLCoSIM), to train the RL agents with IEEE 123-bus benchmark comprising 3 interconnected microgrids. Finally, the learned policies in the simulation are transferred to the real-time hardware-in-the-loop (HIL) test-bed developed using the high-fidelity Hypersim platform. Finally, experiments show that the simulator-trained RL controllers achieve desirable performance with the test-bed platform, validating the minimization of the sim-to-real gap.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2013

An automated voxelized dosimetry tool for radionuclide therapy based on serial quantitative SPECT/CT imaging

Purpose: To create an accurate map of the distribution of radiation dose deposition in healthy and target tissues during radionuclide therapy.Methods: Serial quantitative SPECT/CT images were acquired at 4, 24, and 72 h for 28 {sup 177}Lu-octreotate peptide receptor radionuclide therapy (PRRT) administrations in 17 patients with advanced neuroendocrine tumors. Deformable image registration was combined with an in-house programming algorithm to interpolate pharmacokinetic uptake and clearance at a voxel level. The resultant cumulated activity image series are comprised of values representing the total number of decays within each voxel's volume. For PRRT, cumulated activity was translated to absorbed dose based on Monte Carlo-determined voxel S-values at a combination of long and short ranges. These dosimetric image sets were compared for mean radiation absorbed dose to at-risk organs using a conventional MIRD protocol (OLINDA 1.1).Results: Absorbed dose values to solid organs (liver, kidneys, and spleen) were within 10% using both techniques. Dose estimates to marrow were greater using the voxelized protocol, attributed to the software incorporating crossfire effect from nearby tumor volumes.Conclusions: The technique presented offers an efficient, automated tool for PRRT dosimetry based on serial post-therapy imaging. Following retrospective analysis, this method of high-resolution dosimetry may allow physicians to prescribe activity based on required dose to tumor volume or radiation limits to healthy tissue in individual patients.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2014

How accurately can the peak skin dose in fluoroscopy be determined using indirect dose metrics?

Purpose: Skin dosimetry is important for fluoroscopically-guided interventions, as peak skin doses (PSD) that result in skin reactions can be reached during these procedures. There is no consensus as to whether or not indirect skin dosimetry is sufficiently accurate for fluoroscopically-guided interventions. However, measuring PSD with film is difficult and the decision to do so must be madea priori. The purpose of this study was to assess the accuracy of different types of indirect dose estimates and to determine if PSD can be calculated within ±50% using indirect dose metrics for embolization procedures. Methods: PSD were measured directly using radiochromic film for 41 consecutive embolization procedures at two sites. Indirect dose metrics from the procedures were collected, including reference air kerma. Four different estimates of PSD were calculated from the indirect dose metrics and compared along with reference air kerma to the measured PSD for each case. The four indirect estimates included a standard calculation method, the use of detailed information from the radiation dose structured report, and two simplified calculation methods based on the standard method. Indirect dosimetry results were compared with direct measurements, including an analysis of uncertainty associated with film dosimetry. Factors affecting the accuracy of the different indirect estimates were examined. Results: When using the standard calculation method, calculated PSD were within ±35% for all 41 procedures studied. Calculated PSD were within ±50% for a simplified method using a single source-to-patient distance for all calculations. Reference air kerma was within ±50% for all but one procedure. Cases for which reference air kerma or calculated PSD exhibited large (±35%) differences from the measured PSD were analyzed, and two main causative factors were identified: unusually small or large source-to-patient distances and large contributions to reference air kerma from cone beam computed tomography or acquisition runs acquired at large primary gantry angles. When calculated uncertainty limits [−12.8%, 10%] were applied to directly measured PSD, most indirect PSD estimates remained within ±50% of the measured PSD. Conclusions: Using indirect dose metrics, PSD can be determined within ±35% for embolization procedures. Reference air kerma can be used without modification to set notification limits and substantial radiation dose levels, provided the displayed reference air kerma is accurate. These results can reasonably be extended to similar procedures, including vascular and interventional oncology. Considering these results, film dosimetry is likely an unnecessary effort for these types of procedures when indirect dose metrics are available.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy’s resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this framework, the project team has focused on optimizing resource allocation for improving numerical models through further code development and experimentation. Related to further code development, we have developed a code prioritization index (CPI) for coupled numerical models. CPI is implemented to effectively improve the predictive capability of the coupled model by increasing the sophistication of constituent codes. In relation to designing new experiments, we investigated the information gained by the addition of each new experiment used for calibration and bias correction of a simulation model. Additionally, the variability of ‘information gain’ through the design domain has been investigated in order to identify the experiment settings where maximum information gain occurs and thus guide the experimenters in the selection of the experiment settings. This idea was extended to evaluate the information gain from each experiment can be improved by intelligently selecting the experiments, leading to the development of the Batch Sequential Design (BSD) technique. Additionally, we evaluated the importance of sufficiently exploring the domain of applicability in experiment-based validation of high-consequence modeling and simulation by developing a new metric to quantify coverage. This metric has also been incorporated into the design of new experiments. Finally, we have proposed a data-aware calibration approach for the calibration of numerical models. This new method considers the complexity of a numerical model (the number of parameters to be calibrated, parameter uncertainty, and form of the model) and seeks to identify the number of experiments necessary to calibrate the model based on the level of sophistication of the physics. The final component in the project team’s work to improve model calibration and validation methods is the incorporation of robustness to non-probabilistic uncertainty in the input parameters. This is an improvement to model validation and uncertainty quantification stemming beyond the originally proposed scope of the project. We have introduced a new metric for incorporating the concept of robustness into experiment-based validation of numerical models. This project has accounted for the graduation of two Ph.D. students (Kendra Van Buren and Josh Hegenderfer) and two M.S. students (Matthew Egeberg and Parker Shields). One of the doctoral students is now working in the nuclear engineering field and the other one is a post-doctoral fellow at the Los Alamos National Laboratory. Additionally, two more Ph.D. students (Garrison Stevens and Tunc Kulaksiz) who are working towards graduation have been supported by this project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Investigating Secondary Aerosol Processes in the Amazon through Molecular-level Characterization of Semi-Volatile Organics

In areas where biogenic emissions are oxidized in the presence of anthropogenic pollutants, it has become increasingly apparent that secondary organic aerosol (SOA) formation from biogenic volatile organic compounds (BVOCs) is substantially enhanced. The Amazon forest is the dominant source of BVOCs globally, and the forest is rapidly being converted to urban and agricultural uses. We participated in a collaborative field study located in the Amazon region around Manaus, Brazil, in 2014 (Green Ocean Amazon; GoAmazon). This study was designed to comprehensively examine how BVOC emissions (specifically, the most highly emitted non-methane hydrocarbon, isoprene, and lesser studied sesquiterpenes) and their interaction with anthropogenic pollution (i.e., nitrogen oxides, sulfur dioxide, and black carbon) alter the atmosphere’s oxidative capacity, influence secondary aerosol formation, atmospheric composition and, ultimately, affect the earth’s radiation balance and climate. We provide the first hourly, in-situ measurement of 30 sesquiterpenes and 4 diterpenes, roughly estimating that sesquiterpene oxidation contributes to 10-14% of ozone reactive loss by terpenes and at least 0.4–5% (median 1 %) of total submicron OA mass. However, this is likely a low-end estimate, as evidence for additional unaccounted sesquiterpenes and their oxidation products clearly exists. We also provide new perspectives on sulfate, NO x , and particle acidity influencing isoprene-derived SOA, comparing the central Amazon environment with Southeastern U.S.A. summer, representing clean to polluted conditions, respectively. We find that summed concentrations of isoprene-derived SOA tracers correlated with particulate sulfate spanning three orders of magnitude, suggesting that 1 μg m -3 reduction in sulfate corresponds with at least ~0.5 μg m -3 reduction in isoprene-derived SOA. We also find that SOA mass derived from isoprene oxidation in the presence of NO x is primarily comprised of aerosol sulfate bound with isoprene oxidation products (i.e. organosulfates), ~97% in the Amazon and ~55% in the Southeastern U.S. We infer under natural conditions in high isoprene emission regions, preindustrial aerosol sulfate was almost exclusively isoprene-derived organosulfates, which are traditionally thought as representative of anthropogenic influence. We further report the first field observations showing that particle acidity impacts the distribution of isoprene oxidation tracers in the gas and particle phases, providing physicochemical insight into isoprene SOA formation chemistry. Coupled with other co-located measurements by the DOE Atmospheric Radiation Measurement (ARM) team and collaborating PIs at our measurement site (called T3), on the G1 aircraft, and at additional field sites (T0, T1, T2) this data set has been used to understand emission, oxidation, and particle formation pathways at the molecular level, to elucidate how these pathways change when influenced by anthropogenic sources, and to evaluate their importance for the atmospheric budget of aerosols and the earth’s radiation balance on regional scales. Recommendations: Further constraint of the role of sesquiterpenes on ozone (O 3 ) reactivity and SOA formation is limited by the availability of authentic standards and synthesized compounds of sesquiterpenes and their oxidation products. Future research efforts should focus on making such standards available via custom synthesis to allow for accurate quantification and focused oxidation experiments that will fully elucidate the chemistry of these compounds in the atmosphere. Further, reductions in aerosol sulfate (via SO 2 emissions control) continues to be one of the most effective methods to reduce SOA formation from isoprene, but the concerted role of ammonia (NH 3 ) gas emissions from (agricultural) industry and other sources requires more investigation to better understand the role of aerosol acidity in SOA formation and potential controls. As GoAmazon particles can be more acidic compared to areas with greater anthropogenic NH 3 emissions, this promotes relatively greater organosulfate (OS) formation from isoprene even in the presence of NO x . Because OS and inorganic sulfate differ in water uptake properties, this implies preindustrial aerosol sulfate (albeit less abundant) may have been less reflective than current earth system models assume. Further research should investigate the radiative impacts of organic vs inorganic sulfate in aerosols to improve model representation. Finally, future work (currently underway) should include constraint of the contributions of monoterpene (C 10 H 16 ) BVOCs and biomass burning VOCs as precursors to SOA formation in the region as well as their impacts on radiative forcing in the climate system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

RAVEN: Dynamic Event Tree Approach Level III Milestone

Conventional Event-Tree (ET) based methodologies are extensively used as tools to perform reliability and safety assessment of complex and critical engineering systems. One of the disadvantages of these methods is that timing/sequencing of events and system dynamics are not explicitly accounted for in the analysis. In order to overcome these limitations several techniques, also know as Dynamic Probabilistic Risk Assessment (DPRA), have been developed. Monte-Carlo (MC) and Dynamic Event Tree (DET) are two of the most widely used D-PRA methodologies to perform safety assessment of Nuclear Power Plants (NPP). In the past two years, the Idaho National Laboratory (INL) has developed its own tool to perform Dynamic PRA: RAVEN (Reactor Analysis and Virtual control ENvironment). RAVEN has been designed to perform two main tasks: 1) control logic driver for the new Thermo-Hydraulic code RELAP-7 and 2) post-processing tool. In the first task, RAVEN acts as a deterministic controller in which the set of control logic laws (user defined) monitors the RELAP-7 simulation and controls the activation of specific systems. Moreover, the control logic infrastructure is used to model stochastic events, such as components failures, and perform uncertainty propagation. Such stochastic modeling is deployed using both MC and DET algorithms. In the second task, RAVEN processes the large amount of data generated by RELAP-7 using data-mining based algorithms. This report focuses on the analysis of dynamic stochastic systems using the newly developed RAVEN DET capability. As an example, a DPRA analysis, using DET, of a simplified pressurized water reactor for a Station Black-Out (SBO) scenario is presented.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

RAVEN. Dynamic Event Tree Approach Level III Milestone

42 ENGINEERING↗