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DOE OSTI2025

AUTOMATIC GENERATION OF EVENT TREES AND FAULT TREES: A MODEL-BASED APPROACH

In the past few decades, increasing complexity in modern engineering systems has been driven by the integration of a large number of components and by the fact that the system operations involve many disciplines (e.g., thermal-hydraulics, plant operations, cyber-security). Current safety/reliability modeling approaches to such systems are labor intensive, difficult to learn, and rely heavily on simplistic Boolean logic to depict failure propagation and accident progression. While these methods serve well for simple systems (i.e., linear causal systems with limited small inter- and intra-system interactions), their results are difficult to verify when modeling complex systems (typically performed through the extensive use of modeling assumptions). The development of new methods is addressed to meet these challenges through a model-based system engineering (MBSE) lens. Under MBSE philosophy, every aspect of the system (form or function) is represented by a model that completely characterizes its architecture or behavior. MBSE approach greatly improves the management of design, analysis and verification of complex systems. An integration of Dynamic Probabilistic Risk Assessment (DPRA) methods with MBSE models is proposed to perform safety/reliability analyses of engineering systems. In particular, MBSE representation of the system (performed using Systems Modeling Language [SysML]) is coupled with DPRA methods to automatically generate event trees and fault trees.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Dynamic probabilistic risk assessment and game theory for cyber security risk analysis in nuclear power plants

Nuclear Power Plants and energy systems have become more prone to cyber-attacks with their digitalization and the increased use of smart equipment. Hence, it is important to quantify the risk associated with cyber-attacks in such systems. Dynamic Probabilistic Risk Assessment which involves studying the evolution of a system due to random events and operator and attacker actions during a cyber-attack by employing a physics-based model of the system is a suitable framework to quantify cybersecurity risk in nuclear power plants. In addition to the plant dynamics, it is also important to model the strategies of the attackers and plant operators for an effective cybersecurity risk assessment. Game theory provides a set of necessary tools to model such strategic interactions. In this research, a framework that integrates dynamic probabilistic risk assessment with game theory for cybersecurity risk analysis in nuclear power plants is presented. The mathematical formulation is derived based on the theory of continuous event trees. We propose a game theory based action model, that utilizes physics-based rewards to define the strategies of attackers and operators at every decision epoch. As a case study, the risk associated with cyber-attacks on the digital components in the secondary side of a pressurized water reactor is studied using a reduced order model. A set of attacker actions and a set of operator actions are defined for the system. The operator and attacker interactions were modelled using simultaneous game, their action policies were computed using the concept of mixed strategy Nash equilibrium and the evolution of the system was studied.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

RISK MONITORING CAPABILITES FROM DYNAMIC PRA DATA

Risk Monitors (RMs) are software tools that are employed in nuclear power plants to monitor the safety properties of the plant itself during operation. These safety properties are generated using classical PRA methods which are typically based on static Boolean structures such as Fault-Trees (FTs) and Event-Trees (ETs). The outcomes of these methods are Core Damage Frequency (CDF) and risk importance values of plant components (e.g., valves and pumps). Examples of Risk Importance Measures (RIMs) commonly used are: Risk Achievement Worth (RAW), Risk Reduction Worth (RRW), Birnbaum (B) and Fussell-Vesely (FV) [1,2]. In a RM these values are updated in real time once plant components status is updated (e.g., under maintenance, off-line, testing). In addition, RMs can be used to optimize maintenance schedules so those safety features of the plant are below plant standard values. This paper presents an approach to create temporal profiles of RIMs (i.e., RM capabilities) given a temporal change of the plant configuration. Instead of employing data generated by ETs and FTs, the proposed approach will employ data generated by Dynamic PRA methods. In contrast to classical PRA methods, Dynamic PRA methods couple stochastic methods with safety analysis codes to determine risk associate to complex systems such as nuclear plants. Compared to classical PRA methods, they can evaluate with higher resolution the safety impact of timing and sequencing of events on the accident progression. We will describe how classical RIMs can be generated by Dynamic PRA data and then we will show how the temporal profiles of the RIMs can be generated given a temporal profile of the system configuration.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Vulnerability of Amazon forests to storm-driven tree mortality

Tree mortality is a key driver of forest community composition and carbon dynamics. Strong winds associated with severe convective storms are dominant natural drivers of tree mortality in the Amazon. Why forests vary with respect to their vulnerability to wind events and how the predicted increase in storm events might affect forest ecosystems within the Amazon are not well understood. We found that windthrows are common in the Amazon region extending from northwest (Peru, Colombia, Venezuela, and west Brazil) to central Brazil, with the highest occurrence of windthrows in the northwest Amazon. More frequent winds, produced by more frequent severe convective systems, in combination with well-known processes that limit the anchoring of trees in the soil, help to explain the higher vulnerability of the northwest Amazon forests to winds. Projected increases in the frequency and intensity of convective storms in the Amazon have the potential to increase wind-related tree mortality. A forest demographic model calibrated for the northwestern and the central Amazon showed that northwestern forests are more resilient to increased wind-related tree mortality than forests in the central Amazon. Our study emphasizes the importance of including wind-related tree mortality in model simulations for reliable predictions of the future of tropical forests and their effects on the Earth' system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Compound fire-drought regimes promote ecosystem transitions in Mediterranean ecosystems

Understanding ecosystem responses to compound disturbance regimes and the influence of specific sequences of events in determining ecosystem shifts remains a challenge. We use a modelling framework for Mediterranean-type ecosystems to assess the effects of fire–drought interactions on long-term vegetation dynamics and to identify disturbance-driven changes in trait composition (tree seeder vs. tree resprouter prevalence) and ecosystem state (forest vs. non-forest). Changes in tree seeder and the tree resprouter dominance show nonlinear, threshold-type trends over gradients of increasing compound disturbance frequency. Vegetation composition thresholds mostly occur in a narrow range of the compound fire–drought disturbance space. Additionally, trait compositional switches and the likelihood of sudden changes in ecosystem state are promoted by fire-drought interactions. Distinct sequences of disturbance events cause vegetation transitions, disrupting ecosystem resilience, even under moderate recurrence of individual disturbances. An extreme drought year followed by one or two large fire events promotes shifts from resprouter- to seeder dominance. Contrastingly, a large crown fire followed by an extreme drought promotes changes from seeder to resprouter dominance. This disturbance sequence is also a mechanism strong enough to trigger sudden shifts in ecosystem state (from forest to non-forest). Synthesis. Thresholds of change in vegetation composition occur over a narrow range of the modelled gradients of compound fire-drought recurrence, and the loss of ecosystem resilience is contingent on particular sequences of disturbance events. Overall, our findings highlight that disturbance interactions define the relative location of tipping points in ecosystem state, and that effects and feedbacks of compound disturbance regimes increase the long-term likelihood of sudden ecosystem shifts and, therefore, uncertainty in predicting vegetation state.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

DYNAMIC PRA OF A MULTI-UNIT PLANT

Dynamic Probabilistic Risk Analysis (PRA) methods couple stochastic methods (e.g., RAVEN, ADAPT, ADS, MCDET) with safety analysis codes (RELAP5-3D, MELCOR, MAAP) to determine risk associated to complex systems such as nuclear plants. Compared to classical PRA methods, which are based on static logic structures (e.g., Event-Trees, Fault-Trees), they can evaluate with higher resolution the safety impact of timing and sequencing of events on the accident progression. Recently, special attention has been given to nuclear plants which consist of multiple units and, in particular, on the safety impact of system dependencies, shared systems and common resources on core damage frequencies. In the literature, while classical PRA methods have been employed to model multi-unit plants, Dynamic PRA methods have never been applied to analyze a full multi-unit model. This paper presents a PRA analysis of a multi-unit plant using Dynamic PRA methods. We employ RAVEN as stochastic method coupled with RELAP5-3D. The plant under consideration consists of the three units and their associated spent fuel pools (SFPs). The studied initiating event is a seismic induced station blackout event. We will describe in detail how the multi-unit plant has been constructed and, in particular, how unit dependencies and shared resources are modeled.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Mining data in a dynamic PRA framework

Computational (also known as Dynamic) Probabilistic Risk Assessment (PRA) methods employs system simulation codes coupled with stochastic analysis tools in order to determine probabilities of certain outcomes such as system failure. In contrast to classical PRA methods (i.e., Event-Tree and Fault-Tree) in which timing and sequencing of events is set by the analyst, accident progression is dictated by the system control logic and its interaction with system temporal evolution. Due to the nature of the problem, Simulation-Based PRA methods require large amount of computationally expensive simulation runs. In addition, these methods usually generate a large number of simulation runs (database storage may be on the order of gigabytes or higher). In this paper we investigate and apply several methods and algorithms to analyze these large amounts of time-dependent data. Furthermore, the scope of this article is to present a broad overview of methods and algorithms that can be used to improve data quality and to analyze and extract information from large data sets containing time dependent data. In this context, “extracting information” means constructing input-output correlations, finding commonalities, and identifying outliers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Amazon windthrow disturbances are likely to increase with storm frequency under global warming

Abstract Forest mortality caused by convective storms (windthrow) is a major disturbance in the Amazon. However, the linkage between windthrows at the surface and convective storms in the atmosphere remains unclear. In addition, the current Earth system models (ESMs) lack mechanistic links between convective wind events and tree mortality. Here we find an empirical relationship that maps convective available potential energy, which is well simulated by ESMs, to the spatial pattern of large windthrow events. This relationship builds connections between strong convective storms and forest dynamics in the Amazon. Based on the relationship, our model projects a 51 ± 20% increase in the area favorable to extreme storms, and a 43 ± 17% increase in windthrow density within the Amazon by the end of this century under the high-emission scenario (SSP 585). These results indicate significant changes in tropical forest composition and carbon cycle dynamics under climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

A Simulation-Based Dynamic Approach for External Flooding Analysis in Nuclear Power Plants

All nuclear power plants must consider and evaluate external flooding risks such as local intense precipitation, dam failure, and coastal flooding due to storm surge or tsunami. While these events could challenge off-site power and other plant structure integrity, threaten plant safety systems and components, and limit plant access, they are more than often qualitatively regarded as risk insignificant and screened out from detailed evaluation and quantification. The recent lessons learned from the Fukushima seismic/tsunami initiated nuclear accident (2011), the Fort Calhoun (2011), Vermont Yankee (2013), Arkansas Nuclear One (2013), and St. Luice (2014) flooding events showed otherwise. However, developing an external flood model with traditional event tree/fault tree approach as in a static probabilistic risk assessment (PRA) model could be difficult to accurately represent plant system and component behavior and reliability of manual actions during an ever-progressing flood event. The plant response to external flood may be highly spatial- and time- dependent and subject to the hydrological and hydraulic characteristics of the flood event. Such unique challenges prompt the investigation of using the simulation-based dynamic analysis approaches for external flood risk assessment. Simulation methods can better illustrate the performance of structures, systems, and components during an external flooding event. A general framework to perform a simulation-based dynamic flooding analysis is presented in this paper with the sub-tasks of flood hazard analysis, flood fragility analysis, plant response modeling, safety margin analysis or PRA quantification. A new type of State PRA modeling technique is introduced to incorporate time-related interactions such as those from 3D simulations into a traditional PRA model.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Stem CO2 Efflux measurements from Manaus, Brazil, 2017

This data was collected in order to test the effects of temperatures on the autotrophic respiratory process in the tropics. This data package contains raw real-time stem CO2 efflux files during the night and day from 3 different species near the K34 in Manaus during the day and the night. Raw and derived data files are included in the format of .csv and .xlsx and information about the canopy trees and temperatures recorded can be found in the field event log using microsoft excel. The data was collected from three canopy dominant trees in the central Amazon near the K34 tower. Real-time stem CO2 efflux was determined using a Li7000 gas analyzer configured in differential mode and connected to a dynamic stem chamber secured to the stem at breast height using straps to generate a reasonable seal. Ambient air was continuously pumped into the stem chamber and CO2 concentrations of the air entering and exiting the chamber were continuously monitored. CO2 efflux was calculated based on the CO2 concentration difference between ambient and stem chambers, the flow rate of air through the chamber, and the area of the enclosed stem. Additional auxiliary data, including sap flow and crown temperature were also measured. No data processing or QA/QC was done on the raw data packages.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Prioritizing urban heat adaptation infrastructure based on multiple outcomes: Comfort, health, and energy

Globally, cities face increasing extreme heat, impacting comfort, health, and energy consumption. Infrastructure-based heat adaptation strategies can improve these outcomes, but each strategy has a unique mix of benefits and drawbacks. Here, we apply an urbanized meteorological model (WRF) with the newly integrated multilayer BEP-Tree street tree model to dynamically downscale Earth System Model projections and a 3-D microclimate model (TUF-Pedestrian) to simulate the street-scale radiation environment impacting pedestrians. We evaluate the performance of five heat adaptation strategies (street trees, cool roofs, green roofs, rooftop photovoltaics (PV), and reflective pavements) during extreme heat events in three cities with contrasting background climates (Toronto, Phoenix, and Miami), under contemporary and end-of-century projected climates, based on three metrics: outdoor heat stress, air conditioning (AC) energy use, and ventilation of vehicular air pollution. No single adaptation strategy improves all three outcomes. While street trees inhibit ventilation, they reduce outdoor heat stress four times more effectively than the next best strategy via shade provision, fully offsetting heat stress increases under a high-emissions end-of-century climate scenario in all cities studied. Cool roofs and green roofs moderately reduce heat stress and energy use. Alternatively, rooftop PV with energy storage can generate sufficient power for space cooling but have marginal effects on heat stress. Reflective pavements are the least effective across metrics. Where the ventilation of street-level emissions is of less concern, our results clearly support the combination of street trees and rooftop PV as a highly complementary and effective means of adaptive mitigation across different climates and neighborhood densities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Automatic Generation of Event Trees and Fault Trees: A Model-Based Approach

In the past few decades, the increasing complexity of modern engineering systems has been driven by the integration of a large number of components whose operations may involve many disciplines (e.g., thermal hydraulics, plant operations, cybersecurity). Most computational tools used by industry and regulators for system safety and reliability assessments are still based on the traditional fault tree (FT) and event tree (ET) approach, which may not be able to capture complex interactions among system constituents. The use of simulation tools has widely increased in the past few decades to improve the fidelity of the reliability and safety analyses. However, the direct use of simulation tools as part of dynamic probabilistic risk assessment (DPRA) methods is not getting traction since (1) modeling the whole system under consideration with DPRA methods may be computationally expensive and unnecessary, and (2) the manual integration of DPRA models into existing state-of-practice probabilistic risk assessment models (i.e., based on FTs and ETs) can be time consuming and prone to errors. Here, in this paper we propose a procedure to overcome this limitation by presenting several algorithms designed to automatically construct subsystem ETs and FTs from DPRA methods for integration into an existing ET/FT system model.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Modeling the temporal dynamics of nonstructural carbohydrate pools in forest trees

Trees store carbohydrates, in the form of sugars and starch, as reserves to be used to power both future growth as well as to support day-to-day metabolic functions. These reserves are particularly important in the context of how trees cope with disturbance and stress—for example, as related to pest outbreaks, wind or ice damage, and extreme climate events. In this project, we measured the size of carbon reserves in forest trees, and determined how quickly these reserves are used and replaced—i.e., their “turnover time”. Our work was conducted at Harvard Forest, a temperate deciduous forest in central Massachusetts. Through field sampling, laboratory-based chemical analyses, and allometric modeling, we scaled these measurements up to whole-tree NSC budgets. We used these data to test and improve computer simulation models of carbon flow through forest ecosystems. Our modeling focused on the mathematical representation of these stored carbon reserves, and we examined the sensitivity of model performance to different model structures. This project contributes to DOE’s goal to improve next-generation models of the earth system, and to understand the impacts of climate change on terrestrial ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗

DOE OSTI2016

A new ionospheric electron precipitation module coupled with RAM-SCB within the geospace general circulation model

Electron precipitation down to the atmosphere due to wave-particle scattering in the magnetosphere contributes significantly to the auroral ionospheric conductivity. In order to obtain the auroral conductivity in global MHD models that are incapable of capturing kinetic physics in the magnetosphere, MHD parameters are often used to estimate electron precipitation flux for the conductivity calculation. Such an MHD approach, however, lacks self-consistency in representing the magnetosphere-ionosphere coupling processes. In this study we improve the coupling processes in global models with a more physical method. We calculate the physics-based electron precipitation from the ring current and map it to the ionospheric altitude for solving the ionospheric electrodynamics. In particular, we use the BATS-R-US (Block Adaptive Tree Scheme-Roe type-Upstream) MHD model coupled with the kinetic ring current model RAM-SCB (Ring current-Atmosphere interaction Model with Self-Consistent Magnetic field (B)) that solves pitch angle-dependent electron distribution functions, to study the global circulation dynamics during the 25–26 January 2013 storm event. Since the electron precipitation loss is mostly governed by wave-particle resonant scattering in the magnetosphere, we further investigate two loss methods of specifying electron precipitation loss associated with wave-particle interactions: (1) using pitch angle diffusion coefficients D αα (E,α) determined from the quasi-linear theory, with wave spectral and plasma density obtained from statistical observations (named as “diffusion coefficient method”) and (2) using electron lifetimes τ(E) independent on pitch angles inferred from the above diffusion coefficients (named as “lifetime method”). We found that both loss methods demonstrate similar temporal evolution of the trapped ring current electrons, indicating that the impact of using different kinds of loss rates is small on the trapped electron population. Furthermore, for the precipitated electrons, the lifetime method hardly captures any precipitation in the large L shell (i.e., 4 < L < 6.5) region, while the diffusion coefficient method produces much better agreement with NOAA/POES measurements, including the spatial distribution and temporal evolution of electron precipitation in the region from the premidnight through the dawn to the dayside. Further comparisons of the precipitation energy flux to DMSP observations indicates that the new physics-based precipitation approach using diffusion coefficients for the ring current electron loss can explain the diffuse electron precipitation in the dawn sector, such as the enhanced precipitation flux at auroral latitudes and flux drop near the subauroral latitudes, but the traditional MHD approach largely overestimates the precipitation flux at lower latitudes.

58 GEOSCIENCES↗

DOE OSTI2015

The two-way relationship between ionospheric outflow and the ring current

It is now well established that the ionosphere, because it acts as a significant source of plasma, plays a critical role in ring current dynamics. However, because the ring current deposits energy into the ionosphere, the inverse may also be true: the ring current can play a critical role in the dynamics of ionospheric outflow. This study uses a set of coupled, first-principles-based numerical models to test the dependence of ionospheric outflow on ring current-driven region 2 field-aligned currents (FACs). A moderate magnetospheric storm event is modeled with the Space Weather Modeling Framework using a global MHD code (Block Adaptive Tree Solar wind Roe-type Upwind Scheme, BATS-R-US), a polar wind model (Polar Wind Outflow Model), and a bounce-averaged kinetic ring current model (ring current atmosphere interaction model with self-consistent magnetic field, RAM-SCB). Initially, each code is two-way coupled to all others except for RAM-SCB, which receives inputs from the other models but is not allowed to feed back pressure into the MHD model. The simulation is repeated with pressure coupling activated, which drives strong pressure gradients and region 2 FACs in BATS-R-US. It is found that the region 2 FACs increase heavy ion outflow by up to 6 times over the non-coupled results. The additional outflow further energizes the ring current, establishing an ionosphere-magnetosphere mass feedback loop. This study further demonstrates that ionospheric outflow is not merely a plasma source for the magnetosphere but an integral part in the nonlinear ionosphere-magnetosphere-ring current system.

58 GEOSCIENCES↗

DOE OSTI2021

Recovery of Forest Structure Following Large-Scale Windthrows in the Northwestern Amazon

The dynamics of forest recovery after windthrows (i.e., broken or uprooted trees by wind) are poorly understood in tropical forests. The Northwestern Amazon (NWA) is characterized by a higher occurrence of windthrows, greater rainfall, and higher annual tree mortality rates (~2%) than the Central Amazon (CA). We combined forest inventory data from three sites in the Iquitos region of Peru, with recovery periods spanning 2, 12, and 22 years following windthrow events. Study sites and sampling areas were selected by assessing the windthrow severity using remote sensing. At each site, we recorded all trees with a diameter at breast height (DBH) ≥ 10 cm along transects, capturing the range of windthrow severity from old-growth to highly disturbed (mortality > 60%) forest. Across all damage classes, tree density and basal area recovered to >90% of the old-growth values after 20 years. Aboveground biomass (AGB) in old-growth forest was 380 (±156) Mg ha -1 . In extremely disturbed areas, AGB was still reduced to 163 (±68) Mg ha -1 after 2 years and 323 (± 139) Mg ha -1 after 12 years. This recovery rate is ~50% faster than that reported for Central Amazon forests. The faster recovery of forest structure in our study region may be a function of its higher productivity and adaptability to more frequent and severe windthrows. These varying rates of recovery highlight the importance of extreme wind and rainfall on shaping gradients of forest structure in the Amazon, and the different vulnerabilities of these forests to natural disturbances whose severity and frequency are being altered by climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Topography alters tree growth–climate relationships in a semi-arid forested catchment

Topography and climate play an integral role in the spatial variability and annual dynamics of aboveground carbon sequestration. Despite knowledge of vegetation–climate–topography relationships on the landscape and hillslope scales, little is known about the influence of complex terrain coupled with hydrologic and topoclimatic variation on tree growth and physiology at the catchment scale. Climate change predictions for the semi-arid, western United States include increased temperatures, more frequent and extreme drought events, and decreases in snowpack, all of which put forests at risk of drought induced mortality and enhanced susceptibility to disturbance events. In this study, we determine how species-specific tree growth patterns and water use efficiency respond to interannual climate variability and how this response varies with topographic position. We found that Pinus contorta and Pinus ponderosa both show significant decreases in growth with water-limiting climate conditions, but complex terrain mediates this response by controlling moisture conditions in variable topoclimates. Foliar carbon isotope analyses show increased water use efficiency during drought for Pinus contorta, but indicate no significant difference in water use efficiency of Pinus ponderosa between a drought year and a non-drought year. The responses of the two pine species to climate indicate that semi-arid forests are especially susceptible to changes and risks posed by climate change and that topographic variability will likely play a significant role in determining the future vegetation patterns of semi-arid systems.

54 ENVIRONMENTAL SCIENCES↗