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NASA NTRS2014

Manufacturing Challenges Associated with the Use of Metal Matrix Composites in Aerospace Structures

Metal Matrix Composites (MMCs) consist of a metal alloy reinforced with ceramic particles or fibers. These materials possess a very high strength to weight ratio, good resistance to impact and wear, and a number of other properties which make them attractive for use in aerospace and defense applications. MMCs have found use in the space shuttle orbiter's structural tubing, the Hubble Space Telescope's antenna mast, control surfaces and propulsion systems for aircraft, and tank armors. The size of MMC components is severely limited by difficulties encountered in joining these materials using fusion welding. Melting of the material results in formation of an undesirable phase (formed when molten Aluminum reacts with the reinforcement) which leaves a strength depleted region along the joint line. Friction Stir Welding (FSW) is a relatively nascent solid state joining technique developed at The Welding Institute (TWI) in 1991. The process was first used at NASA to weld the super lightweight external tank for the Space Shuttle. Today FSW is used to join structural components of the Delta IV, Atlas V, and Falcon IX rockets as well as NASA's Orion Crew Exploration Vehicle and Space Launch System. A current focus of FSW research is to extend the process to new materials, such as MMCs, which are difficult to weld using conventional fusion techniques. Since Friction Stir Welding occurs below the melting point of the workpiece material, this deleterious phase is absent in FSW-ed MMC joints. FSW of MMCs is, however, plagued by rapid wear of the welding tool, a consequence of the large discrepancy in hardness between the steel tool and the reinforcement material. This chapter summarizes the challenges encountered when joining MMCs to themselves or to other materials in structures. Specific attention is paid to the influence of process variables in Friction Stir Welding on the wear process characterizes the effect of process parameters (spindle speed, traverse rate, and length of joint) on the wear process. A phenomenological model of the wear process was constructed based on the rotating plug model of Friction Stir Welding. The effectiveness of harder tool materials (such as Tungsten Carbide, high speed steel, and tools with diamond coatings) to combat abrasive wear is also explored. In-process force, torque, and vibration signals are analyzed to assess the feasibility of in situ monitoring of tool shape changes as a result of wear (an advancement which would eliminate the need for off-line evaluation of tool condition during joining). Monitoring, controlling, and reducing tool wear in FSW of MMCs is essential to implementation of these materials in structures (such as launch vehicles) where they would be of maximum benefit. The work presented here is extendable to machining of MMCs, where wear of the tool is also a limiting factor.

Prater, Tracie↗

NASA NTRS2021

Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios

Concerns over climate change are motivated in large part because of their impact on human society. Assessing the effect of that uncertainty on specific potential impacts is demanding, since it requires a systematic survey over both climate and impacts models. We provide a comprehensive evaluation of uncertainty in projected crop yields for maize, spring and winter wheat, rice, and soybean, using a suite of nine crop models and up to 45 CMIP5 and 34 CMIP6 climate projections for three different forcing scenarios. To make this task computationally tractable, we use a new set of statistical crop model emulators. We find that climate and crop models contribute about equally to overall uncertainty. While the ranges of yield uncertainties under CMIP5 and CMIP6 projections are similar, median impact in aggregate total caloric production is typically more negative for the CMIP6 projections (+1% to −19%) than for CMIP5 (+5% to −13%). In the first half of the 21st century and for individual crops is the spread across crop models typically wider than that across climate models, but we find distinct differences between crops: globally, wheat and maize uncertainties are dominated by the crop models, but soybean and rice are more sensitive to the climate projections. Climate models with very similar global mean warming can lead to very different aggregate impacts so that climate model uncertainties remain a significant contributor to agricultural impacts uncertainty. These results show the utility of large-ensemble methods that allow comprehensively evaluating factors affecting crop yields or other impacts under climate change. The crop model ensemble used here is unbalanced and pulls the assumption that all projections are equally plausible into question. Better methods for consistent model testing, also at the level of individual processes, will have to be developed and applied by the crop modeling community.

crop yield projections↗

NASA NTRSDate not supplied

Characterization of Collection Efficiency of the Common Research Model Midspan Wing Section in the IRT

This paper presents a preliminary study for the characterization of collection efficiency from icing tests conducted in the Icing Research Tunnel at NASA Glenn Research Center. A test method previously developed for measuring the attachment line maximum collection efficiency of a swept NACA 0012 airfoil model at zero angle of attack was applied to the leading-edge region of a 65%-scale version of the Common Research Model midspan wing section. A correlation for the stagnation line maximum collection efficiency as a function of the modified inertia parameter was obtained with LEWICE3D simulations utilizing a discrete number of drop diameters. It was then compared with the collection efficiency measurement data obtained in the IRT. For the experimental collection efficiency, two ice shape digitization procedures were utilized to extract 2-D chord-wise ice shape profiles, i.e., the Maximum Combined Cross Section or MCCS, and the Minimum Combined Cross Section or Min CCS, at selected span-wise locations from the 3-D scanned ice shapes. The preliminary result showed that the rime ice thickness method can be used to characterize the collection efficiency distribution, for conditions free of ice erosion, in the main ice shape region. However, a high-order statistical processing of the ice scan is needed for estimating the mean ice thickness in areas where feathers are prevalent. From the limited comparison of the experimental and LEWICE3D collection efficiency data in the CRM65 MS model leading edge area, it was shown that the attachment line maximum collection efficiency is reasonably estimated by the best curve-fit correlation in the range of modified inertia parameter tested. A tighter alignment control of the iced and cold clean model scans is needed to improve the comparison. Further evaluation of this correlation is recommended to assess its applicability for Common Research Model type swept wing icing scaling analysis.

Ice Scailing↗

NASA NTRS1997

Modeling of the Coupled Magnetospheric and Neutral Wind Dynamos

Over the past four years of funding, SRI, in collaboration with the University of Texas at Dallas, has been involved in assessing the influence of thermospheric neutral winds on the electric field and current systems at high latitudes. The initial direction of the project was to perform a set of numerical experiments concerning the contribution of the magnetospheric and neutral wind dynamo processes, under specific boundary conditions, to the polarization electric field and/or the field-aligned current distribution at high latitudes. To facilitate these numerical experiments we developed a numerical scheme that relied on using output from the NCAR Thermosphere-Ionosphere General Circulation Model (NCAR-TIGCM), expanding them in the form of spherical harmonics and solving the dynamo equations spectrally. Once initial calculations were completed, it was recognized that the neutral wind contribution could be significant but its actual contribution to the electric field or currents depended strongly on the generator properties of the magnetosphere. Solutions to this problem are not unique because of the unknown characteristics of the magnetospheric generator, therefore the focus was on two limiting cases. One limiting case was to consider the magnetosphere as a voltage generator delivering a fixed voltage to the high-latitude ionosphere and allowing for the neutral wind dynamo to contribute only to the current system. The second limiting case was to consider the magnetosphere as a current generator and allowing for the neutral wind dynamo to contribute only to the generation of polarization electric fields. This work was completed and presented at the l994 Fall AGU meeting. The direction of the project then shifted to applying the Poynting flux concept to the high-latitude ionosphere. This concept was more attractive as it evaluated the influence of neutral winds on the high-latitude electrodynamics without actually having to determine the generator characteristics of the magnetosphere. The influence of the neutral wind was then determined not by estimating how much electric potential or current density it provides, but by determining the contribution of the neutral wind to the net electromagnetic energy transferred between the ionosphere and magnetosphere. The estimate of the net electromagnetic energy transfer and the role of the neutral winds proves to be a more fundamental quantity in studies of magnetosphere- ionosphere coupling also showed that by using electric and magnetic field measurements from the HILAT satellite, the Poynting flux could be a measurable quantity from polar-orbiting, low- altitude spacecraft. Through collaboration with Dr. Heelis and others at UTD and their expertise of the electric field measurements on the DE-B satellite, an extensive analysis was planned to determine the Poynting flux from the DE-B measurements in combination with a modeling effort to help interpret the observations taking into account the coupled magnetosphere-ionosphere.

Thayer, Jeffrey P.↗

NASA NTRS2017

Knowledge Base for Distributed Spacecraft Mission Design Using the Trade-Space Analysis Tool for Constellations (TAT-C)

Opportunities for multi-point measurements, greater revisit frequency, failure robustness, and improved cost effectiveness motivate consideration of Distributed Spacecraft Missions (DSMs) for future Earth science missions. However, careful analysis is required to assess the distributed sensing capabilities of a constellation compared to more mature monolithic spacecraft while also considering other important dimensions such as cost and risk. The large combinatorial DSM design space limits existing mission analysis tools and exploration methods which emphasize monolithic design variables. The Trade-space Analysis Tool for Constellations (TAT-C) under development at Goddard seeks to enumerate and evaluate alternative mission architectures to minimize cost and maximize scientific return for pre-defined goals during pre-phase A analysis.Similar to other model-centric engineering efforts, efficient data management is a significant challenge for DSM mission analysis. In TAT-C, a Knowledge Base (KB) is envisioned as a cumulative central repository of information and meta-information about DSMs. Initial KB concepts store related data for reuse within or across mission analyses; however, over time, the KB is envisioned to be an important layer to coordinate actions of both human analysts and automated design agents to search a large design space for desirable mission alternatives. Preliminary KB research builds on a modern web technology stack to provide the following functionality: 1) storage of trade-space search requests which set requirements and constraints for DSM concepts, 2) storage of analysis results which quantify performance metrics for evaluated DSM concepts, 3) a RESTful application programming interface (API) for scripted access to data from TAT-C modules, 4) web-based graphical user interface (GUI) for manual access to underlying data, and 5) access control and management restrictions relevant to data protection and security. These efforts have culminated in a prototype KB used by the research team during TAT-C development to assess opportunities for future work.

Pattern Recognition↗

NASA NTRSDate not supplied

Characterization of Collection Efficiency of the Common Research Model Midspan Wing Section in the IRT

This paper presents a preliminary study for the characterization of collection efficiency from icing tests conducted in the Icing Research Tunnel at NASA Glenn Research Center. A test method previously developed for measuring the attachment line maximum collection efficiency of a swept NACA 0012 airfoil model at zero angle of attack was applied to the leading-edge region of a 65%-scale version of the Common Research Model midspan wing section. A correlation for the stagnation line maximum collection efficiency as a function of the modified inertia parameter was obtained with LEWICE3D simulations utilizing a discrete number of drop diameters. It was then compared with the collection efficiency measurement data obtained in the IRT. For the experimental collection efficiency, two ice shape digitization procedures were utilized to extract 2-D chord-wise ice shape profiles, i.e., the Maximum Combined Cross Section or MCCS, and the Minimum Combined Cross Section or MinCCS, at selected span-wise locations from the 3-D scanned ice shapes. The preliminary result showed that the rime ice thickness method can be used to characterize the collection efficiency distribution, for conditions free of ice erosion, in the main ice shape region. However, a high-order statistical processing of the ice scan is needed for estimating the mean ice thickness in areas where feathers are prevalent. From the limited comparison of the experimental and LEWICE3D collection efficiency data in the CRM65 MS model leading edge area, it was shown that the attachment line maximum collection efficiency is reasonably estimated by the best curve-fit correlation in the range of modified inertia parameter tested. A tighter alignment control of the iced and cold clean model scans as well as the model angle of attack are needed to improve the comparison. Further evaluation of this correlation is recommended to assess its applicability for Common Research Model type swept wing icing scaling analysis.

Icing Scaling↗

NASA NTRS2012

A Fast and Efficient Version of the TwO-Moment Aerosol Sectional (TOMAS) Global Aerosol Microphysics Model

This study develops more computationally efficient versions of the TwO-Moment Aerosol Sectional (TOMAS) microphysics algorithms, collectively called Fast TOMAS. Several methods for speeding up the algorithm were attempted, but only reducing the number of size sections was adopted. Fast TOMAS models, coupled to the GISS GCM II-prime, require a new coagulation algorithm with less restrictive size resolution assumptions but only minor changes in other processes. Fast TOMAS models have been evaluated in a box model against analytical solutions of coagulation and condensation and in a 3-D model against the original TOMAS (TOMAS-30) model. Condensation and coagulation in the Fast TOMAS models agree well with the analytical solution but show slightly more bias than the TOMAS-30 box model. In the 3-D model, errors resulting from decreased size resolution in each process (i.e., emissions, cloud processing wet deposition, microphysics) are quantified in a series of model sensitivity simulations. Errors resulting from lower size resolution in condensation and coagulation, defined as the microphysics error, affect number and mass concentrations by only a few percent. The microphysics error in CN70CN100 (number concentrations of particles larger than 70100 nm diameter), proxies for cloud condensation nuclei, range from 5 to 5 in most regions. The largest errors are associated with decreasing the size resolution in the cloud processing wet deposition calculations, defined as cloud-processing error, and range from 20 to 15 in most regions for CN70CN100 concentrations. Overall, the Fast TOMAS models increase the computational speed by 2 to 3 times with only small numerical errors stemming from condensation and coagulation calculations when compared to TOMAS-30. The faster versions of the TOMAS model allow for the longer, multi-year simulations required to assess aerosol effects on cloud lifetime and precipitation.

Lee, Yunha↗

NASA NTRSDate not supplied

FluxSat: Long-term Earth Science Data Record (ESDR) for Terrestrial Gross Primary Production (GPP) based on satellite data calibrated with eddy covariance data

Gross primary production (GPP), the amount of carbon dioxide (CO 2 ) assimilated by plants through photosynthesis, is one of the most variable and uncertain components of the global carbon cycle. Global GPP has been estimated with a number of process-based models, data-driven, and hybrid approaches. Dynamic global vegetation models (DGVMs), driven by observed environmental changes, are used for global carbon budget assessments and long-term (climate) prediction. Benchmarking these and other models globally with data-driven GPP estimates is critical for understanding the land sink and ensuring accurate forecasts of the carbon cycle. In addition, global data-driven GPP estimates are crucial for studies of interannual variability, including trends that are linked to mechanisms with large uncertainties, such as the indirect CO 2 fertilization effect related to greening. In response to a community need for a GPP data set that well captures spatio-temporal variability, we developed FluxSat, a data-driven approach that optimizes the use of satellite reflectance data from the NASA MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites, calibrated using ground-based eddy covariance (EC) data. We are enhancing (spatially, higher resolution) and extending FluxSat (in time, with additional sensors) to create a high quality long term GPP Earth System Data Record (ESDR) for use in model benchmarking, carbon cycle modeling, and studies of trends and interannual variability. Our team’s objectives are to: 1. Update and document the current MODIS FluxSat GPP (daily, 0.05o and 0.5o resolutions) products with latest available MODIS and EC data sets; 2. Extend FluxSat GPP record forward in time with the Visible Infrared Imaging Radiometer Suite (VIIRS) on operational weather satellites going forward; 3. Extend FluxSat GPP record backward in time using the Advanced Very High Resolution Radiometer (AVHRR) on weather satellites dating back to 1981; 4. Provide higher spatial resolution MODIS and VIIRS GPP (0.0083o). 5. Thoroughly evaluate all FluxSat products with independent data; and 6. Create a homogenized long-term GPP record spanning 40+ years. We will discuss plans for this long-term data set that is supported through the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program.

gross Primary Production↗

NASA NTRSDate not supplied

Assessment of Crew Time for Maintenance and Repair Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, understanding how crew repair and maintenance timelines are impacted by mission operations and technology changes is vital for future mission planning. Past work has been done using historical International Space Station (ISS) data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available datasets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat (SH), and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA ISS maintenance and crew time data are logged into two central databases: the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS). Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair time for each failure and repair event. The entire maintenance activity dataset is then categorized based on the class of failed component to ensure a significant sample size for each class and accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time to Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. The authors applied these modeling methods to a case study of a crewed mission to the planned SH and produced expected corrective maintenance crew time distributions. The results produced an expected corrective maintenance crew time at over 24 hours per mission, and a maintenance crew time distribution that reflects the importance of planning for sufficient maintenance requirements each mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗

NASA NTRS2016

Evaluation of 10V Chip Polymer Tantalum Capacitors for Space Applications

Due to low ESR and safe failure mode, new technology chip polymer tantalum capacitors (CPTC) have gained popularity in the electronics design community, first in commercial applications, and now in hi-rel and space systems. The major drawbacks of these parts are high leakage currents, degradation under environmental stresses, and a relatively narrow temperature range of operating and storage conditions. Several studies have shown that a certain amount of moisture in polymer cathodes is necessary for a normal operation of the parts. This might limit applications of CPTCs in space systems and requires analysis of long-term exposure to deep vacuum conditions on their performance and reliability. High leakage currents and limited maximum operational temperature complicate accelerated testing that is necessary to assess long-term reliability and require new screening and qualification procedures for quality assurance. A better understanding of behavior of CPTCs as compared to traditional, MnO2, capacitors is necessary to develop adequate approaches for QA system for space applications. A specific of CPTCs is that different materials and processes might be used for low-voltage (10 V and less) and high-voltage (above 10 V) capacitors, so performance and degradation processes in these groups require separate analysis. In this work, that is a part of the NASA Electronic Parts and Packaging (NEPP) program, degradation of AC and DC characteristics under environmental stresses at different temperatures and voltages have been studied in nine lots of commercial and automotive grade capacitors rated to 10 V. Results of analysis of leakage currents, high temperature storage (HTS) up to 5000 hrs in vacuum and air at different temperatures, and Highly Accelerated Life Testing (HALT) in the range from 85 C to 145 C are presented. Temperature and voltage acceleration factors were calculated based on approximation of distributions of degradation rates with a general log-linear Weibull model. Mechanisms of degradation and failures, and requirements for screening and qualification testing are discussed.

Tantalum Capacitors↗

NASA NTRS1998

Evaluation of the 29-km Eta Model: Objective Verification at Three Selected Stations - Part 1

This paper describes an objective verification of the National Centers for Environmental Prediction (NCEP) 29-km eta model from May 1996 through January 1998. The evaluation was designed to assess the model's surface and upper-air point forecast accuracy at three selected locations during separate warm (May - August) and cool (October - January) season periods. In order to enhance sample sizes available for statistical calculations, the objective verification includes two consecutive warm and cool season periods. Systematic model deficiencies comprise the larger portion of the total error in most of the surface forecast variables that were evaluated. The error characteristics for both surface and upper-air forecasts vary widely by parameter, season, and station location. At upper levels, a few characteristic biases are identified. Overall however, the upper-level errors are more nonsystematic in nature and could be explained partly by observational measurement uncertainty. With a few exceptions, the upper-air results also indicate that 24-h model error growth is not statistically significant. In February and August 1997, NCEP implemented upgrades to the eta model's physical parameterizations that were designed to change some of the model's error characteristics near the surface. The results shown in this paper indicate that these upgrades led to identifiable and statistically significant changes in forecast accuracy for selected surface parameters. While some of the changes were expected, others were not consistent with the intent of the model updates and further emphasize the need for ongoing sensitivity studies and localized statistical verification efforts. Objective verification of point forecasts is a stringent measure of model performance, but when used alone, is not enough to quantify the overall value that model guidance may add to the forecast process. Therefore, results from a subjective verification of the meso-eta model over the Florida peninsula are discussed in the companion paper by Manobianco and Nutter. Overall verification results presented here and in part two should establish a reasonable benchmark from which model users and developers may pursue the ongoing eta model verification strategies in the future.

Nutter, Paul A.↗

NASA NTRS2016

Post-Flight Assessment of Avcoat Thermal Protection System for the Exploration Flight Test-1

On December 5, 2014 NASA conducted the first flight test of its next generation human-class Orion spacecraft. The flight was called the Exploration Flight Test -1 (EFT-1) which lasted for 4 hours and culminated into a re-entry trajectory at 9 km/s. This flight test of the 5-meter Orion Crew Module demonstrated various sub-systems including the Avcoat ablative thermal protection system (TPS) on the heat shield. The Avcoat TPS had been developed from the Apollo-era recipe with a few key modifications. The engineering for thermal sizing was supported by modeling, analysis, and ground tests in arc jet facilities. This paper will describe a postlfight analysis plan and present results from post-recovery inspections, data analysis from embedded sensors, TPS sample extraction and characterization in the laboratory. After the recovery of the vehicle, a full photographic survey and surface scans of the TPS were performed. The recovered vehicle showed physical evidence of flow disturbances, varying degrees of surface roughness, and excessive recession downstream of compression pads. The TPS recession was measured at more than 200 locations of interest on the Avcoat surface. The heat shield was then processed for sample extraction prior to TPS removal using the 7-Axis Milling machine at Marshall Space Flight Center. Around 182 rectangular TPS samples were extracted for subsequent analysis and investigation. The final paper will also present results of sample analysis. The planned investigation includes sidewall imaging, followed by image analysis to characterize TPS response by quantifying different layers in the char and pyrolysis zones. A full postmortem of the instrumentation and sensor ports will also be performed to confirm no adverse effects due to the sensors themselves. A subset of the samples will undergo structural testing and perform detailed characterization of any cracks and integrity of gore seams. Finally, the material will be characterized with layer-by-layer density measurements and SEM investigations to evaluate material morphology at microstructural level including identification of elements and compounds.

Aerothermodynamics↗

NASA NTRS2010

NASA's Soil Moisture Active and Passive (SMAP) Mission

The Soil Moisture Active-Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Decadal Survey. SMAP will make global measurements of soil moisture at the Earth's land surface and its freeze-thaw state. These measurements will allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing over the boreal latitudes will also reduce a major uncertainty in quantifying the global carbon balance and help to resolve an apparent missing carbon sink over land. The SMAP mission concept will utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna flying in a 680 km polar orbit with an 8-day exact ground track repeat aboard a 3-axis stabilized spacecraft to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these surface observations with advanced modeling and data assimilation to provide estimates of deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP recently completed its Phase A Mission Concept Study Phase for NASA and transitioned into Phase B (Formulation and Detailed Design). A number of significant accomplishments occurred during this initial phase of mission development. The SMAP project held several open meetings to solicit community feedback on possible science algorithms, prepared preliminary draft Algorithm Theoretical Basis Documents (ATBDs) for each mission science product, and established a prototype algorithm testbed to enable testing and evaluation of the performance of candidate algorithms. SMAP conducted an Applications Workshop in September 2009 to coordinate with potential application users interested in the mission data. A draft Applications Plan describing the Project s planned outreach to potential applications users has been prepared and will be updated during Phase B. SMAP made a significant evaluation of the potential terrestrial radio frequency interference (RFI) source environment and established radiometer and radar flight hardware and ground processing mitigation approaches. SMAP finalized its science orbit and orbit injection approach to optimize launch mass and prepared launch and commissioning scenarios and timeline. A science data communications approach was developed to maximize available science data volume to improve science margins while maintaining moderately short data product latencies to support many potential applications using existing ground assets and with minimum impact to the flight system. SMAP developed rigid multi-body and flexible body dynamics and control models and system designs for the 6-meter rotating instrument reflector-boom assembly (RBA) and flight system to confirm pointing and control performance, and devised strategies to efficiently implement on-orbit balancing if needed. Industry partners were selected for the spin mechanism assembly (SMA) and RBA. Preliminary designs for the radar and radiometer were initiated, including constructing breadboards of key assemblies.

Kellogg, Kent↗

NASA NTRSDate not supplied

A Scenario-Based Approach to Assess Continuity Gaps in Earth Observations

Decision analysis processes outlined in systems engineering references, such as the Systems Engineering Body of Knowledge [1] or the NASA Systems Engineering Handbook [2], recommend following a series of steps to support decision-making for engineering applications. These steps are consistent across the literature and typically involve defining objectives, defining relevant criteria against which candidate alternatives can be assessed, selecting an evaluation method, assessing alternatives, and making a recommendation based on this assessment. These approaches are well-suited to assess systems for which sets of common objectives and constraints can be identified. A vast body of literature describes their application to numerous engineering problems, and many methods have been developed since the middle of the 20th century to support the assessment of candidate alternatives for such systems [3, 4, 5, 6]. These approaches, however, show some limitations when decisions pertain to systems of systems. These collections of individual systems typically do not share a common set of objectives and constraints, tend to be highly complex, and the definition of assessable, high-value candidate alternatives poses a challenge due to interdependencies. The formulation, development, operation, and funding of Earth observing missions are such that gaps may occur between missions, therefore impacting the continuity of measurements. These Earth observing mission architectures constitute systems of systems for which a common set of objectives and constraints can be challenging to define. When tasked with assessing gaps that may occur for a series of spaceborne missions that address similar science parameters, the authors therefore proposed to depart from the traditional objective- and criteria-based approach and instead adopted a scenario-based approach. This approach does not require a prioritized set of common objectives; rather, it assesses the impact of possible decisions on the system-of-systems and characterizes its possible future states. It also offers the flexibility to adjust assumptions, update inputs, and refine supporting models over time, while enabling the rapid, early identification of challenges and key decision points. By simulating the impact of potential decisions on the entirety of the system-of-systems, the approach enables the synchronization of multiple decisions that typically occur at the level of the individual system. This paper provides an overview of the approach that was developed to assess continuity gaps for a series of operational and planned spaceborne Earth observing missions, a description of its application to the problem at hand, and a discussion of currently known limitations.

scenario earth observations continuity gaps↗

NASA NTRSDate not supplied

A Scenario-Based Approach to Assess Continuity Gaps in Earth Observations

scenario earth observations continuity gaps↗

NASA NTRSDate not supplied

Application of Analytical Hierarchy Process for Narrowing Down Nep Candidate Reactor Designs

Nuclear electric propulsion (NEP)-powered vehicles have been contemplated for human Mars missions. The nuclear power system contemplates using a high temperature light-weight nuclear reactor for the production of electrical power in the range of 2-5 MWe with a 3-10 year service life. A myriad of technology options exist for achieving these mission objectives. The analytic hierarchy process (AHP), a multi-attribute decision method, is being used to narrow down the candidate designs. The AHP is a structured decision process that fuses model-supplied quantitative data with subjective assessments to facilitate decisions that involve multiple competing criteria. Proven end-to-end nuclear design and systems analysis tools will be used to provide quantitative performance data such as end-to-end system reliability, system robustness to recover from off-normal conditions, system specific weight (α in kg/kWe), and the ability to meet the service life-time and power level requirements. Three high assay low enriched uranium (HALEU) reactor concepts, namely, gas-, heat pipe- and pumped liquid-cooled nuclear cores coupled to a He/Xe gas or supercritical CO2- Brayton power conversion system are being modeled using the AHP to understand the trade-offs associated with these design combinations. In addition to the reactor and power conversion options, there are a myriad of additional components and subsystems – e.g., radiators, heat exchangers, and recuperators – that also figure into the evaluation process. The choice of the right overall system is a multidimensional problem that has to include not only quantitative data, but also the so called “external factors”, examples of which include the component and subsystem Technology Readiness Levels (TRLs), the associated Advancement Degrees of Difficulty (AD2), the cost and schedule required to achieve a technical maturity consistent with mission infusion, alignment with the priorities of NASA’s Space Nuclear Propulsion program, and alignment with other ongoing government and commercial investments in micro reactors. Focused expert elicitations form the basis for qualitative data set. As a final step, decision-makers individually express their opinions regarding the relative importance of the criteria and preferences among the alternatives through pairwise comparisons. The paper will describe the AHP approach, progress to-date applying it to the NEP human Mars mission problem, and preliminary results. Use of AHP provides sufficient flexibility for incorporating industry input at different stages as the technologies evolve through additional research and development. It is expected that the decision process will be ongoing and expanded to examine additional options and technology choices, culminating in a defensible set of candidate reactor concepts that will form the basis for developing a multi-year NEP technology maturation strategy. .

Dasari V Rao↗

NASA NTRS2004

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Source record↗

NASA NTRS2013

An Assessment of the Skill of GEOS-5 Seasonal Forecasts

The seasonal forecast skill of the NASA Global Modeling and Assimilation Office coupled global climate model (CGCM) is evaluated based on an ensemble of 9-month lead forecasts for the period 1993 to 2010. The results from the current version (V2) of the CGCM consisting of the GEOS-5 AGM coupled to the MOM4 ocean model are compared with those from an earlier version (V1) in which the AGCM (the NSIPP model) was coupled to the Poseidon Ocean Model. It was found that the correlation skill of the Sea Surface Temperature (SST) forecasts is generally better in V2, especially over the sub-tropical and tropical central and eastern Pacific, Atlantic, and Indian Ocean. Furthermore, the improvement in skill in V2 mainly comes from better forecasts of the developing phase of ENSO from boreal spring to summer. The skill of ENSO forecasts initiated during the boreal winter season, however, shows no improvement in terms of correlation skill, and is in fact slightly worse in terms of root mean square error (RMSE). The degradation of skill is found to be due to an excessive ENSO amplitude. For V1, the ENSO amplitude is too strong in forecasts starting in boreal spring and summer, which causes large RMSE in the forecast. For V2, the ENSO amplitude is slightly stronger than that in observations and V1 for forecasts starting in boreal winter season. An analysis of the terms in the SST tendency equation, shows that this is mainly due to an excessive zonal advective feedback. In addition, V2 forecasts that are initiated during boreal winter season, exhibit a slower phase transition of El Nino, which is consistent with larger amplitude of ENSO after the ENSO peak season. It is found that this is due to weak discharge of equatorial Warm Water Volume (WWV). In both observations and V1, the discharge of equatorial WWV leads the equatorial geostrophic easterly current so as to damp the El Nino starting in January. This process is delayed by about 2 months in V2 due to the slower phase transition of the equatorial zonal current from westerly to easterly.

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