Results for “based” — Page 29

NASA NTRS2016

Lidar-Based Estimates of Above-Ground Biomass in the Continental US and Mexico Using Ground, Airborne, and Satellite Observations

Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar measurements. Two sets of models are generated, the first relating ground estimates of AGB to airborne laser scanning (ALS) measurements and the second set relating ALS estimates of AGB (generated using the first model set) to GLAS measurements. GLAS then, is used as a sampling tool within a hybrid estimation framework to generate stratum-, state-, and national-level AGB estimates. A two-phase variance estimator is employed to quantify GLAS sampling variability and, additively, ALS-GLAS model variability in this current, three-phase (ground-ALS-space lidar) study. The model variance component characterizes the variability of the regression coefficients used to predict ALS-based estimates of biomass as a function of GLAS measurements. Three different types of predictive models are considered in CONUS to determine which produced biomass totals closest to ground-based national forest inventory estimates - (1) linear (LIN), (2) linear-no-intercept (LNI), and (3) log-linear. For CONUS at the national level, the GLAS LNI model estimate (23.95 +/- 0.45 Gt AGB), agreed most closely with the US national forest inventory ground estimate, 24.17 +/- 0.06 Gt, i.e., within 1%. The national biomass total based on linear ground-ALS and ALS-GLAS models (25.87 +/- 0.49 Gt) overestimated the national ground-based estimate by 7.5%. The comparable log-linear model result (63.29 +/-1.36 Gt) overestimated ground results by 261%. All three national biomass GLAS estimates, LIN, LNI, and log-linear, are based on 241,718 pulses collected on 230 orbits. The US national forest inventory (ground) estimates are based on 119,414 ground plots. At the US state level, the average absolute value of the deviation of LNI GLAS estimates from the comparable ground estimate of total biomass was 18.8% (range: Oregon,−40.8% to North Dakota, 128.6%). Log-linear models produced gross overestimates in the continental US, i.e., N2.6x, and the use of this model to predict regional biomass using GLAS data in temperate, western hemisphere forests is not appropriate. The best model form, LNI, is used to produce biomass estimates in Mexico. The average biomass density in Mexican forests is 53.10 +/- 0.88 t/ha, and the total biomass for the country, given a total forest area of 688,096 sq km, is 3.65 +/- 0.06 Gt. In Mexico, our GLAS biomass total underestimated a 2005 FAO estimate (4.152 Gt) by 12% and overestimated a 2007/8 radar study's figure (3.06 Gt) by 19%.

Hybrid 3-Phase sampling↗

NASA NTRS2018

SLS Navigation Model-Based Design Approach

The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and management of design requirements to the development of usable models, model requirements, and model verification and validation efforts. The models themselves are represented in C/C++ code and accompanying data files. Under the idealized process, potential ambiguity in specification is reduced because the model must be implementable versus a requirement which is not necessarily subject to this constraint. Further, the models are shown to emulate the hardware during validation. For models developed by the Navigation Team, a common interface/standalone environment was developed. The common environment allows for easy implementation in design and analysis tools. Mechanisms such as unit test cases ensure implementation as the developer intended. The model verification and validation process provides a very high level of component design insight. The origin and implementation of the SLS variant of Model-based Design is described from the perspective of the SLS Navigation Team. The format of the models and the requirements are described. The Model-based Design approach has many benefits but is not without potential complications. Key lessons learned associated with the implementation of the Model Based Design approach and process from infancy to verification and certification are discussed

Oliver, T. Emerson↗

NASA NTRS2017

Optical Diagnostic Imaging of Multi-Rocket Plume-Induced Base Flow Environments

Non-intrusive optical diagnostic imaging was used for the first time to visualize multi-rocket plume-induced reacting base flows to simulate launch vehicle ascent from sea-level to 250,000 ft. In particular, planar laser induced florescence (PLIF) and infrared (IR) imaging were implemented for the first time to visualize and quantify base flow and rocket plume environments from sub-scale, short-duration propulsion models within a shock tunnel facility. This report discusses the successful imaging diagnostic methods for capturing base flow features and dynamics as a function of altitude. Important base flow and plume features were captured with PLIF and IR diagnostics to develop a conceptual base flow physics model. This imaging data specifically provides insight into the Space Launch System vehicle core-stage and Exploration Upper Stage base environments and further validates short-duration ground test techniques and computational modeling.

Mehta, Manish↗

NASA NTRS2019

Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia)

Satellite-based precipitation is an essential tool for regional water resource applications that requires frequent observations of meteorological forcing, particularly in areas that have sparse rain gauge networks. To fully realize the utility of remotely sensed precipitation products in watershed modeling and decision-making, a thorough evaluation of the accuracy of satellite-based rainfall and regional gauge network estimates is needed. In this study, Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42 v.7 and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) daily rainfall estimates were compared with daily rain gauge observations from 2000 to 2014 in the Lower Mekong River Basin (LMRB) in Southeast Asia. Monthly, seasonal, and annual comparisons were performed, which included the calculations of correlation coefficient, coefficient of determination, bias, root mean square error (RMSE), and mean absolute error (MAE). Our validation test showed TMPA to correctly detect precipitation or no-precipitation 64.9% of all days and CHIRPS 66.8% of all days, compared to daily in-situ rainfall measurements. The accuracy of the satellite-based products varied greatly between the wet and dry seasons. Both TMPA and CHIRPS showed higher correlation with in-situ data during the wet season (June–September) as compared to the dry season (November–January). Additionally, both performed better on a monthly than an annual time-scale when compared to in-situ data. The satellite-based products showed wet biases during months that received higher cumulative precipitation. Based on a spatial correlation analysis, the average r-value of CHIRPS was much higher than TMPA across the basin. CHIRPS correlated better than TMPA at lower elevations and for monthly rainfall accumulation less than 500 mm. While both satellite-based products performed well, as compared to rain gauge measurements, the present research shows that CHIRPS might be better at representing precipitation over the LMRB than TMPA.

Dandridge, Chelsea↗

NASA NTRS2019

Adjoint-Based Anisotropic Mesh Adaptation for a Stabilized Finite-Element Flow Solver

An adjoint solver is implemented in the FUN3D stabilized finite-element flow solver. The adjoint solution is used to generate anisotropic, adapted meshes to control error in scalar out- put functionals, such as lift or drag coefficient. The inviscid and turbulent adjoints are verified with a finite-difference derivative approximation and can be used in design optimization in addition to mesh adaptation. The adjoint capability represents an extension of previous research using the FUN3D stabilized finite-element capability with metric-based mesh adaptation and interpolation-based error estimates to generate highly anisotropic adapted meshes for turbulent flows. In the present work, a metric-based approach is again utilized, where the adjoint and the primal solutions both contribute to the generation of a metric tensor field that is subsequently used to produce the required anisotropic mesh for each adaptation cycle. Adaptive results are then shown for an inviscid supersonic flow over a diamond airfoil, inviscid transonic flow over the ONERA M6 wing, and viscous laminar flow over the NACA 0012 airfoil, all using drag force as the output functional. Adjoint-based adaptation is compared with a multiscale solution-based approach that controls the L norm of Mach number interpolation error to demonstrate the effectiveness and effciency of the adjoint-based adaptive mesh technology.

Balan, Aravind↗

NASA NTRSDate not supplied

HydroSAR: A Cloud-based SAR Data Analysis Service to Monitor Hydrological Disasters and their Impact on Population and Agriculture

Weather-related hazards are ubiquitous around the world including: 1) hurricane storm surges, 2) rapid snowmelt and heavy rainfall, 3) severe weather leading to flash floods, and 4) seasonal freeze and thaw of rivers that may lead to ice jams. Each of these hazards affects human settlements and has the potential to impact agricultural productivity. In each setting, end-users in disaster management need access to data processing tools helpful in mapping past and current disasters. Analysis of past events supports risk mitigation by understanding what has already occurred and how to alleviate those impacts in the future. Having capabilities to generate the same products in a response setting means that lessons learned from risk analysis will carry forward to event response. Synthetic aperture radar (SAR) data are particularly useful for these activities due to their all-weather 24/7 monitoring capabilities. In this effort we present HydroSAR, a cloud-based SAR data analysis service for the mapping of meteorological and hydrological disasters as well as their impact on population and agriculture. As part of this project we have developed a series of SAR-based value added products for the monitoring of surface hydrology (image time series, change detection, flood extent, flood depth) and the assessment of impacts on population (flood depth) and agriculture (active agriculture, inundated agriculture, flood duration). We also developed a cloud-based platform for generating these products over affected areas and are working with end-users to integrate derived product into decision-making workflows The paper will briefly introduce the SAR-based products that were developed for this effort. We describe the cloud-based production pipeline that was built to automatically generate these products in near-real time over extended regions. The integration of SAR-based information into hazard preparation and response activities is described for a number of recent disasters including the 2019 forest fires in Alaska, 2019 flooding in the U.S. Midwest, the 2020 U.S. severe weather easter outbreak, 2020 tropical storm Christobal, 2020 cyclone Amphan, 2020, Alaska Spring breakup flooding, and the 2020 flood season in Eastern India, Bangladesh, and Nepal.

Franz Josef Meyer↗

NASA NTRSDate not supplied

Deep Learning-Based Negotiation Strategy Selection for Cooperative Conflict Resolution in Urban Air Mobility

This paper presents a collaborative conflict resolution technique using deep neural network-based intelligent search of the solution space. This approach offers a rapid convergence to a mutually acceptable solution for real-time conflict resolution, suitable for urban air mobility operations. Furthermore, the presented technique allows operational flexibility to the urban air mobility agents where these agents can collaboratively devise the solution via integrative negotiation, based on their local utility functions, as long as such a solution does not violate the global safety thresholds. The presented machine-to-machine negotiation method is built on our prior work on holistic assessment of the airspace and potential conflict detection implemented at-the-edge, onboard the unmanned aircraft systems. This paper extends the prior work to augment decision-making at-the-edge, thereby, promising a true distributed control architecture for urban air mobility. In this approach, each agent (a) builds a potential in-flight conflict map, (b) identifies the conflicting agents, (c) dynamically prepares a list of alternatives based on its current utility functions, (d) negotiates with the conflicting agents to pick one of these alternatives, and (e) implements the negotiated alternative to mutually resolve the conflict. Note that such an approach does not require a contingency plan to be made pre-flight, as the conflict resolution strategies are decided and negotiated in real time based on the present state of the agent. The contingency plan, if available, can serve as an input to the real-time conflict resolution strategy formulation, and also can be used as a fallback plan in case the negotiation fails and the impacted agents need to switch to a rule-based/supervisory resolution mode from the discussed distributed resolution mode. The presented collaborative negotiation-based conflict resolution technique incorporates a time-dependent reward function to catalyze collaborative resolution by incentivizing the agents with local and global rewards beneficial to their business operations.

Advanced Air Mobility↗

NASA NTRS2018

A Performance-Based Comparison of Deep-Space Navigation using Optical-Communication and Conventional Navigation Techniques: Small Body Missions

Optical communications may be used in future NASA deep-space missions, resulting in much higher data transfer rates. Those optical communication links could also be used for navigation purposes. The performance of deep-space navigation for an asteroid flyby mission using ground-based optical tracking and conventional navigation techniques was investigated in this work. We present the results of variety of asteroid flyby scenarios including low phase and high phase approach angle flybys, one slow flyby in a Trojan tour mission, and also one slow flyby in a Psyche mission. In this task, four different types of observables were simulated, namely ground-based radiometric, spacecraft on-board optical, ground-based optical tracking of spacecraft (astrometry and 2-way range magnitude), and ground-based asteroid astrometry. Different combinations of these four types of observables were compared with currently in-practice ground-based radiometric/on-board optical measurements. The results showed that the ground-based optical tracking is promising and could be a potential candidate for future deep-space navigation. Precise astrometry is not possible for active comets.

McCandless, Sara Elizabeth↗

NASA NTRS2018

A Performance-Based Comparison of Deep-Space Navigation using Optical-Communication and Conventional Navigation Techniques: Small Body Missions

Optical communications may be used in future NASA deep-space missions, resulting in much higher data transfer rates. Those optical communication links could also be used for navigation purposes. The performance of deep-space navigation for an asteroid flyby mission using ground-based optical tracking and conventional navigation techniques was investigated in this work. We present the results of variety of asteroid flyby scenarios including low phase and high phase approach angle flybys, one slow flyby in a Trojan tour mission, and also one slow flyby in a Psyche mission. In this task, four different types of observables were simulated, namely ground-based radiometric, spacecraft on-board optical, ground-based optical tracking of spacecraft (astrometry and 2-way range magnitude), and ground-based asteroid astrometry. Different combinations of these four types of observables were compared with currently in-practice ground-based radiometric/on-board optical measurements. The results showed that the ground-based optical tracking is promising and could be a potential candidate for future deep-space navigation. Precise astrometry is not possible for active comets.

McCandless, Sarah Elizabeth↗

NASA NTRS2021

Pretest Computational Assessment of Boundary Layer Transition in the NASA Juncture Flow Model with an NACA 0015-Based Wing

The first two phases of the NASA Juncture Flow experiment were carried out on a DLR-F6 swept-wing model and were designed to provide “CFD validation-quality” data toward the assessment and improvement of existing CFD turbulence models in predicting onset and extent of three-dimensional separated flow near the wing-juncture trailing-edge region. The next phase of experiments will involve an NACA 0015-based swept wing, as prior risk reduction experiments had indicated that this wing shape resulted in reduced separation near the juncture region than the DLR-F6 wing, thus providing a better option to evaluate the ability of CFD models to predict incipient turbulent separation. The NACA 0015 measurements will also include IR thermography to infer the variation of transition front with respect to an increasing angle of attack. The primary objective of this work is to computationally make a preliminary assessment of the transition front on both surfaces of the NACA 0015 wing at a crank-chord-based Reynolds number of 2.4 x 106 for four different angles of attack, (0°, 2.5°, 5°, and 7.5°) and to determine the dominant mechanisms responsible for transition. This assessment includes both RANS-based transition models from NASA’s OVERFLOW 2.3b flow solver and linear parabolized stability equations (PSE) stability analysis based on the Langley Stability and Transition Analysis code, LASTRAC. Linear PSE results indicate that the upper surface of the wing is dominated by Tollmien- Schlichting (TS) instabilities, and that the laminar flow region shrinks from about 50% chord to a very small region just downstream of the attachment line as the angle of attack is increased from 0° to 7.5°. Consequently, the transition fronts predicted by the Spalart- Allmaras-based amplification factor transport (AFT-2017b) equation model (which accounts for the TS instabilities alone) and the Menter’s shear-stress transport equation (SST2003)- based Langtry-Menter transition model with ability to account for both TS and crossflow effects (LM2015) compare well with those predicted using linear PSE. On the lower surface of the wing, stationary crossflow (CF) instabilities begin to appear on the inboard portion of the wing in addition to the TS-instabilities for the larger angles of attack (5° and 7.5°), further reducing the laminar flow extent within the inboard region. The LM2015 model that accounts for CF effects is able to replicate this trend but appears to predict a slightly earlier transition. The outcome of this effort will inform the experiment and, when the actual experimental data become available, provide further opportunity to assess and improve the various transition models.

CFD modeling↗

NASA NTRS2021

Pretest Computational Assessment of Boundary Layer Transition in the NASA Juncture Flow Model with an NACA 0015-Based Wing

The first two phases of the NASA Juncture Flow experiment were carried out on a DLR-F6 swept-wing model and were designed to provide “CFD validation-quality” data toward the assessment and improvement of existing CFD turbulence models in predicting onset and extent of three-dimensional separated flow near the wing-juncture trailing-edge region. The next phase of experiments will involve an NACA 0015-based swept wing, as prior risk reduction experiments had indicated that this wing shape resulted in reduced separation near the juncture region than the DLR-F6 wing, thus providing a better option to evaluate the ability of CFD models to predict incipient turbulent separation. The NACA 0015 measurements will also include IR thermography to infer the variation of transition front with respect to an increasing angle of attack. The primary objective of this work is to computationally make a preliminary assessment of the transition front on both surfaces of the NACA 0015 wing at a crank-chord-based Reynolds number of 2.4 x 106 for four different angles of attack, (0°, 2.5°, 5°, and 7.5°) and to determine the dominant mechanisms responsible for transition. This assessment includes both RANS-based transition models from NASA’s OVERFLOW 2.3b flow solver and linear parabolized stability equations (PSE) stability analysis based on the Langley Stability and Transition Analysis code, LASTRAC. Linear PSE results indicate that the upper surface of the wing is dominated by Tollmien- Schlichting (TS) instabilities, and that the laminar flow region shrinks from about 50% chord to a very small region just downstream of the attachment line as the angle of attack is increased from 0° to 7.5°. Consequently, the transition fronts predicted by the Spalart- Allmaras-based amplification factor transport (AFT-2017b) equation model (which accounts for the TS instabilities alone) and the Menter’s shear-stress transport equation (SST2003)- based Langtry-Menter transition model with ability to account for both TS and crossflow effects (LM2015) compare well with those predicted using linear PSE. On the lower surface of the wing, stationary crossflow (CF) instabilities begin to appear on the inboard portion of the wing in addition to the TS-instabilities for the larger angles of attack (5° and 7.5°), further reducing the laminar flow extent within the inboard region. The LM2015 model that accounts for CF effects is able to replicate this trend but appears to predict a slightly earlier transition. The outcome of this effort will inform the experiment and, when the actual experimental data become available, provide further opportunity to assess and improve the various transition models.

CFD modeling↗

NASA NTRSDate not supplied

Small Satellite Reliability Initiative (SSRI) Knowledge Base Tool: Use Case Review and Future Functionality and Content Direction

NASA’s Small Satellite Reliability Initiative (SSRI), in conjunction with NASA’s Small Spacecraft Systems Virtual Institute (S3VI), has developed the SSRI Knowledge Base to improve mission confidence for small spacecraft. The SSRI is a collaborative activity with broad participation from civil, Department of Defense, and both national and international commercial space systems providers and stakeholders. The S3VI is jointly sponsored by NASA’s Space Technology Mission Directorate and Science Mission Directorate. The SSRI Knowledge Base is a comprehensive and searchable online tool that consolidates and organizes resources, best practices, and lessons learned from previous small satellite missions sponsored by NASA, other government agencies, and academia. This free, publicly available tool is available to the entire SmallSat community at https://s3vi.ndc.nasa.gov/ssri-kb/. The SSRI Knowledge Base provides vetted, high-quality sources of information on elements that are key to successful small satellite missions. These resources include SSRI working group generated documents and presentations in addition to existing guides, publications, standards, software tools, websites, and books. The Knowledge Base is fully searchable, offers downloadable content when possible, and otherwise links to or references content directly from within the tool. All 58 of the planned topic pages that comprise the SSRI Knowledge Base have been recently completed and include over 450 unique resources that are now available for review. Over the past several months, significant enhancements to the tool’s capabilities have been developed and implemented. These enhancements consist of the completed baseline content, an Application Programming Interface (API), improved user interfaces, new interfaces for crowdsourcing of content and user ratings, and custom website analytics to inform future development. This presentation and paper will discuss the motivation for the SSRI Knowledge Base, review educational use case(s), and outline plans for further development. The 2022 session topic that best fits the abstract (select only one): Coordinating Successful Educational Programs

Small Spacecraft↗

NASA NTRSDate not supplied

Small Satellite Reliability Initiative (SSRI) Knowledge Base Tool: Use Case Review and Future Functionality and Content Direction

The Small Satellite Reliability Initiative (SSRI) Knowledge Base is a comprehensive and searchable online tool that consolidates and organizes resources, best practices, and lessons learned from previous small satellite missions sponsored by NASA, other government agencies, and academia. This free, publicly available tool is available to the entire SmallSat Community. The SSRI Knowledge Base provides vetted, high-quality sources of information on elements that are key to successful small satellite missions. These resources include SSRI working group generated documents and presentations in addition to existing guides, publications, standards, software tools, websites, and books. The Knowledge Base is fully searchable, offers downloadable content when possible, and otherwise links to or references content directly from within the tool. This presentation and paper will discuss the motivation for the SSRI Knowledge Base, review educational use cases, and outline plans for further development. The SSRI is a collaborative activity with broad participation from civil, U.S. Department of Defense, and both national and international commercial space systems providers and stakeholders. NASA’s Small Spacecraft Systems Virtual Institute (S3VI) funds the SSRI Knowledge Base. The S3VI is jointly sponsored by NASA’s Space Technology Mission Directorate and Science Mission Directorate. This presentation and paper will discuss the motivation for the SSRI Knowledge Base, review educational use case(s), and outline plans for further development.

Small Spacecraft↗

NASA NTRSDate not supplied

Using Open Standards and NASA Open Source Simulation Tools to Model Artemis Base Camp Mission Timelines

The United States’ National Aeronautics and Space Administration (NASA) has announced that the Artemis Program will return humans to the Moon, establishing a persistent presence with the Artemis Base Camp (ABC), and extend human exploration to Mars. The NASA Exploration Systems Simulations (NExSyS) team at NASA’s Johnson Space Center is using internationally developed simulation interoperability standards and NASA open source simulation tools to support Artemis concept, analysis, designs, development, training, and ultimately operations. The NExSyS team has been tasked to support early ABC architecture and mission analysis using mission time lines developed by the crew operations mission planning team. The NExSyS team is developing a distributed simulation framework with initial Artemis element implementations to model the ABC mission timelines using the international simulation interoperability standard High Level Architecture (HLA), the Simulation Interoperability Standards Organization’s Space Reference Federation Object Model (SpaceFOM), the NASA open source Trick Simulation Environment, and another NASA open source interface package called TrickHLA. The ABC architecture is composed of a number of key surface elements and resources. Some examples of modeled elements (also known as entities) are landers, habitats, rovers, logistics carriers, and astronauts. Some examples of modeled transferable and consumable resources are power, water, oxygen, nitrogen, scientific samples, and food. These entities and resources are modeled in a collection of individual simulations called Federates. A coordinated collection of interoperable federates is called a Federation and when these federates are tied together in a coordinated simulation run, it is referred to as a Federation Execution. The federates communicate through HLA using data exchange formats defined by a collection of machine readable files called Federation Object Models (FOMs). These FOM files are based on extensions to the SpaceFOM. This enables the instantiation and sharing of objects and interactions between federates in the federation. These provide for entity and resource tracking, object transfer, and data collection. Federate interactions are used to trigger events and notify federates of entity or resource transfers. For the initial implementation, the constituent federates are Trick-based simulations that use TrickHLA to provide the required HLA-base interoperability. These Trick-based simulations provide the required modeling for the individual Artemis elements along with the associated element resources. These federates provide a means to explore traverses between surface elements and exploration sites as scheduled in a mission timeline and explore the affects traverse times have on the overall mission timeline. The mission time lines are modeled using a Trick input file event handling capabilities. Each timeline operation is handled as individual simulation events, and triggered based on previous event status, time of operation, and simulated task completions. In addition, the ABC Federation can be used to perform Monte Carlo analysis. The Monte Carlo tool can vary the inputs, timings, and malfunctions to show how various contingencies in the mission can affect the mission timeline.

Keaton Craig Dodd↗

NASA NTRS2023

Emperor's new clothes: Novel textile-based supercapacitors using sheep wool fiber as electrode substrate

Textile-based supercapacitors (TSCs) are being used to meet the ever-increasing demand for mobile, safe, and convenient energy sources to power personal electronic devices. To that end, the smart textiles used in wearable technology need to be made from highly conductive yarns that are easily manufacturable. To date, synthetic- and cellulosic-based yarns have been exclusively used for the fabrication of TSCs, while other yarns have not been explored. Here, we used conductive protein-based yarns for TSCs and report on the use of wool coated with Ti 3 C 2 T x MXene as a potential electrode material. To knit TSCs, wool and cotton yarns were coated with MXene flakes and their surfaces were characterized using Scanning Electron Microscopy (SEM) and X-Ray Photoelectron Spectroscopy (XPS). The electrochemical characterization was conducted to examine the performance of wool- and cotton-based MXene electrodes as substrates and determine charge storage and resistive behavior. These tests showed that wool TSCs exhibited more pseudocapacitive behavior, while cotton TSCs exhibited a wider current range. At a scan rate of 5 mV/s, cotton TSCs presented an areal capacitance of 823.9 mF/cm 2 while this value for the wool TSCs was 284 mF/cm 2 . The performance of yarns was also tested under various mechanical deformation conditions and after washing in order to assess the stability of TSCs. This study indicates the potential of protein-based yarns as electrode substrates for integration of MXene to fabricate smart textile-based devices.

Alyssa Grube↗

NASA NTRS2024

Thermal Conductivity and Mechanical Properties of Epoxy Composites With Hybridized PAN- and Pitch-Based Fiber Architecture

A series of hybrid polyacrylonitrile- (PAN-) and pitch-based carbon fiber/epoxy composites were fabricated and tested to evaluate the influence of hybrid fiber configurations on composite strength, modulus, and through-thickness thermal conductivity. Two grades of pitch-based fiber were selected based on their thermal conductivity: YSH-60A and YSH-80A from Nippon Graphite. These pitch-based fibers were received in tow form and as plain weave to allow flexibility in the architecture of the multifiber laminate. Two hybridization approaches were followed: (1) interleave of pitch-based fiber weave within braided PAN/epoxy prepreg and (2) incorporation of pitch-based fiber tows within a three-dimensional braided preform. These showed considerable impact on overall composite mechanical properties and through-thickness thermal conductivity.

Polymer Composite↗

NASA NTRSDate not supplied

Determining Optimal Asset Location for Rapid and Efficient Wildfire Suppression: A Simulation-Based Approach

The impact of wildfire incidents has been growing in recent years, posing a serious threat to communities at the urban-wildland interface. To address this problem, there have been growing calls to use UAVs to increase the capacity of responsible agencies to quickly and effectively suppress fires and to reduce risks associated with firefighting. One of the opportunities associated with UAVs is the ability to rapidly and autonomously operate from limited-access air bases where fires are expected to burn. This study provides an approach to determine where these air bases should be placed in order to most rapidly extinguish fires, given provided fuel distributions. This approach uses an integrated simulation of fire propagation and UAV-based suppression actions to determine how much of a given environment was burned over a range of scenarios. It then uses an optimization method to explore the space and determine the location with the least burned area. Results show the approach to efficiently and effectively provide optimal bases for single-base placements over a range of scenarios, though future work is required to adequately calibrate the model and study how it can be used in multiple-base placement problems.

Daniel Hulse↗

NASA NTRSDate not supplied

Determining Optimal Asset Location for Rapid and Efficient Wildfire Suppression: A Simulation-Based Approach

The impact of wildfire incidents has been growing in recent years, posing a serious threat to communities at the urban-wildland interface. To address this problem, there have been growing calls to use UAVs to increase the capacity of responsible agencies to quickly and effectively suppress fires and to reduce risks associated with firefighting. One of the opportunities associated with UAVs is the ability to rapidly and autonomously operate from limited-access air bases where fires are expected to burn. This study provides an approach to determine where these air bases should be placed in order to most rapidly extinguish fires, given provided fuel distributions. This approach uses an integrated simulation of fire propagation and UAV-based suppression actions to determine how much of a given environment was burned over a range of scenarios. It then uses an optimization method to explore the space and determine the location with the least burned area. Results show the approach to efficiently and effectively provide optimal bases for single-base placements over a range of scenarios, though future work is required to adequately calibrate the model and study how it can be used in multiple-base placement problems.

Daniel Hulse↗