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At least 253 records · Page 14

Multiversion software reliability through fault-avoidance and fault-tolerance

In this project we have proposed to investigate a number of experimental and theoretical issues associated with the practical use of multi-version software in providing dependable software through fault-avoidance and fault-elimination, as well as run-time tolerance of software faults. In the period reported here we have working on the following: We have continued collection of data on the relationships between software faults and reliability, and the coverage provided by the testing process as measured by different metrics (including data flow metrics). We continued work on software reliability estimation methods based on non-random sampling, and the relationship between software reliability and code coverage provided through testing. We have continued studying back-to-back testing as an efficient mechanism for removal of uncorrelated faults, and common-cause faults of variable span. We have also been studying back-to-back testing as a tool for improvement of the software change process, including regression testing. We continued investigating existing, and worked on formulation of new fault-tolerance models. In particular, we have partly finished evaluation of Consensus Voting in the presence of correlated failures, and are in the process of finishing evaluation of Consensus Recovery Block (CRB) under failure correlation. We find both approaches far superior to commonly employed fixed agreement number voting (usually majority voting). We have also finished a cost analysis of the CRB approach.

Vouk, Mladen A.↗

Technology Infusion of CodeSonar into the Space Network Ground Segment (RII07): Software Assurance Symposium Technical Summary

Presents a source code analysis tool (CodeSonar) for use in the Space Network Ground Segment. The Space Network requires 99.9% proficiency and 97.0% availability of systems. Software has historically accounted for an annual average of 28% of the Space Network loss of availability and proficiency. CSCI A and CSCI B account for 42% of the previous eight months of software data loss. The technology infusion of CodeSonar into the Space Network Ground segment is meant to aid in determining the impact of the technology on the project both in the expenditure of effort and the technical results of the technology. Running a CodeSonar analysis and performing a preliminary review of the results averaged 3.5 minutes per finding (approximately 20 hours total). An additional 40 hours is estimated to analyze the 37 findings deemed too complex for the initial review. Using CodeSonar's tools to suppress known non-problems, delta tool runs will not repeat findings that have been marked as non-problems, further reducing the time needed for review. The 'non-interesting' finding rate of 70% is a large number, but filtering, search, and detailed contextual features of CodeSonar reduce the time per finding. Integration of the tool into the build process may also provide further savings by preventing developers from having to configure and operate the tool separately. These preliminary results show the tool to be easy to use and incorporate into the engineering process. These findings also provide significant potential improvements in proficiency and availability on the part of the software. As time-to-fix data become available a better cost trade can be made on person hours saved versus tool cost. Selective factors may be necessary to determine where best to apply CodeSonar to balance cost and benefits.

Benson, Markland J.↗

B and F Signal Conditioner Checkout Unit

ATK Thiokol Propulsion, Test Services uses B&F Signal Conditioning units to provide excitation power and shunt calibration information to the data recording systems. Gage measurements such as force, temperature, pressure, strain, etc. are recorded using this equipment. Approximately 2500 reusable instrumentation B&F Signal Conditioning units were purchased over an interval from 1978 to 1988 at a cost of around $1000 each. Through use and over time, the relay contacts on the signal conditioning mode cards have become corroded, resulting in excessive contact resistance. This causes inaccurate and inconsistent calibration data and could jeopardize the test results. These signal conditioning cards are needed for product testing for an estimated five more years, therefore, it is necessary to develop a solution to isolate the malfunctioning units for repair. The current screening method requires Test Area technicians to check cards manually, however the connections and measurements required for this process are inefficient and time consuming. To resolve this problem, funding was approved to design and build two B&F Signal Conditioner Checkout Units. Each unit will allow technicians to test relay contact resistance on signal conditioning mode cards before they are installed for data collection procedures. This tool will allow Test Area to resolve calibration accuracy problems and extend the life of the data acquisition equipment, as well as save troubleshooting time for the technicians.

Magleby, Alyssa↗

In-Flight Evaluation of the Traffic Aware Planner on the NASA HU-25A Guardian Aircraft

NASA’s Traffic Aware Planner (TAP) software is a research-prototype decision support tool that provides pilots with time- and fuel-saving route recommendations that optimize their current trajectory. The software runs on a first-of-a-kind system architecture onboard three aircraft in revenue service conducting operational evaluations with a major domestic airline. Therefore, significant NASA-internal testing is required prior to releasing the software to the partner airline. This paper describes a flight test plan that exercises the functionality of the TAP software in a representative operational environment, describes the system architecture developed and implemented for the NASA Langley HU-25A Guardian aircraft to support the test objectives, presents outcomes of the flight test campaign, and discusses use cases that demonstrate the value of flight testing for this activity.Research into flight path optimization of transport aircraft conducted by the National Aeronautics and SpaceAdministration (NASA) has produced an operational concept known as Traffic Aware Strategic Aircrew Requests(TASAR) [1, 2]. This near-term concept [3] provides the aircrew with a flight deck decision support tool known asthe Traffic Aware Planner (TAP). The TAP software leverages a growing number of information sources on the flightdeck to make time- and fuel-saving route optimization recommendations to the aircrew while en route. The aircrewcan then use the suggestions provided by the tool to make route change requests with a greater likelihood of acceptanceby air traffic control (ATC). Since TASAR is a concept intended for the current operational environment, it isintentionally designed to have no safety-critical impact or require any changes to current Federal AviationAdministration (FAA) rules and procedures [4, 5].The research prototype TAP system [6–8], explained further in Section III.C, continually incorporates up-to-dateaircraft state data from onboard avionics, as well as the latest position of surrounding traffic, the most recent windforecast, and the most recent convective weather forecast, in order to calculate candidate trajectory modifications thatimprove upon the current active route. These trajectories account for user-selectable objective functions [3] of reducedfuel burn, reduced flight time, or an airline-derived combination of factors known as trip cost. Previous analyses andsimulations have estimated substantial savings for airlines employing this technique within the U.S. National AirspaceSystem (NAS) [9–11]. Operational evaluations with Alaska Airlines seek to validate these projected benefits usingmeasured data while simultaneously providing benefits to the airline [12, 13].The TAP software has undergone a number of human-in-the-loop simulations [14] and flight test activities[15–17] in order to validate the operational concept, evaluate human factors considerations (e.g., workload, usability,distraction, etc.), and to assess the ability of the software to function in a representative operational environment (e.g.,connected to live avionics data, using in-flight internet connectivity, etc.). However, these simulations and flight testcampaigns did not account for the hardware architecture implemented on the three aircraft for Alaska Airlines’operational evaluations of the TAP software. Therefore, a need was identified to thoroughly test the functionality ofthe software in a similar hardware architecture to that of the partner airline’s aircraft. Information regarding testapparatus and environments used to evaluate TAP prior to testing on the HU-25A can be found in reference [18].A campaign of flight trials on a NASA aircraft, the HU-25A Guardian, was conducted to ensure that the researchprototype TAP system functions well in a configuration similar to the Alaska Airlines aircraft prior to deployment.This airborne, networked environment enables an assessment of the operational factors unique to the flight environment. Additionally, this activity evaluated the effectiveness and benefit of new TAP functionality andoperation in a relevant flight environment while allowing the rapid prototyping of new concepts and features.This paper is organized as follows: Section II discusses the details of the flight test plan, flight profiles, and theduties of personnel involved with conducting flight operations. Section III describes the test platform, avionicsequipage, and system architecture. Section IV presents a discussion of results, and Section V contains concludingremarks.

Underwood, Matthew C.↗

Neural Architectures for Control

The cerebellar model articulated controller (CMAC) neural architectures are shown to be viable for the purposes of real-time learning and control. Software tools for the exploration of CMAC performance are developed for three hardware platforms, the MacIntosh, the IBM PC, and the SUN workstation. All algorithm development was done using the C programming language. These software tools were then used to implement an adaptive critic neuro-control design that learns in real-time how to back up a trailer truck. The truck backer-upper experiment is a standard performance measure in the neural network literature, but previously the training of the controllers was done off-line. With the CMAC neural architectures, it was possible to train the neuro-controllers on-line in real-time on a MS-DOS PC 386. CMAC neural architectures are also used in conjunction with a hierarchical planning approach to find collision-free paths over 2-D analog valued obstacle fields. The method constructs a coarse resolution version of the original problem and then finds the corresponding coarse optimal path using multipass dynamic programming. CMAC artificial neural architectures are used to estimate the analog transition costs that dynamic programming requires. The CMAC architectures are trained in real-time for each obstacle field presented. The coarse optimal path is then used as a baseline for the construction of a fine scale optimal path through the original obstacle array. These results are a very good indication of the potential power of the neural architectures in control design. In order to reach as wide an audience as possible, we have run a seminar on neuro-control that has met once per week since 20 May 1991. This seminar has thoroughly discussed the CMAC architecture, relevant portions of classical control, back propagation through time, and adaptive critic designs.

Peterson, James K.↗

NASA Software Engineering Benchmarking Study

To identify best practices for the improvement of software engineering on projects, NASA's Offices of Chief Engineer (OCE) and Safety and Mission Assurance (OSMA) formed a team led by Heather Rarick and Sally Godfrey to conduct this benchmarking study. The primary goals of the study are to identify best practices that: Improve the management and technical development of software intensive systems; Have a track record of successful deployment by aerospace industries, universities [including research and development (R&D) laboratories], and defense services, as well as NASA's own component Centers; and Identify candidate solutions for NASA's software issues. Beginning in the late fall of 2010, focus topics were chosen and interview questions were developed, based on the NASA top software challenges. Between February 2011 and November 2011, the Benchmark Team interviewed a total of 18 organizations, consisting of five NASA Centers, five industry organizations, four defense services organizations, and four university or university R and D laboratory organizations. A software assurance representative also participated in each of the interviews to focus on assurance and software safety best practices. Interviewees provided a wealth of information on each topic area that included: software policy, software acquisition, software assurance, testing, training, maintaining rigor in small projects, metrics, and use of the Capability Maturity Model Integration (CMMI) framework, as well as a number of special topics that came up in the discussions. NASA's software engineering practices compared favorably with the external organizations in most benchmark areas, but in every topic, there were ways in which NASA could improve its practices. Compared to defense services organizations and some of the industry organizations, one of NASA's notable weaknesses involved communication with contractors regarding its policies and requirements for acquired software. One of NASA's strengths was its software assurance practices, which seemed to rate well in comparison to the other organizational groups and also seemed to include a larger scope of activities. An unexpected benefit of the software benchmarking study was the identification of many opportunities for collaboration in areas including metrics, training, sharing of CMMI experiences and resources such as instructors and CMMI Lead Appraisers, and even sharing of assets such as documented processes. A further unexpected benefit of the study was the feedback on NASA practices that was received from some of the organizations interviewed. From that feedback, other potential areas where NASA could improve were highlighted, such as accuracy of software cost estimation and budgetary practices. The detailed report contains discussion of the practices noted in each of the topic areas, as well as a summary of observations and recommendations from each of the topic areas. The resulting 24 recommendations from the topic areas were then consolidated to eliminate duplication and culled into a set of 14 suggested actionable recommendations. This final set of actionable recommendations, listed below, are items that can be implemented to improve NASA's software engineering practices and to help address many of the items that were listed in the NASA top software engineering issues. 1. Develop and implement standard contract language for software procurements. 2. Advance accurate and trusted software cost estimates for both procured and in-house software and improve the capture of actual cost data to facilitate further improvements. 3. Establish a consistent set of objectives and expectations, specifically types of metrics at the Agency level, so key trends and models can be identified and used to continuously improve software processes and each software development effort. 4. Maintain the CMMI Maturity Level requirement for critical NASA projects and use CMMI to measure organizations developing software for NASA. 5.onsolidate, collect and, if needed, develop common processes principles and other assets across the Agency in order to provide more consistency in software development and acquisition practices and to reduce the overall cost of maintaining or increasing current NASA CMMI maturity levels. 6. Provide additional support for small projects that includes: (a) guidance for appropriate tailoring of requirements for small projects, (b) availability of suitable tools, including support tool set-up and training, and (c) training for small project personnel, assurance personnel and technical authorities on the acceptable options for tailoring requirements and performing assurance on small projects. 7. Develop software training classes for the more experienced software engineers using on-line training, videos, or small separate modules of training that can be accommodated as needed throughout a project. 8. Create guidelines to structure non-classroom training opportunities such as mentoring, peer reviews, lessons learned sessions, and on-the-job training. 9. Develop a set of predictive software defect data and a process for assessing software testing metric data against it. 10. Assess Agency-wide licenses for commonly used software tools. 11. Fill the knowledge gap in common software engineering practices for new hires and co-ops.12. Work through the Science, Technology, Engineering and Mathematics (STEM) program with universities in strengthening education in the use of common software engineering practices and standards. 13. Follow up this benchmark study with a deeper look into what both internal and external organizations perceive as the scope of software assurance, the value they expect to obtain from it, and the shortcomings they experience in the current practice. 14. Continue interactions with external software engineering environment through collaborations, knowledge sharing, and benchmarking.

Rarick, Heather L.↗

Automation and robotics human performance

The scope of this report is limited to the following: (1) assessing the feasibility of the assumptions for crew productivity during the intra-vehicular activities and extra-vehicular activities; (2) estimating the appropriate level of automation and robotics to accomplish balanced man-machine, cost-effective operations in space; (3) identifying areas where conceptually different approaches to the use of people and machines can leverage the benefits of the scenarios; and (4) recommending modifications to scenarios or developing new scenarios that will improve the expected benefits. The FY89 special assessments are grouped into the five categories shown in the report. The high level system analyses for Automation & Robotics (A&R) and Human Performance (HP) were performed under the Case Studies Technology Assessment category, whereas the detailed analyses for the critical systems and high leverage development areas were performed under the appropriate operations categories (In-Space Vehicle Operations or Planetary Surface Operations). The analysis activities planned for the Science Operations technology areas were deferred to FY90 studies. The remaining activities such as analytic tool development, graphics/video demonstrations and intelligent communicating systems software architecture were performed under the Simulation & Validations category.

Mah, Robert W.↗

Quantification of Uncertainty and Risk Sensitivity for Safety of Emerging Operations

The growing need to develop and deploy small unmanned aerial vehicles (sUAVs) for various applications in the airspace necessitates reliable tools to accurately predict the flight trajectories of the sUAVs. The knowledge of the predicted trajectories help decision makers anticipate potential conflict, assess the risk, and take appropriate risk mitigation actions. In addition, uncertainties in vehicle models, weather, and controller action further highlights the need for reliable prediction tools. In this project, the application of mixed sparse grid-based quadrature and generalized polynomial chaos(gPC) expansion method for uncertainty quantification and collision assessment in air traffic consisting of fixed-wing small unmanned aerial vehicles (sUAV) was studied. From the results obtained, it can be concluded that this provides a reliable framework to carry out quantitative conflict assessment in an unmanned air traffic, which when employed, can improve the functionalities of the unmanned traffic management system. It was observed that the results from the gPC expansion framework developed in the project can be utilized to conduct rapid probabilistic collision assessment for near real-time unmanned traffic management in the airspace. From the vehicle models, position updates, and wind-field data, a priori gPC based 3-σcon-fidence ellipses can provide estimates of potential conflict at some future instants. The computational costs scaled linearly when the uncertain inputs were fewer. Further, the largest allowable distribution of para-metric uncertainties that leads to the smallest risk of collision in traffic of small unmanned aerial vehicles could be calculated. The time of closest approach between two sUAVs can be established paving way for development of proactive mitigation strategies. The separation between the sUAVs was found to be most significantly affected by uncertainties in the maximum available thrusts, zero-lift drag coefficients, and wing planform areas of the sUAVs. The study of uncertain wind-fields indicated that a heterogeneous traffic mix resulted in an increased probability of conflict. Increased measurement update rate reduced the uncertain-ties in the trajectories of the vehicles, further reducing the probability of conflict but rapid updates of all vehicles in the airspace poses a stringent communication limitation. The gPC framework also provided the means to analyze vehicle impact (crash region) due to loss of control resulting from actuator failure in sUAS traffic, essentially to predict impact and crash zones for representative vehicles. The predicted regions when compared with non-participant density, provides a means to develop an early mitigation strategy, should the sUAV detect an imminent actuator failure.

Rajnish Bhusal↗

Statistical and Probabilistic Extensions to Ground Operations' Discrete Event Simulation Modeling

NASA's human exploration initiatives will invest in technologies, public/private partnerships, and infrastructure, paving the way for the expansion of human civilization into the solar system and beyond. As it is has been for the past half century, the Kennedy Space Center will be the embarkation point for humankind's journey into the cosmos. Functioning as a next generation space launch complex, Kennedy's launch pads, integration facilities, processing areas, launch and recovery ranges will bustle with the activities of the world's space transportation providers. In developing this complex, KSC teams work through the potential operational scenarios: conducting trade studies, planning and budgeting for expensive and limited resources, and simulating alternative operational schemes. Numerous tools, among them discrete event simulation (DES), were matured during the Constellation Program to conduct such analyses with the purpose of optimizing the launch complex for maximum efficiency, safety, and flexibility while minimizing life cycle costs. Discrete event simulation is a computer-based modeling technique for complex and dynamic systems where the state of the system changes at discrete points in time and whose inputs may include random variables. DES is used to assess timelines and throughput, and to support operability studies and contingency analyses. It is applicable to any space launch campaign and informs decision-makers of the effects of varying numbers of expensive resources and the impact of off nominal scenarios on measures of performance. In order to develop representative DES models, methods were adopted, exploited, or created to extend traditional uses of DES. The Delphi method was adopted and utilized for task duration estimation. DES software was exploited for probabilistic event variation. A roll-up process was used, which was developed to reuse models and model elements in other less - detailed models. The DES team continues to innovate and expand DES capabilities to address KSC's planning needs.

Trocine, Linda↗

Space Shuttle Debris Impact Tool Assessment Using the Modern Design of Experiments

Complex computer codes are used to estimate thermal and structural reentry loads on the Shuttle Orbiter induced by ice and foam debris impact during ascent. Such debris can create cavities in the Shuttle Thermal Protection System. The sizes and shapes of these cavities are approximated to accommodate a code limitation that requires simple "shoebox" geometries to describe the cavities -- rectangular areas and planar walls that are at constant angles with respect to vertical. These approximations induce uncertainty in the code results. The Modern Design of Experiments (MDOE) has recently been applied to develop a series of resource-minimal computational experiments designed to generate low-order polynomial graduating functions to approximate the more complex underlying codes. These polynomial functions were then used to propagate cavity geometry errors to estimate the uncertainty they induce in the reentry load calculations performed by the underlying code. This paper describes a methodological study focused on evaluating the application of MDOE to future operational codes in a rapid and low-cost way to assess the effects of cavity geometry uncertainty.

DeLoach, Richard↗

Integrated INS/GPS Navigation from a Popular Perspective

Inertial navigation, blended with other navigation aids, Global Positioning System (GPS) in particular, has gained significance due to enhanced navigation and inertial reference performance and dissimilarity for fault tolerance and anti-jamming. Relatively new concepts based upon using Differential GPS (DGPS) blended with Inertial (and visual) Navigation Sensors (INS) offer the possibility of low cost, autonomous aircraft landing. The FAA has decided to implement the system in a sophisticated form as a new standard navigation tool during this decade. There have been a number of new inertial sensor concepts in the recent past that emphasize increased accuracy of INS/GPS versus INS and reliability of navigation, as well as lower size and weight, and higher power, fault tolerance, and long life. The principles of GPS are not discussed; rather the attention is directed towards general concepts and comparative advantages. A short introduction to the problems faced in kinematics is presented. The intention is to relate the basic principles of kinematics to probably the most used navigation method in the future-INS/GPS. An example of the airborne INS is presented, with emphasis on how it works. The discussion of the error types and sources in navigation, and of the role of filters in optimal estimation of the errors then follows. The main question this paper is trying to answer is 'What are the benefits of the integration of INS and GPS and how is this, navigation concept of the future achieved in reality?' The main goal is to communicate the idea about what stands behind a modern navigation method.

Omerbashich, Mensur↗

Multidisciplinary Optimization Branch Experience Using iSIGHT Software

The Multidisciplinary Optimization (MDO) Branch at NASA Langley Research Center is investigating frameworks for supporting multidisciplinary analysis and optimization research. An optimization framework call improve the design process while reducing time and costs. A framework provides software and system services to integrate computational tasks and allows the researcher to concentrate more on the application and less on the programming details. A framework also provides a common working environment and a full range of optimization tools, and so increases the productivity of multidisciplinary research teams. Finally, a framework enables staff members to develop applications for use by disciplinary experts in other organizations. Since the release of version 4.0, the MDO Branch has gained experience with the iSIGHT framework developed by Engineous Software, Inc. This paper describes experiences with four aerospace applications: (1) reusable launch vehicle sizing, (2) aerospike nozzle design, (3) low-noise rotorcraft trajectories, and (4) acoustic liner design. All applications have been successfully tested using the iSIGHT framework, except for the aerospike nozzle problem, which is in progress. Brief overviews of each problem are provided. The problem descriptions include the number and type of disciplinary codes, as well as all estimate of the multidisciplinary analysis execution time. In addition, the optimization methods, objective functions, design variables, and design constraints are described for each problem. Discussions on the experience gained and lessons learned are provided for each problem. These discussions include the advantages and disadvantages of using the iSIGHT framework for each case as well as the ease of use of various advanced features. Potential areas of improvement are identified.

Padula, S. L.↗

Closed-form solution of decomposable stochastic models

Markov and semi-Markov processes are increasingly being used in the modeling of complex reconfigurable systems (fault tolerant computers). The estimation of the reliability (or some measure of performance) of the system reduces to solving the process for its state probabilities. Such a model may exhibit numerous states and complicated transition distributions, contributing to an expensive and numerically delicate solution procedure. Thus, when a system exhibits a decomposition property, either structurally (autonomous subsystems), or behaviorally (component failure versus reconfiguration), it is desirable to exploit this decomposition in the reliability calculation. In interesting cases there can be failure states which arise from non-failure states of the subsystems. Equations are presented which allow the computation of failure probabilities of the total (combined) model without requiring a complete solution of the combined model. This material is presented within the context of closed-form functional representation of probabilities as utilized in the Symbolic Hierarchical Automated Reliability and Performance Evaluator (SHARPE) tool. The techniques adopted enable one to compute such probability functions for a much wider class of systems at a reduced computational cost. Several examples show how the method is used, especially in enhancing the versatility of the SHARPE tool.

Sjogren, Jon A.↗

Applying a Crew Accommodations Resource Model to Future Space Vehicle Research

The success of research and development for human space flight depends heavily on modeling. In addition, the use of such models is especially critical at the earliest phase of research and development of any manned vehicle or habitat. NASA is currently studying various innovative and futuristic propulsion technologies to enable further exploration of space by untended as well as tended vehicles. Details such as vehicle mass, volume, shape and configuration are required variables to evaluate the success of the propulsion concepts. For tended vehicles, the impact of the crew's requirements on those parameters must be included. This is especially important on long duration missions where the crew requirements become more complex. To address these issues, a crew accommodations resource model, developed as a mission planning tool for human spaceflight (Stillwell, Boutros, & Connolly), was applied to a reference mission in order to estimate the volume and mass required to sustain a crew for a variety of long duration missions. The model, which compiled information from numerous different sources and contains various attributes which can be modified to enable comparisons across different dimensions, was instrumental in deriving volume and mass required for a tended long duration space flight. With the inclusion of some additional variables, a set of volume and mass requirements were provided to the project. If due consideration to crew requirements for volume and mass had not been entertained, the assumptions behind validation of the propulsion technology could have been found to be incorrect, possibly far into development of the technology or even into the design and build of test vehicles. The availability and use of such a model contributes significantly by increasing the accuracy of human space flight research and development activities and acts as a cost saving measure by preventing inaccurate assumptions from driving design decisions.

Blume, Jennifer Linda↗

A Practical Approach to Uncertainty Quantification Using Probability Boxes

To date, while the use of CFD for aerospace vehicle design and development is prevalent, the documentation of uncertainties associated with the simulations are rare. Instead, the current state-of-the-art relies heavily on the experience of the CFD practitioner to estimate the uncertainty associated with their simulations through simple sensitivity studies or subject matter expertise. This practice will have to be replaced with a formal uncertainty quantification (UQ) process if CFD is to play an expanded role in the research and engineering design community, test and evaluation community, and ultimately certification for flight. Accounting for uncertainties in a formal manner is a tedious process. Moreover, the typical CFD practitioner is not likely to be familiar with formal UQ methods. These factors have prevented the adoption of UQ methods in the engineering design and development cycle. This presentation will outline a credible approach to UQ using Probability Boxes that is straightforward to apply, and can readily be automated using existing UQ tool sets such as the DAKOTA packaged developed at Sandia. The added expense incurred when moving away from a deterministic CFD process to a stochastic one that captures uncertainties to enable risk-informed decision making will be discussed, as well as effective ways to reduce the computational costs.

Uncertainty Quantification↗

Optimizing a Coupled Solution for the Orion MPCV Using DPLR and NEQAIR

The goal of this project is to study the convective and radiative heat flux predictions using computational fluid dynamics (CFD) on a smooth body representation of the NASA Orion Multi-Purpose Crew Vehicle (MPCV). The Orion MPCV is designed for long duration missions in space and will play a crucial role in transporting astronauts in the upcoming Artemis missions. With Orion's aim for cost-effective reusability comes a need to study its Thermal Protection System (TPS), which allows for safe entry into the atmospheres of the Earth, Moon, and Mars. In order to study the effects of the TPS on test flights and better understand the aerothermal environment, CFD is a necessary tool used to create simulations of entry vehicles and calculate the heat load and heat flux. However, solutions are often performed using an uncoupled approach between the flow and the radiation solver. This leads to an overestimation of the overall heating effects because they do not consider radiative cooling. Furthermore, the effects of radiation on the aft-body is an area of research with significant uncertainty. Through the use of codes developed at NASA Ames, DPLR and NEQAIR, a coupled solution can be attained for the Orion capsule which will more accurately solve for the effects of radiation in both the fore and aft-body regions. This yields more accurate design margins for the TPS, which produces a better estimate of the thickness required. By developing an accurate coupled solution of the TPS on the Orion MPCV, planners will have greater flexibility in carrying out future missions to the Moon and beyond.

Design↗

The GeoCarb Mission: One Tool in the Evolving Understanding of Methane and Carbon Monoxide Budgets

NASA plans to operate an instrument in geostationary orbit over the Americas beginning in 2022. This mission allows a coordinated study of climate-determining carbon species. Prime focus is on CO2 fluxes, but the reactive species CO and CH4 are particularly relevant to IGAC. Measurements of solar-induced fluorescence will describe plant photosynthesis contemporaneous with emissions. To outline the technology: Grating mapping spectrometery, using a single slit and four focal planes set at 0.76, 1.60, 2.07, and 2.32 microns and ~17000 resolving power. Retrieval profiting from the rich heritage of OCO-2, GOSAT, TropOMI, and GOME/SCIAMACHY. Column concentrations of CO2, CH4, and CO, with finest resolution at 3 km x 6 km. A selection of scans allowing appreciable refinement in fluxes of CO2 and CH4. Rapid re-pointing allowing at least one synoptic observation of all North and South America daily, and 3 observations through the day for selected areas.This presentation is an appeal to IGAC community to use GeoCarb to help improve the attribution of fluxes by sector and by geography. Cost constraints allow GeoCarb only limited listed goals. For example, GeoCarb aspires to constrain CH4 emissions for the whole US, closing the ~60% gap between US EPA estimation and 3-d models. Detailed CO measurements should also aid photochemical and aerosol studies. NASA's TEMPO (UV-Vis geostationary) instrument will overlap GeoCarb. Consequently, HCHO, NO2, aerosol, and CO may be intercompared, allowing elucidation of chemical sources and also transformation timescales. We expect that Sentinel-5P's TropOMI will lead the way here; geostationary imaging will allow diurnal views and reduced cloud obscuration of interesting areas. Analysis of current data suggests interesting questions: (a) puzzling XCH4 diel variations in the Amazonian rainforest; (b) time-varying CO/NO2 relationships in urban plumes. We also urge the suite of airborne and small-sat measurements needed to complete the story at fine scales.

Chatfield, Robert B.↗

Mission Scenario Development Workbench

The Mission Scenario Development Workbench (MSDW) is a multidisciplinary performance analysis software tool for planning and optimizing space missions. It provides a number of new capabilities that are particularly useful for planning the surface activities on other planets. MSDW enables rapid planning of a space mission and supports flight system and scientific-instrumentation trades. It also provides an estimate of the ability of flight, ground, and science systems to meet high-level mission goals and provides means of evaluating expected mission performance at an early stage of planning in the project life cycle. In MSDW, activity plans and equipment-list spreadsheets are integrated with validated parameterized simulation models of spacecraft systems. In contrast to traditional approaches involving worst-case estimates with large margins, the approach embodied in MSDW affords more flexibility and more credible results early in the lifecycle through the use of validated, variable- fidelity models of spacecraft systems. MSDW is expected to help maximize the scientific return on investment for space missions by understanding early the performance required to have a successful mission while reducing the risk of costly design changes made at late stages in the project life cycle.

Kordon, Mark↗