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At least 433 records · Page 24

Flight Mechanics Modeling and Simulation of the Earth Entry System

Introduction: The Mars Sample Return (MSR) Campaign being planned by NASA and ESA has the ambitious goal to return Mars samples back to Earth. This international collaboration had developed a concept of operations that included a ESA-designed Earth Return Orbiter (ERO) and NASA-designed Capture, Containment, and Return System (CCRS). The Earth Entry System (EES), consisting of a protective aeroshell that houses the samples as well as sample containment vessels, would conduct entry, descent, and landing (EDL) on a direct Earth trajectory. The EES would enter on a spin-stabilized ballistic trajectory with the goal to passively achieve aerodynamic stability throughout all regions of flight. The EDL sequence would end with the EES impacting the soft playa soil of the Utah Test and Training Range (UTTR). As of the submission of this abstract, the MSR campaign is undergoing a re-architecture leading to a pause in EES development. However, the novel approaches developed in flight mechanics modeling and simulation can significantly benefit the greater IPPW community in the development of Earth return vehicles. This paper will present the latest state of EES flight mechanics modeling and simulation. The paper will highlight the simulation architecture developed and key lessons learned from understanding of EDL trajectory sensitivities. Modeling and Simulation: Figure 1 provides a high-level concept of operations for the approach, entry, descent, and landing (AEDL) phase of the CCRS-portion of MSR. The objective of EES flight mechanics is to model and simulate the EES trajectory from ERO separation to ground impact at UTTR. A variety of flight mechanics simulation models were utilized to model both exo-atmopsheric and atmospheric portions of flight. 42, a 6-DOF simulation developed at Goddard Space Flight Center, is utilized for propagating the attitude of EES during exo-atmospheric flight. 42 allows for a variety of spin eject mechanism scenarios to be simulated for analysis. 10 minutes prior to entry, the 42 states are handed off to the EDL sims. The prime EDL sim utilized by EES is the Program to Optimize Simulated Trajectories II (POST2), a 6-DOF sim developed at Langley Research Center, and the independent verification and validation EDL sim utilized is DSENDS, a 6-DOF sim developed at Jet Propulsion Laboratory. Figure 2 provides a visualization of the flight mechanics simulation model flow through various points in the AEDL phase. Due to the existence of a variety of sim models, the EES flight mechanics team developed processes for data hand-off. These processes included the development of a centralized coordinate frame document, utilization of a single, centralized simulation input document for all sims to reference, and hand-off files containing both the technical data to be ingested by other flight mechanics sims as well as annotations of modeling assumptions utilized to generate the data. Figure~\ref{fig:post2simarchitecture} provides an overview of the POST2 sim architecture wherein POST2 ingests numerous subsystem models and input files. The dispersed state file generated by MONTE provides the position/velocity state of the trajectory while the 42 Handoff file provides the attitude. The aerodynamics database, delivered by the EES aeroscience team, is utilized to simulate the aerodynamic forces and moments experienced during EDL. A custom atmosphere model, developed by EES atmosphere team, is utilized to simulate the anticipated atmosphere environment around the region of Earth through which the EES trajectory flys. These inputs and subsystem models can be varied depending on the AEDL flight mechanics scenario being simulated. Monte Carlo simulations are utilized to generate statistical AEDL performance metrics in the form of scorecards and violin plots. Furthermore, outputs from the POST2 simulation are utilized for follow-on analyses including aerothermal and landing performance. \section{Flight Mechanics Lessons Learned} Though the EES flight mechanics team uncovered a variety of lessons learned through the analysis conducted to support CCRS through preliminary design review, this paper will highlight the most important lessons. A key AEDL performance goal is to ensure the landing footprint of EES remains on the UTTR south range. A common modeling strategy used in EDL analysis is One-Variable-At-a-Time (OVAT). OVAT analysis provides insight into the key drivers that affect AEDL performance metrics. Figure 3 shows the landing ellipses for single dispersion sources as compared to the baseline aggregate of all dispersions. The figure shows that atmosphere winds alone dominate the size of the footprint ellipse (note: EES does not use a parachute unlike previous Earth-return missions and is in wind-driven free fall for ~5min). The significance of the wind led the EES flight mechanics team to pursue the development of a Custom Atmosphere Model [4], in lieu of EarthGRAM [1], built on actual radiosonde wind measurements around the UTTR-region. This decision was driven by the realism in the generated footprint ellipses and lessons-learned from Stardust [5]. These findings will be invaluable for future Earth-return missions in providing an early understanding of the key drivers affecting footprint size and modeling considerations for which to account. Another lesson learned is tied to the AEDL performance goal of achieving passive stability throughout all regions of flight. It is well understood that blunt-body aeroshells are less stable as they transition from supersonic to subsonic. Eliminating a backshell does help improvestability; however, other phenomena such as roll-induced instability during terminal descent can still arise. The EES flight mechanics team developed stability metrics as tools to better understand the causes of and better predict the onset of dynamic instability. These tools were built upon analytical models developed by Jaffe [3] and Murphy [2]. The tools were shown to both be very accurate in correlation with actual unstable cases and useful in developing stability margin policies based on the vehicle design and simulation considerations (e.g. sphere-cone angle change, mass change, wind turbulence). These tools allowed for the current EES design to demonstrate the ability to achieve passive stability and can be an invaluable tool for consideration in the design of parachute-less Earth-return vehicles.

Rohan Deshmukh↗

Dynamic resource allocation drives growth under nitrogen starvation in eukaryotes

Cells can sense changes in their extracellular environment and subsequently adapt their biomass composition. Nutrient abundance defines the capability of the cell to produce biomass components. Under nutrient-limited conditions, resource allocation dramatically shifts to carbon-rich molecules. Here, we used dynamic biomass composition data to predict changes in growth and reaction flux distributions using the available genome-scale metabolic models of five eukaryotic organisms (three heterotrophs and two phototrophs). We identified temporal profiles of metabolic fluxes that indicate long-term trends in pathway and organelle function in response to nitrogen depletion. Surprisingly, our calculations of model sensitivity and biosynthetic cost showed that free energy of biomass metabolites is the main driver of biosynthetic cost and not molecular weight, thus explaining the high costs of arginine and histidine. We demonstrated how metabolic models can accurately predict the complexity of interwoven mechanisms in response to stress over the course of growth.

59 BASIC BIOLOGICAL SCIENCES↗

Understanding the compound flood risk along the coast of the contiguous United States

Abstract. Compound flooding is a type of flood event caused by multiple flood drivers. The associated risk has usually been assessed using statistics-based analyses or hydrodynamics-based numerical models. This study proposes a compound flood (CF) risk assessment (CFRA) framework for coastal regions in the contiguous United States (CONUS). In this framework, a large-scale river model is coupled with a global ocean reanalysis dataset to (a) evaluate the CF exposure related to the coastal backwater effects on river basins, and (b) generate spatially distributed data for analyzing the CF hazard using a bivariate statistical model of river discharge and storm surge. The two kinds of risk are also combined to achieve a holistic understanding of the continental-scale CF risk. The estimated CF risk shows remarkable inter- and intra-basin variabilities along the CONUS coast with more variabilities in the CF hazard over the US west and Gulf coastal basins. Different risk assessment methods present significantly different patterns in a few key regions such as the San Francisco Bay area, the lower Mississippi River, and Puget Sound. Our results highlight the need to weigh different CF risk measures and avoid using single statistics-based or hydrodynamics-based CFRAs. Uncertainty sources in these CFRAs include the use of gauge observations, which cannot account for the flow physics or resolve the spatial variability of risks, and underestimations of the flood extremes and the dependence of CF drivers in large-scale models, highlighting the importance of understanding the CF risks for developing a more robust CFRA.

54 ENVIRONMENTAL SCIENCES↗

Numerical model of solar dynamic radiator for parametric analysis

Growth power requirements for Space Station Freedom will be met through addition of 25 kW solar dynamic (SD) power modules. The SD module rejects waste heat from the power conversion cycle to space through a pumped-loop, multi-panel, deployable radiator. The baseline radiator configuration was defined during the Space Station conceptual design phase and is a function of the state point and heat rejection requirements of the power conversion unit. Requirements determined by the overall station design such as mass, system redundancy, micrometeoroid and space debris impact survivability, launch packaging, costs, and thermal and structural interaction with other station components have also been design drivers for the radiator configuration. Extensive thermal and power cycle modeling capabilities have been developed which are powerful tools in Station design and analysis, but which prove cumbersome and costly for simple component preliminary design studies. In order to aid in refining the SD radiator to the mature design stage, a simple and flexible numerical model was developed. The model simulates heat transfer and fluid flow performance of the radiator and calculates area mass and impact survivability for many combinations of flow tube and panel configurations, fluid and material properties, and environmental and cycle variations. A brief description and discussion of the numerical model, it's capabilities and limitations, and results of the parametric studies performed is presented.

Rhatigan, Jennifer L.↗

Bipolar planetary nebulae from outflow collimation by common envelope evolution

ABSTRACT The morphology of bipolar planetary nebulae (PNe) can be attributed to interactions between a fast wind from the central engine and the dense toroidal-shaped ejecta left over from common envelope (CE) evolution. Here we use the 3D hydrodynamic adaptive mesh refinement (AMR) code AstroBEAR to study the possibility that bipolar PN outflows can emerge collimated even from an uncollimated spherical wind in the aftermath of a CE event. The output of a single CE simulation via the smoothed particle hydrodynamics (SPH) code phantom serves as the initial conditions. Four cases of winds, all with high enough momenta to account for observed high momenta pre-PN outflows, are injected spherically from the region of the CE binary remnant into the ejecta. We compare cases with two different momenta and cases with no radiative cooling versus application of optically thin emission via a cooling curve to the outflow. Our simulations show that in all cases highly collimated bipolar outflows result from deflection of the spherical wind via the interaction with the CE ejecta. Significant asymmetries between the top and bottom lobes are seen in all cases. The asymmetry is strongest for the lower momentum case with radiative cooling. While real post-CE winds may be aspherical, our models show that collimation via ‘inertial confinement’ will be strong enough to create jet-like outflows even beginning with maximally uncollimated drivers. Our simulations reveal detailed shock structures in the shock-focused inertial confinement (SFIC) model and develop a lens-shaped inner shock that is a new feature of SFIC-driven bipolar lobes.

79 ASTRONOMY AND ASTROPHYSICS↗

The Atlantic Multidecadal Oscillation: Key Drivers and Climate Impacts (Final Technical Report)

The goal of this project was to investigate the Atlantic multidecadal variability (AMV) using a hierarchical modeling framework to advance our process-level understanding on the respective roles of, and the feedback between, the key drivers of the AMV, in particular the ocean circulation associated with the Atlantic meridional overturning circulation and stochastic atmospheric forcing, primarily due to the North Atlantic Oscillation. The focus was primarily on the AMV due to natural variability, but the investigation will be extended to the possible modulation on the main characteristics of AMV under external climate forcing. Furthermore, we examined the impact of the AMV, with a special emphasis on the possible augmentation of predictability the AMV may bring to the regional weather and climate of North America, Western Europe, and the Arctic. Under this goal, we have published 15 peer-reviewed journal papers, and presented our results in more than 30 conferences over the project duration.

58 GEOSCIENCES↗

Modeling Mycorrhizal Carbon Costs in Temperate Forests: The Impacts of Functional Diversity and Global Change Factors

Mycorrhizal fungi form symbiotic relationships with most plant species, facilitating nutrient acquisition while consuming a significant fraction of the plant's photosynthetic carbon (C), which we define as the mycorrhizal C cost. Drivers of the mycorrhizal C cost, which is crucial for predicting environmental impacts on plant productivity, remain under-explored and difficult to quantify. Ecosystem models that incorporate mycorrhizae can offer insights into mycorrhizal C cost dynamics, but their predictions have rarely been validated against empirical data. Here, in this study, we used the Myco-CORPSE model, which explicitly simulates mycorrhizal processes alongside soil carbon and nitrogen cycling, to investigate the drivers of mycorrhizal C cost in temperate forests. Applying this model to over 1,800 forest inventory plots across the eastern United States, we found that the simulations matched published data, showing higher C allocation to ectomycorrhizal (ECM) fungi (16.0% of net primary production (NPP)) compared to arbuscular mycorrhizal (AM) fungi (5.8% of NPP). Further analysis showed that mixed forests, co-dominated by both AM and ECM trees, allocated less C to mycorrhizal fungi compared to forests dominated by either AM or ECM fungi alone, due to complementary nutrient acquisition strategies. Elevated Nitrogen (N) deposition and higher temperatures reduce mycorrhizal C costs, favoring AM strategies. Conversely, elevated CO 2 (eCO 2 ) increased plant N demand and mycorrhizal C costs, favoring ECM strategies that access organic N sources. These findings underscore the critical role of mycorrhizal functional diversity in plant nutrient acquisition and C dynamics, providing new insights into how mycorrhizal symbioses respond to global change.

Shao, Siya [Dartmouth College, Hanover, NH (United↗

Weather and climate extremes in a changing Arctic

Weather and climate extremes are increasingly occurring in the Arctic. Here, in this Review, we evaluate historical and projected changes in rare Arctic extremes across the atmosphere, cryosphere and ocean and elucidate their driving mechanisms. Clear shifts occur in mean and extreme distributions after ~2000. For instance, pre-2000 to post-2000 observational probabilities of 1.5 standard deviation events increase by 20% for atmospheric heat waves, 76.7% for Atlantic layer warm events, 83.5% for Arctic sea ice loss and 62.9% for Greenland Ice Sheet melt extent — in many cases, low probability, rare extreme events in the early period become the norm in the latter period. These observed changes can be explained using a ‘pushing and triggering’ concept, representing interplay between external forcing and internal variability: long-term warming destabilizes the climate system and ‘pushes’ it to a new state, allowing subsequent variability associated with large-scale atmosphere–ocean–ice interactions and synoptic systems to ‘trigger’ extreme events over different timescales. Ongoing anthropogenic warming is expected to further increase the frequency and magnitude of extremes, such that simulated probabilities of 1.5 standard deviation events increase by 72.6% for atmospheric heat waves, 68.7% for Atlantic layer warm events and 93.3% for Greenland Ice Sheet melt rate between historic (1984–2014) and future (2069–2099) periods under a very high emission scenario. Future research should prioritize the development of physically based metrics, enhance high-resolution observation and modelling capabilities and improve understanding of multiscale Arctic climate drivers.

atmospheric dynamics↗

Reconstruction framework advancements to support streaming for the ePIC detector at the EIC

The ePIC collaboration adopted the JANA2 framework to manage its reconstruction algorithms. This framework has since evolved substantially in response to ePIC’s needs. There have been three main design drivers: integrating cleanly with the Podio-based data models and other layers of the key4hep stack, enabling external configuration of existing components, and supporting timeframe splitting for streaming readout. The result is a unified component model featuring a new declarative interface for specifying inputs, outputs, parameters, services, and resources. This interface enables the user to instantiate, configure, and wire components via an external file. One critical new addition to the component model is a hierarchical decomposition of data boundaries into levels such as Run, Timeframe, PhysicsEvent, and Subevent. Two new component abstractions, Folder and Unfolder, are introduced in order to traverse this hierarchy, e.g. by splitting or merging. The pre-existing components can now operate at different event levels, and JANA2 will automatically construct the corresponding parallel processing topology. This means that a user may write an algorithm once, and configure it at runtime to operate on timeframes or on physics events. Overall, these changes mean that the user requires less knowledge about the framework internals, obtains greater flexibility with configuration, and gains the ability to reuse the existing abstractions in new streaming contexts.

Brei, Nathan [Thomas Jefferson National Accelerato↗

Are there differences in public interest toward automated vehicles’ ownership in burdened and non-burdened communities?

This study examines differences in public interest toward automated vehicle (AV) adoption between burdened communities (BCs) and non-burdened communities (non-BCs). The study uniquely captures travel behavior by integrating the census tract-level community indicators with the 2017–2019 Puget Sound Household Travel Survey. Public interest in AV ownership is modeled as a five-level ordered outcome, ranging from ‘Not interested at all’ to ‘Very interested.’ Segmented ordered logit models and Random Forest are used to identify key drivers and barriers to AV adoption across BCs and non-BCs. Results show that longer commute times, lack of personal vehicles, and concerns about AV performance in adverse weather conditions are significantly associated with higher interest levels toward owning AVs in BCs. In conclusion, the findings offer insights for developing targeted policies to promote AV adoption and address differences between BCs and non-BCs in accessing emerging transportation technologies.

Automated vehicles↗

A Stochastic Charging Station Deployment Model for Electrified Taxi Fleets in Coupled Urban Transportation and Power Distribution Networks

Metropolitansworldwide are increasingly adopting electric taxis (ET) to address concerns about transportation-related emissions. However, the widespread deployment of electric taxis presents challenges in terms of increased electricity demand and changing demand profiles. This transition impacts both the urban transportation network (TN) and the electricity power distribution network (PDN), highlighting the interdependence between these two systems. Here, in this paper, we propose a two-stage stochastic programming planning model that aims to optimize both the TN and PDN, enabling efficient deployment of charging stations and grid upgrades. Our model seeks to strike a balance between meeting ET drivers' charging preferences, minimizing the costs associated with infrastructure deployment and grid expansion, and harmonizing the coordination between the TN and PDN. Additionally, we explore the potential benefits of utilizing an autonomous ET fleet to enhance overall system performance.

33 ADVANCED PROPULSION SYSTEMS↗

A molecular conveyor belt-associated protein controls the rotational direction of the bacterial type 9 secretion system

ABSTRACT Many bacteria utilize the type 9 secretion system (T9SS) for gliding motility, surface colonization, and pathogenesis. This dual-function motor supports both gliding motility and protein secretion, where rotation of the T9SS plays a central role. Fueled by the energy of the stored proton motive force and transmitted through the torque of membrane-anchored stator units, the rotary T9SS propels an adhesin-coated conveyor belt along the bacterial outer membrane like a molecular snowmobile, thereby enabling gliding motion. However, the mechanisms controlling the rotational direction and gliding motility of T9SS remain elusive. Shedding light on this mechanism, we find that in the gliding bacteriumFlavobacterium johnsoniae, deletion of the C-terminus of the conveyor belt-associated protein GldJ controls and, in fact, reverses the rotational direction of T9SS from counterclockwise (CCW) to clockwise (CW). This suggests that the interface between the conveyor belt-associated protein GldJ and the T9SS ring protein GldK plays an important role in controlling the directionality of T9SS, potentially by modulating its interaction with the stator complex GldLM, which drives motor rotation. Combined with MD simulation of the T9SS stator units GldLM, we suggest a “tri-component gearset” model where GldJ controls the rotational direction of its driver, the T9SS, thus providing adaptive sensory feedback to influence the motility of the gliding bacterium. IMPORTANCE The type 9 secretion system (T9SS) is fundamental to bacterial gliding motility, pathogenesis, and surface colonization. Our findings reveal that the C-terminal region of the conveyor belt-associated protein GldJ functions as a molecular switch which is capable of reversing the rotational direction of T9SS. Through the coordinated actions of the T9SS stator units (akin to a driving motor), the GldK ring (the gear that converts rotational energy into linear movement), and GldJ, this machinery forms a smart conveyor belt system reminiscent of flexible or cognitive mechanical conveyors. Such advanced conveyors can alter their direction to adapt to shifting demands. Here, we show that the bacterial T9SS similarly adjusts its rotational bias based on feedback from the conveyor belt-associated protein GldJ. This dual-role feedback mechanism underscores an evolved, controllable biological snowmobile, offering new avenues for studying how bacteria fine-tune motility in dynamic environments.

Microbiology↗

Electromagnetic heating of minor planets in the early solar system

Electromagnetic processes occurring in the primordial solar system are likely to have significantly affected planetary evolution. In particular, electrical coupling of the kinetic energy of a dense T-Tauri-like solar wind into the interior of the smaller planets could have been a major driver of thermal metamorphism. Accordingly a grid of asteroid models of various sizes and solar distances was constructed using dc transverse magnetic induction theory. Plausible parameterizations with no requirement for a high environmental temperature led to complete melting for Vesta with no melting for Pallas and Ceres. High temperatures were reached in the Pallas model, perhaps implying nonmelting thermal metamorphosis as a cause of its anomalous spectrum. A reversal of this temperature sequence seems implausible, suggesting that the Ceres-Pallas-Vesta dichotomy is a natural outcome of the induction mechanism. Highly localized heating is expected to arise due to an instability in the temperature-controlled current distribution. Localized metamorphosis resulting from this effect may be relevant to the production and evolution of pallasites, the large presumed metal component of S object spectra, and the formation of the lunar magma ocean.

Herbert, F.↗

Recent developments in mass drivers

In the past eight months a new mass driver concept has been explored through calculation and inductance model verification. It retains the linear synchronous principle and freedom from arcs, plasmas or physical contact between the accelerated bucket and accelerator. However, it discards passive magnetic flight and obtains transverse focussing from strong off-axis restoring forces produced by drive coils operating in a pull-only mode. This paper gives the reasoning on which the new concept is based, and applies the concept to a lunar catapult design.

Oneill, G. K.↗

Experimental study of a three-dimensional, shear-driven, turbulent boundary layer using a three-dimensional laser Doppler velocimeter

Experimental data have been obtained in a three-dimensional, shear-driven, turbulent boundary layer subjected to sudden transverse strain. Measurements made with a newly developed, three-dimensional laser Doppler velocimeter include all components of mean flow, turbulent Reynolds stresses, and triple-product correlations. Eddy viscosities, production, convection, turbulent diffusion, and dissipation (balance of kinetic energy equation) are extracted from the data. It was shown experimentally that eddy viscosity is strongly direction-dependent (not a scalar), indicating a need for full Reynolds stress modeling. Turbulence models for eddy viscosity, stress diffusion, pressure rate-of-strain, and anisotropy of Reynolds stresses are tested using the data. Calculations using a Reynolds stress equation model are compared with the data.

Driver, D. M.↗

Aviation System Analysis Capability Air Carrier Investment Model-Cargo

The purpose of the Aviation System Analysis Capability (ASAC) Air Cargo Investment Model-Cargo (ACIMC), is to examine the economic effects of technology investment on the air cargo market, particularly the market for new cargo aircraft. To do so, we have built an econometrically based model designed to operate like the ACIM. Two main drivers account for virtually all of the demand: the growth rate of the Gross Domestic Product (GDP) and changes in the fare yield (which is a proxy of the price charged or fare). These differences arise from a combination of the nature of air cargo demand and the peculiarities of the air cargo market. The net effect of these two factors are that sales of new cargo aircraft are much less sensitive to either increases in GDP or changes in the costs of labor, capital, fuel, materials, and energy associated with the production of new cargo aircraft than the sales of new passenger aircraft. This in conjunction with the relatively small size of the cargo aircraft market means technology improvements to the cargo aircraft will do relatively very little to spur increased sales of new cargo aircraft.

Johnson, Jesse↗

Airframe Design and Integration

The objectives of the project this viewgraph presentation summarizes include the following: (1) Decompose operational, safety, and cost requirements into a comprehensive and consistent set of design criteria for different structural and material concepts for Reusable Launch Vehicles (RLVs); (2) Develop compliance methods to ensure that different structural and material concepts are assessed at a consistent and adequate level of fidelity and safety; (3) Develop and assess weight reduction potential of integrated airframe concepts for RLVs, e.g., Thermal Protection System (TPS)/TPS Support/Cryogenic Tank System; (4) Compare performance and weight of various airframe structural and material concepts and structural arrangements and identify technology development needs; and (5) Develop high fidelity parametric models that include airframe structural interactions and major design drivers. The approaches taken to complete these objectives include the definition of vehicle requirements, airframe structural design requirements, load conditions, factors of safety, and integrated concepts.

Scotti, Stephen↗

Kinetic Simulation and Energetic Neutral Atom Imaging of the Magnetosphere

Advanced simulation tools and measurement techniques have been developed to study the dynamic magnetosphere and its response to drivers in the solar wind. The Comprehensive Ring Current Model (CRCM) is a kinetic code that solves the 3D distribution in space, energy and pitch-angle information of energetic ions and electrons. Energetic Neutral Atom (ENA) imagers have been carried in past and current satellite missions. Global morphology of energetic ions were revealed by the observed ENA images. We have combined simulation and ENA analysis techniques to study the development of ring current ions during magnetic storms and substorms. We identify the timing and location of particle injection and loss. We examine the evolution of ion energy and pitch-angle distribution during different phases of a storm. In this talk we will discuss the findings from our ring current studies and how our simulation and ENA analysis tools can be applied to the upcoming TRIO-CINAMA mission.

Fok, Mei-Ching H.↗