Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “learning rate”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

NASA GPM Status and Future Activities

The joint U.S.-Japan Global Precipitation Measurement (GPM) mission is approaching a decade of operations, and continues to pursue research, dataset production, and outreach related to precipitation. One key activity over the last year was the release of an improved “Version 07” of all GPM precipitation and latent heating products. This talk summarizes key improvements to the GPM products for which NASA has lead responsibility and provides some examples of the changes between Versions 06 and 07 in algorithm performance. One important operational change that affected Version 07 is that the scanning strategy for the Ka-band radar channel changed in May 2018; all products that depend on Ka were revised to accommodate this change. For example, in Version 07 the Goddard Profiling (GPROF) algorithm has implemented improvements in regions where orographic enhancement and suppression take place and where the surface is snowy/icy, and again covers radiometers reaching back to 1987. The Combined Radar Radiometer Algorithm (CORRA) now incorporates modified drop-size distribution constraints that substantially reduce bias. Revisions to the Convective-Stratiform Heating (CSH) algorithm employ new radiative transfer retrievals as well as accounting for terrain in the vertical coordinates. Each algorithm was adjusted to ensure continuity for each product across the boundary in 2014 between the predecessor Tropical Rainfall Measuring Mission (TRMM) and the GPM Core Observatory. The U.S. Science Team’s Integrated Multi-satellitE Retrievals for GPM (IMERG) was upgraded to account for distortions in the probability density function of regional precipitation rates due to weighted averaging in the Kalman filter used for “morphing” the passive microwave data. The talk will conclude by considering major issues that require continued attention, including the use of machine learning algorithms, the operational challenge of swarms of “small”, perhaps short-lived satellites, and estimates of the remaining lifespan of the Core Observatory.

Global Precipitation Measuremen↗
NASA NTRSDate not supplied

Ground Test Stand Development for One-step Electrochemical Production of High-Pressure Oxygen

NASA designed a test rig, High-Pressure Oxygen Generation Assembly (HPOGA) to test a novel method of electrolysis as an alternative technology to the state-of-the-art Oxygen Generation Assembly (OGA) currently on the International Space Station (ISS). This approach involves utilizing a specialized electrolysis cell stack designed to both generate and compress high-pressure oxygen up to 3600 PSIG. The design eliminates the need for an external compressor and hydrogen separator, streamlining the oxygen generation process. HPOGA tests the viability of an electrolysis cell stack for extended life usage. Within the system, there are several key subsystems: nitrogen, high/low pressure oxygen, hydrogen, water recirculation, and water injection. The water injection subsystem supplies deionized (DI) water to a centralized reservoir for consumption. Subsequently, a water recirculation loop transfers the DI water across the cathode side of the electrolysis cell stack with constant flow rate. The result is a supply of hydrogen in the water loop and oxygen accumulation on the anode side of the cell stack. Hydrogen is evaporated out as part of the hydrogen sub-system which also measures hydrogen/oxygen concentration for safety. The oxygen subsystem is responsible for managing high pressure oxygen, O2 exhaust, and conducting hydrogen/oxygen concentration measurements. The nitrogen subsystem serves dual functions, purging the hydrogen/oxygen subsystems, and regulating pressure in both high/low-pressure O2 sections via pneumatic back pressure regulators. Various sensors monitor pressure, temperature, humidity, gas concentration and flow rate in each subsystem. This paper presents the design and testing of a comprehensive test stand, which serves to operate and functionally verify the performance of the electrolysis cell while offering valuable lessons learned.

electrolysis↗
NASA NTRSDate not supplied

Machine Learning to Predict Joint Performance in Epoxy Composites Based on Process Parameters

Polymer matrix composites are gaining popularity in the aerospace industry due to their high specific strength, fatigue properties, and processability. However, based on current FAA certification guidelines, manufacturers utilizing current state-of-the art composites made with adhesive bonds commonly install redundant fasteners to guarantee the strength of these adhesively bonded composite parts.1,2 The number of fasteners in a single-aisle commercial transport aircraft is typically on the order of 105, which reduces manufacturing rate, increases cost tremendously, and reduces the advantage of the specific strength composites provide. Due to this, the Adhesive Free Bonding of Composites (AERoBOND) project at NASA Langley Research Center has developed a novel assembly process to manufacture complex composite parts without the use of adhesives and fasteners.1 However, optimization of the process is currently challenging due to the complex and interdependent process parameters. To assist with the optimization, four machine learning algorithms utilizing gradient boosting decision trees were created to provide predictions for the mechanical and characterization properties of the composite parts. Approximately 200 random states from each algorithm were tested, and the models from each state were isolated and analyzed based on their accuracy, a validation process, and their feature importance. This analysis concluded that the models created from the machine learning algorithms could accelerate a parametric study for the AERoBOND process by rapidly optimizing process parameters to achieve desired performance characteristics.

Brennen M Middleton↗
NASA NTRS2000

Preliminary Analysis of Photoreading

The purpose of this project was to provide a preliminary analysis of a reading strategy called PhotoReading. PhotoReading is a technique developed by Paul Scheele that claims to increase reading rate to 25,000 words per minute (Scheele, 1993). PhotoReading itself involves entering a "relaxed state" and looking at, but not reading, each page of a text for a brief moment (about I to 2 seconds). While this technique has received attention in the popular press, there had been no objective examinations of the technique's validity. To examine the effectiveness of PhotoReading, the principal investigator (i.e., trainee) participated in a PhotoReading workshop to learn the technique. Parallel versions of two standardized and three experimenter-created reading comprehension tests were administered to the trainee and an expert user of the PhotoReading technique to compare the use of normal reading strategies and the PhotoReading technique by both readers. The results for all measures yielded no benefits of using the PhotoReading technique. The extremely rapid reading rates claimed by PhotoReaders were not observed; indeed, the reading rates were generally comparable to those for normal reading. Moreover, the PhotoReading expert generally showed an increase in reading time when using the PhotoReading technique in comparison to when using normal reading strategies to process text. This increase in reading time when PhotoReading was accompanied by a decrease in text comprehension.

McNamara, Danielle S.↗
NASA NTRS2004

Microgravity Spray Cooling Research for High Powered Laser Applications

An extremely powerful laser is being developed at Goddard Space Flight Center for use on a satellite. This laser has several potential applications. One application is to use it for upper atmosphere weather research. In this case, the laser would reflect off aerosols in the upper atmosphere and bounce back to the satellite, where the aerosol velocities could be calculated and thus the upper atmosphere weather patterns could be monitored. A second application would be for the US. Air Force, which wants to use the laser strategically as a weapon for satellite defense. The Air Force fears that in the coming years as more and more nations gain limited space capabilities that American satellites may become targets, and the laser could protect the satellites. Regardless of the ultimate application, however, a critical step along the way to putting the laser in space is finding a way to efficiently cool it. While operating the laser becomes very hot and must be cooled to prevent overheating. On earth, this is accomplished by simply running cool tap water over the laser to keep it cool. But on a satellite, this is too inefficient. This would require too much water mass to be practical. Instead, we are investigating spray cooling as a means to cool the laser in microgravity. Spray cooling requires much less volume of fluid, and thus could be suitable for use on a satellite. We have inherited a 2.2 second Drop Tower rig to conduct our research with. In our experiments, water is pressurized with a compressed air tank and sprayed through a nozzle onto our test plate. We can vary the pressure applied to the water and the temperature of the plate before an experiment trial. The whole process takes place in simulated microgravity in the 2.2 second Drop Tower, and a high speed video camera records the spray as it hits the plate. We have made much progress in the past few weeks on these experiments. The rig originally did not have the capability to heat the test plate, but I did some heat transfer calculations and picked out a heater to order for the rig. I learned QBasic programming language to change the operating code for our drops, allowing us to rapidly cycle the spray nozzle open and closed to study the effects. We have derived an equation for flow rate vs. pressure for our experiment. We have recorded several videos of drops at different pressures, some with heated test plate and some without, and have noticed substantial differences in the liquid behavior. I have also changed the computer program to write a file with temperature vs. time profiles for the test plate, and once the necessary thermocouple comes in (it was ordered last week), we will have temperature profiles to accompany the videos. Once we have these temperature profiles to go with the videos, we will be able to see how the temperature is affected by the spray at different pressures, and how the spray changes its behavior once as the plate changes from hot to cool. With quantitative temperature data, we can then mathematically model the heat transfer from the plate to the cooling spray. Finally, we can look at the differences between trials in microgravity and those in normal earth gravity.

Zivich, Chad P.↗
NASA NTRS2017

Neural Predictors of Visuomotor Adaptation Rate and Multi-Day Savings

Recent studies of sensorimotor adaptation have found that individual differences in task-based functional brain activation are associated with the rate of adaptation and savings at subsequent sessions. However, few studies to date have investigated offline neural predictors of adaptation and multi-day savings. In the present study, we explore whether individual differences in the rate of visuomotor adaptation and multi-day savings are associated with differences in resting state functional connectivity and gray matter volume. Thirty-four participants performed a manual adaptation task during two separate test sessions, on average 9 days apart. We found that resting state functional connectivity strength between sensorimotor, anterior cingulate, and temporoparietal areas of the brain was a significant predictor of adaptation rate during the early, cognitive phase of practice. In contrast, default mode network functional connectivity strength was found to predict late adaptation rate and savings on day two, which suggests that these behaviors may rely on overlapping processes. We also found that gray matter volume in temporoparietal and occipital regions was a significant predictor of early learning, whereas gray matter volume in superior posterior regions of the cerebellum was a significant predictor of late adaptation. The results from this study suggest that offline neural predictors of early adaptation facilitate the cognitive mechanisms of sensorimotor adaptation, with support from by the involvement of temporoparietal and cingulate networks. In contrast, the neural predictors of late adaptation and savings, including the default mode network and the cerebellum, likely support the storage and modification of newly acquired sensorimotor representations. These findings provide novel insights into the neural processes associated with individual differences in sensorimotor adaptation.

Cassady, Kaitlin↗
NASA NTRS2010

Evaluating Heuristics for Planning Effective and Efficient Inspections

A significant body of knowledge concerning software inspection practice indicates that the value of inspections varies widely both within and across organizations. Inspection effectiveness and efficiency can be measured in numerous ways, and may be affected by a variety of factors such as Inspection planning, the type of software, the developing organization, and many others. In the early 1990's, NASA formulated heuristics for inspection planning based on best practices and early NASA inspection data. Over the intervening years, the body of data from NASA inspections has grown. This paper describes a multi-faceted exploratory analysis performed on this · data to elicit lessons learned in general about conducting inspections and to recommend improvements to the existing heuristics. The contributions of our results include support for modifying some of the original inspection heuristics (e.g. Increasing the recommended page rate), evidence that Inspection planners must choose between efficiency and effectiveness, as a good tradeoff between them may not exist, and Identification of small subsets of inspections for which new inspection heuristics are needed. Most Importantly, this work illustrates the value of collecting rich data on software Inspections, and using it to gain insight into, and Improve, inspection practice.

Shull, Forrest J.↗
NASA NTRS2017

From Prototype to Flight: Qualifying a Ka-Band Parabolic Deployable Antenna (KaPDA) for CubeSats

CubeSats have experienced a number of exciting technological advancements in the past several years. However, until recently, there has been very limited development in the area of high gain CubeSat antennas, which are critical for both high data rate communications and radar science. A Ka-band high gain antenna would provide a 10,000 times increase in data communication rates over an X-band patch antenna and a 100 times increase over state-of-the-art S-band parabolic antennas. Because of this, three years ago the Jet Propulsion Laboratory (JPL) initiated a research and technology development effort to advance CubeSat communication capabilities, with one of the key thrusts being the Ka-band parabolic deployable antenna (KaPDA). This antenna started with the ambitious goal of fitting a 42 dB, 0.5 meter, 35 Ghz antenna in a 1.5U (10 cm x 10 cm x 17 cm) canister. This paper discusses the process of taking the antenna from a first prototype to the flight design, which is flying on the RainCube mission, and earth science CubeSat. The prototype antenna was constructed in early 2015, and then upgraded to an engineering model at the end of 2016 to compensate for lessons learned. The flight version is currently under construction, and scheduled to be finished in 2016. KaPDA is the second deployable parabolic antenna to fly on a CubeSat, and the first of its kind to operate at Ka-band enabling a number of opportunities for high rate deep space antenna communications and radar science.

Sauder, Jonathan↗
NASA NTRS2009

Using Decision Trees to Detect and Isolate Simulated Leaks in the J-2X Rocket Engine

The goal of this work was to use data-driven methods to automatically detect and isolate faults in the J-2X rocket engine. It was decided to use decision trees, since they tend to be easier to interpret than other data-driven methods. The decision tree algorithm automatically "learns" a decision tree by performing a search through the space of possible decision trees to find one that fits the training data. The particular decision tree algorithm used is known as C4.5. Simulated J-2X data from a high-fidelity simulator developed at Pratt & Whitney Rocketdyne and known as the Detailed Real-Time Model (DRTM) was used to "train" and test the decision tree. Fifty-six DRTM simulations were performed for this purpose, with different leak sizes, different leak locations, and different times of leak onset. To make the simulations as realistic as possible, they included simulated sensor noise, and included a gradual degradation in both fuel and oxidizer turbine efficiency. A decision tree was trained using 11 of these simulations, and tested using the remaining 45 simulations. In the training phase, the C4.5 algorithm was provided with labeled examples of data from nominal operation and data including leaks in each leak location. From the data, it "learned" a decision tree that can classify unseen data as having no leak or having a leak in one of the five leak locations. In the test phase, the decision tree produced very low false alarm rates and low missed detection rates on the unseen data. It had very good fault isolation rates for three of the five simulated leak locations, but it tended to confuse the remaining two locations, perhaps because a large leak at one of these two locations can look very similar to a small leak at the other location.

Schwabacher, Mark A.↗
NASA NTRS2021

TLife-LSTM: Forecasting Future COVID-19 Progression with Topological Signatures of Atmospheric Conditions

Understanding the impact of atmospheric conditions on SARS-CoV2 is critical to model COVID-19 dynamics and sheds a light on the future spread around the world. Furthermore, geographic distri- butions of expected clinical severity of COVID-19 may be closely linked to prior history of respiratory diseases and changes in humidity, tem- perature, and air quality. In this context, we postulate that by tracking topological features of atmospheric conditions over time, we can provide a quanti?able structural distribution of atmospheric changes that are likely to be related to COVID-19 dynamics. As such, we apply the machinery of persistence homology on time series of graphs to extract topological signatures and to follow geographical changes in relative humidity and temperature. We develop an integrative machine learning framework named Topological Lifespan LSTM (TLife-LSTM) and test its predictive capabilities on forecasting the dynamics of SARS-CoV2 cases. We validate our framework using the number of con?rmed cases and hospitalization rates recorded in the states of Washington and California in the USA. Our results demonstrate the predictive potential of TLife-LSTM in forecasting the dynamics of COVID-19 and modeling its complex spatio-temporal spread dynamics.

Gel, Yulia R.↗
NASA NTRS2004

Digital communication constraints in prior space missions

Digital communication is crucial for space endeavors. Jt transmits scientific and command data between earth stations and the spacecraft crew. It facilitates communications between astronauts, and provides live coverage during all phases of the mission. Digital communications provide ground stations and spacecraft crew precise data on the spacecraft position throughout the entire mission. Lessons learned from prior space missions are valuable for our new lunar and Mars missions set by our president s speech. These data will save our agency time and money, and set course our current developing technologies. Limitations on digital communications equipment pertaining mass, volume, data rate, frequency, antenna type and size, modulation, format, and power in the passed space missions are of particular interest. This activity is in support of ongoing communication architectural studies pertaining to robotic and human lunar exploration. The design capabilities and functionalities will depend on the space and power allocated for digital communication equipment. My contribution will be gathering these data, write a report, and present it to Communications Technology Division Staff. Antenna design is very carefully studied for each mission scenario. Currently, Phased array antennas are being developed for the lunar mission. Phased array antennas use little power, and electronically steer a beam instead of DC motors. There are 615 patches in the phased array antenna. These patches have to be modified to have high yield. 50 patches were created for testing. My part is to assist in the characterization of these patch antennas, and determine whether or not certain modifications to quartz micro-strip patch radiators result in a significant yield to warrant proceeding with repairs to the prototype 19 GHz ferroelectric reflect-array antenna. This work requires learning how to calibrate an automatic network, and mounting and testing antennas in coaxial fixtures. The purpose of this activity is to assist in the set-up of phase noise instrumentation, assist in the process of automated wire bonding, assist in the design and optimization of tunable microwave components, especially phase shifters, based on thin ferroelectric films, and learn how to use commercial electromagnetic simulation software.

Yassine, Nathan K.↗
NASA NTRS2021

Data-driven landslide nowcasting at the global scale

Landslides affect nearly every country in the world each year. To better understand this global hazard, the Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed previously. LHASA version 1 combines satellite precipitation estimates with a global landslide susceptibility map to produce a gridded map of potentially hazardous areas from 60° North-South every 3 h. LHASA version 1 categorizes the world’s land surface into three ratings: high, moderate, and low hazard with a single decision tree that first determines if the last seven days of rainfall were intense, then evaluates landslide susceptibility. LHASA version 2 has been developed with a data-driven approach. The global susceptibility map was replaced with a collection of explanatory variables, and two new dynamically varying quantities were added: snow and soil moisture. Along with antecedent rainfall, these variables modulated the response to current daily rainfall. In addition, the Global Landslide Catalog (GLC) was supplemented with several inventories of rainfall-triggered landslide events. These factors were incorporated into the machine-learning framework XGBoost, which was trained to predict the presence or absence of landslides over the period 2015–2018, with the years 2019–2020 reserved for model evaluation. As a result of these improvements, the new global landslide nowcast was twice as likely to predict the occurrence of historical landslides as LHASA version 1, given the same global false positive rate. Furthermore, the shift to probabilistic outputs allows users to directly manage the trade-off between false negatives and false positives, which should make the nowcast useful for a greater variety of geographic settings and applications. In a retrospective analysis, the trained model ran over a global domain for 5 years, and results for LHASA version 1 and version 2 were compared. Due to the importance of rainfall and faults in LHASA version 2, nowcasts would be issued more frequently in some tropical countries, such as Colombia and Papua New Guinea; at the same time, the new version placed less emphasis on arid regions and areas far from the Pacific Rim. LHASA version 2 provides a nearly real-time view of global landslide hazard for a variety of stakeholders.

XGBoos↗
NASA NTRS2011

Solid Rocket Booster (SRB) - Evolution and Lessons Learned During the Shuttle Program

The Solid Rocket Booster (SRB) element integrates all the subsystems needed for ascent flight, entry, and recovery of the combined Booster and Motor system. These include the structures, avionics, thrust vector control, pyrotechnic, range safety, deceleration, thermal protection, and retrieval systems. This represents the only human-rated, recoverable and refurbishable solid rocket ever developed and flown. Challenges included subsystem integration, thermal environments and severe loads (including water impact), sometimes resulting in hardware attrition. Several of the subsystems evolved during the program through design changes. These included the thermal protection system, range safety system, parachute/recovery system, and others. Obsolescence issues occasionally required component recertification. Because the system was recovered, the SRB was ideal for data and imagery acquisition, which proved essential for understanding loads and system response. The three main parachutes that lower the SRBs to the ocean are the largest parachutes ever designed, and the SRBs are the largest structures ever to be lowered by parachutes. SRB recovery from the ocean was a unique process and represented a significant operational challenge; requiring personnel, facilities, transportation, and ground support equipment. The SRB element achieved reliability via extensive system testing and checkout, redundancy management, and a thorough postflight assessment process. Assembly and integration of the booster subsystems was a unique process and acceptance testing of reused hardware components was required for each build. Extensive testing was done to assure hardware functionality at each level of stage integration. Because the booster element is recoverable, subsystems were available for inspection and testing postflight, unique to the Shuttle launch vehicle. Problems were noted and corrective actions were implemented as needed. The postflight assessment process was quite detailed and a significant portion of flight operations. The SRBs provided fully redundant critical systems including thrust vector control, mission critical pyrotechnics, avionics, and parachute recovery system. The design intent was to lift off with full redundancy. On occasion, the redundancy management scheme was needed during flight operations. This paper describes some of the design challenges, how the design evolved with time, and key areas where hardware reusability contributed to improved system level understanding.

Kanner, Howard S.↗
NASA NTRS2024

Optimizing Air Traffic - Integrating Artificial Intelligence and Machine Learning in Flight Path Planning and 3D Airspace Visualization for Air Traffic Control

Air Traffic Control (ATC) systems are vital components of the National Airspace System (NAS). ATC, Airport Traffic Control Towers (ATCT), and Terminal Radar Approach Control (TRACON) are responsible for directing all flights departing from and arriving at airports, managing our nation’s airspace, preventing potential accidents, and ensuring that every flight is accounted for. However, these systems often face challenges in effectively monitoring the skies. Issues such as poor communication between operators, difficulty in performing operations, and the constant need for vigilance frequently burden ATC operators. Additionally, the projected increase in air traffic in the coming years will only exacerbate the stress associated with this role. To address these issues, we propose a system that assists ATC operators in situations such as handovers, emergencies, and routing aircraft to avoid weather hazards. Our solution includes an Artificial Intelligence (AI) and Machine Learning (ML)-based Flight Pathways Planning System (FPPS) designed to find the fastest and most optimal routes for aircraft, taking into account weather conditions, restricted terrain, and Extended-Range Twin-Engine Operational Performance Standards (ETOPS) ratings. The proposed Predictive Weather Planning Model, included in FPPS, adjusts routes based on real-time and forecasted weather conditions. Additionally, our NVIDIA Omniverse 3D Visualization System offers a highly interactive environment for better visualization and a clear view of the airspace. By incorporating these systems, the roles of ATC, ATCT, and TRACON operators will become more manageable and less stressful, equipping them to efficiently handle the growing density of airspace.

Regina Ayoubi↗
NASA NTRS2006

Near-Miss Evaluation Bias as an Obstacle to Organizational Learning: Lessons from NASA

After the Shuttle Columbia catastrophe, the investigation board (CAIB) stated that NASA needs to develop a "learning culture", meaning a capability to learn from past failures by understanding the technical and organizational causes of these mistakes (CAIB report, 2003). While many organizations learn from obvious failures, we argue that it is harder for organizations to learn from near-miss events (i.e., situations where a failure does not occur but nearly did), because these near-misses are processed as successes. For the shuttle program, prior debris problems could have caused a similar failure as on the Columbia mission except that the large pieces missed the highly sensitive portions of the orbiter. This acceptance of foam debris was adopted as a normal occurrence by the shuttle program managers similar to the problems at the time of the Challenger Disaster (detailed in Vaughan, 1996). We extend that work to show that an outcome bias influences people's evaluation of project managers, such that managers of failed missions were perceived more poorly than managers who made the same decisions but whose mission ended in either success or a near-miss. The similarity of ratings between the near-miss and success condition imply that even when a problem occurs that is clearly linked to prior managerial decisions, if the project is not harmed because of good luck, that manager is not held accountable for faculty decision making and neither the individual manager nor the organization learn from the experience potentially increasing the likelihood of a failure in the future.

Dillon, Robin L.↗
NASA NTRS1988

Portable high-speed photometry systems for observing occultations

Because of their high spatial resolution, stellar occultations have proven extremely effective for learning about planetary upper atmospheres, asteroids, and planetary rings. The ring orbit studies for Uranus have been particularly fruitful because researchers have been able, through occultations, to obtain data of high spatial resolution (approximately 2 km) at the rate of 1 to 2 times per year. THe occultation program at M.I.T. involves: (1) identifying the scientific questions that can be answered by occultation events, (2) predicting the zone of visibilty for the useful events, (3) maintaining and improving a set of portable high-speed photometric systems, (4) obtaining the observations, and (5) reducing the data and interpreting the results. Accomplishments during the past year include: (1) a comprehensive analysis of stellar occultation data to obtain an oblateness for Uranus at the 10 ubar level of 0.0193 plus or minus 0.0010, a value consistent with the planet being in hydrostatic equilibrium and undergoing rotation at the period found by Voyger; (2) establishing an upper limit of 0.004 km on the equivalent depth of 1986U1R from 2.2 micrometer occultation data; (3) the discovery of low-amplitude waves on the edges of the epsilon ring of Uranus; and (4) the acquisition of several hundred charge coupled device strip scans of 6 weeks at Mauna Kea for the purpose of generating a prediction for the stellar occultation of Pluto.

Elliot, James L.↗
NASA NTRS1992

Workshop on the Physics and Chemistry of Magma Oceans from 1 Bar to 4 Mbar

Evidence for the existence of magma oceans is discussed in great detail, and among the many new items introduced were high-pressure phase equilibrium experiments, calculations of depth of impact-produced melting, models incorporating crystal growth rates with degree of crystallinity and convection, and models of hard turbulent convection. It was agreed that before we can point to some present-day observable parameters and confidently establish the existence of magma oceans, we must learn much more about their phase equilibria and solidification dynamics.

Agee, Carl B.↗
NASA NTRS2000

X-38 Vehicle 131R Free Flights 1 and 2

The X-38 program is using a modern flight control system (FCS) architecture originally developed by Honeywell called MACH. During last year's SAE G&C subcommittee meeting, we outlined the design, implementation and testing of MACH in X-38 Vehicles 132, 131R & 201. During this year's SAE meeting, I'll focus upon the first two free flights of V131R, describing what caused the roll-over in FF1 and how we fixed it for FF2. I only have 30 minutes, so it will be a quick summary including VHS video. X-38 is a NASA JSC/DFRC experimental flight test program developing a series of prototypes for an International Space Station (ISS) Crew Return Vehicle (CRV), often described as an ISS "lifeboat." X-38 Vehicle 132 Free Flight 3 was the first flight test of a modern FCS architecture called Multi-Application ControlH (MACH), developed by the Honeywell Technology Center in Minneapolis and Honeywell's Houston Engineering Center. MACH wraps classical Proportional+integral (P+I) outer attitude loops around modern dynamic inversion attitude rate loops. The presentation at last year's SAE Aerospace Meeting No. 85 focused upon the design and testing of the FCS algorithm and Vehicle 132 Free Flight 3. This presentation will summarize flight control and aerodynamics lessons learned during Free Flights 1 and 2 of Vehicle 131R, a subsonic test vehicle laying the groundwork for the orbital/entry test of Vehicle 201 in 2003.

Munday, Steve↗