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At least 1,189 records · Page 66

Global Soil Water Estimates as Landslide Predictor: The Effectiveness of SMOS, SMAP, and GRACE Observations, Land Surface Simulations, and Data Assimilation

This global feasibility study assesses the potential of coarse-scale, gridded soil water estimates for the probabilistic modeling of hydrologically-triggered landslides, using Soil Moisture Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP) and Gravity Recovery and Climate Experiment (GRACE) remote sensing data, Catchment Land Surface Model (CLSM) simulations and six data products based on the assimilation of SMOS, SMAP, and/or GRACE observations into CLSM. SMOS or SMAP observations (~40-km resolution) are only available for less than 20% of the globally reported landslide events, because they are intermittent and uncertain in regions with complex terrain. GRACE terrestrial water storage estimates include 75% of the reported landslides but have coarse spatial and temporal resolutions (monthly, ~300-km). CLSM soil water simulations have the added advantage of complete spatial and temporal coverage, and are found to be able to distinguish between “stable slope” (no landslide) conditions and landslide-inducing conditions in a probabilistic way. Assimilating SMOS and/or GRACE data increases the landslide probability estimates based on soil water percentiles for the reported landslides, relative to model-only estimates at 36-km resolution for the period 2011-2016, unless the CLSM model-only soil water content is already high (≥ 50th percentile). The SMAP Level 4 data assimilation product (at 9-km resolution, period 2015-2019) more generally updates the soil water conditions towards higher landslide probabilities for the reported landslides, but is similar to model-only estimates for the majority of landslides where SMAP data cannot easily be converted to soil moisture owing to complex terrain.

Anne Felsberg↗

Design of a Lunar Plume-Surface Interaction Measurement System

Plume-surface interactions between a rocket plume and the lunar surface will be studied in-situ during two of NASA’s upcoming Commercial Lunar Payload Services Program missions. The payload, Stereo Cameras for Lunar Plume-Surface Studies (SCALPSS), will employ a multiple-camera photogrammetry system to obtain stereo images of the lunar regolith before, during, and after significant erosion and subsequent crater formation. The evaluation of measurement system capabilities and design process of the payload is informed by computational fluid dynamics predictions, accuracy modeling based on experimental data, camera simulation, and lander design, all of which are combined in the Virtual Diagnostic Interface. The second SCALPSS mission, traveling to the moon on Firefly Aerospace’s Blue Ghost lander in early 2023, aims to build on the design and complexity of the first payload, which is launching in early 2022 on Intuitive Machines’ Nova-C lander. The Blue Ghost SCALPSS mission will include two additional cameras and a total of three different lens focal lengths which will target specific points in the vehicle’s descent to obtain quantitative and accurate 3D reconstruction of the lunar surface both prior to and after crater formation.

photogrammetry↗

Causal Interactions between Southern Ocean Polynyas and High-Latitude Atmosphere–Ocean Variability

Abstract Weddell Sea open-ocean polynyas have been observed to occasionally release heat from the deep ocean to the atmosphere, indicating that their sporadic appearances may be an important feature of high-latitude atmosphere–ocean variability. Yet, observations of the phenomenon are sparse and many standard-resolution models represent these features poorly, if at all. We use a fully coupled, synoptic-scale preindustrial control simulation of the Energy Exascale Earth System Model (E3SMv0-HR) to effectively simulate open-ocean polynyas and investigate their role in the climate system. Our approach employs statistical tests of Granger causality to diagnose local and remote drivers of, and responses to, polynya heat loss on interannual to decadal time scales. First, we find that polynya heat loss Granger causes a persistent increase in surface air temperature over the Weddell Sea, strengthening the local cyclonic wind circulation. Along with responding to polynyas, atmospheric conditions also facilitate their development. When the Southern Ocean experiences a rapid poleward shift in the circumpolar westerlies following a prolonged negative phase of the southern annular mode (SAM), Weddell Sea salinity increases, promoting density destratification and convection in the water column. Finally, we find that the reduction of surface heat fluxes during periods of full ice cover is not fully compensated by ocean heat transport into the high latitudes. This imbalance leads to a buildup of ocean heat content that supplies polynya heat loss. These results disentangle the complex, coupled climate processes that both enable the polynya’s existence and respond to it, providing insights to improve the representation of these highly episodic sea ice features in climate models.

Kaufman, Zachary S.↗

Modeling Logistics and Supportability for Crewed Missions Beyond Low Earth Orbit

NASA’s future missions aim to establish a sustained human presence on the lunar surface and send humans to Mars. These missions will send crews farther from home than previous missions, limiting the opportunities for resupply missions. Additionally, the use of multiple launches and reusable elements will increase mission and campaign complexity. Logistics and supportability analysis evaluates the link between mission and system characteristics and key metrics such as logistics and spares mass and volume, crew time, and risk. As missions become increasingly complex and crews are logistically isolated for longer periods of time, logistics and supportability will become more powerful drivers of risk and cost and, therefore, more important considerations during system and mission development. When logistics and supportability are considered from the beginning of system and mission development, opportunities arise to create more efficient, lower-risk systems. Design choices made without detailed consideration of logistics and supportability have the potential to result in greater risks and increased costs as all options may not have been analyzed. This paper provides an overview of a methodology used for space mission logistics and supportability analysis, including key metrics, assumptions, and required inputs. Example applications of this methodology to explore the impacts of system architecture, dormancy, and synergies between lunar and Mars missions are also presented. Conducting these holistic analyses enables informed decision-making for mission planning and system design, which can help mitigate the risk of loss of mission, vehicle, or crew. Using the knowledge of historical missions, experiences gained on the lunar surface, and logistics and supportability analyses, NASA can examine and optimize supportability characteristics for safer and more effective operations for future lunar and Mars missions.

Supportability↗

Modeling Logistics and Supportability for Crewed Missions Beyond Low Earth Orbit

NASA’s future missions aim to establish a sustained human presence on the lunar surface and send humans to Mars. These missions will send crews farther from home than previous missions, limiting the opportunities for resupply missions. Additionally, the use of multiple launches and reusable elements will increase mission and campaign complexity. Logistics and supportability analysis evaluates the link between mission and system characteristics and key metrics such as logistics and spares mass and volume, crew time, and risk. As missions become increasingly complex and crews are logistically isolated for longer periods of time, logistics and supportability will become more powerful drivers of risk and cost and, therefore, more important considerations during system and mission development. When logistics and supportability are considered from the beginning of system and mission development, opportunities arise to create more efficient, lower-risk systems. Design choices made without detailed consideration of logistics and supportability have the potential to result in greater risks and increased costs as all options may not have been analyzed. This paper provides an overview of a methodology used for space mission logistics and supportability analysis, including key metrics, assumptions, and required inputs. Example applications of this methodology to explore the impacts of system architecture, dormancy, and synergies between lunar and Mars missions are also presented. Conducting these holistic analyses enables informed decision-making for mission planning and system design, which can help mitigate the risk of loss of mission, vehicle, or crew. Using the knowledge of historical missions, experiences gained on the lunar surface, and logistics and supportability analyses, NASA can examine and optimize supportability characteristics for safer and more effective operations for future lunar and Mars missions.

Supportability↗

Scattering of impact wave by a crack in composite plate

The surface responses due to impact load on an infinite uniaxial graphite/epoxy plate with and without delamination cracks are investigated both in time and frequency domain by using a hybrid method combining the finite element discretization of the near-field with boundary integral representation of the field outside a contour enclosing completely the crack. This combined method leads to a set of linear unsymmetric complex matrix equations which are solved to obtain the response in the frequency domain by biconjugate gradient method. The time domain response is then obtained by using an FFT. In order to capture the time-domain characteristics accurately, high order finite elements have been used. Also, both the six node singular elements and eight node transition elements are used around the crack tips to model the crack-tip singularity. It is shown that from the numerical results for surface responses both depth and length of this crack can be identified.

Ju, T. H.↗

Insights into Waterflooding in Hydrocarbon-Bearing Nanochannels of Varying Cross Sections from Mesoscopic Multiphase Flow Simulations

Waterflooding is one of the geotechnique used to recover fuel sources from nanoporous geological formations. The scientific understanding of the process that involves the multiphase flow of nanoconfined fluids, however, has lagged, mainly due to the complex nanopore geometries and chemical compositions. To enable benchmarked flow of nanoconfined fluids, the architected geomaterials, such as synthesized mesoporous silica with tunable pore shapes and surface chemical properties, are used for designing and conducting experiments and simulations. This work uses a modified many-body dissipative particle dynamics (mDPD) model with accurately calibrated parameters to perform parametric flow simulations for studying the influences of waterflooding driven power, pore shape, surface roughness, and surface wettability on the multiphase flow in heptane-saturated silica nanochannels. Remarkably, up to 80\% reduction in the effective permeability is found for water-driven heptane flow in a baseline 4.5 nm-wide slit channel, when compared with the Hagen–Poiseuille equation. In the 4.5 nm-wide channels with architected surface roughness, the flow rate is found either higher or lower than the baseline case, depending on the shape and size of cross-sections. High wettability of the solid surface to water is essential for achieving high recovery of heptane, regardless of surface roughness. When the solid surface is less wetting or non-wetting to water, the existence of an optimal waterflooding driven power is found to allow for the highest possible recovery. A detailed analysis on the evolution of the transient water-heptane interface in those nanochannels is presented to elucidate the underlying mechanisms that impact or dictate the multiphase flow behaviors.

58 GEOSCIENCES↗

Mapping Glacier Basal Sliding Applying Machine Learning

During the RESOLVE project (“High-resolution imaging in subsurface geophysics: development of a multi-instrument platform for interdisciplinary research”), continuous surface displacement and seismic array observations were obtained on Glacier d’Argentière in the French Alps for 35 days in May 2018. The data set is used to perform a detailed study of targeted processes within the highly dynamic cryospheric environment. In particular, the physical processes controlling glacial basal motion are poorly understood and remain challenging to observe directly. Especially in the Alpine region for temperate based glaciers where the ice rapidly responds to changing climatic conditions and thus, processes are strongly intermittent in time and heterogeneous in space. Spatially dense seismic and Global Positioning System (GPS) measurements are analyzed applying machine learning to gain insight into the processes controlling glacial motions of Glacier d’Argentière. Using multiple bandpass-filtered copies of the continuous seismic waveforms, we compute energy-based features, develop a matched field beamforming catalog and include meteorological observations. Features describing the data are analyzed with a gradient boosting decision tree model to directly estimate the GPS displacements from the seismic noise. We posit that features of the seismic noise provide direct access to the dominant parameters that drive displacement on the highly variable and unsteady surface of the glacier. The machine learning model infers daily fluctuations and longer term trends. The results show on-ice displacement rates are strongly modulated by activity at the base of the glacier. The techniques presented provide a new approach to study glacial basal sliding and discover its full complexity.

58 GEOSCIENCES↗

Surrogate models to optimize plasma-assisted atomic layer deposition in high aspect ratio features

In this work, we explore surrogate models to optimize plasma enhanced atomic layer deposition (PEALD) in high aspect ratio features. In plasma-based processes such as PEALD and atomic layer etching (ALE), surface recombination can dominate the reactivity of plasma species with the surface, which can lead to unfeasibly long exposure times to achieve full conformality inside nanostructures like high aspect ratio vias. Using a synthetic dataset based on simulations of PEALD, we train artificial neural networks to predict saturation times based on cross section thickness data obtained for partially coated conditions. The results obtained show that just two experiments in undersaturated conditions contain enough information to predict saturation times within 10% of the ground truth. A surrogate model trained to determine whether surface recombination dominates the plasma–surface interactions in a PEALD process achieves 99% accuracy. This demonstrates that machine learning can provide a new pathway to accelerate the optimization of PEALD processes in areas such as microelectronics. Our approach can be easily extended to ALE and more complex structures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Leveraging Additive Manufacturing to Fabricate High Temperature Alloys With Co-Designed Mechanical Properties and Environmental Resistance

A paradigm shift in the traditional sequential design approaches is critically essential to create application-specific hierarchical and multifunctional materials with superior long-term performance for next-generation energy technologies involving extreme environments. In the current work, we aim to leverage the flexibility and geometric/compositional complexity offered by additive manufacturing to demonstrate this new approach by codesigning a compositionally graded Ni-based alloy for molten salts\sCO 2 heat exchangers to enable mitigation of environmental degradation of surfaces exposed to molten halide salts, while simultaneously suppressing the consequent deterioration in mechanical stability. Further, thermokinetic modeling describing the underlying physics of thermally- and environmentally induced spatiotemporal compositional and microstructural evolution will be employed to predict the parameter space of material deposition processes and precisely identify the required composition gradient. Preliminary corrosion and mechanical testing of the dual material demonstrated the potential of the material to replace existing solid solution strengthened materials for this application.

36 MATERIALS SCIENCE↗

Implications of reduced-complexity aerosol thermodynamics on organic aerosol mass concentration and composition over North America

Atmospheric organic aerosol (OA) mass concentrations can be affected by water uptake through its impact on the gas–particle partitioning of semi-volatile compounds. Current chemical transport models (CTMs) neglect this process. We have implemented the Binary Activity Thermodynamics model coupled to a volatility basis set partitioning scheme in the GEOS-Chem CTM, providing an efficient reduced-complexity OA model that predicts relative-humidity-dependent mixing and partitioning thermodynamics, while limiting the impact on computational efficiency. We provide a quantitative assessment of this water-sensitive OA treatment, focusing on a subdomain over North America. The updated OA scheme predicts a spatiotemporal mean enhancement in surface-level OA mass concentration of 145 % for January 2019 and 76 % for July 2019 compared to GEOS-Chem's most advanced OA scheme. The temporal mean surface-level OA organic mass concentration can increase by up to ∼590 % for January 2019 and ∼280 % for July 2019, with the greatest enhancements occurring over the ocean. The updated OA scheme also quantifies the OA-associated water content. The simulations show how different OA precursors and related OA surrogates contribute and respond to water uptake, including that due to changes in temperature and relative humidity over the diurnal cycle in selected winter and summer months. These results are independent of future CTM improvements involving updates to chemical reaction schemes and emission inventories. Our water-sensitive OA scheme allows for a better representation of the seasonal and regional variations in OA mass concentration in CTMs.

54 ENVIRONMENTAL SCIENCES↗

Single expansion ramp nozzle simulations

The single-expansion-ramp-nozzle (SERN) experiment underway at NASA Ames Research Center simulates the National Aerospace Plane propulsive jet-plume flow. Recently, limited experimental data has become available from an experiment with a generic nozzle/afterbody model in a hypersonic wind tunnel. The present paper presents full three-dimensional solutions obtained with the implicit Navier-Stokes solver, FL3D, for the baseline model and a version of the model with side extensions. Analysis of the computed flow clearly shows the complex 3-D nature of the flow, critical flow features, and the effect of side extensions on the plume flow development. Flow schematics appropriate for the conditions tested are presented for the baseline model and the model with side extensions. The computed results show excellent agreement with experimental shadowgraph and with surface pressure measurements. The computed and experimental surface oil-flows show the same features but may be improved by appropriate turbulence modeling.

Ruffin, Stephen M.↗

Feedback controlled optics with wavefront compensation

The sensitivity model of a complex optical system obtained by linear ray tracing is used to compute a control gain matrix by imposing the mathematical condition for minimizing the total wavefront error at the optical system's exit pupil. The most recent deformations or error states of the controlled segments or optical surfaces of the system are then assembled as an error vector, and the error vector is transformed by the control gain matrix to produce the exact control variables which will minimize the total wavefront error at the exit pupil of the optical system. These exact control variables are then applied to the actuators controlling the various optical surfaces in the system causing the immediate reduction in total wavefront error observed at the exit pupil of the optical system.

Breckenridge, William G.↗

Large Eddy Simulation of Cirrus Clouds

The Regional Atmospheric Modeling System (RAMS) with mesoscale interactive nested-grids and a Large-Eddy Simulation (LES) version of RAMS, coupled to two-moment microphysics and a new two-stream radiative code were used to investigate the dynamic, microphysical, and radiative aspects of the November 26, 1991 cirrus event. Wu (1998) describes the results of that research in full detail and is enclosed as Appendix 1. The mesoscale nested grid simulation successfully reproduced the large scale circulation as compared to the Mesoscale Analysis and Prediction System's (MAPS) analyses and other observations. Three cloud bands which match nicely to the three cloud lines identified in an observational study (Mace et al., 1995) are predicted on Grid #2 of the nested grids, even though the mesoscale simulation predicts a larger west-east cloud width than what was observed. Large-eddy simulations (LES) were performed to study the dynamical, microphysical, and radiative processes in the 26 November 1991 FIRE 11 cirrus event. The LES model is based on the RAMS version 3b developed at Colorado State University. It includes a new radiation scheme developed by Harrington (1997) and a new subgrid scale model developed by Kosovic (1996). The LES model simulated a single cloud layer for Case 1 and a two-layer cloud structure for Case 2. The simulations demonstrated that latent heat release can play a significant role in the formation and development of cirrus clouds. For the thin cirrus in Case 1, the latent heat release was insufficient for the cirrus clouds to become positively buoyant. However, in some special cases such as Case 2, positively buoyant cells can be embedded within the cirrus layers. These cells were so active that the rising updraft induced its own pressure perturbations that affected the cloud evolution. Vertical profiles of the total radiative and latent heating rates indicated that for well developed, deep, and active cirrus clouds, radiative cooling and latent heating could be comparable in magnitude in the cloudy layer. This implies that latent heating cannot be neglected in the construction of a cirrus cloud model. The probability density function (PDF) of w was analyzed to assist in the parameterization of cloud-scale velocities in large-scale models. For the more radiatively-driven, thin cirrus case, the PDFs are approximately Gaussian. However, in the interior of the deep, convectively unstable case, the PDFs of w are multi-modal and very broad, indicating that parameterizing cloud-scale motions for such clouds can be very challenging. The results of this research are described in detail in a paper submitted to the Journal of Atmospheric Science (Wu and Cotton, 1999), which is enclosed as Appendix 2. Using soundings extracted from a mesoscale simulation of the November 26, 1991 cirrus event, the radiative effects on vapor deposition/sublimation of ice crystals was studied using a two-dimensional cloud-resolving model (CRM) version of RAMS, coupled to an explicit bin-resolving microphysics. The CRM simulations of the November 26, 1991 cirrus event demonstrate that the radiative impact on the diffusional growth (or sublimation) of ice crystals is significant. In this case, the ice particles experienced radiative warming. Model results show that radiative feedbacks in the diffusional growth of ice particles can be very complex. Radiative warming of an ice particle will restrict the particle's diffusional growth. In the case of radiative warming, ice particles larger than a certain size will experience so much radiative warming that surface ice saturation vapor pressures become large enough to cause sublimation of the larger crystals, while smaller crystals are growing by vapor deposition. However, ice mass production can be enhanced in the case of radiative cooling of an ice particle. For the November 26, 1991 cirrus event, radiative feedback results in significant reduction in the total ice mass, especially in the production of large ice crystals, and consequently, both radiative and dynamic properties of the cirrus cloud are significantly affected. A complete description of this research has been submitted as a paper to the Journal of Atmospheric Science (Wu et al., 1999), and included as Appendix 3.

Wu, Ting↗

Spatial Distribution of Volcanic Hotspots and Paterae on Io: Implications for Tidal Heating Models and Magmatic Pathways

Io, the innermost of Jupiter's Galilean satellites, is the most volcanically active body in the Solar. System. Io's global mean heat flow is approximately 2 W/square m, which is approximately 20 times larger than on Earth. High surface temperatures concentrate within "hotspots" and, to date, 172 Ionian hotspots have been identified by spacecraft and Earth-based telescopes. The Laplace resonance between Io, Europa, and Ganymede maintains these satellites in noncircular orbits and causes displacement of their tidal bulges as the overhead position of Jupiter changes for each moon. Gravitational interactions between Jupiter and Io dominate the orbital evolution of the Laplacian system and generate enormous heat within to as tidal energy is dissipated. If this energy were transferred out of Io at the same rate as it is generated, then the associated surface heat flux would be 2.24 +/- 0.45 W/square m. This estimate is in good agreement with observed global heat flow, but to better constrain tidal dissipation mechanisms and infer how thermal energy is transferred to Io's surface, it is critical to closely examine the spatial distribution of volcanic features. End-member tidal dissipation models either consider that heating occurs completely in the mantle, or completely in the asthenosphere. Mixed models typically favor one-third mantle and two-thirds asthenosphere heating. Recent models also consider the effects of mantle-asthenosphere boundary permeability and asthenospheric instabilities. Deep-mantle heating models predict maximum surface heat flux near the poles, whereas asthenosphere heating models predict maxima near the equator-particularly in the Sub-Jovian and Anti-Jovian hemispheres, with smaller maxima occurring at orbit tangent longitudes. Previous studies have examined the global distribution of Ionian hotspots and patera (i.e., irregular or complex craters with scalloped edges that are generally interpreted to be volcanic calderas), but in this study, we combine a new geospatial analysis technique with an improved hotspot and paterae database .

Hamilton, C. W.↗

Analysis of High-Speed Aerodynamics of a Swept Wing with Seamless Flaps

Computational fluid dynamics (CFD) analysis was conducted to evaluate the high-speed aerodynamics of a Gulfstream GIII airplane (Gulfstream Aerospace Corporation, Savannah, Georgia) swept wing modified with an experimental seamless, compliant flap called the Adaptive Compliant Trailing Edge (ACTE) flap for airworthiness. The high-speed aerodynamics of the modified ACTE wing were analyzed at a Mach number of 0.85 and an altitude of 40,000 ft. A polyhedral finite-volume unstructured Reynolds-averaged Navier-Stokes CFD code was used with a two-equation turbulence model. Wing aerodynamics sensitivities to lift coefficients, airplane engine operation, vortex generators (VGs), and ACTE flap deflections were examined. High-speed flow over the clean GIII wing without VGs was found to be complex with outboard shock and boundary-layer interactions causing flow separation over the upper wing surface upstream of the aileron, which could result in buffet and controllability problems at higher lift coefficient values. The VGs were found to improve the high-speed aerodynamics of the clean wing, as expected; however, ACTE flap deflections of as little as 1 to 2 deg were found to negate all of the aerodynamic benefits provided by the VGs at high speeds.

wings↗

MBSE Applications for the MSR SRC Mars Ascent Vehicle

The objective of the NASA Mars Sample Return (MSR) Campaign is to collect samples from the surface of Mars and return them to Earth for scientific research. The Mars Ascent Vehicle (MAV) will be integrated into a larger Mars Sample Retrieval Lander (SRL) for transit to and storage on Mars. After all Martian samples have been collected and loaded into the MAV payload assembly, MAV will deliver the samples from the Martian surface to Mars orbit. A separate spacecraft, the Earth Return Orbiter (ERO) will retrieve the samples from Mars orbit and return them to Earth. To address common systems engineering challenges associated with using traditional systems engineering practices on complex projects, the MAV systems engineering team has explored implementation of Model-Based Systems Engineering (MBSE) tools and languages. This paper describes the current state of implementation and development of the MAV MBSE model with the Systems Modeling Language (SysML) within the scope of the MAV Systems Requirement Cycle (SRC) systems engineering workflow. The MAV MBSE model has been developed within Magic Draw – a SysML editor commonly used to implement MBSE. The MAV MBSE model has been used to develop mission phase functional flow diagrams for the Concept of Operations, decompose mission to vehicle subsystem functions, develop a functional decomposition, derive functional requirements, trace requirements up to customer-imposed requirements, trace requirements within MAV requirement space, identify requirements trace gaps, define and map the physical design space architecture, allocate requirements to subsystems, develop validation items, define assembly, integration, and test (AI&T) operations, and trace these items across driving goals to develop an integrated digital thread of systems engineering information used to drive design specifications, decision making, and ultimately design verification and validation. Findings and results associated with implementing MBSE in these ways, alongside traditional methods will be discussed.

MBSE↗

MBSE Applications for the MSR SRC Mars Ascent Vehicle

The objective of the NASA Mars Sample Return (MSR) Campaign is to collect samples from the surface of Mars and return them to Earth for scientific research. The Mars Ascent Vehicle (MAV) will be integrated into a larger Mars Sample Retrieval Lander (SRL) for transit to and storage on Mars. After all Martian samples have been collected and loaded into the MAV payload assembly, MAV will deliver the samples from the Martian surface to Mars orbit. A separate spacecraft, the Earth Return Orbiter (ERO) will retrieve the samples from Mars orbit and return them to Earth. To address common systems engineering challenges associated with using traditional systems engineering practices on complex projects, the MAV systems engineering team has explored implementation of Model-Based Systems Engineering (MBSE) tools and languages. This paper describes the current state of implementation and development of the MAV MBSE model with the Systems Modeling Language (SysML) within the scope of the MAV Systems Requirement Cycle (SRC) systems engineering workflow. The MAV MBSE model has been developed within Magic Draw – a SysML editor commonly used to implement MBSE. The MAV MBSE model has been used to develop mission phase functional flow diagrams for the Concept of Operations, decompose mission to vehicle subsystem functions, develop a functional decomposition, derive functional requirements, trace requirements up to customer-imposed requirements, trace requirements within MAV requirement space, identify requirements trace gaps, define and map the physical design space architecture, allocate requirements to subsystems, develop validation items, define assembly, integration, and test (AI&T) operations, and trace these items across driving goals to develop an integrated digital thread of systems engineering information used to drive design specifications, decision making, and ultimately design verification and validation. Findings and results associated with implementing MBSE in these ways, alongside traditional methods will be discussed.

MBSE↗