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In this volume, volume 4 (of five volumes), the discussion is focussed on the system models and related data references and has the following subsections: space shuttle main engine, integrated solid rocket booster, orbiter auxiliary power units/hydraulics, and electrical power system.
Ongoing integration of outrunner brushless electric motors into drones and Advanced Air Mobility aircraft presents a need for accurate acoustic predictions derived from prediction of the motor rotor vibrations. In outrunner motors, the external rotor vibrates and drives the acoustic field. At resonant frequencies of the rotor, the rotor displacements will be the largest. The vibrations can lead to acoustic tones that are relevant to the overall acoustic design of these types of vehicles. This study performs a finite element analysis to assess the modes in two electric motor rotors. This model is then refined into a simple parameterized geometry that can make the same predictions for motors of the same class. A parametric sweep and least-squares-curve fit to the finite element analysis data results in a series of simple curves that can predict the mode shapes and frequencies that are likely to appear in this class of motors without the need for any simulation. The simulations are validated by comparison to acoustic and experimental modal-analysis data.
Ongoing integration of outrunner brushless electric motors into drones and Advanced Air Mobility aircraft presents a need for accurate acoustic predictions derived from prediction of the motor rotor vibrations. In outrunner motors, the external rotor vibrates and drives the acoustic field. At resonant frequencies of the rotor, the rotor displacements will be the largest. The vibrations can lead to acoustic tones that are relevant to the overall acoustic design of these types of vehicles. This study performs a finite element analysis to assess the modes in two electric motor rotors. This model is then refined into a simple parameterized geometry that can make the same predictions for motors of the same class. A parametric sweep and least-squares-curve fit to the finite element analysis data results in a series of simple curves that can predict the mode shapes and frequencies that are likely to appear in this class of motors without the need for any simulation. The simulations are validated by comparison to acoustic and experimental modal-analysis data.
Challenge and Motivation: The ocean plays a critical role in mitigating climate change by removing approximately a quarter of annual anthropogenic CO 2 emissions from the atmosphere. Model-based estimates point to the Southern Ocean as a key marine region, responsible for approximately 40 % of the anthropogenic carbon uptake by the global ocean. However, the contemporary strength of the Southern Ocean carbon sink has recently come into question. On the one hand, airborne-based observations of atmospheric CO 2 gradients indicate that the Southern Ocean represents a strong net sink of atmospheric CO 2 , consistent in magnitude with atmospheric inversion estimates and surface-ocean partial pressure of CO 2 (pCO 2 )-based products. On the other hand, estimates of pCO 2 based on in situ pH measurements taken by biogeochemical profiling floats yield strong wintertime outgassing fluxes that greatly reduce the Southern Ocean’s annually integrated CO 2 uptake. This uncertainty in the strength of the Southern Ocean air-sea CO 2 flux and its role in the global carbon cycle hinders our ability to constrain global carbon fluxes, one of the major goals of NASA’s Carbon Monitoring System (CMS). Opportunity: The NASA Ocean Biogeochemical Model (NOBM) produces near-global pCO 2 and air-sea CO 2 flux estimates that are currently included into the NASA’s Goddard Earth Observing System (GEOS) models in support of the CMS effort to monitor global carbon fluxes. The NOBM assimilates ocean color data to improve the representation of biogeochemical fluxes and overcome spatial and temporal gaps in the space-based retrievals. Here, we propose to advance the satellite-constrained flux estimates by investigating the uncertainties in the Southern Ocean air-sea CO 2 flux produced by the NOBM, and assess the value that remote sensing ocean color data can have in providing improved estimates of carbon fluxes in the ocean. Our proposed work includes the delivery of refined in situ float-based carbon fluxes to serve as a constraint on the model-based estimates. Taking advantage of the model’s integration of satellite ocean color data to represent multiple phytoplankton groups, we propose to deliver maps of biogenic carbon export specific to each modeled phytoplankton type and investigate the role of ecological plankton complexity in regulating marine carbon uptake and export. Goals: (a) Delivery of seasonally-adjusted float-based Southern Ocean air-sea CO 2 fluxes: We will produce updated and improved float-based air-sea CO 2 fluxes that will serve as a bias-reduced float-based constraint to evaluate our model-based estimates of the NOBM. (b) Investigation of uncertainties in Southern Ocean air-sea CO 2 flux from the NOBM: Modeled air-sea carbon fluxes will be evaluated against the updated float product as well as ship- and airborne-based data to identify uncertainties and potential model deficiencies. (c) Delivery of model-based carbon export partitioning by phytoplankton functional types (PFTs): We will produce depth-resolved maps of particulate organic export production integrated for all phytoplankton groups and allocated to each individual PFT in the model. The expected significance of this goal is to quantify the role that the functional-oriented diversity in phytoplankton groups represented in the NOBM plays in regulating air-sea CO 2 fluxes in the Southern Ocean.
NASA Space Radiation Program Element scientists have been actively involved in development of an integrative risk models toolkit that includes models for acute radiation risk and organ dose projection (ARRBOD), NASA space radiation cancer risk projection (NSCR), hemocyte dose estimation (HemoDose), GCR event-based risk model code (GERMcode), and relativistic ion tracks (RITRACKS), NASA radiation track image (NASARTI), and the On-Line Tool for the Assessment of Radiation in Space (OLTARIS). This session will introduce the components of the risk toolkit with opportunity for hands on demonstrations. The brief descriptions of each tools are: ARRBOD for Organ dose projection and acute radiation risk calculation from exposure to solar particle event; NSCR for Projection of cancer risk from exposure to space radiation; HemoDose for retrospective dose estimation by using multi-type blood cell counts; GERMcode for basic physical and biophysical properties for an ion beam, and biophysical and radiobiological properties for a beam transport to the target in the NASA Space Radiation Laboratory beam line; RITRACKS for simulation of heavy ion and delta-ray track structure, radiation chemistry, DNA structure and DNA damage at the molecular scale; NASARTI for modeling of the effects of space radiation on human cells and tissue by incorporating a physical model of tracks, cell nucleus, and DNA damage foci with image segmentation for the automated count; and OLTARIS, an integrated tool set utilizing HZETRN (High Charge and Energy Transport) intended to help scientists and engineers study the effects of space radiation on shielding materials, electronics, and biological systems.
A major task of the program to develop an expert system to predict the loads on selected components of a generic space propulsion engine is the design development and application of a probabilitic loads model. This model is being developed in order to account for the random nature of the loads and assess the variable load ranges' effect on the engine performance. A probabilistic model has been developed. The model is based primarily on simulation methods, but also has a Gaussian algebra method (if all variables are near normal), a fast probability integrator routine (for the calculation of low probability events), and a separate, stand alone program for performing barrier crossing calculations. Each of these probabilistic methods has been verified with theoretical calculations using assumed distributional forms.
In an attempt to improve the land cover/use classification accuracy obtainable from remotely sensed multispectral imagery, Airborne Imaging Spectrometer-1 (AIS-1) images were analyzed in conjunction with Thematic Mapper Simulator (NS001) Large Format Camera color infrared photography and black and white aerial photography. Specific portions of the combined data set were registered and used for classification. Following this procedure, the resulting derived data was tested using an overall accuracy assessment method. Precise photogrammetric 2D-3D-2D geometric modeling techniques is not the basis for this study. Instead, the discussion exposes resultant spectral findings from the image-to-image registrations. Problems associated with the AIS-1 TMS integration are considered, and useful applications of the imagery combination are presented. More advanced methodologies for imagery integration are needed if multisystem data sets are to be utilized fully. Nevertheless, research, described herein, provides a formulation for future Earth Observation Station related multisensor studies.
This report documents efforts to analyze a sample of aviation safety programs, using the LMI-developed integrated safety analysis tool to determine the change in system risk resulting from Aviation Safety Program (AvSP) technology implementation. Specifically, we have worked to modify existing system safety tools to address the safety impact of synthetic vision (SV) technology. Safety metrics include reliability, availability, and resultant hazard. This analysis of SV technology is intended to be part of a larger effort to develop a model that is capable of "providing further support to the product design and development team as additional information becomes available". The reliability analysis portion of the effort is complete and is fully documented in this report. The simulation analysis is still underway; it will be documented in a subsequent report. The specific goal of this effort is to apply the integrated safety analysis to SV technology. This report also contains a brief discussion of data necessary to expand the human performance capability of the model, as well as a discussion of human behavior and its implications for system risk assessment in this modeling environment.
The NASA Digital Astronaut Project (DAP) implements well-vetted computational models to predict and assess spaceflight health and performance risks, and to enhance countermeasure development. The DAP Musculoskeletal Modeling effort is developing computational models to inform exercise countermeasure development and to predict physical performance capabilities after a length of time in space. For example, integrated exercise device-biomechanical models can determine localized loading, which will be used as input to muscle and bone adaptation models to estimate the effectiveness of the exercise countermeasure. In addition, simulations of mission tasks can be used to estimate the astronaut's ability to perform the task after exposure to microgravity and after using various exercise countermeasures. The software package OpenSim (Stanford University, Palo Alto, CA) (Ref. 1) is being used to create the DAP biomechanical models and its built-in muscle model is the starting point for the DAP muscle model. During Exploration missions, such as those to asteroids and Mars, astronauts will be exposed to reduced gravity for extended periods. Therefore, the crew must have access to exercise countermeasures that can maintain their musculoskeletal and aerobic health. Exploration vehicles may have very limited volume and power available to accommodate such capabilities, even more so than the International Space Station (ISS). The exercise devices flown on Exploration missions must be designed to provide sufficient load during the performance of various resistance and aerobic/anaerobic exercises while meeting potential additional requirements of limited mass, volume and power. Given that it is not practical to manufacture and test (ground, analog and/or flight) all candidate devices, nor is it always possible to obtain data such as localized muscle and bone loading empirically, computational modeling can estimate the localized loading during various exercise modalities performed on a given device to help formulate exercise prescriptions and other operational considerations. With this in mind, NASA's Digital Astronaut Project (DAP) is supporting the Advanced Exercise Concepts (AEC) Project, Exercise Physiology and Countermeasures (ExPC) laboratory and NSBRI-funded researchers by developing and implementing well-validated computational models of exercises with advanced exercise device concepts. This report focuses specifically on lower-body resistance exercises performed with the Hybrid Ultimate Lifting Kit (HULK) device as a deliverable to the AEC Project.
The National Aeronautics and Space Administration's (NASA) Airspace Systems Program is contributing air traffic management research in support of the 2025 Next Generation Air Transportation System (NextGen). Contributions support research and development needs provided by the interagency Joint Planning and Development Office (JPDO). These needs generally call for integrated technical solutions that improve system-level performance and work effectively across multiple domains and planning time horizons. In response, the Airspace Systems Program is pursuing an integrated research approach and has adapted systems engineering best practices for application in a research environment. Systems engineering methods aim to enable researchers to methodically compare different technical approaches, consider system-level performance, and develop compatible solutions. Systems engineering activities are performed iteratively as the research matures. Products of this approach include a demand and needs analysis, system-level descriptions focusing on NASA research contributions, system assessment and design studies, and common systemlevel metrics, scenarios, and assumptions. Results from the first systems engineering iteration include a preliminary demand and needs analysis; a functional modeling tool; and initial system-level metrics, scenario characteristics, and assumptions. Demand and needs analysis results suggest that several advanced concepts can mitigate demand/capacity imbalances for NextGen, but fall short of enabling three-times current-day capacity at the nation s busiest airports and airspace. Current activities are focusing on standardizing metrics, scenarios, and assumptions, conducting system-level performance assessments of integrated research solutions, and exploring key system design interfaces.
The photon-scattering winds of cool, low-gravity stars (K-M giants and supergiants) produce absorption features in the strong chromospheric emission lines. This provides us with an opportunity to assess important parameters of the wind, including flow and turbulent velocities, the optical depth of the wind above the region of photon creation, and the star's mass-loss rate. We have used the Lamers et al. Sobolev with Exact Integration (SEI) radiative transfer code along with simple models of the outer atmospheric structure to compute synthetic line profiles for comparison with the observed line profiles. The SEI code has the advantage of being computationally fast and allows a great number of possible wind models to be examined. We therefore use it here to obtain initial first-order estimates of the wind parameters. More sophisticated, but more time-consuming and resource intensive calculations will be performed at a later date, using the SEI-deduced wind parameters as a starting point. A comparison of the profiles over a range of wind velocity laws, turbulence values, and line opacities allows us to constrain the wind parameters, and to estimate the mass-loss rates. We have applied this analysis technique (using lines of Mg II, 0 I, and Fe II) so far to four stars: the normal K5-giant alpha Tau, the hybrid K-giant gamma Dra, the K5 supergiant lambda Vel, and the M-giant gamma Cru. We present in this paper a description of the technique, including the assumptions which go into its use, an assessment of its robustness, and the results of our analysis.
Spruce beetle-induced (Dendroctonus rufipennis (Kirby)) mortality on the Kenai Peninsula has been hypothesized by local ecologists to result in the conversion of forest to grassland and subsequent increased fire danger. This hypothesis stands in contrast to empirical studies in the continental US which suggested that beetle mortality has only a negligible effect on fire danger. In response, we conducted a study using Landsat data and modeling techniques to map land cover change in the Kenai Peninsula and to integrate change maps with other geospatial data to predictively map fire danger for the same region. We collected Landsat imagery to map land cover change at roughly five-year intervals following a severe, mid-1990s beetle infestation to the present. Landcover classification was performed at each time step and used to quantify grassland encroachment patterns over time. The maps of land cover change along with digital elevation models (DEMs),temperature, and historical fire data were used to map and assess wildfire danger across the study area. Results indicate the highest wildfire danger tended to occur in herbaceous and black spruce land cover types, suggesting that the relationship between spruce beetle damage and wildfire danger in costal Alaskan forested ecosystems differs from the relationship between the two in the forests of the coterminous United States. These change detection analyses and fire danger predictions provide the Kenai National Wildlife Refuge (KENWR) ecologists and other forest managers a better understanding of the extent and magnitude of grassland conversion and subsequent change in fire danger following the 1990s spruce beetle outbreak.
Climate change presents a great challenge to the agricultural sector as changes in precipitation, temperature, humidity, and circulation patterns alter the climatic conditions upon which many agricultural systems rely. Projections of future climate conditions are inherently uncertain owing to a lack of clarity on how society will develop, policies that may be implemented to reduce greenhouse-gas (GHG) emissions, and complexities in modeling the atmosphere, ocean, land, cryosphere, and biosphere components of the climate system. Global climate models (GCMs) are based on well-established physics of each climate component that enable the models to project climate responses to changing GHG concentration scenarios (Stocker et al., 2013).The most recent iteration of the Coupled Model Intercomparison Project (CMIP5; Taylor et al., 2012) utilized representative concentration pathways (RCPs) to cover the range of plausible GHG concentrations out past the year 2100, with RCP8.5 representing an extreme scenario and RCP4.5 representing a lower concentrations scenario (Moss et al., 2010).
This paper describes the spectral analysis of integrated pressures on patches of the scale model of the Space Launch System (SLS) Block 1B crew vehicle with the Unsteady Pressure-Sensitive Paint (uPSP) measurements, which were collected in the ascent transient aerodynamics tests with the Unitary Plan Wind Tunnel 11-by-11-foot Transonic Wind Tunnel in September 2019 at NASA Ames Research Center. Recent research has demonstrated that uPSP can be an essential tool for the assessment of the unsteady, aerodynamic phenomena. The work described in this paper is a part of NASA’s development of a new state-of-the-art uPSP capability in production wind tunnels. In this paper, 108 patches are defined with x station values and azimuth angles of the scale model. For each patch, the polygons are determined from the surface cells of the grid of the model, clipped with the edges of the patch, and each of the polygons is divided into triangles. The inputs of the pressure integration algorithm are the time series of pressure coefficients on the vertices of the grid of the model, generated by the uPSP data processing program from the videos taken with 4 Phantom high-speed cameras during the wind tunnel tests. The integrated pressure of the patch is determined as the ratio of the sum of the forces on the triangles over the sum of the areas of the triangles. For each of the test cases, the Cross Power Spectral Density (CPSD) and Magnitude-Squared Coherence (msCohere) are computed for frequencies over 1/3 octave bands from the time series of the integrated pressures on the patches. The spectral analysis outputs of different cases of the wind tunnel tests are analyzed and the coherence of patches is investigated over frequencies, x station values, azimuth angles, Mach numbers and SLS vehicle attitudes. The pressure integration and spectral analysis described in this paper were executed on the NASA Pleiades supercomputer. Funding for this research was provided by the NASA Aeroscience Evaluation and Test Capabilities (AETC) Project.
The National Facility Study (NFS) was initiated in 1992 by Daniel S. Goldin, Administrator of NASA as an initiative to develop a comprehensive and integrated long-term plan for future facilities. The resulting, multi-agency NFS consisted of three Task Groups: Aeronautics, Space Operations, and Space Research and Development (R&D) Task Groups. A fourth group, the Engineering and Cost Analysis Task Group, was subsequently added to provide cross-cutting functions, such as assuring consistency in developing an inventory of space facilities. Space facilities decisions require an assessment of current and future needs. Therefore, the two task groups dealing with space developed a consistent model of future space mission programs, operations and R&D. The model is a middle ground baseline constructed for NFS analytical purposes with excursions to cover potential space program strategies. The model includes three major sectors: DOD, civilian government, and commercial space. The model spans the next 30 years because of the long lead times associated with facilities development and usage. This document, Volume 3 of the final NFS report, is organized along the following lines: Executive Summary -- provides a summary view of the 30-year mission forecast and requirements baseline, an overview of excursions from that baseline that were studied, and organization of the report; Introduction -- provides discussions of the methodology used in this analysis; Baseline Model -- provides the mission and requirements model baseline developed for Space Operations and Space R&D analyses; Excursions from the baseline -- reviews the details of variations or 'excursions' that were developed to test the future program projections captured in the baseline; and a Glossary of Acronyms.
Controlling carbon dioxide (CO2) and water (H2O) vapor concentrations in a space suit is critical to ensuring an astronauts safety, comfort, and capability to perform extra-vehicular activity (EVA) tasks. Historically, this has been accomplished using lithium hydroxide (LiOH) and metal oxide (MetOx) canisters. Lithium hydroxide is a consumable material that requires priming with water before it becomes effective at removing carbon dioxide. MetOx is regenerable through a power-intensive thermal cycle but is significantly heavier on a volume basis than LiOH. As an alternative, amine-based vacuum swing beds are under aggressive development for EVA applications. The vacuum swing units control atmospheric concentrations of both CO2 and H2O through fully-regenerative process. The current concept, referred to as the rapid cycle amine (RCA), has resulted in numerous laboratory prototypes. Performance of these prototypes have been assessed experimentally and documented in previous reports. To support developmental e orts, a first principles model has also been established for the vacuum swing sorption technology. For the first time in several decades, a major re-design of Portable Life Support System (PLSS) for the extra-vehicular mobility unit (EMU) is underway. NASA at Johnson Space Center built and tested an integrated PLSS test bed of all subsystems under a variety of simulated EVA conditions of which the RCA prototype played a significant role. The efforts documented herein summarize RCA test performance and simulation results for single and variable metabolic rate experiments in an integrated context. In addition, a variety of off-nominal tests were performed to assess the capability of the RCA to function under challenging circumstances. Tests included high water production experiments, degraded vacuum regeneration, and deliberate valve/power failure and recovery.
We ask how lightning measurements might best be used to improve short-term (0-24 hr) weather forecasting. We examine recently developed strategies for the integration of lightning data into Short-term forecasts (nowcasts) of convective and severe weather hazards and the assimilation of lightning data into numerical weather prediction models. In each strategy we define specific metrics of forecast improvement and a progress assessment. We also address the conventional observing system deficiencies and potential gap-filling information that can be addressed through the use of the lightning measurement.
Quantifying the probability of significant launch vehicle failure scenarios for a given design, while still in the design process, is critical to mission success and to the safety of the astronauts. Probabilistic risk assessment (PRA) is chosen from many system safety and reliability tools to verify the loss of mission (LOM) and loss of crew (LOC) requirements set by the NASA Program Office. To support the integrated vehicle PRA, probabilistic design analysis (PDA) models are developed by using vehicle design and operation data to better quantify failure probabilities and to better understand the characteristics of a failure and its outcome. This PDA approach uses a physics-based model to describe the system behavior and response for a given failure scenario. Each driving parameter in the model is treated as a random variable with a distribution function. Monte Carlo simulation is used to perform probabilistic calculations to statistically obtain the failure probability. Sensitivity analyses are performed to show how input parameters affect the predicted failure probability, providing insight for potential design improvements to mitigate the risk. The paper discusses the application of the PDA approach in determining the probability of failure for two scenarios from the NASA Ares I project