SEARCH · Search NASA

Results for “dynamic events”

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 505 records · Page 28

All sources NASA NTRS DOE OSTI

DOE OSTI2021

A new coupled multiphase flow–finite strain deformation–fault slip framework for induced seismicity

Production of hydrocarbons and water from subsurface reservoirs are known to cause permanent deformation of the reservoir and seismicity along faults both of which are detrimental to sustainable development of natural resources. Most of the prior studies on understanding fluid flow-induced plasticity and seismicity have focused on one or the other phenomenon due to the numerical difficulty associated with simultaneous modeling of the two failure phenomena because stress and deformation evolve non-linearly in both plasticity and seismicity. However, in reservoirs undergoing long-term production, plastic failure can alter the stress paths of points on a fault such that the onset, location, and magnitude of actual seismic events can no longer be predicted by a poroelastic simulation due to inaccurate stress and deformation history. We present a computational framework for coupled multiphase flow, finite strain poroplastic deformation, and dynamic fault slip and use it to understand the impact of plastic deformation on the onset, location, and magnitude of induced fault slip events. We evaluate the impact of plasticity on reservoir pressure, deformation, induced stress, and fault slip by comparing infinitesimal strain elastic and finite strain poro-elastoplastic models. For real-world applications, we consider different scenarios where the reservoir is either mechanically weaker or stronger than the caprock. We analyze the stress evolution as a function of the change in reservoir pressure to understand the role of contrast in reservoir and caprock elastic moduli on geomechanical stability. The results show that the poroplastic reservoir exhibits larger vertical deformation and delayed slip than the poroelastic reservoir after the same amount of oil production. For the same amount of pressure drop, a reservoir with a smaller modulus than the caprock displays a larger vertical displacement and an earlier onset of both plastic failure and fault slip. For a reservoir with a larger modulus than the caprock, vertical displacement is larger on the reservoir top boundary and smaller on the ground surface, and a higher pressure drop is needed to induce plastic failure and fault slip.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Contrasting Effects of Urban Land Cover Change and Anthropogenic Heat on Summer Precipitation Over the Yangtze River Delta of China: Analyses From an Atmospheric Moisture Budget Perspective

Both urban land cover (ULC) change and anthropogenic heat (AH) emission are important causes of urban heat island, but their relative contributions to the changes in urban precipitation and the related mechanism remain unclear. Based on numerical simulations utilizing the latest realistic urban fraction and AH data over the Yangtze River Delta urban agglomeration, we found that ULC and AH resulted in nearly opposite effects on precipitation. Various dynamical and thermodynamic processes were involved according to the atmospheric moisture budget analyses. AH increased precipitation particularly during afternoon, and the increases were stronger during heavy precipitation events because of the enhanced moisture convergence effect together with the release of moisture storage previously accumulated in the atmosphere. Differently, ULC reduced mean precipitation mainly due to suppressed evaporation. During weak precipitation events, the suppressed evaporation was largely balanced by the intensified moisture convergence, but during heavy events, ULC caused more pronounced precipitation reduction because the moisture convergence response disappeared and failed to offset the evaporation effect. Here, the relative contributions of different dynamical and thermodynamic processes such as those related to circulation, moisture gradient, and background moisture availability to the temporal variation in the total moisture convergence were further quantified. Overall, our results help better understand the relative roles of different aspects of urbanization on precipitation, and suggest that compared to ULC, reduction in AH emission that is tightly related to the energy consumption structure could be more efficient for mitigating the risk of extreme precipitation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

New Particle Formation Event Dataset at the Southern Great Plains (SGP) Observatory from 2018 to 2023

This data set contains observations of new particle formation (NPF) events collected at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory from 2018 to 2023. Measurements include particle number size distributions, radiance measurements, and associated meteorological variables from onsite instrumentation relevant for identifying and characterizing NPF events. Events were identified using standardized criteria and documented to support investigations of aerosol nucleation, growth dynamics, and their interactions with local atmospheric conditions. The data set provides a multi-year record that enables evaluation of seasonal and interannual variability in NPF occurrence and intensity at a mid-continental site. These data are intended to support studies of aerosol-cloud-climate interactions and model evaluation within both ARM and the broader atmospheric science community. More information can be found within the README_NPF_SGP_2018_2023.docx file.

event↗

DOE OSTI2020

Risk-Informed ATF and FLEX Analysis for an Enhanced Resilient BWR Under Design-Basis and Beyond-Design-Basis Accidents

This report documents the activities performed by the Idaho National Laboratory (INL) during fiscal year (FY) 2020 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of accident-tolerant fuel (ATF), optimal use of diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, and the incorporation of augmented or new passive cooling systems, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors’ safety features (both active and passive) and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. One main focus of the FY 2020 efforts documented in this report was to extend the analyses conducted in FYs 2018 and 2019 for a pressurized water reactor (PWR) to a boiling water reactor (BWR). The same analysis process, risk analysis approaches, and analysis tools as in the previous work for PWR were used for a generic BWR with near-term ATF cladding (i.e., Iron-Chromium-Aluminum [FeCrAl] cladding and Chromium [Cr]-coated cladding) designs under the postulated station blackout (SBO) and medium loss-of-coolant (MLOCA) accident scenarios. In addition, a FLEX model was developed and incorporated into a generic BWR probabilistic risk assessment (PRA) model using the INL-developed software tool, Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE), to assess the risk impact from FLEX. The other main focus of the FY 2020 efforts was to advance analysis methods, including developing dynamic approach for FLEX human reliability analysis (HRA) using the INL-developed software tool, Event Modeling Risk Assessment using Linked Diagrams (EMRALD), as well as developing a multicriterion benefit evaluation (MCBE) method for evaluating costs and benefits of safety enhancements in nuclear power plants (NPPs). As a case study, the MCBE method was applied to evaluate the costs and benefits brought by FLEX implementation.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

How do axisymmetric black holes grow monopole and dipole hair?

Here, we study the dynamical formation of scalar monopole and dipole hair in scalar Gauss-Bonnet theory and dynamical Chern-Simons theory. We prove that the spherically symmetric mode of the dipole hair is completely determined by the product of the mass of the spacetime and the value of the monopole hair. We then show that the dynamics of the ℓ = 1 mode of the dipole hair is intimately tied to the appearance of the event horizon during axisymmetric collapse, which results in the radiation of certain modes that could have been divergent in the future of the collapse. We confirm these analytical predictions by simulating the gravitational collapse of a rapidly rotating neutron star in the decoupling limit, both in scalar Gauss-Bonnet and dynamical Chern-Simons theory. Our results, combined with those provide a clear physical picture of the dynamics of scalar monopole and dipole radiation in axisymmetric and spherical gravitational collapse in these theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Floods due to Atmospheric Rivers along the U.S. West Coast: The Role of Antecedent Soil Moisture in a Warming Climate

Precipitation extremes are projected to become more frequent along the U.S. West Coast due to increased atmospheric river (AR) activity, but the frequency of less intense precipitation events may decrease. Antecedent soil moisture (ASM) conditions can have a large impact on flood responses, especially if prestorm precipitation decreases. Taken together with increased antecedent evaporative demand due to warming, this would result in reduced soil moisture at the onset of extreme precipitation events. In this work, we examine the impact of ASM on AR-related floods in a warming climate in three basins that form a transect along the U.S. Pacific Coast: the Chehalis River basin in Washington, the Russian River basin in Northern California, and the Santa Margarita River basin in Southern California. Additionally, we ran the Distributed Hydrology Soil Vegetation Model (DHSVM) over the three river basins using forcings downscaled from 10 global climate models (GCMs). We examined the dynamic role of ASM by comparing the changes in the largest 50, 100, and 150 extreme events in two periods, 1951–2000 and 2050–99. In the Chehalis basin, the projected fraction of AR-related extreme discharge events slightly decreases. In the Russian basin, this fraction increases, however, and more substantially so in the Santa Margarita basin. This is due to increases in AR-related extreme precipitation events, as well as the fact that the relationship of extreme precipitation to extreme discharge is strengthened by projected increases in year-to-year volatility of annual precipitation in California, which increases the likelihood of concurrent occurrence of large storms and wet ASM conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

The Dynamics of Megafire Smoke Plumes in Climate Models: Why a Converged Solution Matters for Physical Interpretations

As the climate system warms, megafires have become more frequent with devastating effects. A byproduct of these events is the creation of smoke plumes that can rise into the stratosphere and spread across the globe where they reside for many months. To gain a deeper understanding of the plume dynamics, global climate simulations of a megafire were performed at a wide range of grid spacings from 2.0° down to 7 km, including a 7 km nonhydrostatic experiment. The analysis focuses on how the resolved dynamics affects the specification of the plume characteristics such as injection height and black carbon (BC) mass. Prior studies initialize the smoke plume at one or a few grid points and this is shown here to produce severely dissipative dynamics. In order to validate such simulations with observations, enhancements of the plume characteristics to offset the dissipation is necessary. Using a numerically converged simulation, sensitivity tests show that to approximate the observed stratospheric lifetime, a reduction in BC fraction by 50% is necessary for external mixtures. The vorticity dynamics of the plume is also analyzed with a Lagrangian budget to understand the mechanisms responsible for the evolution of a collocated anticyclonic vortex. The results can be distilled down into a simple conceptual model. As the plume rises, the air diverges at the top of the updraft where the largest concentrations of smoke are found. This divergence induces a dilution of the background cyclonic absolute vorticity producing an anticyclonic vortex. Vortex decay occurs from opposite arguments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Regional and Temporal Variability of Atmospheric River Seasonality: Influences of Detection Algorithms and Moisture Transport Dynamics

Abstract Understanding the regional and temporal variability of atmospheric river (AR) seasonality is crucial for preparedness and mitigation of extreme events. While ARs were thought to peak in winter, recent research shows they exhibit region‐specific seasonality and are heavily influenced by the chosen detection algorithm. This study examines the link between the year‐to‐year consistency of peak‐AR activity to the presence of a dominant seasonal pattern, considering both location and algorithm choice. Regions are categorized by their temporal characteristics: consistent patterns (e.g., East Asia), patterns with occasional outliers (e.g., British Columbia coast), and regions lacking a clear dominant peak season (e.g., South Atlantic, parts of Australia). Hence, not all regions display a consistent seasonal cycle of AR activity. This study quantifies the extent to which a region experiences a dominant peak season of AR activity (or lacks one) and offers insights to enhance decision‐making in water management, natural hazard preparedness, and forecasting. Furthermore, given our finding that detection algorithms influence the peak season of AR activity, we also examine two diagnostic variables representative of moisture transport to corroborate our results. Integrated vapor transport, which captures meridional and zonal moisture transport, and Moist Wave Activity, representing moisture intrusions from lower to higher latitudes, are examined. Our analysis indicates that inconsistencies in the seasonal cycle of AR activity are not solely due to discrepancies in detection algorithms but also arise from changes in moisture transport. Plain Language Summary Atmospheric rivers (ARs) are critical weather phenomena that can cause extreme events like heavy rainfall and flooding. Understanding when and where ARs are most likely to occur throughout the year is essential for preparing and responding to these events. Traditionally, ARs were thought to peak in winter, but recent studies show this varies by region. Our study helps address the challenge decision‐makers face in anticipating and preparing for AR events by providing insights into the consistency of peak seasonal patterns across different areas. Some regions, like East Asia, and the British Columbia coast, show a consistent peak season, while others, like the South Atlantic and parts of Australia, have significant year‐to‐year variations, making it hard to identify a dominant season. To better understand these changes over time, the study also examines how moisture moves in the atmosphere, using Integrated Vapor Transport (which looks at moisture movement in various directions) and Moist Wave Activity (which tracks moisture shifts from lower to higher latitudes). The findings suggest that inconsistencies in AR patterns are due not only to detection methods but also due to changes in moisture transport. Key Points The peak season of atmospheric river activity can change depending on the year in some areas Interannual variations in the peak season can make identifying a dominant season challenging for some regions Frequent shifts in peak season across years reflect inconsistencies tied to detection algorithms and to underlying dynamics

Kamnani, Diya↗

DOE OSTI2023

Dissolved Oxygen and Temperature Data from the Hyporheic Zone of the East River Watershed July 2017 to October 2018

Dissolved oxygen (DO) is critical for aquatic ecosystems. Our focus is on the long-term DO dynamics in hyporheic zone of rivers, which are a function of both transport (hydrologic exchange between river and hyporheic zone) and uptake by biogeochemical reactions or respiration. The study site is the alpine East River watershed in Colorado, USA, meander A downstream from the pump house. Opti O2 probes were deployed in the water column and directly within the river-bed at 10, 20, and 35 cm depth (38°55'23.38"N, 106°57'4.21"W, 9046.88m) to monitor DO and temperature. A continuous data stream from July 24, 2017 to Oct 24, 2018 was autonomously telemetered to the cloud. This 14-month DO and temperature time series were obtained without any servicing for maintenance or data downloads; additionally the ability to remotely verify probe performance during field deployment was essential to confirm data validity during winter freeze-in and hydrological/weather events, such as spring melt and summer monsoons. We investigate the variations in dissolved oxygen dynamics of this snow-pack dominated watershed during a comparatively low flow water year (2018) and a relatively normal water year (2017), enabled by distinctive, in-situ, high frequency (∆t = 5min) sensors that provided a continuous time-series from the undisturbed study site over multiple seasons.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

The impact of the atmospheric turbulence-development tendency on new particle formation: a common finding on three continents

Abstract A new mechanism of new particle formation (NPF) is investigated using comprehensive measurements of aerosol physicochemical quantities and meteorological variables made in three continents, including Beijing, China; the Southern Great Plains site in the USA; and SMEAR II Station in Hyytiälä, Finland. Despite the considerably different emissions of chemical species among the sites, a common relationship was found between the characteristics of NPF and the stability intensity. The stability parameter (ζ = Z/L, where Z is the height above ground and L is the Monin–Obukhov length) is found to play an important role; it drops significantly before NPF as the atmosphere becomes more unstable, which may serve as an indicator of nucleation bursts. As the atmosphere becomes unstable, the NPF duration is closely related to the tendency for turbulence development, which influences the evolution of the condensation sink. Presumably, the unstable atmosphere may dilute pre-existing particles, effectively reducing the condensation sink, especially at coarse mode to foster nucleation. This new mechanism is confirmed by model simulations using a molecular dynamic model that mimics the impact of turbulence development on nucleation by inducing and intensifying homogeneous nucleation events.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Multi-variate model of T cell clonotype competition and homeostasis

Abstract Diversity of the naive T cell repertoire is maintained by competition for stimuli provided by self-peptides bound to major histocompatibility complexes (self-pMHCs). We extend an existing bi-variate competition model to a multi-variate model of the dynamics of multiple T cell clonotypes which share stimuli. In order to understand the late-time behaviour of the system, we analyse: (i) the dynamics until the extinction of the first clonotype, (ii) the time to the first extinction event, (iii) the probability of extinction of each clonotype, and (iv) the size of the surviving clonotypes when the first extinction event takes place. We also find the probability distribution of the number of cell divisions per clonotype before its extinction. The mean size of a new clonotype at quasi-steady state is an increasing function of the stimulus available to it, and a decreasing function of the fraction of stimuli it shares with other clonotypes. Thus, the probability of, and time to, extinction of a new clonotype entering the pool of T cell clonotypes is determined by the extent of competition for stimuli it experiences and by its initial number of cells.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

How robust are estimates of key parameters in standard viral dynamic models?

Mathematical models of viral infection have been developed, fitted to data, and provide insight into disease pathogenesis for multiple agents that cause chronic infection, including HIV, hepatitis C, and B virus. However, for agents that cause acute infections or during the acute stage of agents that cause chronic infections, viral load data are often collected after symptoms develop, usually around or after the peak viral load. Consequently, we frequently lack data in the initial phase of viral growth, i.e., when pre-symptomatic transmission events occur. Missing data may make estimating the time of infection, the infectious period, and parameters in viral dynamic models, such as the cell infection rate, difficult. However, having extra information, such as the average time to peak viral load, may improve the robustness of the estimation. Here, we evaluated the robustness of estimates of key model parameters when viral load data prior to the viral load peak is missing, when we know the values of some parameters and/or the time from infection to peak viral load. Although estimates of the time of infection are sensitive to the quality and amount of available data, particularly pre-peak, other parameters important in understanding disease pathogenesis, such as the loss rate of infected cells, are less sensitive. Viral infectivity and the viral production rate are key parameters affecting the robustness of data fits. Fixing their values to literature values can help estimate the remaining model parameters when pre-peak data is missing or limited. We find a lack of data in the pre-peak growth phase underestimates the time to peak viral load by several days, leading to a shorter predicted growth phase. On the other hand, knowing the time of infection (e.g., from epidemiological data) and fixing it results in good estimates of dynamical parameters even in the absence of early data. While we provide ways to approximate model parameters in the absence of early viral load data, our results also suggest that these data, when available, are needed to estimate model parameters more precisely.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Hourly PM 2.5 Estimates across California from 2018 to 2023

This study presents a new data set of hourly PM 2.5 concentrations across California from 2018 to 2023 at a three-kilometer resolution. This data set was developed by assimilating observations from PurpleAir and the U.S. EPA Air Quality System monitors into wildfire smoke forecasts from the High-Resolution Rapid Refresh Smoke (HRRR-Smoke) model using the Gridpoint Statistical Interpolation (GSI) three-dimensional variational data assimilation framework. Archived forecasts of modeled wildfire smoke PM 2.5 from HRRR-Smoke create the background field for assimilation, which is then corrected using surface observations of total PM 2.5 . The resulting reanalysis from GSI provides an estimate of total PM 2.5 that minimizes error from both the observational and the model data. Validation results indicate strong performance, with monthly R 2 values ranging from 0.73 to 0.91 across the six-year data set, comparable to other PM 2.5 data sets. Case studies are presented for three major fire events, the 2018 Camp Fire, 2019 Kincade Fire, and 2020 Lightning Complex Fires to demonstrate the data set’s fidelity in resolving plume dynamics and local exposure patterns. Root-mean-squared error averaged over each month scales with average PM 2.5 concentrations, resulting in a low error under typical conditions but higher absolute errors during extreme smoke events. This is the first long-term, hourly PM 2.5 data set of its kind for California and enables the generation of subdaily exposure metrics, such as peak hourly concentrations, exceedance durations, and time-of-day exposure peaks. The novelty and strong validation of this data set make it a compelling resource for future studies on the impact and significance of subdaily PM 2.5 exposure.

PM2.5↗

DOE OSTI2023

Cool carriers: triplet diffusion dominates upconversion yield

Perovskites have gained popularity both as the active material in photovoltaics and as bulk triplet sensitizers for solid-state triplet–triplet annihilation upconversion (TTA-UC). Prior to widespread implementation into commercial photovoltaics, an in-depth understanding of the environmental influences on device performance is required. To this point, the temperature-dependent structure–function properties of TTA-UC within methylammonium formamidinium lead triiodide (MAFA)/rubrene UC devices are explored. A strong temperature dependence of the underlying UC dynamics is observed, where the maximum UC efficiency is achieved at 170 K, reflecting the competition between triplet diffusion length, diffusion rate, and triplet–triplet encounter events. Furthermore, a combination of spectroscopic and structural methods and theoretical modelling illustrates that despite the significantly increased carrier lifetime of the perovskite at low temperatures, the TTA-UC dynamics are not governed by the underlying sensitizer properties but rather limited by the underlying triplet diffusion.

Sullivan, Colette M.↗

DOE OSTI2026

Record-Breaking Atmospheric River Drives April 2024 Extreme Precipitation in the United Arab Emirates and the Surrounding Gulf Region

In mid-April 2024, the United Arab Emirates (UAE) and the surrounding Gulf region experienced unprecedented rainfall and catastrophic flooding, causing widespread damage, loss of life, and significant economic costs. During the 3-day period from 15 to 17 April, rainfall in the UAE exceeded 100 mm in the hardest-hit areas, with more than 170% of the typical annual precipitation recorded in just 72 h. The event was associated with exceptionally strong integrated water vapor transport (IVT), driven by a persistent low pressure system and a focused corridor of moisture transport. This environment, combined with favorable dynamical and convective conditions, triggered intense thunderstorms and widespread flooding. This article examines the role of an atmospheric river (AR) in the April 2024 extreme precipitation event, emphasizing the contribution of extreme IVT to preconditioning and amplifying the heavy rainfall. While this event has previously been described primarily in terms of a mesoscale convective system (MCS) and potential vorticity (PV) streamers, here we document and illustrate its close relationship to a record-breaking moisture transport corridor. This AR-based perspective highlights how large-scale moisture-transport frameworks can complement synoptic and mesoscale analyses in understanding extreme rainfall in arid and semiarid regions such as the UAE and the Gulf. The event serves as a stark example of the vulnerabilities faced by arid regions, where atmospheric conditions conducive to extreme flooding may become more frequent in the future.

Massoud, Elias [ORNL] (ORCID:0000000217725361)↗

DOE OSTI2024

Agent-based simulations of shared automated vehicle operations: reflecting travel-party size, season and day-of-week demand variations

Here, this paper explores the effects of day of week and season of year demand variations for shared rides, along with realistic travel party sizes, on shared autonomous vehicle (SAV) services across the Austin, Texas region. Using the agent-based POLARIS program, synthetic person-trips that reflect travel-party size (from one to four persons) and demand variations over days and months, as evident in the National Household Travel Survey data were simulated in each scenario over a 24 h travel day. Results show that realistic party sizes can bring considerable changes to SAV fleet performance, including up to 8.5% higher service rates (number of requests accepted within 15 min), 5 min shorter journey times (wait time + travel time), 28% higher vehicle occupancies on weekends, and roughly 4% lower empty fleet VMT. Weekend travel is most impacted by season of year, with weekday travel patterns looking more uniform (thanks to work and school trips). Various performance metrics for the Austin network, like total and empty VMT, change by up to 30% when considering realistic variations in party size and time of year. This paper underscores the value of recognizing day-to-day and month-to-month variations in travel demand, and the importance of agent-based model equations to reflect travel-party size. Such realism can help quantify SAV seat occupancies more accurately, highlighting the importance of shared mobility. However, it also creates demand and supply issues for operators that now need more information on party size to manage dynamic ride-sharing, or those that may wish to shift their fleet vehicles to other regions for special events to protect profits while offering reasonable wait times to customers throughout the year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Assessing Simulations of Forest Hurricane Disturbance and Recovery in Puerto Rico by ELM-FATES Using Field Measurements

In the past three decades, Puerto Rico (PR) experienced five hurricanes that met or exceeded category three, and they caused severe forest structural damage and elevated tree mortality. To improve our mechanistic understanding of hurricane impacts on tropical forests and assess hurricane-affected forest dynamics in Earth system models, we use in situ forest measurements at the Bisley Experimental Watersheds in Northeast PR to evaluate the Functionally Assembled Terrestrial Ecosystem Simulator coupled with the Energy Exascale Earth System Model Land Model (ELM-FATES). The observations show that before Hurricane Hugo, 77.3% of the aboveground biomass (AGB) is from the shade-tolerant plant function type (PFT). The Hugo-induced mortality rates are over ~50%, and they induce a ~39% AGB reduction, which recovers to a level like the pre-Hugo condition in 2014, following a second, lower intensity hurricane, Georges. We perform numerical experiments that simulate damage from Hugo and Georges on the forests, including defoliation, sapwood and structural biomass damage, and hurricane-induced mortality. ELM-FATES can reasonably represent coexistence between the two PFTs–light-demanding and shade-tolerant–for both the pre-Hugo and post-Hugo conditions. The model represents a reasonable size distribution of mid-and large-sized trees although it underestimates AGB, likely due to the overestimated nonhurricane mortality. ELM-FATES temporarily stimulated leaf biomass and diameter increment after Georges, an effect that should be tested with observations of future hurricane defoliation events. This research indicates that addressing model-data mismatches in tree mortality and understory dynamics are essential to simulation of more extreme hurricane effects under climate change.

58 GEOSCIENCES↗

DOE OSTI2023

An interoperable implementation of collective‐variable based enhanced sampling methods in extended phase space within the OpenMM package

Collective variable (CV)-based enhanced sampling techniques are widely used today for accelerating barrier-crossing events in molecular simulations. A class of these methods, which includes temperature accelerated molecular dynamics (TAMD)/driven-adiabatic free energy dynamics (d-AFED), unified free energy dynamics (UFED), and temperature accelerated sliced sampling (TASS), uses an extended variable formalism to achieve quick exploration of conformational space. These techniques are powerful, as they enhance the sampling of a large number of CVs simultaneously compared to other techniques. Extended variables are kept at a much higher temperature than the physical temperature by ensuring adiabatic separation between the extended and physical subsystems and employing rigorous thermostatting. Here, in this work, we present a computational platform to perform extended phase space enhanced sampling simulations using the open-source molecular dynamics engine OpenMM. The implementation allows users to have interoperability of sampling techniques, as well as employ state-of-the-art thermostats and multiple time-stepping. This work also presents protocols for determining the critical parameters and procedures for reconstructing high-dimensional free energy surfaces. As a demonstration, we present simulation results on the high dimensional conformational landscapes of the alanine tripeptide in vacuo, tetra-N-methylglycine (tetra-sarcosine) peptoid in implicit solvent, and the Trp-cage mini protein in explicit water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗