Results for “Simulator” — Page 28

NASA NTRS2017

Relating a Jet-Surface Interaction Experiment to a Commercial Supersonic Transport Aircraft Using Numerical Simulations

Reynolds-Averaged Navier-Stokes (RANS) simulations were performed for a commercial supersonic transport aircraft concept and experimental hardware models designed to represent the installed propulsion system of the conceptual aircraft in an upcoming test campaign. The purpose of the experiment is to determine the effects of jet-surface interactions from supersonic aircraft on airport community noise. RANS simulations of the commercial supersonic transport aircraft concept were performed to relate the representative experimental hardware to the actual aircraft. RANS screening simulations were performed on the proposed test hardware to verify that it would be free from potential rig noise and to predict the aerodynamic forces on the model hardware to assist with structural design. The simulations showed a large region of separated flow formed in a junction region of one of the experimental configurations. This was dissimilar with simulations of the aircraft and could invalidate the noise measurements. This configuration was modified and a subsequent RANS simulation showed that the size of the flow separation was greatly reduced. The aerodynamic forces found on the experimental models were found to be relatively small when compared to the expected loads from the model’s own weight.Reynolds-Averaged Navier-Stokes (RANS) simulations were completed for two configurations of a three-stream inverted velocity profile (IVP) nozzle and a baseline single-stream round nozzle (mixed-flow equivalent conditions). For the Sideline and Cutback flow conditions, while the IVP nozzles did not reduce the peak turbulent kinetic energy on the lower side of the jet plume, the IVP nozzles did significantly reduce the size of the region of peak turbulent kinetic energy when compared to the jet plume of the baseline nozzle cases. The IVP nozzle at Sideline conditions did suffer a region of separated flow from the inner stream nozzle splitter that did produce an intense, but small, region of turbulent kinetic energy in the vicinity of the nozzle exit. When viewed with the understanding that jet noise is directly related to turbulent kinetic energy, these IVP nozzle simulations show the potential to reduce noise to observers located below the nozzle. However, these RANS simulations also show that some modifications may be needed to prevent the small region of separated flow-induced turbulent kinetic energy from the inner stream nozzle splitter at Sideline conditions.

Reynolds-Averaged Navier Stokes↗

NASA NTRS2017

Time and Frequency-Domain Cross-Verification of SLS 6DOF Trajectory Simulations

The Space Launch System (SLS) Guidance, Navigation, and Control (GNC) team and its partners have developed several time- and frequency-based simulations for development and analysis of the proposed SLS launch vehicle. The simulations differ in fidelity and some have unique functionality that allows them to perform specific analyses. Some examples of the purposes of the various models are: trajectory simulation, multi-body separation, Monte Carlo, hardware in the loop, loads, and frequency domain stability analyses. While no two simulations are identical, many of the models are essentially six degree-of-freedom (6DOF) representations of the SLS plant dynamics, hardware implementation, and flight software. Thus at a high level all of those models should be in agreement. Comparison of outputs from several SLS trajectory and stability analysis tools are ongoing as part of the program's current verification effort. The purpose of these comparisons is to highlight modeling and analysis differences, verify simulation data sources, identify inconsistencies and minor errors, and ultimately to verify output data as being a good representation of the vehicle and subsystem dynamics. This paper will show selected verification work in both the time and frequency domain from the current design analysis cycle of the SLS for several of the design and analysis simulations. In the time domain, the tools that will be compared are MAVERIC, CLVTOPS, SAVANT, STARS, ARTEMIS, and POST 2. For the frequency domain analysis, the tools to be compared are FRACTAL, SAVANT, and STARS. The paper will include discussion of these tools including their capabilities, configurations, and the uses to which they are put in the SLS program. Determination of the criteria by which the simulations are compared (matching criteria) requires thoughtful consideration, and there are several pitfalls that may occur that can severely punish a simulation if not considered carefully. The paper will discuss these considerations and will present a framework for responding to these issues when they arise. For example, small event timing differences can lead to large differences in mass properties if the criteria are to measure those properties at the same time, or large differences in altitude if the criteria are to measure those properties when the simulation experiences a staging event. Similarly, a tiny difference in phase can lead to large gain margin differences for frequency-domain comparisons of gain margins.

Johnson, Matthew↗

NASA NTRS2016

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

We have recently developed a new modeling capability to embed the implicit particle-in-cell (PIC) model iPIC3D into the Block-Adaptive-Tree-Solarwind-Roe-Upwind-Scheme magnetohydrodynamic (MHD) model. The MHD with embedded PIC domains (MHO-EPIC) algorithm Is a two-way coupled kinetic-fluid model. As one of the very first applications of the MHD-EPIC algorithm, we simulate the Interaction between Jupiter's magnetospherlc plasma and Ganymede's magnetosphere. We compare the MHO-EPIC simulations with pure Hall MHD simulations and compare both model results with Galileo observations to assess the Importance of kinetic effects In controlling the configuration and dynamics of Ganymede's magnetosphere. We find that the Hall MHD and MHO-EPIC solutions are qualitatively similar, but there are significant quantitative differences. In particular. the density and pressure inside the magnetosphere show different distributions. For our baseline grid resolution the PIC solution is more dynamic than the Hall MHD simulation and it compares significantly better with the Galileo magnetic measurements than the Hall MHD solution. The power spectra of the observed and simulated magnetic field fluctuations agree extremely well for the MHD-EPIC model. The MHO-EPIC simulation also produced a few flux transfer events (FTEs) that have magnetic signatures very similar to an observed event. The simulation shows that the FTEs often exhibit complex 3-0 structures with their orientations changing substantially between the equatorial plane and the Galileo trajectory, which explains the magnetic signatures observed during the magnetopause crossings. The computational cost of the MHO-EPIC simulation was only about 4 times more than that of the Hall MHD simulation.

Toth, Gabor↗

NASA NTRS2017

Damage Simulation in Composite Materials: Why It Matters and What Is Happening Currently at NASA in This Area

Use of lightweight composite materials in space and aircraft structure designs is often challenging due to high costs associated with structural certification. Of primary concern in the use of composite structures is durability and damage tolerance. This concern is due to the inherent susceptibility of composite materials to both fabrication and service induced flaws. Due to a lack of general industry accepted analysis tools applicable to composites damage simulation, a certification procedure relies almost entirely on testing. It is this reliance on testing, especially compared to structures comprised of legacy metallic materials where damage simulation tools are available, that can drive costs for using composite materials in aerospace structures. The observation that use of composites can be expensive due to testing requirements is not new and as such, research on analysis tools for simulating damage in composite structures has been occurring for several decades. A convenient approach many researchers/model-developers in this area have taken is to select a specific problem relevant to aerospace structural certification and develop a model that is accurate within that scope. Some examples are open hole tension tests, compression after impact tests, low-velocity impact, damage tolerance of an embedded flaw, and fatigue crack growth to name a few. Based on the premise that running analyses is cheaper than running tests, one motivation that many researchers in this area have is that if generally applicable and reliable damage simulation tools were available the dependence on certification testing could be lessened thereby reducing overall design cost. It is generally accepted that simulation tools if applied in this manner would still need to be thoroughly validated and that composite testing will never be completely replaced by analysis. Research and development is currently occurring at NASA to create numerical damage simulation tools applicable to damage in composites. The Advanced Composites Project (ACP) at NASA Langley has supported the development of composites damage simulation tools in a consortium of aerospace companies with a goal of reducing the certification time of a commercial aircraft by 30%. And while the scope of ACP does not include spacecraft, much of the methodology and simulation capabilities can apply to spacecraft certification in the Space Launch System and Orion programs as well. Some specific applications of composite damage simulation models in a certification program are (1) evaluation of damage during service when maintenance may be difficult or impossible, (2) a tool for early design iterations, (3) gaining insight into a particular damage process and applying this insight towards a test coupon or structural design, and (4) analysis of damage scenarios that are difficult or impossible to recreate in a test. As analysis capabilities improve, these applications and more will become realized resulting in a reduction in cost for use of composites in aerospace vehicles. NASA is engaged in this process from both research and application perspectives. In addition to the background information discussed previously, this presentation covers a look at recent research at NASA in this area and some current/potential applications in the Orion program.

McElroy, Mack↗

NASA NTRS2019

Motion Cueing for Stall Recovery Training in Commercial Transport Simulators

Starting in 2019, airline pilots will be required to perform full stall recovery training in flight simulators. Historically, training simulators weren't required to provide training at conditions outside their normal flight envelope. Post-stall aircraft models are generally required to be implemented to simulate the aircraft response after the stall point. In addition, motion cues need to adequately represent this response to ensure the skills learned in simulator training are directly usable in real flight. This paper provides and overview of six simulator experiments conducted at NASA Ames Research Center to develop a motion cueing strategies for stall recovery training in commercial transport simulators. One of the experiments verified an enhanced motion cueing strategy for stall recovery training on a level-D-certified full flight simulator. This study showed that the enhanced motion results in lower maximum roll angles in the stall maneuver, lower minimum load factors in the recovery, lower numbers of secondary stick shakers in the stall recovery, and a lower maximum airspeed in the recovery. These results indicate that relatively minor enhancements to the motion logic of heritage commercial transport simulators can significantly improve pilot performance in simulated stall recoveries, and potentially improve stall recovery training.

stall recovery↗

NASA NTRS2019

Use of Polarimetric Radar Measurements to Constrain Simulated Convective Cell Evolution: A Pilot Study with Lagrangian Tracking

To probe the potential value of a radar-driven field campaign to constrain simulation of isolated convection subject to a strong aerosol perturbation, convective cells observed by the operational KHGX weather radar in the vicinity of Houston, Texas, are examined individually and statistically. Cells observed in a single case study of onshore flow conditions during July 2013 are first examined and compared with cells in a regional model simulation. Observed and simulated cells are objectively identified and tracked from observed or calculated positive specific differential phase (K(sub DP)) above the melting level, which is related to the presence of supercooled liquid water. Several observed and simulated cells are subjectively selected for further examination. Below the melting level, we compare sequential cross sections of retrieved and simulated raindrop size distribution parameters. Above the melting level, we examine time series of KDP and radar differential reflectivity (Z(sub DR)) statistics from observations and calculated from simulated supercooled rain properties, alongside simulated vertical wind and supercooled rain mixing ratio statistics. Results indicate that the operational weather radar measurements offer multiple constraints on the properties of simulated convective cells, with substantial value added from derived K(sub DP) and retrieved rain properties. The value of collocated three-dimensional lightning mapping array measurements, which are relatively rare in the continental US, supports the choice of Houston as a suitable location for future field studies to improve the simulation and understanding of convective updraft physics. However, rapid evolution of cells between routine volume scans motivates consideration of adaptive scan strategies or radar imaging technologies to amend operational weather radar capabilities. A 3-year climatology of isolated cell tracks, prepared using a more efficient algorithm, yields additional relevant information. Isolated cells are found within the KHGX domain on roughly 40 % of days year-round, with greatest concentration in the northwest quadrant, but roughly 5-fold more cells occur during June through September. During this enhanced occurrence period, the cells initiate following a strong diurnal cycle that peaks in the early afternoon, typically follow a south-to-north flow, and dissipate within 1 h, consistent with the case study examples. Statistics indicate that ∼ 150 isolated cells initiate and dissipate within 70 km of the KHGX radar during the enhanced occurrence period annually, and roughly 10 times as many within 200 km, suitable for multi-instrument Lagrangian observation strategies. In addition to ancillary meteorological and aerosol measurements, robust vertical wind speed retrievals would add substantial value to a radar-driven field campaign.

Fridlind, Ann M.↗

NASA NTRS2019

Motion Cueing for Stall Recovery Training in Commercial Transport Simulators

Starting in 2019, airline pilots will be required to perform full stall recovery training in flight simulators. Historically, training simulators weren't required to provide training at conditions outside their normal flight envelope. Post-stall aircraft models are generally required to be implemented to simulate the aircraft response after the stall point. In addition, motion cues need to adequately represent this response to ensure the skills learned in simulator training are directly usable in real flight. This paper provides and overview of six simulator experiments conducted at NASA Ames Research Center to develop a motion cueing strategies for stall recovery training in commercial transport simulators. One of the experiments verified an enhanced motion cueing strategy for stall recovery training on a level-D-certified full flight simulator. This study showed that the enhanced motion results in lower maximum roll angles in the stall maneuver, lower minimum load factors in the recovery, lower numbers of secondary stick shakers in the stall recovery, and a lower maximum airspeed in the recovery. These results indicate that relatively minor enhancements to the motion logic of heritage commercial transport simulators can significantly improve pilot performance in simulated stall recoveries, and potentially improve stall recovery training.

stall recovery↗

NASA NTRSDate not supplied

Implementation of Charged Particle Behavior in Discrete Element Method (DEM) Simulations

Lunar landers will agitate the surface of the Moon with an exhaust plume during descent which will, due to the particulate nature of the lunar regolith, loosen and eject grains from the surface. This ejection is not only coupled with the charged plume gas, but also results in significant particle-particle interactions. Settling of these grains after plume effects have subsided takes much longer than expected in a ballistic trajectory. The prevailing hypothesis attributes this behavior to the accumulated charge on the particles. We are thus developing a discrete element method (DEM) approach to explore these charged particle interactions on the lunar surface. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) Improved for General Granular and Granular Heat Transfer Simulations (LIGGGHTS) software package provides a DEM modeling framework for granular interactions. It includes many complexities such as non-spherical particle shapes, cohesion and frictional forces, and heat transfer, but has no provision for inter-particle electrostatic forces and charge transfer that are important to examine in the lunar environment. In this work, a standard Coulomb potential and a Yukawa potential are integrated into the LIGGGHTS framework to provide a basis for particle-particle electrostatic interactions, as well as a gravitational potential to enable inter-grain gravitational interactions. A preliminary approach to charge transfer between grains incorporating properties such as work function and electrical conductivity to the library of available material characteristics will be presented. Several scenarios have been simulated that include charged particle interactions within a diffuse granular gas, settling of charged grains into a regolith bed, sliding of granular material along an incline, and vibration of settled grains to produce a behavior similar to fluidization. There are numerous challenges to incorporate realistic interactions between complex lunar particles. Currently, grains are modeled to behave as if the entirety of the charge acts at the center of mass, such as conductors with spherical symmetry and insulators with homogeneously distributed charge. We are developing improvements that will include the use of non-spherical particle geometries, as well as reasonable approximations of insulating/dielectric materials that have non-uniform charge distributions. The cases simulated thus far will be examined in a relevant environment within a vacuum chamber to validate the simulations. These simulations will be bounded by experiments utilizing high-speed camera observations of the motion for validation. The grains in the experiment will exchange charge during their motion and this can be quantified by collection within a charge measurement device such as a Faraday cup. Such a device may be modeled within the software by defining an integration region and computing the contained charge as a function of simulation time, allowing for side-by-side comparison of simulated and measured bulk charging results. Any differences will be reconciled by updating the mathematical mechanisms described within the simulation suite. Successfully combining results from experiments within a relevant environment into the LIGGGHTS framework will improve modeling of the charged grain dynamics experienced on the Moon to provide insights into dust behavior for future lunar exploration missions.

Electrostatics↗

NASA NTRSDate not supplied

Simulating Underexpanded Jets in Martian and Lunar Environments

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The GCD PSI Project, planned to be accomplished over a four year period, contains a Predictive Simulation Capability (PSC) Element focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the PSC Element, the PSI Project also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper describes the activities and accomplishments in the past year for the Prediction of Plume Flow in low pressure environments component of the PSI Project. While the Loci/Chem Computational fluid dynamics (CFD) application has been validated and used extensively for simulating launch environments in atmospheric conditions, use of this tool for simulating supersonic plumes at Mars-like ambient pressure requires further validation. CFD simulations of underexpanded jets have been performed using Loci/Chem for Mars-like conditions to predict several metrics for steady laminar, turbulent, and impinging plumes. The CFD results are compared with an experimental data set for low Reynolds number plumes at these conditions in order to evaluate the current capability of the Loci/Chem tool for these types of environments. The CFD validation results to date show reasonable agreement with the experimental data across all of the metrics of interest for the configurations considered. The Loci/Chem-Boltzmann CFD application is a hybrid continuum/rarefied flow solver which extends modeling capabilities to very low pressure environments such as those on the Moon. The Loci/Chem-Boltzmann solver uses a gradient-based continuum breakdown criterion to restrict solution of the computationally expensive Boltzmann equation to only a subset of the domain, while using the Navier-Stokes equations elsewhere. This CFD application is under active development, and current efforts toward establishing production ready capability for evaluating Lunar plume surface interactions are well under way. Initial simulations of an Apollo LEM indicate that several regions of the flow require solving the Boltzmann equations due to extreme rarefaction. Early simulations are promising, indicating reasonable overall computational time for a full 3D human scale lander simulation.

Thomas Shurtz↗

NASA NTRSDate not supplied

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A Liever↗

NASA NTRSDate not supplied

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A. Liever↗

NASA NTRSDate not supplied

A 3D Simulation Platform for Decentralized Decision-Making in Advanced Air Mobility

This paper presents a general purpose, plug-and-play simulation platform for the use of future aviation stakeholders, such as urban airspace planners, air vehicle operators, ground operation managers, air traffic controllers and aviation researchers. The presented simulator platform is envisioned to serve as a toolkit to visualize, evaluate, and configure future advanced air mobility (AAM) operations. Highlighting features of this toolkit include a modular architecture that allows multiple smart unmanned aerial systems (UASs) to remotely connect to the simulation server and participate in decentralized decision-making scenario simulations. As an example of the decentralized decision-making scenario, an inter-agent negotiation-based conflict resolution use case is considered in this paper, where the UASs leverage the on-board/on-the-edge artificial intelligence (AI) capability to continually build situational awareness, and use this information to predict future conflicts and resolve them through machine-to-machine negotiation. As such operations are non-existent at scale currently, the presented simulation platform offers a viable and cost-effective alternative for assessing the efficacy of AAM research outcomes and challenges in future shared airspace usage. The simulation platform allows plug-n-play connectivity with AI and non-AI compute modules representing individual UAS’s flight control. Each module can interact with the simulation platform independently to communicate current and desired future states, situational awareness, and conflict resolution utilization costs for inter-agent negotiation. The simulation environment orchestrates realistic operational scenarios with spatiotemporal details, dynamic events, tactical conflict-resolution methods, interfaces for customizing air traffic control parameters, and information exchange uncertainties. In the future, this can serve as a community focused cloud simulation platform, incorporating multi-stakeholder airspace constraints from regulatory, government, city, and local agencies.

Aditya N Das↗

NASA NTRS2022

A 3D Simulation Platform for Decentralized Decision-Making in Advanced Air Mobility

This paper presents a general purpose, plug-and-play simulation platform for the use of future aviation stakeholders, such as urban airspace planners, air vehicle operators, ground operation managers, air traffic controllers and aviation researchers. The presented simulator platform is envisioned to serve as a toolkit to visualize, evaluate, and configure future advanced air mobility (AAM) operations. Highlighting features of this toolkit include a modular architecture that allows multiple smart unmanned aerial systems (UASs) to remotely connect to the simulation server and participate in decentralized decision-making scenario simulations. As an example of the decentralized decision-making scenario, an inter-agent negotiation-based conflict resolution use case is considered in this paper, where the UASs leverage the on-board/on-the-edge artificial intelligence (AI) capability to continually build situational awareness, and use this information to predict future conflicts and resolve them through machine-to-machine negotiation. As such operations are non-existent at scale currently, the presented simulation platform offers a viable and cost-effective alternative for assessing the efficacy of AAM research outcomes and challenges in future shared airspace usage. The simulation platform allows plug-n-play connectivity with AI and non-AI compute modules representing individual UAS’s flight control. Each module can interact with the simulation platform independently to communicate current and desired future states, situational awareness, and conflict resolution utilization costs for inter-agent negotiation. The simulation environment orchestrates realistic operational scenarios with spatiotemporal details, dynamic events, tactical conflict-resolution methods, interfaces for customizing air traffic control parameters, and information exchange uncertainties. In the future, this can serve as a community focused cloud simulation platform, incorporating multi-stakeholder airspace constraints from regulatory, government, city, and local agencies.

Aditya Das↗

NASA NTRSDate not supplied

Validation of A Simulation Environment for Future Space Traffic Management

This study presents initial results of a newly developed simulation environment intendedto explore and assess future Space Traffic Management (STM) scenarios. The number ofnew Resident Space Objects (RSOs) in near-Earth orbit is expected to increase significantlywith the expected future deployment of a number of large constellations. These futurescenarios involve the addition of many tens of thousands of new RSOs, making the analysisinto their impact on collision risk extend beyond what traditional data-mining of present-dayconjunction data can reliably predict. To address this, a robust simulation environment wasdeveloped that implements a full force-model for orbit propagation, and computes continuousall-on-all conjunction statistics for arbitrarily large catalog sizes and simulation timeframes.Collision avoidance and station-keeping maneuvers can be optionally implemented based onconfigurable user inputs including physical characteristics and spacecraft meta-data (e.g.,commercial/government, owner country, etc.). Constellation build-out and de-orbit scenarioswere also implemented and modeled based on real-data analysis. Validation of the simulationresults was a critical component of the simulation development, and was done using the currentcatalog with comparisons against both public and internal NASA data-sets. The comparisonsdemonstrate that, with the appropriate settings, representative levels of conjunction ratesand probabilities can be obtained, providing confidence that the simulation tool can generatemeaningful outcomes for test scenarios. As an initial demonstration of the tool’s capabilities,year-long simulations with station-keeping were conducted to examine conjunction historiesusing both the current object catalog (5800 active satellites) and a hypothetical 60,000 objectscenario involving five potential large constellations. Output metrics include the number ofconjunction events, estimates of collision consequence (fragmentation), delta-V maneuver costs,and the probability of at least one collision occurring. The results highlight the potential thatthe simulation tool has for incorporating and running performance comparisons between, e.g.,various sets of maneuver guidelines, industry norms, and definitions of risk, with the overallobjective of providing actionable data to STM policy makers. The presentation will providean overview of the simulation development and validation efforts, as well as a discussion ofobservations gathered from the initial simulations performed.

conjunction assessment↗

NASA NTRS2024

Improved Simulations of Biomass Burning Aerosol Optical Properties and Lifetimes in the NASA GEOS Model during the ORACLES-I Campaign

In order to improve aerosol representation in the NASA Goddard Earth Observing System (GEOS) model, we evaluated simulations of the aerosol properties and transport over the southern African biomass burning source and outflow region using observations made during the first deployment of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field campaign in September 2016. An example case study of September 24 was analyzed in detail, during which aircraft-based in-situ and remote sensing observations showed the presence of a multi-layered smoke plume structure with significant vertical variation in single scattering albedo (SSA). Our baseline GEOS simulations were not able to represent the observed SSA variation, nor the observed organic aerosol-to-black carbon ratio (OA : BC). Analyzing the simulated smoke age suggests that the higher altitude, less absorbing smoke plume was younger (~4 days), while the lower altitude and more absorbing smoke plume was older (~7 days). We hypothesize a chemical or microphysical loss process exists to explain the change in aerosol absorption as the smoke plume ages, and we apply a simple 6-day e-folding loss rate to the model hydrophilic biomass burning OA to mimic this process. Adding this loss process required some adjustment to the model assumed scaling factors of aerosol emissions to conserve the regional aerosol loading and further improve the simulated OA : BC ratio. Accordingly, we have increased our biomass burning emissions of OA by 60 % and biomass burning BC by 15 %. We also utilized the ORACLES airborne observations to better constrain the simulation of aerosol optical properties, adjusting the assumed particle size, hygroscopic growth, and absorption. Our final GEOS model simulation with additional OA loss and updated optics showed a better performance in simulating AOD and SSA compared to independent ground and space-based retrievals for the entire month of September 2016, including the OMI Aerosol Index. In terms of radiative implications of our model adjustments, the final GEOS simulation suggested a decreased atmospheric warming of about 10 % (~2 W m -2 ) over the south-east Atlantic region and above the stratocumulus cloud decks compared to the model baseline simulations. These results improve the representation of the smoke age, transport, and optical properties in Earth system models.

aerosols↗

NASA NTRS2023

Modeling the Formation and Eruption of Coronal Structures by Linking Data-Driven Magnetofrictional and MHD Simulations for AR 12673

Context .The data-driven and time-dependent modeling of coronal magnetic fields is crucial for understanding solar eruptions. These efforts are complicated by the challenges of finding a balance between physical realism and computing efficiency. One possible technique is to couple two modeling approaches. Aims . Our aim here is to showcase our progress in using time-dependent magnetofrictional model (TMFM) results as input to dynamical magnetohydrodynamic (MHD) simulations. However, due to the different evolution processes in these two models, using TMFM snapshots in an MHD simulation is nontrivial. We address these issues, both physically and numerically, discuss the incompatibility of the TMFM output to serve as the initial condition in MHD simulations, and show our methods of mitigating this. The evolution of the flux systems and the cause of the eruption are investigated. Methods . TMFM is a prevalent approach that has proven to be a very useful tool in the study of the formation of unstable structures in the solar corona. In particular, it is capable of incorporating observational data as initial and boundary conditions and requires shorter computational time compared to MHD simulations. To leverage the efficiency of data-driven TMFM and also to simulate eruptive events in the MHD framework, one can apply TMFM up to a certain time before the expected eruption(s) and then proceed with the simulation in the full or ideal MHD regime in order to more accurately capture the eruption process. Results . We show the results of a benchmark test case with a linked TMFM and MHD simulation to study the evolution of NOAA active region 12673. A rise of a twisted flux bundle through the MHD simulation domain is observed, but we find that the rate of the rise and the altitude reached depends on the time of the TMFM snapshot that was used to initialize the MHD simulation and the helicity injected into the system. The analysis suggested that torus instability and slip-running reconnection could play an important role in the eruption. Conclusions . The results show that the linkage of TMFM and zero-β MHD models can be successfully used to model the eruptive coronal magnetic fields.

F. Daei↗

NASA NTRSDate not supplied

Independent Verification and Validation for Artemis I Ascent Integrated Flight Performance Simulation

The NASA Engineering and Safety Center (NESC) has performed independent model development to support cross-model verification for the Space Launch System (SLS) Program since 2012 which culminated, for Artemis I, in a postflight reconciliation analysis of the Artemis I ascent trajectory (validation). This post-flight analysis was completed by both the NESC and the SLS Program. Upon successful completion of the Artemis I mission, multiple preflight simulations of the nominal ascent trajectory were updated with Day of Launch (DOL) conditions and simulated results were compared to reconstructed flight data derived from telemetry measurements. Dispersed trajectories were also produced using a combination of DOL conditions and preflight uncertainties, which ideally should bound the Artemis I flight data. Finally, multibody dynamics were simulated for some of the separation events to support clearance analyses. This paper focuses on validating and understanding the accuracy of the models by comparing simulated results against the Artemis I flight data. In addition, discrepancies uncovered between simulations led to opportunities to investigate areas for potential model improvement to refine preflight simulations for future Artemis missions. Included in this paper is background on the flight performance simulation tools, the postflight analysis approach, and a comparison of simulation results against the Artemis I flight data. Simulated results were found to generally be in close agreement with each other and the Artemis I flight data.

Jacob Fleck↗

DOE OSTI2024

Using Computer Simulations to Optimize Biofuel Production

The DOE strives to ensure America's security and prosperity by addressing energy challenges. NREL shares this goal and tries to achieve a clean energy world. Fossil fuels are problematic for both organizations. Using them endangers American security. Their supply is finite and burning them causes environmental damage. Biofuels are a good alternative to fossil fuels. They are renewably produced on American soil and can lower greenhouse gas emissions. Also, cars and planes need no costly mechanical adjustments to use biofuels. However, the fuels themselves are expensive. For my SULI project, I reduced the cost of biofuels by optimizing the production process through computer simulations. Existing simulations were accurate but slow. One simulation takes up to eight hours, and researchers must do hundreds. My solution reduces the computing time. I treated the biomass particles in the simulation as one-dimensional. That simplified the simulation equations, making them easier for the computer to solve. Still, biomass particles are three-dimensional. The 1D assumption was wrong and produced inaccurate results. To maintain accuracy while increasing speed, I developed a method to convert 1D simulation results into usable 3D data. I adjusted the 1D simulation until the output matched the 3D results for a specific environment. I found out how much the simulation changed when the environment changed. Machine learning algorithms defined a relationship between 1D and 3D data for all environments. This lets scientists convert fast 1D simulation results into valid 3D data.

1D↗