SEARCH · Engineering Papers

Results for “Dynamic Event Tree”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

MEDPRAT Treatment Clusters: Improving Representation of Mission Medical Risk

INTRODUCTION The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) implements a computational model that aims to quantify spaceflight medical risk by utilizing probabilistic techniques to simulate critical event incidence and outcomes over thousands of simulated mission trials. The goal of MEDPRAT is to characterize mission medical risk and provide insight into medical resource utilization. In order to analyze the medical resource space, treatment must be mapped from each simulated condition, and resources consumed as a result of this treatment must be tracked throughout the course of the mission. A new MEDPRAT feature, ‘treatment clusters’, provide a more sophisticated method of defining the structure and interaction between resources, more closely mimicking the way treatment is carried out clinically. METHODS Treatment clusters expand on the two existing treatment groupings (combination and alternate) adding a new grouping: bundled treatment. Treatment clusters may be combined to any depth, giving users the ability to specify complex treatment trees whose behavior is governed by several user-specified parameters. This approach emphasizes reusability, as treatment clusters, once defined, can be used to create more complex treatment trees or applied to many conditions. By configuring parameters for contribution, efficacy, necessity, primacy, and equivalence, resource relationships and dependencies can be more accurately represented, thereby allowing users to build capabilities with desired treatment properties, for example an intravenous capability for conditions such as anaphylaxis, acute radiation syndrome, etc. MEDPRAT v1.0 remains backward compatible with existing treatment structures, giving users the ability to define new treatment clusters as evidence becomes available, without having to recode their existing treatment databases. In addition to facilitating the representation of more complex treatment options, by pairing treatment clusters with the internal optimization routine, the MEDPRAT set selector, medical resources can be identified as organized in bundles, where appropriate, so that optimized resource sets include groups of highly-dependent resources only when all resources of the group are together. For example, it would be wasteful to include ultrasound gel but not an ultrasound machine, since the gel provides no benefit as a treatment without the ultrasound machine. With treatment clusters, the user may require that both resources are available to provide any benefit as treatment, so that if one resource is optimized out of the set, the other resource will be optimized out as well. RESULTS AND CONCLUSIONS We will report on MEDPRAT treatment clusters used in a bundling study under the IMPACT project of the ExMC element. We will discuss an example of a complex treatment tree. Through the implementation of this feature MEDPRAT enables treatment to be defined and applied in a way that is more representative of the real world, providing more accurate insight into mission medical risk and the medical resource space.

Lawrence Leinweber↗

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↗

NASA NTRS2001

Visualization of CFD Results in Immersive Virtual Environments

An object-oriented event-driven immersive virtual environment (VE) is described for the visualization of computational fluid dynamics (CFD) results. The VE incorporates the following types of primitive software objects: interface objects, support objects, geometric entities, and finite elements. The fluid domain is discretized using either a multi-block structured grid or an unstructured finite element mesh. The VE allows natural 'fly-through' visualization of the model, the CFD grid, and the model's surroundings. In order to help visualize the flow and its effects on the model, the VE incorporates the following objects: stream objects (lines, surface-restricted lines. ribbons. and volumes); colored surfaces; elevation surfaces; surface arrows; global and local iso-surfaces; vortex cores; and separation/attachment surfaces and lines. Most of these objects can be used for dynamically probing the flow. Particles and arrow animations can be displayed on top of stream objects. Primitive response quantities as well as derived quantities can be used. A recursive tree search algorithm is used for real-time point and value search in the CFD grid.

Wasfy, Tamer M.↗

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↗

NASA NTRS2015

Reliability and Probabilistic Risk Assessment - How They Play Together

PRA methodology is one of the probabilistic analysis methods that NASA brought from the nuclear industry to assess the risk of LOM, LOV and LOC for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability and statistical data to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: What can go wrong? How likely is it? What is the severity of the degradation? Since 1986, NASA, along with industry partners, has conducted a number of PRA studies to predict the overall launch vehicles risks. Planning Research Corporation conducted the first of these studies in 1988. In 1995, Science Applications International Corporation (SAIC) conducted a comprehensive PRA study. In July 1996, NASA conducted a two-year study (October 1996 - September 1998) to develop a model that provided the overall Space Shuttle risk and estimates of risk changes due to proposed Space Shuttle upgrades. After the Columbia accident, NASA conducted a PRA on the Shuttle External Tank (ET) foam. This study was the most focused and extensive risk assessment that NASA has conducted in recent years. It used a dynamic, physics-based, integrated system analysis approach to understand the integrated system risk due to ET foam loss in flight. Most recently, a PRA for Ares I launch vehicle has been performed in support of the Constellation program. Reliability, on the other hand, addresses the loss of functions. In a broader sense, reliability engineering is a discipline that involves the application of engineering principles to the design and processing of products, both hardware and software, for meeting product reliability requirements or goals. It is a very broad design-support discipline. It has important interfaces with many other engineering disciplines. Reliability as a figure of merit (i.e. the metric) is the probability that an item will perform its intended function(s) for a specified mission profile. In general, the reliability metric can be calculated through the analyses using reliability demonstration and reliability prediction methodologies. Reliability analysis is very critical for understanding component failure mechanisms and in identifying reliability critical design and process drivers. The following sections discuss the PRA process and reliability engineering in detail and provide an application where reliability analysis and PRA were jointly used in a complementary manner to support a Space Shuttle flight risk assessment.

Safie, Fayssal M.↗

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↗

NASA NTRS1988

PDA: A coupling of knowledge and memory for case-based reasoning

Problem solving in most domains requires reference to past knowledge and experience whether such knowledge is represented as rules, decision trees, networks or any variant of attributed graphs. Regardless of the representational form employed, designers of expert systems rarely make a distinction between the static and dynamic aspects of the system's knowledge base. The current paper clearly distinguishes between knowledge-based and memory-based reasoning where the former in its most pure sense is characterized by a static knowledge based resulting in a relatively brittle expert system while the latter is dynamic and analogous to the functions of human memory which learns from experience. The paper discusses the design of an advisory system which combines a knowledge base consisting of domain vocabulary and default dependencies between concepts with a dynamic conceptual memory which stores experimental knowledge in the form of cases. The case memory organizes past experience in the form of MOPs (memory organization packets) and sub-MOPs. Each MOP consists of a context frame and a set of indices. The context frame contains information about the features (norms) common to all the events and sub-MOPs indexed under it.

Bharwani, S.↗

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↗

NASA NTRS2021

Ecosystem age-class dynamics and distribution in the LPJ-wsl v2.0 global ecosystem model

Forest ecosystem processes follow classic responses with age, peaking production around canopy closure and declining thereafter. Although age dynamics might be more dominant in certain regions over others, demographic effects on net primary production (NPP) and heterotrophic respiration (Rh) are bound to exist. Yet, explicit representation of ecosystem demography is notably absent in many global ecosystem models. This is concerning because the global community relies on these models to regularly update our collective understanding of the global carbon cycle. This paper aims to present the technical developments of a computationally efficient approach for representing age-class dynamics within a global ecosystem model, the Lund–Potsdam–Jena – Wald, Schnee, Landschaft version 2.0 (LPJ-wsl v2.0) dynamic global vegetation model and to determine if explicit representation of demography influenced ecosystem stocks and fluxes at global scales or at the level of a grid cell. The modeled age classes are initially created by simulated fire and prescribed wood harvesting or abandonment of managed land, otherwise aging naturally until an additional disturbance is simulated or prescribed. In this paper, we show that the age module can capture classic demographic patterns in stem density and tree height compared to inventory data, and that simulated patterns of ecosystem function follow classic responses with age. We also present two scientific applications of the model to assess the modeled age-class distribution over time and to determine the demographic effect on ecosystem fluxes relative to climate. Simulations show that, between 1860 and 2016, zonal age distribution on Earth was driven predominately by fire, causing a 45- to 60-year difference in ages between older boreal (50–90° N) and younger tropical (23° S–23° N) ecosystems. Between simulation years 1860 and 2016, land-use change and land management were responsible for a decrease in zonal age by −6 years in boreal and by −21 years in both temperate (23–50° N) and tropical latitudes, with the anthropogenic effect on zonal age distribution increasing over time. A statistical model helped to reduce LPJ-wsl v2.0 complexity by predicting per-grid-cell annual NPP and Rh fluxes by three terms: precipitation, temperature, and age class; at global scales, R2 was between 0.95 and 0.98. As determined by the statistical model, the demographic effect on ecosystem function was often less than 0.10 kg C/sq. myr but as high as 0.60 kg C/sq. myr where the effect was greatest. In the eastern forests of North America, the simulated demographic effect was of similar magnitude, or greater than, the effects of climate; simulated demographic effects were similarly important in large regions of every vegetated continent. Simulated spatial datasets are provided for global ecosystem ages and the estimated coefficients for effects of precipitation, temperature and demography on ecosystem function. The discussion focuses on our finding of an increasing role of demography in the global carbon cycle, the effect of demography on relaxation times (resilience) following a disturbance event and its implications at global scales, and a finding of a 40 Pg C increase in biomass turnover when including age dynamics at global scales. Whereas time is the only mechanism that increases ecosystem age, any additional disturbance not explicitly modeled will decrease age. The LPJ-wsl v2.0 age module represents another step forward towards understanding the role of demography in global ecosystems.

LPJ-wsl↗

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↗

NASA NTRSDate not supplied

Global Landslide Hazard Assessment for Situational Awareness (LHASA) Version 2: New Activities and Future Plans

A remote sensing-based system has been developed to characterize the potential for rainfall-triggered landslides across the globe in near real-time. The Landslide Hazard Assessment for Situational Awareness (LHASA) model uses a decision tree framework to combine a static susceptibility map derived from information on slope, rock characteristics, forest loss, distance to fault zones and distance to road networks with satellite precipitation estimates from the Global Precipitation Measurement (GPM) mission. Since 2016, the LHASA model has been providing near real-time and retrospective estimates of potential landslide activity. Results of this work are available at https://landslides.nasa.gov. In order to advance LHASA’s capabilities to characterize landslide hazards and impacts dynamically, we have implemented a new approach that leverages machine learning, new parameters, and new inventories. LHASA 2.0 uses the XGBoost machine learning model to bring in dynamic variables as well as additional static variables to better represent landslide hazard globally. Global rainfall forecasts are also being evaluated to provide a 1-3 day forecast of potential landslide activity. Additional factors such as recent seismicity and burned areas are also being considered to represent the preconditioning or changing interactions with subsequent rainfall over affected areas. A series of parameters are being tested within this structure using NASA’s Global Landslide Catalog as well as many other event-based and multi-temporal inventories mapped by the project team or provided by project partners. In addition to estimates of landslide hazard, LHASA Version 2 will incorporate dynamic estimates of exposure including population, roads and infrastructure to highlight the potential impacts that rainfall-triggered landslides. The ultimate goal of LHASA Version 2.0 is to approximate the relative probabilities of landslide hazard and exposure across different space and time scales to inform hazard assessment retrospectively over the past 20 years, in near real-time, and in the future. In addition to the hazard. This presentation will outline the new activities for LHASA Version 2.0 and present some next steps for this system.

Dalia Kirschbaum↗

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↗

NASA NTRS2016

Extended Magnetohydrodynamics with Embedded Particle-in-Cell Simulation of Ganymede's Magnetosphere

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 (MHO-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 magnetospherlc plasma and Ganymede's magnetosphere. We compare the MHO-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 MHO-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 MHO-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 3-0 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 MHO-EPIC simulation was only about 4 times more than that of the Hall MHD simulation.

Toth, Gabor↗