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At least 181 records · Page 10

Collapse models for dark interstellar clouds

Properties of self-consistent numerical hydrodynamic models are compared with observed properties of several dark clouds. The results are consistent with the view that these clouds are undergoing gravitational collapse. The clouds appear to have evolved from similar initial states and to have ages comparable to their free-fall times. Derived cloud masses range between 10 and 1000 solar masses, correlating with cloud size. The models reproduce observed cloud-to-cloud variations in the (C-13)O abundance, and they offer additional evidence that the (C-13)O abundance varies within individual clouds.

Villere, K. R.↗

A hybrid CNN-LSTM surrogate model for hyper-resolution spatiotemporal flood forecasting in Norfolk, Virginia

Study region: Norfolk, Virginia, United States Study focus: Accurate and timely flood forecasting is essential for enhancing resilience in coastal urban areas in the context of increasing frequency and intensity of rainfall, sea level rise and urbanization. This study presents a hybrid deep learning-based surrogate model that integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to enable real-time spatiotemporal flood forecasting. The model leverages CNN to capture spatial features from inputs such as elevation and Topographic Wetness Index (TWI), while LSTM processes time-series inputs of rainfall and tide data to capture temporal features. New hydrologic insights for the region: The hybrid CNN-LSTM model was trained using the physics-based hydrodynamic model simulations obtained from the Two-dimensional Unsteady FLOW (TUFLOW) model for Norfolk, Virginia, and achieved high predictive accuracy across diverse flood-prone areas. The reduced computational time from four to six hours using TUFLOW to 3.2 min per event using CNN-LSTM enables rapid flood inundation mapping and early warning applications. The model effectively captured both spatial flood extents and their temporal evolution across different flooding scenarios, providing forecasts at a 2.5-m spatial resolution and 15-min temporal resolution and a one-hour-ahead prediction horizon. While challenges remain in terms of transferability to new regions and real-time data assimilation, this approach demonstrates strong potential for supporting operational flood risk management in coastal urban environments.

Coastal urban flooding↗

What is the source of observed annual variations in plasmaspheric density?

Plasmaspheric densities have been observed previously to be higher in December than in June, with the ratio varying between 1.5 and 3.0 and with larger variations at lower L shells. In order to search for the cause of the observed annual variations, we have modeled plasmaspheric density, using a time-dependent hydrodynamic model. On an L = 2 field line with geomagnetic longitude equal to 300 deg, the modeled plasmaspheric densities were a factor of 1.5 times higher in December than in June. The modeled December to June density ratio was found to increase slightly with L shell, in contrast to observations; this discrepancy may be due to the fact that outer plasmaspheric flux tubes are never completely full. In addition, for an L = 2 field line with geomagnetic longitude equal to 120 deg, the modeled plasmaspheric density was higher in June than in December by a factor of about 1.2. Various numerical tests were also performed in order to examine the sensitivity of plasmaspheric density to various parameters. In particular, a large vertical neutral wind was applied in order to raise the O(+) profile which had the effect of raising plasmaspheric density by a factor of 6. This in conjunction with a theoretical analysis suggests that plasmaspheric density levels are very sensitive to O(+) levels in the upper ionosphere. We conclude that annual variations in plasmaspheric density are due to similar variations in ionospheric O(+).

Guiter, S. M.↗

Plasmasphere Modeling with Ring Current Heating

Coulomb collisions between ring current ions and the thermal plasma in the plasmasphere will heat the plasmaspheric electrons and ions. During a storm such heating would lead to significant changes in the temperature and density of the thermal plasma. This was modeled using a time- dependent, one-stream hydrodynamic model for plasmaspheric flows, in which the model flux tube is connected to the ionosphere. The model simultaneously solves the coupled continuity, momentum, and energy equations of a two-ion (H(+) and O(+) quasineutral, currentless plasma. Heating rates due to collisions with ring current ions were calculated along the field line using a kinetic ring current model. First, diurnally reproducible results were found assuming only photoelectron heating of the thermal electrons. Then results were found with heating of the H(+) ions by the ring current during the recovery phase of a magnetic storm.

Guiter, S. M.↗

Development of an ab initio learned model of electron deposition range in deuterium-tritium plasmas through time-dependent density functional theory calculations and machine learning

Accurate hydrodynamic modeling for laser-direct-drive (LDD) inertial-confinement-fusion (ICF) relies on precise calculations of the electron thermal conduction in all target materials. The nonlocal stopping range of electrons in ICF plasmas directly influences thermal conduction; yet, no first principles model exists for the electron mean free path in the conduction-zone regime. This work utilized time-dependent stochastic density-functional theory (TD-sDFT) to calculate the electron stopping power in deuterium-tritium (DT) plasmas at (ρ, T) conditions relevant to the conduction zone and the compressed shell in ICF. Using a combination of our TD-sDFT data and already established analytical models, we developed and trained an artificial neural network to create a global model for the nonlocal electron deposition range, λ E . We compared our machine-learning (ML) based model for λ E to the currently-used modified-Lee-More model in LDD radiation-hydrodynamic codes, such as lilac, and saw an overall decrease in the deposition range. To understand the effects of λ E on LDD ICF implosion dynamics, we implemented the ML-based model into lilac; specifically, we looked at designs consistent with a current experiment on the OMEGA laser and for a newly designed LDD-ICF target for the future OMEGA-Next facility. In both cases, we saw an overall drop in predicted ablation pressure, peak areal density, and neutron yield due to the reduced thermal conduction (smaller λ E ) in DT plasmas. Comparisons with the experiment on OMEGA are also made.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A three-dimensional time-dependent model of the plasmasphere

A three-dimensional, time-dependent, nonlinear, hydrodynamic model of the plasmasphere has been developed which includes the self-consistent coupling of conjugate hemispheres within the plasmasphere as well as the effects of cross-L drifts due to convection electric fields. The inner region of the plasmasphere was modeled from an L of 1.5 to an L of 3.5 to 4.5, depending on local time. In this first study of the global plasmasphere, the model was run for solar minimum conditions until diurnally reproducible results were obtained, indicating that the plasmasphere was fully filled. The results of the model were then compared with applicable measurements of the plasmasphere. It was found that the model tends to overestimate densities somewhat, although it is within a factor of 2 of an average of June and December whistler observations. The model predicts densities within a factor of 2 of most of the satellite observations as well. As anticipated, the diurnal variation of the plasmasphere was found to depend on magnetic latitude. At low latitudes the diurnal variation in density was relatively small, with the largest densities occurring in the afternoon time sector. However, near the plasmapause, the effects of changes in volume of drifting tubes of plasma due to cross-L drifts led to a factor of 3 variation in equatorial density, with the highest densities occurring near local midnight where the volume was lowest. Various limitations of the current model and suggested improvements are also discussed.

Rasmussen, C. E.↗

Numerical modeling of the interstellar medium in galactic disks

We have been developing detailed hydrodynamic models of the global interstellar medium in the hope of understanding the mass and volume occupied by various phases, as well as their structure and kinematics. In our model, the gas is modeled by one fluid while representative Pop 1 stars are modeled by a second fluid. The two fluids are coupled in that the gas forms into stars at a rate given by a Schmidt law while stellar mass loss returns matter into the gas phase (on a time scale of 100 Myr). Also, the stars heat the gas through stellar winds and the gas cools through optically thin radiation. The time behavior of these two fluids is studied in two spatial dimensions with the Eulerian finite difference numerical hydrodynamic code Zen. The two spatial dimensions are along the plane of a disk (x, total length of 2 kpc) and perpendicular to the disk (z, total height of +/- 15 kpc) and a galactic gravitational field in the z direction, typical of that at the solar circle, is imposed upon the simulation; self-gravity and rotation are absent. For the boundary conditions, outflow is permitted at the top and bottom of the grid (z = +/- 15 kpc) while periodic boundary conditions are imposed upon left and right sides of the grid. As initial conditions, we assumed a gaseous distribution like that seen for the H1 by earlier researchers, although the results are insensitive to the initial conditions. We have run simulations in which the heating due to stars, parameterized as a stellar wind velocity, a, is varied from low (a = 150 km/s), to intermediate (a = 300 km/s), to high (a = 600 km/s). Since the intermediate case is roughly equivalent to the Galactic energy injection rate from supernovae, this summary will concentrate on results from this simulation.

Rosen, A.↗

Life Cycle Cost Analysis of Prestressed Concrete Poles Subjected to Wind, Surges, and Waves

Prestressed concrete (PC) poles are becoming popular choices to support coastal power transmission systems. However, the existing literature does not offer a detailed analysis of the effectiveness of PC poles in terms of long-term vulnerabilities and the direct and indirect costs. This is due to (1) lack of fragility models for PC poles and (2) lack of probabilistic wind, storm surge, and wave models in coastal settings. In this study, we address these gaps through a series of Monte Carlo simulations to estimate fragility of PC poles as a function of age and hazard (wind, surges, and waves) intensity, and the development of a probabilistic hazard model based on 10,000 years of synthetic tropical cyclone data. The probabilistic hazard model is used in conjunction with high-resolution hydrodynamic models to generate realizations of coastal wind, storm surges, and waves for the Louisiana and Mississippi coasts. A comprehensive life cycle cost analysis for a service life of 70 years considering direct and indirect losses is conducted to compare the performance of a transmission line located in Pascagoula, Mississippi, when wood poles are replaced by PC poles. Results showed that aging has a minor effect on the reliability of PC poles, highlighting the advantages of replacing wood poles with PC poles, especially in coastal areas. In addition, PC poles are significantly more cost-effective compared with wood poles over their life cycle, leading to an estimated saving of $11.55 million (68.17% reduction). The results of this study provide key insight to inform decision-making processes to keep the coastal power grids resilient and cost-effective against future storm hazards.

natural disasters↗

Ponderosa pine hydraulic stress predicts more extreme wildfire behavior under future conditions in Bandelier National Monument, New Mexico

Background Live fuel moisture contributes to wildfire spread and reflects plant stress and physiological traits. The anticipated change in live fuel moisture under future conditions is likely non-linear, owing to physiological plant thresholds in water hydraulics. We constructed a mechanistic model of live fuel moisture’s response to water stress to understand the impact of future climate on live fuel moisture. We first gathered data on plant physiology and live fuel moisture for Pinus ponderosa at Bandelier National Monument, NM, USA, and modeled their relationship. We then parameterized a mechanistic plant hydrodynamics model (FATES-HYDRO) to simulate changes in plant stress and a statistical model to simulate the resulting impact on live fuel moisture. We then simulated FATES-HYDRO under future climate anomalies (SSP2-4.5 and SSP5-8.5: 2080–2100) to understand the change in plant stress and estimate its impact on live fuel moisture. Results We found that the number of days below crucial thresholds of live fuel moisture (100% and 79%) increased from contemporary levels (< 100%: 72 days, < 79%: 1.4 days) under SSP2-4.5 (< 100%: 185 days, < 79%: 10.2 day) and increased exponentially under SSP5-8.5 (< 100%: 215 days, < 79%: 65 days). We found that gross primary productivity decreased under both future climate scenarios (contemporary: 336 g C m −2 , SSP2-4.5: 203 g C m −2 , SSP5-8.5: 243 g C m −2 ); however, spring productivity increased under SSP5-8.5, potentially altering fuel loading. We additionally see a potentially lethal loss of conductivity in hydraulic P. ponderosa under SSP5-8.5. Conclusions The overall increase in plant water stress (as represented by loss of hydraulic conductivity and leaf water potential) and lower live fuel moisture appear to be driven by reduced precipitation during late summer monsoons typical of the region, extending the fire season later in the year. We predict increasing variability in the P. ponderosa wildfire regime under both climate projections driven by changing productivity, rising mortality, and an overall decrease in live fuel moisture.

54 ENVIRONMENTAL SCIENCES↗

Kinetic modeling of O(+) upflows resulting from E x B convection heating in the high-latitude F region ionosphere

We report here the results of modeling work aimed at understanding the development of ionospheric O(+) field-aligned upflows that develop in response to high-latitude E x B drift induced frictional heating. The model used is a collisional semikinetic model which includes ion-neutral resonant charge exchange and polarization collisions as well as Coulomb self-collisions. It also includes the process of chemical removal of O(+) as well as all of the macroscopic forces: ambipolar electric, gravity, magnetic mirror, and centripetal. Model results show the development of several types of non-Maxwellian velocity distributions including toroids at low altitude, distributions with large heat flow in the perpendicular component at intermediate altitudes, and distributions with a separate upflowing population or upward superthermal tail at high altitudes. Whenever the convection electric field increases from a small value (less than 25 mV/m) to a large value (100-200 mV/m) in 6 min or less large upflows develop with parallel drift speeds which peak (below 1000 km) at values between 500 m/s and 2 km/s, parallel fluxes which peak between 6.0 x 10(exp 8) and 3.2 x 10(exp 9)/sq cm/s, and parallel per particle heat flows which peak between 8.0 x 10(exp -9) and 8.0 x 10(exp -8) ergs cm/s. The higher values in these ranges occur for a cooler neutral atmosphere, with a larger convection electric field that is turned on quickly. The model produces field-aligned O(+) flow speeds that are larger than those produced by a 20-moment generalized transport model but smaller then those produced by an isotropic hydrodynamic model for comparable values of the convection turn on times. The model results compare favorably with some topside satellite and radar data.

Wilson, G. R.↗

HYDRODYNAMIC ANALYSIS OF MACROALGAE LOCAL MODEL USING COMPUTATIONAL FLUID DYNAMICS

In this article, a local scale, fully nonlinear coupled fluid-structural interaction (FSI) sugar kelp model has been developed using a computational fluid dynamics (CFD) method. In this model, to be consistent with available experimental data, the sugar kelp is approximated as elongated rectangles with smoothed isosceles triangles at the ends and a single kelp model with one end fixed in a channel with constant current model is developed. Several different current speeds are simulated, and the resulting drag forces and calculated drag coefficients are validated by comparison with experimental data from the literature. In a previous study, a global scale model was developed using a computational structural dynamics (CSD) method to simulate macroalgae farming system and guide the system configuration design. In the global scale model, the hydrodynamic forces are calculated using Morison’s equation and the kinematics and dynamics of the sugar kelp are simplified and the group of kelps attached to the long line is modeled as a slender structure with the same length and an effective diameter such that the volumes are consistent with the real physical system. This simplified model matches the weight and buoyancy but adjusting the hydrodynamic properties when the general hydrodynamic coefficients are employed. Therefore, optimal hydrodynamic coefficients used in global scale model were determined to obtain the hydrodynamic force more accurately. The validated local scale model is then be applied to determine the hydrodynamic coefficients of the simplified sugar kelp model for global dynamic analysis.

hydrodynamic modeling, macroalgae, CFD model↗

Bayesian calibration of viscous anisotropic hydrodynamic simulations of heavy-ion collisions

Owing to large pressure gradients at early times, standard hydrodynamic model simulations of relativistic heavy-ion collisions do not become reliable until O(1) fm/c after the collision. To address this one often introduces a prehydrodynamic stage that models the early evolution microscopically, typically as a conformal, weakly interacting gas. In such an approach the transition from the prehydrodynamic to the hydrodynamic stage is discontinuous, introducing considerable theoretical model ambiguity. Alternatively, fluids with large anisotropic pressure gradients can be handled macroscopically using the recently developed viscous anisotropic hydrodynamics (VAH). In high-energy heavy-ion collisions VAH is applicable already at very early times, and at later times transitions smoothly into conventional second-order viscous hydrodynamics. Here we present a Bayesian calibration of the VAH model with experimental data for Pb-Pb collisions at the LHC at $\sqrt{^{S}NN}$ = 2.76 A TeV. We find that the VAH model has the unique capability of constraining the specific viscosities of the quark-gluon plasma at higher temperatures than other previously used models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Model structure of a cosmic-ray mediated stellar or solar wind

An idealized hydrodynamic model is presented for the mediation of a free-streaming stellar wind by galactic cosmic rays or energetic particles accelerated at the stellar wind termination shock. The spherically-symmetric stellar wind is taken to be cold; the only body force is the cosmic ray pressure gradient. The cosmic rays are treated as a massless fluid with an effective mean diffusion coefficient k proportional to radial distance r. The structure of the governing equations is investigated both analytically and numerically. Solutions for a range of values of k are presented which describe the deceleration of the stellar wind and a transition to nearly incompressible flow and constant cosmic ray pressure at large r. In the limit of small k the transition steepens to a strong stellar wind termination shock. For large k the stellar wind is decelerated gradually with no shock transition. It is argued that the solutions provide a simple model for the mediation of the solar wind by interstellar ions as both pickup ions and the cosmic ray anomalous component which together dominate the pressure of the solar wind at large r.

Lee, M. A.↗

Reduced order models for Lagrangian hydrodynamics

It is reported, as a mathematical model of high-speed flow and shock wave propagation in a complex multimaterial setting, Lagrangian hydrodynamics is characterized by moving meshes, advection-dominated solutions, and moving shock fronts with sharp gradients. These challenges hinder the existing projection-based model reduction schemes from being practical. We develop several variations of projection-based reduced order model techniques for Lagrangian hydrodynamics by introducing three different reduced bases for position, velocity, and energy fields. A time-windowing approach is also developed to address the challenge imposed by the advection-dominated solutions. Lagrangian hydrodynamics is formulated as a nonlinear problem, which requires a proper hyper-reduction technique. Therefore, we apply the over-sampling DEIM and SNS approaches to reduce the complexity due to the nonlinear terms. Finally, we also present both a posteriori and a priori error bounds associated with our reduced order model. We compare the performance of the spatial and time-windowing reduced order modeling approaches in terms of accuracy and speed-up with respect to the corresponding full order model for several numerical examples, namely Sedov blast, Gresho vortices, Taylor-Green vortices, and triple-point problems.

97 MATHEMATICS AND COMPUTING↗

HydroChrono: An Open-Source Hydrodynamics Package for Project Chrono

In this paper we present the development and verification of HydroChrono, a hydrodynamics package for the Project Chrono physics engine. This package includes the implementation of hydrodynamics equations, the added mass for multibody systems, the development of I/O functions as well as a Python API, and comparison against standard reference cases and other existing tools. HydroChrono provides a flexible, fully open-source solution for simulating wave energy converters (WECs), floating offshore wind turbines (FOWTs) platforms, and other hydrodynamic systems. Here we show, via comparisons with existing tools for benchmark verification cases, that HydroChrono accurately models hydrodynamic forces - making it a useful tool for the design and optimization of these systems. Additionally, the integration of HydroChrono with Project Chrono offers access to finite element modeling capabilities and high-fidelity modelling - with Chrono's existing coupling to CFD and SPH codes. This provides numerical modelers with a multifidelity simulation framework for designing and validating these systems. The development of HydroChrono provides a new, open-source solution for simulating hydrodynamic systems. Its compatibility with other simulation tools enables a more streamlined and efficient design process, advancing the field and providing new opportunities for innovation in this area.

BEM↗

Estuarine Dissolved Organic Carbon Flux from Space: With Application to Chesapeake and Delaware Bays

This study uses a neural network model trained with in situ data, combined with satellite data and hydrodynamic model products, to compute the daily estuarine export of dissolved organic carbon (DOC) at the mouths of Chesapeake Bay (CB) and Delaware Bay (DB) from 2007 to 2011. Both bays show large flux variability with highest fluxes in spring and lowest in fall as well as interannual flux variability (0.18 and 0.27 Tg C/year in 2008 and 2010 for CB; 0.04 and 0.09 Tg C/year in 2008 and 2011 for DB). Based on previous estimates of total organic carbon (TOCexp) exported by all Mid-Atlantic Bight estuaries (1.2 Tg C/year), the DOC export (CB + DB) of 0.3 Tg C/year estimated here corresponds to 25% of the TOCexp. Spatial and temporal covariations of velocity and DOC concentration provide contributions to the flux, with larger spatial influence. Differences in the discharge of fresh water into the bays (74 billion m(exp3)/year for CB and 21 billion m9exp3)/year for DB) and their geomorphologies are major drivers of the differences in DOC fluxes for these two systems. Terrestrial DOC inputs are similar to the export of DOC at the bay mouths at annual and longer time scales but diverge significantly at shorter time scales (days to months). Future efforts will expand to the Mid-Atlantic Bight and Gulf of Maine, and its major rivers and estuaries, in combination with coupled terrestrial-estuarine-ocean biogeochemical models that include effects of climate change, such as warming and CO2 increase.

Signorini, Sergio↗

Estuarine Dissolved Organic Carbon Flux From Space: With Application to Chesapeake and Delaware Bays

This study uses a neural network model trained with in situ data, combined with satellite data and hydrodynamic model products, to compute the daily estuarine export of dissolved organic carbon (DOC) at the mouths of Chesapeake Bay (CB) and Delaware Bay (DB) from 2007 to 2011. Both bays show large flux variability with highest fluxes in spring and lowest in fall as well as interannual flux variability (0.18 and 0.27 Tg C/year in 2008 and 2010 for CB; 0.04 and 0.09 Tg C/year in 2008 and 2011 for DB). Based on previous estimates of total organic carbon (TOCexp) exported by all Mid-Atlantic Bight estuaries (1.2 Tg C/year), the DOC export (CB + DB) of 0.3 Tg C/year estimated here corresponds to 25% of the TOCexp. Spatial and temporal covariations of velocity and DOC concentration provide contributions to the flux, with larger spatial influence. Differences in the discharge of fresh water into the bays (74 billion cu. m/year for CB and 21 billion cu. m/year for DB) and their geomorphologies are major drivers of the differences in DOC fluxes for these two systems. Terrestrial DOC inputs are similar to the export of DOC at the bay mouths at annual and longer time scales but diverge significantly at shorter time scales (days to months). Future efforts will expand to the Mid-Atlantic Bight and Gulf of Maine, and its major rivers and estuaries, in combination with coupled terrestrial-estuarine-ocean biogeochemical models that include effects of climate change, such as warming and CO2 increase.

Estuarine DOC export↗