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NASA NTRSDate not supplied

Recent BOLT Discrete-Roughness Trip Results from the 20-Inch Mach 6 Tunnel

- Air Force Office of Scientific Research (AFOSR) primary sponsor of BOLT (for Boundary Layer Transition) sounding rocket flight project as continuation of previous HIFiRE flights (1 & 5) - Sounding rockets provide cost-effective flight research tool - Study hypersonic BoLT on increasingly complex geometries - BOLT shape includes concave surfaces and swept leading edges - Two missions, two flights: - BOLT mission at Esrange, Sweden - Johns Hopkins University Applied Physics Laboratory as lead - Focus on transition onset measurements - Flew June 2021 (staging anomaly) - BOLT II mission at Wallops Flight Facility, Virginia - Texas A&M and CUBRC provide primary leadership - Focus on turbulence measurements - Flew March 2022 - Flight named in memory of Mike Holden - NASA’s support to both BOLT missions provided through the Hypersonic Technologies Project (HTP)

Hypersonic↗
NASA NTRS2006

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗
NASA NTRS2006

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗
NASA NTRS2000

Pathfinder Program

The Pathfinder Program is presented. The topics include: 1) High Visibility Flight Projects; 3) Significant Events/Accomplishments; 4) Pathfinder Flight Experiments; 5) Top level Goals; 6) Flight Testing for a Multistage Reusable System; 7) Key Embedded Technologies; 8) X-34 Vehicle Description; 9) Government Participation; 10) X-37 Vehicle Characteristics; 10) X-37 Vehicle Deployment Process; and 11) X-37 Configuration Modification Options.

London, John R., III↗
NASA NTRS2018

GOES-16 ABI Navigation Assessment

The US Geostationary Operational Environmental Satellite – R Series (GOES-R) was launched on November 19, 2016and was designated GOES-16 upon reaching geostationary orbit ten days later. After checkout and calibration, GOES-16 was relocated to its operational location of 75.2 degrees west and officially became GOES East on December 18, 2017. The Advanced Baseline Imager (ABI) is the primary instrument on the GOES-R series for imaging Earth's surface and atmosphere to significantly improve the detection and observation of severe environmental phenomena. A team supporting the GOES-R Flight Project at NASA's Goddard Space Flight Center developed algorithms and software for independent verification of ABI Image Navigation and Registration (INR), which became known as the INR Performance Assessment Tool Set (IPATS). In this paper, we will briefly describe IPATS on top concept level, and then introduce the Landsat chips, chip registration algorithms, and how IPATS measurements are filtered. We present GOES-16 navigation (NAV) errors from flight data from January 2017 to May 2018. The results show a) IPATS characterized INR variations throughout the post-launch test phase; and b) ABI INR has improved over time as post-launch tests were performed and corrections applied. Finally, we will describe how estimated NAV errors have been used to assess and understand satellite attitude anomalies and scale errors etc. This paper shows that IPATS is an effective tool for assessing and improving GOES-16 ABI INR and is also useful for INR long-term monitoring.

GOES-R↗
NASA NTRS2012

MBSE in Development: SMAP Pilot Project

Customer-focused objective: Provide value to a flight project using Model-Based Systems Engineering (MBSE) methodology and products. Institution-focused objective: Advance and improve our systems engineering practices, leveraging MBSE where applicable: Streamline our interfaces across JPL Divisions, to provide better cross-organization products; Streamline our interfaces across lifecycle phase boundaries; Update our SE practices to make them more competitive and able to handle systems of ever-increasing complexity.

Soil Moisture Active and Passive (SMAP)↗
NASA NTRS2011

Risk Balance: A Key Tool for Mission Operations Assurance

The Mission Operations Assurance (MOA) discipline actively participates as a project member to achieve their common objective of full mission success while also providing an independent risk assessment to the Project Manager and Office of Safety and Mission Success staff. The cornerstone element of MOA is the independent assessment of the risks the project faces in executing its mission. Especially as the project approaches critical mission events, it becomes imperative to clearly identify and assess the risks the project faces. Quite often there are competing options for the project to select from in deciding how to execute the event. An example includes choices between proven but aging hardware components and unused but unproven components. Timing of the event with respect to visual or telecommunications visibility can be a consideration in the case of Earth reentry or hazardous maneuver events. It is in such situations that MOA is called upon for a risk balance assessment or risk trade study to support their recommendation to the Project Manager for a specific option to select. In the following paragraphs we consider two such assessments, one for the Stardust capsule Earth return and the other for the choice of telecommunications system configuration for the EPOXI flyby of the comet Hartley 2. We discuss the development of the trade space for each project's scenario and characterize the risks of each possible option. The risk characterization we consider includes a determination of the severity or consequence of each risk if realized and the likelihood of its occurrence. We then examine the assessment process to arrive at a MOA recommendation. Finally we review each flight project's decision process and the outcome of their decisions.

operations↗
NASA NTRS2006

Uplink Coding

This viewgraph presentation reviews uplink coding. The purpose and goals of the briefing are (1) Show a plan for using uplink coding and describe benefits (2) Define possible solutions and their applicability to different types of uplink, including emergency uplink (3) Concur with our conclusions so we can embark on a plan to use proposed uplink system (4) Identify the need for the development of appropriate technology and infusion in the DSN (5) Gain advocacy to implement uplink coding in flight projects Action Item EMB04-1-14 -- Show a plan for using uplink coding, including showing where it is useful or not (include discussion of emergency uplink coding).

flight projects↗
NASA NTRS2001

Improving Space Project Cost Estimating with Engineering Management Variables

Current space project cost models attempt to predict space flight project cost via regression equations, which relate the cost of projects to technical performance metrics (e.g. weight, thrust, power, pointing accuracy, etc.). This paper examines the introduction of engineering management parameters to the set of explanatory variables. A number of specific engineering management variables are considered and exploratory regression analysis is performed to determine if there is statistical evidence for cost effects apart from technical aspects of the projects. It is concluded that there are other non-technical effects at work and that further research is warranted to determine if it can be shown that these cost effects are definitely related to engineering management.

Hamaker, Joseph W.↗
NASA NTRS2004

Enabling a New Planning and Scheduling Paradigm

The Flight Projects Directorate at NASA's Marshall Space Flight Center is developing a new planning and scheduling environment and a new scheduling algorithm to enable a paradigm shift in planning and scheduling concepts. Over the past 33 years Marshall has developed and evolved a paradigm for generating payload timelines for Skylab, Spacelab, various other Shuttle payloads, and the International Space Station. The current paradigm starts by collecting the requirements, called "tasks models," from the scientists and technologists for the tasks that they want to be done. Because of shortcomings in the current modeling schema, some requirements are entered as notes. Next a cadre with knowledge of vehicle and hardware modifies these models to encompass and be compatible with the hardware model; again, notes are added when the modeling schema does not provide a better way to represent the requirements. Finally, another cadre further modifies the models to be compatible with the scheduling engine. This last cadre also submits the models to the scheduling engine or builds the timeline manually to accommodate requirements that are expressed in notes. A future paradigm would provide a scheduling engine that accepts separate science models and hardware models. The modeling schema would have the capability to represent all the requirements without resorting to notes. Furthermore, the scheduling engine would not require that the models be modified to account for the capabilities (limitations) of the scheduling engine. The enabling technology under development at Marshall has three major components. (1) A new modeling schema allows expressing all the requirements of the tasks without resorting to notes or awkward contrivances. The chosen modeling schema is both maximally expressive and easy to use. It utilizes graphics methods to show hierarchies of task constraints and networks of temporal relationships. (2) A new scheduling algorithm automatically schedules the models without the intervention of a scheduling expert. The algorithm is tuned for the constraint hierarchies and the complex temporal relationships provided by the modeling schema. It has an extensive search algorithm which can exploit timing flexibilities and constraint and relationship options. (3) A web-based architecture allows multiple remote users to simultaneously model science and technology requirements and other users to model vehicle and hardware characteristics. The architecture allows the users to submit scheduling requests directly to the scheduling engine and immediately see the results. These three components are integrated so that science and technology experts with no knowledge of the vehicle or hardware subsystems and no knowledge of the internal workings of the scheduling engine have the ability to build and submit scheduling requests and see the results. The immediate feedback will hone the users' modeling skills and ultimately enable them to produce the desired timeline. This paper summarizes the three components of the enabling technology and describes how this technology would make a new paradigm possible.

Jaap, John↗
NASA NTRS2004

Autonomous Formation Flight

NASA's Strategic Plan for the Aerospace Technology Enterprise includes ambitious objectives focused on affordable air travel, reduced emissions, and expanded aviation-system capacity. NASA Dryden Flight Research Center, in cooperation with NASA Ames Research Center, the Boeing Company, and the University of California, Los Angeles, has embarked on an autonomous-formation-flight project that promises to make significant strides towards these goals. For millions of years, birds have taken advantage of the aerodynamic benefit of flying in formation. The traditional "V" formation flown by many species of birds (including gulls, pelicans, and geese) enables each of the trailing birds to fly in the upwash flow field that exists just outboard of the bird immediately ahead in the formation. The result for each trailing bird is a decrease in induced drag and thus a reduction in the energy needed to maintain a given speed. Hence, for migratory birds, formation flight extends the range of the system of birds over the range of birds flying solo. The Autonomous Formation Flight (AFF) Project is seeking to extend this symbiotic relationship to aircraft.

Schkolnik, Gerard S.↗
NASA NTRS2012

Improving operations: Metrics to Results

As a result of the mission failure of the Mars Climate Orbiter (MCO) spacecraft in 1999, the Jet Propulsion Laboratory (JPL) initiated the development of a Mission Operations Assurance (MOA) program to be implemented across all flight projects managed by JPL. One of the initiatives undertaken in 2001 was the collection of data on command file errors occurring in the operational phase of the mission. This paper defines command file errors and how and where they occur in the operations process. It also describes the problem reporting system (PRS) in use for mission operations at JPL. We examine the recent modifications to the PRS that enable the collection of metrics, specifically on command file errors. This paper discusses what the data show us since metrics have been collected for the operational missions conducted by JPL. We examine the evolution of an operational working group initiative to evaluate proximate, contributing, and root causes for the errors. As part of this discussion we see what the metrics have indicated over a decade. At the macro level, we can say that the aggregate command file error rate has been cut to roughly one third of the initial 2001 level by the end of 2011. Additionally, we explore efficient and innovative means to continually integrate the findings and recommendations from the working group back into the flight operations environment.

command file errors↗
NASA NTRS1976

Skylab results - Review and outlook

In the history of space flight, Project Skylab marks the transition from short manned flights to long-time manned orbital operations, from single-purpose spacecraft to multipurpose space stations, and from a time of space exploration to a time of space utilization. In the present paper, some of the Skylab scientific programs in the areas of solar physics, stellar astronomy, space physics, earth observations, life sciences, and materials sciences are reviewed. Visible, UV, and X-ray observations showed the sun's surface to be far more active and more differentiated than was earlier assumed. The unexpected apparition of the comet Kohoutek provided valuable information on the composition of cometary nuclei and tails. Pictures taken with earth-looking cameras have provided insight into specific data analysis and assessment problems. Results of the materials science program offer much promise for future work.

Stuhlinger, E.↗
NASA NTRS1995

Propulsion Controlled Aircraft design and development

This paper describes the design, development, and ground testing of the propulsion controlled aircraft (PCA) flight control system. A backup flight control system which uses only engine thrust, the PCA system utilizes collective and differential thrust changes to steer an aircraft that experiences partial or complete failure of the hydraulically actuated control surfaces. The objective of the program was to investigate, in flight, the throttles-only control capability of the F-15, using manual control, and also an augmented PCA mode in which computer-controlled thrust was used for flight control. The objective included PCA operation in up-and-away flight and, if performance was adequate, a secondary objective to make actual PCA landings. The PCA design began with a feasibility study which evaluated many control law designs. The study was done using off-line control analysis, simulation, and on-line manned flight simulator tests. Control laws, cockpit displays, and cockpit controls were evaluated by NASA test pilots. A flight test baseline configuration was selected based on projected flight performance, applicability to transport and fighter aircraft, and funding costs. During the PCA software and hardware development, the initial design was updated as data became available from throttle-only flight experiments conducted by NASA on the F-15. This information showed basic airframe characteristics that were not observed in the F-15 flight simulator and resulted in several design changes. After the primary objectives of the PCA flight testing were accomplished, additional PCA modes of operation were developed and implemented. The evolution of the PCA system from the initial feasibility study, control law design, simulation, hardware-in-the-loop tests, pilot-in-the-loop tests, and ground tests is presented.

Wells, Edward A.↗
NASA NTRS2005

Let's Roll! Rolling Out or Deploying SEPG Assets

The topics covered in this slide presentation are: the general approach to software quality improvement (SQI) at Jet Propulsion Institute, the SQI deployment process, and lessons learned in regard to SQI. The Software Engineering Process Group (SEPG) is the group charged with SQI. The initial focus of the Software Quality Improvement (SQI) Project is on mission-critical software for flight projects, their spacecraft and instrument systems, and their ground systems.

process improvements↗
NASA NTRSDate not supplied

TPSAS-NF1676L-32084-DND

We present aerosol and cloud observations obtained from the satellite-, aircraft- and ship-based measurements of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). The data span three seasons (November 2015, May 2016, and September 2017), which correspond to substantial variation in ocean ecosystem characteristics, continental long-range transport, and local aerosol-cloud microphysics and meteorology. For example, below-cloud aerosol number concentrations in November 2015 were of order 10-50 cm-3, while concentrations observed in May and September were of order 100-500 cm-3. Here, we focus on 20 cloud sampling flight modules carried out during NAAMES, which encompass approximately 27 flight hours of the more than 220 NAAMES project flight hours. The nominal cloud module pattern consists of a series of 5-6 vertically-stacked, horizontal flight legs of 10-15 minute duration (~50-90 km in length) that profile the near-surface (300 ft. altitude) and below-cloud aerosol characteristics, the cloud properties near cloud base and top, the aerosol properties above cloud, and finally a high-altitude remote sensing leg that characterizes the cloud top and above-cloud atmosphere. Ship-based aerosol and ceilometer measurements provide the below-cloud context over time, while GOES satellite imagery and cloud retrieval products fill in the above-cloud story.

Richard H Moore↗
NASA NTRSDate not supplied

Multiphase Simulations of the SLS Launch Environment

NASA’s Space Launch System (SLS), which will send astronauts back to the Moon in the next few years, is powered by four RS-25 engines and two RSRMV solid rocket boosters (SRBs). During launch the SLS propulsion system generates intense acoustics and other powerful waves, such as ignition overpressure (IOP) which, if unmitigated, have the potential to damage the vehicle and possibly cause loss of mission or crew. To protect the vehicle from these powerful waves, the SLS launch pad design includes an ignition overpressure/sound suppression (IOP/SS) system which sprays 270,000 gallons per minute of water very close to the SRB and RS-25 nozzles. The SRB and RS-25 engine plumes, and the proximity of the IOP/SS water, create a complex multiphase (gas and liquid) environment during the SLS ignition sequence. The interplay among these systems creates challenges related to water spray into/onto engine nozzles, potential debris transport, and additional transient loads due to strong plume-water interactions - all of which the SLS vehicle must be able to withstand. Prior to the Artemis I launch, the SLS multiphase liftoff environment was largely unknown due to differences from the Space Shuttle and other programs. Some data was available from tests of individual systems, but no integrated testing or analysis was available. Even post-launch analysis of Artemis I cannot provide a full understanding of the complex physics involved due to limited (or obstructed) camera views and instrumentation. Computational fluid dynamics (CFD) is being used to investigate the details of the multiphase environment which could not be measured, help comprehend the data gathered from the launch, and ultimately identify phenomena that are a concern for future flights. Project Details Engineers at NASA’s Marshall Space Flight Center (MSFC) have executed simulations using the Loci/STREAM-Volume of Fluid (VoF) multiphase CFD solver to understand this environment. Initial efforts successfully validated the CFD solver on various tests, giving confidence to simulate the SLS multiphase liftoff environment prior to the Artemis I launch. The CFD simulation of the SLS ignition sequence was conducted in three phases. First the IOP/SS water system was simulated for approximately 6 seconds to reach a quasi-steady state. Next, the RS-25 engine plumes were activated and held at full power for 1 second. Lastly, the SRB booster was activated and the simulation was carried out until just prior to vehicle motion. This simulation process mimics the conditions that exist at launch. Results and Impact The SLS ignition sequence simulation results provide deep understanding of the underlying physics occuring during launch. Observations from the simulation include reduction of water splashing into/onto the engine nozzles, change in angling of the dense water sheets, and the origin of the powerful ignition overpressure (IOP) wave. These observations directly inform the SLS program on subjects including plume-water induced side loads, debris transport, and the acoustic launch environment. Additionally, with post launch comparison of CFD observations to flight data, these tools can be applied to launch vehicles and environments other than SLS with confidence. Why HPC Matters The SLS ignition sequence CFD simulations are conducted on meshes up to hundreds of millions of cells on thousands of processors for weeks at a time. These simulations generate terabytes of data that must also be stored and archived for future use on HPC systems. Simply put, the CFD simulations would not be possible without NASA HPC resources. What’s Next Comparisons between the Artemis I flight data and the CFD simulations will be continued to both improve confidence in the CFD results and provide deeper understanding into the SLS multiphase launch environment. This will be used to provide insight for decision making for the first manned SLS flight, Artemis II. Future simulations will target new configurations of the SLS IOP/SS water required to support the more powerful variants of the SLS vehicle, such as Block 1B. Additionally, this capability provides NASA the ability to investigate launch environments for vehicles other than SLS to support other missions.

Travis Rivord↗