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At least 811 records · Page 45

Historical (1700–2012) Global Multi-Model Estimates of the Fire Emissions from the Fire Modeling Intercomparison Project (FireMIP)

Fire emissions are critical for carbon and nutrient cycles, climate, and air quality. Dynamic Global Vegetation Models (DGVMs) with interactive fire modeling provide important estimates for long-term and large-scale changes of fire emissions. Here we present the first multi-model estimates of global gridded historical fire emissions for 1700-2012, including carbon and 33 species of trace gases and aerosols. The dataset is based on simulations of nine DGVMs with different state-of-the-art global fire models that participated in the Fire Modeling Intercomparison Project (FireMIP), using the same and standardized protocols and forcing data, and the most up-to-date fire emission factor table from field and laboratory studies over various land cover types. We evaluate the simulations of present-day fire emissions by comparing them with satellite-based products. Evaluation results show that most DGVMs simulate present-day global fire emission totals within the range of satellite-based products, and can capture the high emissions over the tropical savannas, low emissions over the arid and sparsely vegetated regions, and the main features of seasonality. However, most of the models fail to simulate the interannual variability, partly due to a lack of modeling peat fires and tropical deforestation fires. Historically, all models show only a weak trend in global fire emissions before ~1850s, consistent with multi-source merged historical reconstructions. The long-term trends among DGVMs are quite different for the 20th century, with some models showing an increase and others a decrease in fire emissions, mainly as a result of the discrepancy in their simulated responses to human population density change and land-use and land-cover change (LULCC). Our study provides a basic dataset for developing regional and global multi-source merged historical reconstructions and merging methods, and analyzing historical changes of fire emissions and their uncertainties as well as their role in the Earth system. It also highlights the importance of accurately modeling the responses of fire emissions to LULCC and population density change in reducing uncertainties in historical reconstructions of fire emissions and providing more reliable future projections.

Li, Fang↗

Gravity Modeling Effects on Surface-Interacting Vehicles in Supersonic Flight

A vehicle simulation is "surface-interacting" if the state of the vehicle (position, velocity, and acceleration) relative to the surface is important. Surface-interacting simulations per-form ascent, entry, descent, landing, surface travel, or atmospheric flight. The dynamics of surface-interacting simulations are influenced by the modeling of gravity. Gravity is the sum of gravitation and the centrifugal acceleration due to the world s rotation. Both components are functions of position relative to the world s center and that position for a given set of geodetic coordinates (latitude, longitude, and altitude) depends on the world model (world shape and dynamics). Thus, gravity fidelity depends on the fidelities of the gravitation model and the world model and on the interaction of these two models. A surface-interacting simulation cannot treat gravitation separately from the world model. This paper examines the actual performance of different pairs of world and gravitation models (or direct gravity models) on the travel of a supersonic aircraft in level flight under various start-ing conditions.

Madden, Michael M.↗

INFUSION: Modeling Robot and Crew Interaction

Brahms is a multi-agent modeling and simulation language and distributed runtime system developed at NASA. It can be used to model and run a simualtion of the distributed work activities of multiple agents, such as humans,robots, and software agents, to coordinate a mission on one or more locations.Brahms is being used to model activities at the Flashline Man Arctic Research Station for possible use in planning Mars missions. The station is located at Haughton Crater, Devon Island, Nutiavut, Arctic Canada.

Laufenberg, Lawrence↗

Process Modeling of Aerosol‐Cloud Interaction in Summertime Precipitating Shallow Cumulus Over the Western North Atlantic

Abstract Process modeling of Aerosol‐cloud interaction (ACI) is essential to bridging gaps between observational analysis and climate modeling of aerosol effects in the Earth system and eventually reducing climate projection uncertainties. In this study, we examine ACI in summertime precipitating shallow cumuli observed during the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). Aerosols and precipitating shallow cumuli were extensively observed with in‐situ and remote‐sensing instruments during two research flight cases on 02 June and 07 June, respectively, during the ACTIVATE summer 2021 deployment phase. We perform observational analysis and large‐eddy simulation (LES) of aerosol effect on precipitating cumulus in these two cases. Given the measured aerosol size distributions and meteorological conditions, LES is able to reproduce the observed cloud properties by aircraft such as liquid water content (LWC), cloud droplet number concentration ( N c ) and effective radius r eff . However, it produces smaller liquid water path (LWP) and larger N c compared to the satellite retrievals. Both 02 and 07 June cases are over warm waters of the Gulf Stream and have a cloud top height over 3 km, but the 07 June case is more polluted and has larger LWC. We find that the N a ‐induced LWP adjustment is dominated by precipitation feedback for the 2 June precipitating case and there is no clear entrainment feedback in both cases. An increase of cloud fraction due to a decrease of aerosol number concentration is also shown in the simulations for the 02 June case.

54 ENVIRONMENTAL SCIENCES↗

A Model Intercomparison Study of Aerosol‐Cloud‐Turbulence Interactions in a Cloud Chamber: 1. Model Results

This study presents the first model intercomparison of aerosol‐cloud‐turbulence interactions in a controlled cloudy Rayleigh‐Bénard Convection chamber environment, utilizing the Pi Chamber at Michigan Technological University. We analyzed simulated cloud chamber‐averaged statistics of microphysics and thermodynamics in a warm‐phase, cloudy environment under steady‐state conditions at varying aerosol injection rates. Simulation results from seven distinct models (DNS, LES, and a 1D turbulence model) were compared. Our findings demonstrate that while all models qualitatively capture observed trends in droplet number concentration, mean radius, and droplet size distributions at both high and low aerosol injection rates, significant quantitative differences were observed. Notably, droplet number concentrations varied by over two orders of magnitude between models for the same injection rates, indicating sensitivities to the model treatments in droplet activation and removal and wall fluxes. Furthermore, inconsistencies in vertical relative humidity profiles and in achieving steady‐state liquid water content suggest the need for further investigation into the mechanisms driving these variations. Despite these discrepancies, the models generally reproduced consistent power‐law relationships between the microphysical variables. This model intercomparison underscores the importance of controlled cloud chamber experiments for validating and improving cloud microphysical parameterizations. Recommendations for future modeling studies are also highlighted, including constraining wall conditions and processes, investigating droplet/aerosol removal (including sidewall losses), and conducting simplified experiments to isolate specific processes contributing to model divergence and reduce model uncertainties.

54 ENVIRONMENTAL SCIENCES↗

Compressible pairwise interaction extended point-particle model for force prediction of shock-particle bed interaction

We propose a pairwise influence framework for the complex unsteady compressible particle-laden flow problem by accounting for the scattered hydrodynamic waves emitting from neighboring particles in a Euler-Lagrange simulation. It has been observed from particle-resolved (PR) simulations of randomly dispersed particle beds under a loading shock that the compressible pseudoturbulence dominates the flow system even after the primary shock has passed, which causes fluctuations observed in the forces experienced by the particle. Moreover, the fact that each particle exists in the vicinity of a random arrangement of other particles modifies the time history of the drag force experienced by each particle during and after the passage of the shock. First, the scattering flow field due to an incoming shock interacting with a single sphere is constructed using an analysis of the flow in the acoustic limit. Then we examine the validity of the compressible Maxey-Riley-Gatignol force model by comparing the force prediction against a PR simulation of two interacting particles for various particle arrangements and incoming shock strength. Subsequently, the neighboring influences are stored as a library of maps that can be used readily in the calculation of the perturbation force. Lastly, the pairwise interaction assumption is evaluated by comparing the force predicted with the model with PR simulations of a randomly packed particle bed of 10% volume fraction for both water and air as the fluid medium for an incoming shock Mach number 1.22. With a considerably lower cost for the implementation of the model compared to PR simulations, it is verified that the model is reasonably accurate in pinpointing particles whose peak force is significantly larger or smaller than the mean drag but also to capture the prolonged fluctuations after the initial shock.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Integrative teaching of metabolic modeling and flux analysis with interactive python modules

Abstract The modeling of rates of biochemical reactions—fluxes—in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint‐based (Metabolic Flux Analysis and flux balance analysis) approaches. Although different resources exist for teaching these methods individually, to‐date no resources have been developed to teach these approaches in an integrative way that equips learners with an understanding of each modeling paradigm, how they relate to one another, and the information that can be gleaned from each. We have developed a series of modeling simulations in Python to teach kinetic modeling, metabolic control analysis, 13C‐metabolic flux analysis, and flux balance analysis. These simulations are presented in a series of interactive notebooks with guided lesson plans and associated lecture notes. Learners assimilate key principles using models of simple metabolic networks by running simulations, generating and using data, and making and validating predictions about the effects of modifying model parameters. We used these simulations as the hands‐on computer laboratory component of a four‐day metabolic modeling workshop and participant survey results showed improvements in learners' self‐assessed competence and confidence in understanding and applying metabolic modeling techniques after having attended the workshop. The resources provided can be incorporated in their entirety or individually into courses and workshops on bioengineering and metabolic modeling at the undergraduate, graduate, or postgraduate level.

Kaste, Joshua A. M.↗

The simulation of complete 11 and 12 year modulation cycles for cosmic rays in the heliosphere using a drift model with global merged interaction regions

Two-dimensional, time-dependent drift models have done exceptionally well in explaining major modulation features, especially during the A less than 0 magnetic polarity cycle of the heliospheric magnetic field when positively charge particles are drifting in along the heliospheric neutral sheet (HNS). These models were found to do well when the heliospheric 'tilt angles' alpha less than approximately 30 deg (le Roux & Potgeiter). However, they seem to do less well when alpha greater than approximately 30 deg during A less than 0 cycles seem to fail when this happens in A greater than 0 cycles. Progress was made in understanding these phases of the modulation cycle when merged interaction regions (MIRs) were incorporated in time-dependent drift models (Potgieter et al.). It was also explicitly shown that in obtaining large step decreases in cosmic rays, the MIRs had to be global, i.e., having a latitudinal extent of more than approximately 60 deg. Other classes of MIRs, such as local MIRs and co-rotating MIRs were found to be of secondary importance for establishing long-term modulation. In a previous paper we studied the effects of two consecutive, identical global MIRs, together with a changing wavy HNS, on long-term modulation (Potegieter & le Roux). This approach gave a very natural and convincing explanation for the observed step decreases in cosmic-ray modulation. Emphasis was placed in the declining and recovery phases of the 11 yr modulation cycle. In this paper, four consecutive, nonidentical global MIRs, in combination with a varying wavy HNS, were included in our time-dependent drift model in order to do simulations closer to what was observed between 1977 and 1987. By doing this we could model, for the first time, complete 11 and 22 yr cycles in the heliospheric modulation of galactic cosmic-rays, including the solar magnetic polarity reversals.

Le Roux, J. A.↗

Modeling radiative-shocks created by laser–cluster interactions

Radiative-shocks induced by laser–cluster interactions are modeled using radiation-hydrodynamic simulations. A good agreement—in both shock velocity and density profiles—is obtained between experiment and simulations, indicating that non-local thermodynamic equilibrium (NLTE) radiative effects are important in the experimental regime examined, particularly at early times (≤30 ns) due to the elevated temperatures (≥35 eV). The enhanced NLTE radiative emission causes the shock to be reduced in amplitude, increased in width, and reduced in propagation velocity, while the amplitude of the radiative precursor is increased. As the density and temperature conditions are relatively modest, this potentially has important implications for the scalings that are used in laboratory–astrophysics to transform between laboratory and astrophysical scales, which do not hold for non-LTE systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Experience with turbulence interaction and turbulence-chemistry models at Fluent Inc.

This viewgraph presentation discusses (1) turbulence modeling: challenges in turbulence modeling, desirable attributes of turbulence models, turbulence models in FLUENT, and examples using FLUENT; and (2) combustion modeling: turbulence-chemistry interaction and FLUENT equilibrium model. As of now, three turbulence models are provided: the conventional k-epsilon model, the renormalization group model, and the Reynolds-stress model. The renormalization group k-epsilon model has broadened the range of applicability of two-equation turbulence models. The Reynolds-stress model has proved useful for strongly anisotropic flows such as those encountered in cyclones, swirlers, and combustors. Issues remain, such as near-wall closure, with all classes of models.

Choudhury, D.↗

Event Generators for Simulating Heavy Ion Interactions of Interest in Evaluating Risks in Human Spaceflight

Simulating the Space Radiation environment with Monte Carlo Codes, such as FLUKA, requires the ability to model the interactions of heavy ions as they penetrate spacecraft and crew member's bodies. Monte-Carlo-type transport codes use total interaction cross sections to determine probabilistically when a particular type of interaction has occurred. Then, at that point, a distinct event generator is employed to determine separately the results of that interaction. The space radiation environment contains a full spectrum of radiation types, including relativistic nuclei, which are the most important component for the evaluation of crew doses. Interactions between incident protons with target nuclei in the spacecraft materials and crew member's bodies are well understood. However, the situation is substantially less comfortable for incident heavier nuclei (heavy ions). We have been engaged in developing several related heavy ion interaction models based on a Quantum Molecular Dynamics-type approach for energies up through about 5 GeV per nucleon (GeV/A) as part of a NASA Consortium that includes a parallel program of cross section measurements to guide and verify this code development.

Wilson, Thomas L.↗