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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Insights into the origin of halo mass profiles from machine learning

ABSTRACT The mass distribution of dark matter haloes is the result of the hierarchical growth of initial density perturbations through mass accretion and mergers. We use an interpretable machine-learning framework to provide physical insights into the origin of the spherically-averaged mass profile of dark matter haloes. We train a gradient-boosted-trees algorithm to predict the final mass profiles of cluster-sized haloes, and measure the importance of the different inputs provided to the algorithm. We find two primary scales in the initial conditions (ICs) that impact the final mass profile: the density at approximately the scale of the haloes’ Lagrangian patch RL ($R\sim 0.7\, R_L$) and that in the large-scale environment (R ∼ 1.7 RL). The model also identifies three primary time-scales in the halo assembly history that affect the final profile: (i) the formation time of the virialized, collapsed material inside the halo, (ii) the dynamical time, which captures the dynamically unrelaxed, infalling component of the halo over its first orbit, (iii) a third, most recent time-scale, which captures the impact on the outer profile of recent massive merger events. While the inner profile retains memory of the ICs, this information alone is insufficient to yield accurate predictions for the outer profile. As we add information about the haloes’ mass accretion history, we find a significant improvement in the predicted profiles at all radii. Our machine-learning framework provides novel insights into the role of the ICs and the mass assembly history in determining the final mass profile of cluster-sized haloes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Plant-specific Model and Data Analysis using Dynamic Security Modeling and Simulation

The requirements for U.S. nuclear power plants to maintain a large on-site physical security force contribute to their high operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability (LWRS) program’s physical security pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. The conservatisms built into current security postures may be analyzed and minimized in order to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within LWRS program’s physical security pathway has successfully developed a dynamic force-on-force modeling framework using various computer simulation tools and integrating them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This document provides an update on the progress in applying a dynamic computational framework that links results from a commercially available force-on-force simulation tool, a commercially available thermal-hydraulic tool, and EMRALD to an operating commercial nuclear power plant. This report is only a summary of the progress and does not contain specific modeling results as those contain sensitive security information. This process of including plant procedures and multiple analysis results is being called Modeling and Analysis for Safety Security using Dynamic EMRALD Framework or MASS-DEF. Previous reports described how a user could integrate their plant-specific force-on-force models with the dynamic simulation tool EMRALD, model operator actions, integrate with probabilistic risk assessment tools, such as CAFTA (Computer Aided Fault Tree Analysis System) or SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations), and with thermal-hydraulic tools, such as RELAP-5. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report documents the results of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. This report does not contain any plant's sensitive information and/or Safeguards Information. The purpose of this study was to verify that results achieved using generic models are similar to actual plant results and to refine our guidance on the use of the framework. This assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Modeling subauroral polarization streams during the 17 March 2013 storm

Abstract The subauroral polarization streams (SAPS) are one of the most important features in representing magnetosphere‐ionosphere coupling processes. In this study, we use a state‐of‐the‐art modeling framework that couples an inner magnetospheric ring current model RAM‐SCB with a global MHD model Block‐Adaptive Tree Solar‐wind Roe Upwind Scheme (BATS‐R‐US) and an ionospheric potential solver to study the SAPS that occurred during the 17 March 2013 storm event as well as to assess the modeling capability. Both ionospheric and magnetospheric signatures associated with SAPS are analyzed to understand the spatial and temporal evolution of the electrodynamics in the midlatitude regions. Results show that the model captures the SAPS at subauroral latitudes, where Region 2 field‐aligned currents (FACs) flow down to the ionosphere and the conductance is lower than in the higher‐latitude auroral zone. Comparisons to observations such as FACs observed by Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE), cross‐track ion drift from Defense Meteorological Satellite Program (DMSP), and in situ electric field observations from the Van Allen Probes indicate that the model generally reproduces the global dynamics of the Region 2 FACs, the position of SAPS along the DMSP, and the location of the SAPS electric field around L of 3.0 in the inner magnetosphere near the equator. The model also demonstrates double westward flow channels in the dusk sector (the higher‐latitude auroral convection and the subauroral SAPS) and captures the mechanism of the SAPS. However, the comparison with ion drifts along DMSP trajectories shows an underestimate of the magnitude of the SAPS and the sensitivity to the specific location and time. The comparison of the SAPS electric field with that measured from the Van Allen Probes shows that the simulated SAPS electric field penetrates deeper than in reality, implying that the shielding from the Region 2 FACs in the model is not well represented. Possible solutions in future studies to improve the modeling capability include implementing a self‐consistent ionospheric conductivity module from inner magnetosphere particle precipitation, coupling with the thermosphere‐ionosphere chemical processes, and connecting the ionosphere with the inner magnetosphere by the stronger Region 2 FACs calculated in the inner magnetosphere model.

Yu, Yiqun↗
DOE OSTI2017

Operational Performance Risk Assessment in Support of A Supervisory Control System

Supervisory control system (SCS) is developed for multi-unit advanced small modular reactors to minimize human interventions in both normal and abnormal operations. In SCS, control action decisions made based on probabilistic risk assessment approach via Event Trees/Fault Trees. Although traditional PRA tools are implemented, their scope is extended to normal operations and application is reversed; success of non-safety related system instead failure of safety systems this extended PRA approach called as operational performance risk assessment (OPRA). OPRA helps to identify success paths, combination of control actions for transients and to quantify these success paths to provide possible actions without activating plant protection system. In this paper, a case study of the OPRA in supervisory control system is demonstrated within the context of the ALMR PRISM design, specifically power conversion system. The scenario investigated involved a condition that the feed water control valve is observed to be drifting to the closed position. Alternative plant configurations were identified via OPRA that would allow the plant to continue to operate at full or reduced power. Dynamic analyses were performed with a thermal-hydraulic model of the ALMR PRISM system using Modelica to evaluate remained safety margins. Successful recovery paths for the selected scenario are identified and quantified via SCS.

Denning, Richard S.↗
DOE OSTI2021

Rapid Cis–Trans Coevolution Driven by a Novel Gene Retroposed from a Eukaryotic Conserved CCR4–NOT Component in Drosophila

Young, or newly evolved, genes arise ubiquitously across the tree of life, and they can rapidly acquire novel functions that influence a diverse array of biological processes. Previous work identified a young regulatory duplicate gene in Drosophila, Zeus that unexpectedly diverged rapidly from its parent, Caf40, an extremely conserved component in the CCR4–NOT machinery in post-transcriptional and post-translational regulation of eukaryotic cells, and took on roles in the male reproductive system. This neofunctionalization was accompanied by differential binding of the Zeus protein to loci throughout the Drosophila melanogaster genome. However, the way in which new DNA-binding proteins acquire and coevolve with their targets in the genome is not understood. Here, by comparing Zeus ChIP-Seq data from D. melanogaster and D. simulans to the ancestral Caf40 binding events from D. yakuba, a species that diverged before the duplication event, we found a dynamic pattern in which Zeus binding rapidly coevolved with a previously unknown DNA motif, which we term Caf40 and Zeus-Associated Motif (CAZAM), under the influence of positive selection. Interestingly, while both copies of Zeus acquired targets at male-biased and testis-specific genes, D. melanogaster and D. simulans proteins have specialized binding on different chromosomes, a pattern echoed in the evolution of the associated motif. Using CRISPR-Cas9-mediated gene knockout of Zeus and RNA-Seq, we found that Zeus regulated the expression of 661 differentially expressed genes (DEGs). Our results suggest that the evolution of young regulatory genes can be coupled to substantial rewiring of the transcriptional networks into which they integrate, even over short evolutionary timescales. Our results thus uncover dynamic genome-wide evolutionary processes associated with new genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Machine Learning Classification of Molten Salt Heat Exchanger Channel Plugging using Synthetic Data

This report addresses the requirements of Milestone M3.4 AI capability to identify and predict maintenance events. Development of digital twins (DT) for molten salt reactor (MSR) components is crucial for reducing operating and maintenance costs (O&M) and ensuring commercial viability of these reactors. Our focus is on development of DT for MSR primary system heat exchanger (HX), a critical component, the fault in which can reduce operating efficiency and force reactor shutdown. We are investigating the feasibility of a conceptual DT of HX consisting of internal distributed temperature sensing with fiber optics and machine learning (ML) algorithms to detect and localize faults. To determine the optimal approach to detection and localization of channel plugging, we benchmark seven different ML models: Logistic Regression, K-Nearest Neighbors (KNN), Gaussian Naïve Bayes, Support Vector Machines (SVM), Decision Tree Classifier, Random Forest Tree Classifier, and Feed-Forward Neural Network. ML algorithms are benchmarked using synthetic HX plugging data generated with computational fluid dynamics COMSOL software, with added brown noise to represent experimental noise. We show that the best performance is obtained with the Decision Tree classifier.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

The matrix product approximation for the dynamic cavity method

Stochastic dynamics of classical degrees of freedom, defined on vertices of locally tree-like graphs, can be studied in the framework of the dynamic cavity method which is exact for tree graphs. Such models correspond for example to spin-glass systems, Boolean networks, neural networks, and other technical, biological, and social networks. The central objects in the cavity method are edge messages—conditional probabilities of two vertex variable trajectories. In this paper, we discuss a rather pedagogical derivation for the dynamic cavity method, give a detailed account of the novel matrix product edge message (MPEM) algorithm for the solution of the dynamic cavity equation as introduced, and present optimizations and extensions. Matrix product approximations of the edge messages are constructed recursively in an iteration over time. Computation costs and precision can be tuned by controlling the matrix dimensions of the MPEM in truncations. Without truncations, the dynamics is exact. Data for Glauber–Ising dynamics shows a linear growth of computation costs in time. In contrast to Monte Carlo simulations, the approach has a much better error scaling. Hence, it gives for example access to low probability events and decaying observables like temporal correlations. Here, we discuss optimized truncation schemes and an extension that allows to capture models which have a continuum time limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Southwest Pacific tropical cyclone development classification utilizing machine learning and synoptic composites

This study evaluates the ability of machine learning algorithms to classify tropical depressions (TDs) and tropical storms (TSs) in the western region of the southwest Pacific Ocean (SWPO). Decision rules are generated to predict the environment required for a depression to fully develop into a mature storm, and the most influential predictors in the classification decision are ranked. TD and TS are discriminated based on a maximum sustained wind speed threshold (≥17 ms -1 ). Various aerosol, thermodynamic, and dynamic parameters are extracted closest to the initiation point of each non-developing and developing sample. The covariates associated with each labelled sample are used to train a decision tree and random forest model. Results using a testing dataset suggest the random forest approach more accurately distinguishes between non-developing and developing samples. The classification accuracy of the decision tree and random forest are 72% and 91%, respectively. Random forest outperformed the decision tree by providing higher accuracy in test data. The most important variables for binary classification are sea salt aerosol optical depth (AOD), 1,000 mb relative humidity, and sea surface temperature. AOD is a quantitative estimate of the aerosols presents in the air through the extinction of a ray of light as it passes through the atmosphere. Mean composite maps constructed in an unsupervised manner have been created for the most important variables identified by the random forest classifier during TD and TS events to highlight the difference in geophysical and aerosol variables' climatology during the two different classifications. This work will advance the risk management strategies for northeastern Australia and other SWPO basin islands to control their tropical cyclone related losses through prioritizing forecasting variables that are the strongest predictors of the strengthening of tropical depressions into tropical cyclones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Drought-influenced mortality of tree species with different predawn leaf water dynamics in a decade-long study of a central US forest

Using decade-long continuous observations of tree mortality and predawn leaf water potential (ψ pd ) at the Missouri Ozark AmeriFlux (MOFLUX) site, we studied how the mortality of important tree species varied and how such variations may be predicted. Water stress determined inter-annual variations in tree mortality with a time delay of 1 year or more, which was correlated fairly tightly with a number of quantitative predictors formulated based on ψ pd and precipitation regimes. Predictors based on temperature and vapor pressure deficit anomalies worked reasonably well, particularly for moderate droughts. The exceptional drought of the year 2012 drastically increased the mortality of all species, including drought-tolerant oaks, in the subsequent year. The drought-influenced tree mortality was related to the species position along the spectrum of ψ pd regulation capacity with those in either ends of the spectrum being associated with elevated risk of death. Regardless of species and drought intensity, the ψ pd of all species recovered rapidly after sufficiently intense rain events in all droughts. This result, together with a lack of immediate leaf and branch desiccation, suggests an absence of catastrophic hydraulic disconnection in the xylem and that tree death was caused by significant but indirect effects. Species differences in the capacity of regulating ψ pd and its temporal integral were magnified under moderate drought intensities but diminished towards wet and dry extremes. Severe droughts may overwhelm the capacity of even drought-tolerant species to maintain differential levels of water potential as the soil becomes exhausted of available water in the rooting zone, thus rendering them more susceptible to death if predisposed by other factors such as age.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Lateral Gene Transfer Dynamics in the Ancient Bacterial Genus Streptomyces

Lateral gene transfer (LGT) profoundly shapes the evolution of bacterial lineages. LGT across disparate phylogenetic groups and genome content diversity between related organisms suggest a model of bacterial evolution that views LGT as rampant and promiscuous. It has even driven the argument that species concepts and tree-based phylogenetics cannot be applied to bacteria. For this paper, we show that acquisition and retention of genes through LGT are surprisingly rare in the ubiquitous and biomedically important bacterial genus Streptomyces . Using a molecular clock, we estimate that the Streptomyces bacteria are ~380 million years old, indicating that this bacterial genus is as ancient as land vertebrates. Calibrating LGT rate to this geologic time span, we find that on average only 10 genes per million years were acquired and subsequently maintained. Over that same time span, Streptomyces accumulated thousands of point mutations. By explicitly incorporating evolutionary timescale into our analyses, we provide a dramatically different view on the dynamics of LGT and its impact on bacterial evolution.Tree-based phylogenetics and the use of species as units of diversity lie at the foundation of modern biology. In bacteria, these pillars of evolutionary theory have been called into question due to the observation of thousands of lateral gene transfer (LGT) events within and between lineages. Here, we show that acquisition and retention of genes through LGT are exceedingly rare in the bacterial genus Streptomyces , with merely one gene acquired in Streptomyces lineages every 100,000 years. These findings stand in contrast to the current assumption of rampant genetic exchange, which has become the dominant hypothesis used to explain bacterial diversity. Our results support a more nuanced understanding of genetic exchange, with LGT impacting evolution over short timescales but playing a significant role over long timescales. Deeper understanding of LGT provides new insight into the evolutionary history of life on Earth, as the vast majority of this history is microbial.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Dry-Season Greening and Water Stress in Amazonia: The Role of Modeling Leaf Phenology

Large uncertainties on the sensitivity of Amazon forests to drought exist. Even though water stress should suppress photosynthesis and enhance tree mortality, a green-up has been often observed during the dry season. This interplay between climatic forcing and forest phenology is poorly understood and inadequately represented in most of existing dynamic global vegetation models calling for an improved description of the Amazon seasonal dynamics. Recent findings on tropical leaf phenology are incorporated in the state-of-the-art eco-hydrological model Thetys & Chloris. The new model accounts for a mechanistic light-controlled leaf development, synchronized dry-season litterfall, and an age-dependent leaf photosynthetic capacity. Simulation results from 32 sites in the Amazon basin over a 15-year period successfully mimic the seasonality of gross primary productivity; evapotranspiration (ET); as well as leaf area index, leaf age, and leaf productivity. Representation of tropical leaf phenology reproduces the observed dry-season greening, reduces simulated gross primary productivity, and does not alter ET, when compared with simulations without phenology. Tolerance to dry periods, with the exception of major drought events, is simulated by the model. Deep roots rather than leaf area index regulation mechanisms control the response to short-term droughts, but legacy effects can exacerbate multiyear water stress. Our results provide a novel mechanistic approach to model leaf phenology and flux seasonality in the tropics, reconciling the generally observed dry-season greening, ET seasonality, and decreased carbon uptake during severe droughts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Comparative transcriptomics uncovers poplar and fungal genetic determinants of ectomycorrhizal compatibility

Ectomycorrhizal symbiosis supports tree growth and is crucial for nutrient cycling and temperate and boreal ecosystems functioning. The establishment of functional ectomycorrhiza (ECM) first requires the association of compatible partners. However, host and fungal genetic determinants governing mycorrhizal compatibility are unknown. To identify such factors in poplar and its fungal associates, we mined existing and de novo tree and fungal transcriptional datasets. We identified co-expressed genes enabling ECM symbiosis at early and mature stages of the interaction. These sets of genes can be divided into general fungal-sensing and ECM-specific components. We highlight the importance of fungal modulation of plant JA-related defenses and the regulation of secretory pathways for ECM compatibility, including upregulation of key fungal small secreted proteins, the downregulation of plant secreted peroxidases, and the downregulation of plant cell wall remodeling proteins concomitantly with the upregulation of fungal glycosyl hydrolases acting on pectin. Not only gene regulation, but also its temporal scale and dynamics seem to play a crucial role for mycorrhizal compatibility. The expression profile of the host Common Symbiosis Pathway and nutrient transporters was also studied, revealing constitutive levels of expression and moderate upregulation in compatible ECM interactions. Overall, these results underscore the importance of novel biological functions during the establishment of ECM symbiosis, help us gain insights into the molecular events determining mycorrhiza compatibility, and serve as a data-rich transcriptomic resource to open new research questions in the field.

Marqués‐Gálvez, José Eduardo↗
DOE OSTI2025

Growth–Mortality Coordination Differs Among Xerophytic Versus Mesophytic Tree Species During Severe Drought

ABSTRACT Forest composition is changing, yet the consequences for terrestrial carbon cycling are unclear. In the eastern United States, water‐demanding “mesophytic” tree species are replacing “xerophytic” oaks (Quercusspp.) and hickories (Caryaspp.), raising concerns that forest productivity will become increasingly sensitive to more frequent and severe drought conditions predicted for the region. However, we have a limited understanding of the extent to which the mortality risk of xerophytes versus mesophytes is coordinated with their growth sensitivity during drought. Here, we evaluated growth and mortality dynamics for 20 abundant eastern United States tree species following a severe drought in the summer of 2012. We synthesized data from ~4500 forest inventory plots and used an approach that quantified relative drought responses between co‐located trees to minimize impacts from environmental heterogeneity. We found that mesophytes were just as likely to perish as co‐occurring xerophytes but were more sensitive to drought in terms of diminished growth. These findings suggest that xerophytic decline is likely to lead to reduced carbon uptake during drought and that management efforts to conserve oak‐hickory stands will be decisive to sustain the carbon mitigation potential of these forests. However, we also found that growth‐mortality relationships differed between functional groups. Among xerophytes, growth and survival during drought were decoupled. Among mesophytes, there was a high degree of coordination, where species that experienced greater mortality also experienced greater growth reductions. Therefore, mesophytes with high growth sensitivity to water deficits are likely to be the most vulnerable to drought‐driven die‐off events moving forward.

Biodiversity & Conservation↗
DOE OSTI2017

Operational performance risk assessment in support of a supervisory control system - 251

A supervisory control system is being developed for multiunit advanced small modular reactors to minimize human interventions during normal and abnormal operations. In the supervisory control system, control action decisions are made based on a probabilistic risk assessment that employs event trees and fault trees. Although traditional probabilistic risk assessment tools are implemented, their scope is extended to normal operations, and the application is reversed to assess the success of non-safety related systems and to enable continued operation of the plant. This extended probabilistic risk assessment approach is called operational performance risk assessment (OPRA). OPRA helps to identify available paths, combine control actions for maintaining plant conditions within operational limits, and to quantify the likelihood of success of these operational trajectories to optimize the selection of alternative actions without activating reactor protection system. In this paper, a case study of OPRA in a supervisory control system is demonstrated for the Advanced Liquid Metal Reactor (ALMR) Power Reactor Inherently Safe Module (PRISM) design, specifically the power conversion system. The scenario investigated involved a condition in which the feedwater control valve that was observed to be drifting to the closed position. Alternative plant configurations that would allow the plant to continue to operate at full or reduced power were identified using OPRA. Dynamic analyses were performed with a thermal-hydraulic model of the ALMR PRISM system using Modelica to evaluate the magnitude of safety margins. Successful recovery paths for the selected scenario were identified and quantified using the supervisory control system. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Extended magnetohydrodynamics with embedded particle-in-cell simulation of Ganymede's magnetosphere

Here, we have recently developed a new modeling capability to embed the implicit particle–in–cell (PIC) model iPIC3D into the Block–Adaptive–Tree–Solarwind–Roe–Upwind–Scheme magnetohydrodynamic (MHD) model. The MHD with embedded PIC domains (MHD–EPIC) algorithm is a two–way coupled kinetic–fluid model. As one of the very first applications of the MHD–EPIC algorithm, we simulate the interaction between Jupiter's magnetospheric plasma and Ganymede's magnetosphere. We compare the MHD–EPIC simulations with pure Hall MHD simulations and compare both model results with Galileo observations to assess the importance of kinetic effects in controlling the configuration and dynamics of Ganymede's magnetosphere. We find that the Hall MHD and MHD–EPIC solutions are qualitatively similar, but there are significant quantitative differences. In particular, the density and pressure inside the magnetosphere show different distributions. For our baseline grid resolution the PIC solution is more dynamic than the Hall MHD simulation and it compares significantly better with the Galileo magnetic measurements than the Hall MHD solution. The power spectra of the observed and simulated magnetic field fluctuations agree extremely well for the MHD–EPIC model. The MHD–EPIC simulation also produced a few flux transfer events (FTEs) that have magnetic signatures very similar to an observed event. The simulation shows that the FTEs often exhibit complex 3–D structures with their orientations changing substantially between the equatorial plane and the Galileo trajectory, which explains the magnetic signatures observed during the magnetopause crossings. The computational cost of the MHD–EPIC simulation was only about 4 times more than that of the Hall MHD simulation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Cosmological simulations of early black hole formation: halo mergers, tidal disruption, and the conditions for direct collapse

Gravitational collapse of a massive primordial gas cloud is thought to be a promising path for the formation of supermassive black holes in the early universe. We study conditions for the so-called direct collapse (DC) black hole formation in a fully cosmological context. We combine a semianalytic model of early galaxy formation with halo merger trees constructed from dark matter N-body simulations. We locate a total of 68 possible DC sites in a volume of 20 h{sup −1} Mpc on a side. We then perform hydrodynamics simulations for 42 selected halos to study in detail the evolution of the massive clouds within them. We find only two successful cases where the gas clouds rapidly collapse to form stars. In the other cases, gravitational collapse is prevented by the tidal force exerted by a nearby massive halo, which otherwise should serve as a radiation source necessary for DC. Ram pressure stripping disturbs the cloud approaching the source. In many cases, a DC halo and its nearby light source halo merge before the onset of cloud collapse. When the DC halo is assembled through major mergers, the gas density increases rapidly to trigger gravitational instability. Based on our cosmological simulations, we conclude that the event rate of DC is an order of magnitude smaller than reported in previous studies, although the absolute rate is still poorly constrained. It is necessary to follow the dynamical evolution of a DC cloud and its nearby halo(s) in order to determine the critical radiation flux for DC.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Cumulative effects of fire and drought in Mediterranean ecosystems

Here, the occurrence of multiple disturbances can jointly affect the recovery capacity of ecosystems, potentially leading to changes in vegetation dynamics or loss of resilience. The effects of interacting disturbances on ecosystems are, however, not well understood. We use a model system based on Mediterraneantype ecosystems (MTEs) to examine how the interplay between vegetation regeneration traits and compound, stochastic disturbances modulate ecosystem dynamics. We developed a state-and-transition simulation model including two tree species with contrasting regeneration strategies (seeder vs. resprouter) and a shrubland formation. We aim to assess potential compositional switches under contrasted scenarios of compound fire-drought regimes, and to characterize the cumulative effects of fire-drought (synergism vs. antagonism) relative to the effects of individual disturbance regimes. Our simulation results indicate that interaction between moderate fire and sporadic drought recurrence-as opposed to chronic dryness-can act as a strong mechanism generating highly heterogeneous landscapes in which different regeneration types coexist, as observed in MTEs. Resprouters dominated under individual, moderate disturbance regimes of fire or drought, whereas the interaction of the two disturbances promoted the longterm coexistence of both tree regeneration strategies. However, shrubland expansion and persistence at the expanse of forests was favored by increases in drought recurrence and associated fire-drought interactions, highlighting the potential for important vegetation changes in MTEs under climate change. Overall, the cumulative effects of fire and drought can lead to distinct landscape configurations under moderate disturbance regimes that are otherwise only attained under high frequency of individual disturbances. At the ecosystem level, however, we suggest that disturbance-induced vegetation dynamics can modify vegetation sensitivity and resilience to further disturbances precluding the prevalence of synergistic effects of the two disturbances.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Reliability Assessment of Safety-Critical Network Communication in a Digitalized Nuclear Power Plant

In analog instrumentation and control (I and C) systems for nuclear power plants (NPPs), most connections are comprised of hardwired point-to-point types. Since they are based on analog technologies, they are fragile to noise and require analog-to-digital conversion time. Therefore, many NPPs have adopted communication network for the exchange of safety-critical data between programmable logic controllers (PLCs) in digital I and C systems to effectively accommodate a huge number of field controllers. However, the primary issue of digital network communication in a safety-critical system involves potential hazards, such as partial or total loss of communication between PLCs, which may result in a failure of safety critical signal generation when it is needed. Therefore, the probability that a safety-critical system in digitalized NPP becomes unsafe due to a network failure must be evaluated to quantify the risk of digital I and C system. In Korea, the Engineered Safety Feature-Component Control System (ESF-CCS) was developed as one of the digital safety-critical system in Advanced Power Reactor- 1400 (APR-1400). The function of a digital engineered safety feature (ESF) actuation system and field actuator controllers of conventional NPPs are performed by the ESF-CCS. In this system, safety-critical network, High Reliable- Safety Data Network (HR-SDN), was employed for the safety-critical data transmission from group controllers (GCs) to loop controllers (LCs). In this study, a framework for assessing the reliability of a HR-SDN network communication between GCs and LCs in the ESF-CCS in addition to a fault-tree model for ESF components considering network failure between GCs and LCs were developed to assess the plant risk effect of a newly developed digitalized ESF-CCS. Based on the case studies and cut set analysis, the risk effect of network failure on plant risk and the important risk contributors of network failure were quantitatively addressed. A framework for identifying the potential hazardous states of network communication in the ESFCCS was proposed. In addition, a fault-tree model for network communication failure was developed to estimate the risk effects of network failure between the GCs and LCs on ESF-CCS signal failure. The developed fault-tree model was then applied to several case studies. The fault-tree model of ESF-CCS signal failure for ESF components required for various mitigation actions regarding NPP DBAs was designed by considering the identified hazardous states of network failure that would result in a failure to provide input signals to the corresponding LC. As a sensitivity study, three case studies were performed based on the periodic test methods for hardware components in HR-SDN module and their test intervals in this study. The quantitative results for three case studies demonstrated that the probability of overall network communication failure, which was calculated as the sum of the failure probability associated with each failure cause, contributed up to 1.58% on the Small-LOCA CD frequency. The results also revealed the important basic events related to network failure in the case studies which included CCF of hardware and software in HR-SDN module. This study is expected to provide insight into the development of the fault-tree model for the network failure in digital I and C system and into the quantification of the risk effect of network failure for safety-critical data transmission in NPPs. As a further study, the risk effects of network failure in the ESF-CCS on the plant risk can be estimated in a more detailed manner by analyzing the failure modes and causes in a sub-component level and the fault detection coverage of the fault tolerance techniques for network failure implemented in ESF-CCS after the detailed configuration of ESF-CCS is decided. In terms of the failure of manual ESF actuation, the relationship among the human action failures must be investigated to consider multiple human error condition since ESF-CCS provides multiple manual actuation to assure the diversity of the system. Since the conventional HEP method cannot accommodate the multiple conditions in a fault tree, condition-based human reliability assessment (CBHRA) method or the dynamic human reliability modeling approach can be applied to include a complex relationship among the automated safety signal generation and the human operator's manual actuation, avoiding the optimistic estimation of HEP of the human action failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗