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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.

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NASA NTRS2011

Long-Term International Space Station (ISS) Risk Reduction Activities

As the assembly of the ISS nears completion, it is worthwhile to step back and review some of the actions pursued by the Program in recent years to reduce risk and enhance the safety and health of ISS crewmembers, visitors, and space flight participants. While the initial ISS requirements and design were intended to provide the best practicable levels of safety, it is always possible to further reduce risk given the determination, commitment, and resources to do so. The following is a summary of some of the steps taken by the ISS Program Manager, by our International Partners, by hardware and software designers, by operational specialists, and by safety personnel to continuously enhance the safety of the ISS, and to reduce risk to all crewmembers. While years of work went into the development of ISS requirements, there are many things associated with risk reduction in a Program like the ISS that can only be learned through actual operational experience. These risk reduction activities can be divided into roughly three categories: Areas that were initially noncompliant which have subsequently been brought into compliance or near compliance (i.e., Micrometeoroid and Orbital Debris [MMOD] protection, acoustics) Areas where initial design requirements were eventually considered inadequate and were subsequently augmented (i.e., Toxicity hazard level-4 materials, emergency procedures, emergency equipment, control of drag-throughs) Areas where risks were initially underestimated, and have subsequently been addressed through additional mitigation (i.e., Extravehicular Activity [EVA] sharp edges, plasma shock hazards). Due to the hard work and cooperation of many parties working together across the span of more than a decade, the ISS is now a safer and healthier environment for our crew, in many cases exceeding the risk reduction targets inherent in the intent of the original design. It will provide a safe and stable platform for utilization and discovery for years to come.

Forroci, Michael P.↗
NASA NTRS2011

The Application of Lean Thinking Principles and Kaizen Practices for the Successful Development and Implementation of the Ares I-X Flight Test Rocket and Mission

On October 28, 2009 the Ares I-X flight test rocket launched from Kennedy Space Center and flew its suborbital trajectory as designed. The mission was successfully completed as data from the test, and associated development activities were analyzed, transferred to stakeholders, and well documented. A positive lesson learned from Ares I-X was that the application of lean thinking principles and kaizen practices was very effective in streamlining development activities. Ares I-X, like other historical rocket development projects, was hampered by technical, cost, and schedule challenges and if not addressed boldly could have resulted in cancellation of the test. The mission management team conducted nine major meetings, referred to as lean events, across its elements to assess plans, procedures, processes, requirements, controls, culture, organization, use of resources, and anything that could be changed to optimize schedule or reduce risk. The preeminent aspect of the lean events was the focus on value added activities and the removal or at least reduction in non-value added activities. Trained Lean Six Sigma facilitators assisted the Ares I-X developers in conducting the lean events. They indirectly helped formulate the mission s own unique methodology for assessing schedule. A core team was selected to lead the events and report to the mission manager. Each activity leveraged specialized participants to analyze the subject matter and its related processes and then recommended alternatives and solutions. Stakeholders were the event champions. They empowered and encouraged the team to succeed. The keys to success were thorough preparation, honest dialog, small groups, adherence to the Ares I-X ground rules, and accountability through disciplined reporting and tracking of actions. This lean event formula was game-changing as demonstrated by Ares I-X. It is highly recommended as a management tool to help develop other complex systems efficiently. The key benefits for Ares I-X were obtaining unambiguous schedule margin, defining enabling options for risk reduction, and most importantly a stronger more unified team.

Askins, B. R.↗
NASA NTRS1996

Cascade Error Projection: A Learning Algorithm for Hardware Implementation

In this paper, we workout a detailed mathematical analysis for a new learning algorithm termed Cascade Error Projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters. Furthermore, CEP learning algorithm is operated only on one layer, whereas the other set of weights can be calculated deterministically. In association with the dynamical stepsize change concept to convert the weight update from infinite space into a finite space, the relation between the current stepsize and the previous energy level is also given and the estimation procedure for optimal stepsize is used for validation of our proposed technique. The weight values of zero are used for starting the learning for every layer, and a single hidden unit is applied instead of using a pool of candidate hidden units similar to cascade correlation scheme. Therefore, simplicity in hardware implementation is also obtained. Furthermore, this analysis allows us to select from other methods (such as the conjugate gradient descent or the Newton's second order) one of which will be a good candidate for the learning technique. The choice of learning technique depends on the constraints of the problem (e.g., speed, performance, and hardware implementation); one technique may be more suitable than others. Moreover, for a discrete weight space, the theoretical analysis presents the capability of learning with limited weight quantization. Finally, 5- to 8-bit parity and chaotic time series prediction problems are investigated; the simulation results demonstrate that 4-bit or more weight quantization is sufficient for learning neural network using CEP. In addition, it is demonstrated that this technique is able to compensate for less bit weight resolution by incorporating additional hidden units. However, generation result may suffer somewhat with lower bit weight quantization.

Duong, Tuan A.↗
NASA NTRSDate not supplied

Overview of Advanced Stirling Convertor Dual Convertor Controller Development and Testing at NASA Glenn Research Center

For over two decades, NASA Glenn Research Center (GRC) has been supporting the development of Radioisotope Power Systems (RPS). NASA desires higher conversion efficiency RPS options that are reliable and robust with long life design. Dynamic conversion, such as Stirling offer the potential for higher conversion efficiencies than current RPS but have yet to be demonstrated in a flight application. GRC developed a non-nuclear representation of a RPS consisting of a pair of Advanced Stirling Convertors (ASC), a Dual Convertor Controller (DCC), and associated support equipment. The DCC was designed by the Johns Hopkins University/Applied Physics Laboratory (JHU/APL) to actively control a pair of ASCs. Based on lessons learned, three generations of DCCs were developed over the past decade. After each generation of the DCC was completed, tests were performed to verify functionality. These tests include acceptance testing, fault testing, characterization testing, and testing with the Radioisotope Power System Systems Integration Laboratory (RSIL). Acceptance testing verifies that the DCC can control a pair of ASCs to produce full convertor power output. The fault testing verifies that the DCC can maintain control of the ASCs during either internal or external faults. Characterization testing verifies the functionality of the DCC over a range of bus voltage values. RSIL provides insight into the electrical interactions between a representative radioisotope power generator, its associated control schemes, and realistic electric system loads. The DCC design, development, lessons learned, test results, and future work are presented in this paper.

Stirling↗
NASA NTRS1980

Mission management - Lessons learned from early Spacelab missions

The concept and the responsibilities of a mission manager approach are reviewed, and some of the associated problems in implementing Spacelab mission are discussed. Consideration is given to program control, science management, integrated payload mission planning, and integration requirements. Payload specialist training, payload and launch site integration, payload flight/mission operations, and postmission activities are outlined.

Craft, H. G., Jr.↗
NASA NTRS2004

Multi-Agent Methods for the Configuration of Random Nanocomputers

As computational devices continue to shrink, the cost of manufacturing such devices is expected to grow exponentially. One alternative to the costly, detailed design and assembly of conventional computers is to place the nano-electronic components randomly on a chip. The price for such a trivial assembly process is that the resulting chip would not be programmable by conventional means. In this work, we show that such random nanocomputers can be adaptively programmed using multi-agent methods. This is accomplished through the optimization of an associated high dimensional error function. By representing each of the independent variables as a reinforcement learning agent, we are able to achieve convergence must faster than with other methods, including simulated annealing. Standard combinational logic circuits such as adders and multipliers are implemented in a straightforward manner. In addition, we show that the intrinsic flexibility of these adaptive methods allows the random computers to be reconfigured easily, making them reusable. Recovery from faults is also demonstrated.

Lawson, John W.↗
NASA NTRS2017

Methodology for Assessing Reusability of Spaceflight Hardware

In 2011 the Space Shuttle, the only Reusable Launch Vehicle (RLV) in the world, returned to earth for the final time. Upon retirement of the Space Shuttle, the United States (U.S.) no longer possessed a reusable vehicle or the capability to send American astronauts to space. With the National Aeronautics and Space Administration (NASA) out of the RLV business and now only pursuing Expendable Launch Vehicles (ELV), not only did companies within the U.S. start to actively pursue the development of either RLVs or reusable components, but entities around the world began to venture into the reusable market. For example, SpaceX and Blue Origin are developing reusable vehicles and engines. The Indian Space Research Organization is developing a reusable space plane and Airbus is exploring the possibility of reusing its first stage engines and avionics housed in the flyback propulsion unit referred to as the Advanced Expendable Launcher with Innovative engine Economy (Adeline). Even United Launch Alliance (ULA) has announced plans for eventually replacing the Atlas and Delta expendable rockets with a family of RLVs called Vulcan. Reuse can be categorized as either fully reusable, the situation in which the entire vehicle is recovered, or partially reusable such as the National Space Transportation System (NSTS) where only the Space Shuttle, Space Shuttle Main Engines (SSME), and Solid Rocket Boosters (SRB) are reused. With this influx of renewed interest in reusability for space applications, it is imperative that a systematic approach be developed for assessing the reusability of spaceflight hardware. The partially reusable NSTS offered many opportunities to glean lessons learned; however, when it came to efficient operability for reuse the Space Shuttle and its associated hardware fell short primarily because of its two to four-month turnaround time. Although there have been several attempts at designing RLVs in the past with the X-33, Venture Star and Delta Clipper Experimental (DC-X), reusability within the spaceflight arena is still in its infancy. With unlimited resources (namely, time and money), almost any launch vehicle and its associated hardware can be made reusable. However, an endless supply of funds for space exploration is not the case in today's economy for neither government agencies nor their commercial counterparts. Therefore, any organization wanting to be a leader in space exploration and remain competitive in this unforgiving space faring industry must confront shrinking budgets with more cost conscious and efficient designs. Therefore, standards for developing reusable spaceflight hardware need to be established. By having standards available to existing and emerging companies, some of the potential roadblocks and limitations that plagued previous attempts at reuse may be minimized or completely avoided.

Childress-Thompson, Rhonda↗
NASA NTRS2019

Flow Boiling and Condensation Experiment Flight Hardware Development

The Flow Boiling and Condensation Experiment (FBCE) to be manifested on the International Space Station (ISS) consists of a fluid system and the associated electronics to provide for conditioning the test fluid (normal-PerFluorohexane or nPFH-C6F14) to the proper thermodynamic state prior to entering a test module, which can be interchangeable based on the science objectives. Two separate test modules have been manufactured for the FBCE, the Flow Boiling Module (FBM), which investigates flow boiling for a subcooled liquid, saturated liquid, or two phase mixture, and the Condensation Module Heat Transfer (CM-HT), which investigates condensation of a flowing saturated or superheated vapor. The test fluid heating is accomplished using the Bulk Heater Module (BHM), which heats the fluid to various states based on the demands of the currently installed test module. ISS Internal Thermal Control System (ITCS) water is utilized to cool the test fluid prior to entering the circulation pump, and is also utilized for cooling for condensation in CM-HT, for cooling of a camera in FBM. An adjustable pressure bellows-type accumulator is used to set the pressure at the inlet of the test section, but does not provide active pressure control during testing. The flow of the test fluid is achieved using a gear pump controlled by a coriolis flow meter, which also provides the flow rate measurement. Flow rates for the ITCS water loops are measured and controlled using coriolis flow meters with directly controlled proportional valves. During execution of FBCE operations, the FBM is scheduled to collect data for three months before being exchanged with CM-HT for another three month data collection run. In this work, we present the development of the flight hardware, the associated challenges experienced during the development such as packaging flight system hardware, and the lessons learned in overcoming the encountered challenges.

Guzik, Monica C.↗
NASA NTRS2020

Shape Memory Alloys – Not Your Ordinary Metal

Sixty years after the discovery of shape memory alloys (SMAs), many actuation and structural applications using these materials have been conceived and developed. SMAs are a unique class of multifunctional materials that have the ability to recover large deformations and generate high stresses in response to thermal, mechanical and/or electromagnetic stimuli. These abilities have made them a viable option for actuation/structural systems in aerospace applications, amongst others. However, designing with SMAs is a paradigm shift from the conventional way we look at metals and mechanisms. In this course, you will learn how the unique properties of SMAs can be applied to designing mechanisms and the associated benefits. Basic primer will be provided on what they are and why they work with examples of the most successful applications that have been imagined. Common design tool and properties-database will be discussed.

Othmane Benafan↗
NASA NTRS1993

New Technologies for Space Avionics, 1993

The report reviews a 1993 effort that investigated issues associated with the development of requirements, with the practice of concurrent engineering and with rapid prototyping, in the development of a next-generation Reaction Jet Drive Controller. This report details lessons learned, the current status of the prototype, and suggestions for future work. The report concludes with a discussion of the vision of future avionics architectures based on the principles associated with open architectures and integrated vehicle health management.

Aibel, David W.↗
NASA NTRS2007

Learning from Past Experiences

Space flight is a risky business. This truism has been bandied about since the earliest days of the space program. When asked by the young daughter of a coworker, one of the Mercury astronauts likened launching into space to "riding a Roman candle" -- it was both exciting and dangerous. Even in these more technologically advanced days, the solid rocket boosters and external tanks of the space shuttle provide a no less exciting, or dangerous, ride into space. However much the phrase "risk mitigation" is bandied about within the U.S. space program, there is still the history of the Apollo 1 fire during a ground test at Cape Canaveral, Fla., the loss of the shuttle Challenger during liftoff, and the loss of the shuttle Columbia when returning to Earth to remind us that while we give lip-service to risk management, we have not learned to manage risk as well as we ought. Moreover, there are many more less dramatic, but equally critical, incidents that have occurred in association with the space program that also highlight our inability to accurately gauge and manage risk. Why do we seem caught in a senseless spiral in which we focus most on risk only after a tragedy? Why do we repeat serious mishaps and not learn from our mistakes? This paper reviews some possible explanations for our risk-taking behavior and provides examples of interest to the NASA centers, while also discussing inter center and intra-center opportunities for sharing information to mitigate risk.

Hulet, Michael W.↗
NASA NTRS2007

Passive Endwall Treatments for Enhancing Stability

These lecture notes were presented at the von Karman Institutes lecture series on Advances in Axial Compressor Aerodynamics, May 2006. They provide a fairly extensive overview of what's been learned from numerous investigations of various passive casing endwall technologies that have been proposed for alleviating the stall limiting physics associated with the compressor endwall flow field. The lecture notes are organized to give an appreciation for the inventiveness and understanding of the earliest compressor technologists and to provide a coherent thread of understanding that has arisen out of the early investigations. As such the lecture notes begin with a historical overview of casing treatments from their infancy through the earliest proposed concepts involving blowing, suction and flow recirculation. A summary of lessons learned from these early investigations is provided at the end of this section. The lecture notes then provide a somewhat more in-depth overview of recent advancements in the development of passive casing treatments from the late 1990's through 2006, including advancements in understanding the flow mechanism of circumferential groove casing treatments, and the development of discrete tip injection and self-recirculating casing treatments. At the conclusion of the lecture notes a final summary of lessons learned throughout the history of the development of passive casing treatments is provided. Finally, a list of future needs is given. It is hoped that these lecture notes will be a useful reference for future research endeavors to improve our understanding of the fluid physics of passive casing treatments and how they act to enhance compressor stability, and that they will perhaps provide a springboard for future research activities in this area of interest

Hathaway, Michael D.↗
NASA NTRS1994

Recursive heuristic classification

The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.

Wilkins, David C.↗
NASA NTRS2003

NASA's Bioreactor: Growing Cells in a Simulated Microgravity Environment

National Science Education Standards (NSES), Science for All Americans, the Secretary's Commission on Achieving Necessary Skills (SCANS) as well as the National Aeronautics and Space Administration (NASA) are all making an effort to promote scientific literacy in America. Unfortunately, major evaluation programs such as the National Assessment of Educational Progress (NAEP) and the Third International Mathematics and Science Study (TIMSS) have provided information that suggested our students are not able to compete with peers from comparable countries. Although results indicated that American students are recalling memorized, factual knowledge well enough, the real problem is the ability to apply what they know. Concerned with these reports, the National Science Teacher's Association (NSTA) has developed a mission to support innovation and high quality in science teaching and learning for every student. NSTA recommends less emphasis on factual knowledge (memorization) and information and more understanding of the concepts. Science process skills are considered imperative to prepare America's students for the 21st century. The National Aeronautics and Space Administration (NASA) supports this mission and adds that NASA strives to help prepare and encourage the next generation of researchers and explorers. One method that NASA supports educators and its mission is to publish educational briefs. NASA describes a brief as a publication that ranges from one-to-thirty pages. The focus is on mission discoveries and results. The brief provides curriculum to educators that supports their objectives and NASA's interest. Educational Briefs are specific to the grade level and course so that educators may have choices that fit their methods and students level. Sometimes, the brief includes lessons and activities teachers may use. For example, NASA's Microgravity Division has designed a student bioreactor. Consequently, an Educational Brief is being written that focuses on how to build a student bioreactor and experiments that can be conducted in it. These experiments mimic the experiments done by NASA and other researchers in the real world of work.

Richardson, Denise↗
NASA NTRSDate not supplied

Green Propulsion : A NASA GSFC Assessment

In the ever-changing paradigm of efficient and capable spacecraft design, scientific missions continue pushing spacecraft subsystems to deliver effective solutions to meet challenging new mission/spacecraft applications. From an in-space storable liquid chemical propulsion perspective, monopropellant hydrazine is a dependable propellant. Bi-propellant architectures offer even superior performance, but add the complexity of a hypergolic fuel (hydrazine/ mono-methyl hydrazine) and oxidizer (Nitrogen Tetroxide/ mixed oxides of nitrogen) dual tank combination. These propulsion system designs (mono-propellant and bi-propellant) have high heritage, high propellant throughput qualified engines, widely tested material compatibility, qualified fluid delivery commercial-off-the-shelf components, known handling practices, and repeatable performance in successfully delivering on mission requirements. NASA and the broader propulsion community have historically selected hypergolic propellants for most mission applications. The space propulsion community has learned to successfully handle these highly toxic and hazardous materials, navigate the regulated use and the associated safety protocols, personnel protective equipment, and unique training standards – all requisite for loading spacecraft propulsion systems with hypergolic propellants. The question now arises as to what is next for in-space chemical propulsion? Is there an alternative, or even replacement, to the reliable hypergolic fluids, or propellant alternatives that promise increased mission benefits? With the evolution and proven advancements in innovative in-space green propellant technologies capable of delivering benefits to scientific missions, concern over the reliability and infusibility of this higher performing and safer to handle class of propellants is waning. As NASA science missions move forward with the potential flight infusion of green propulsion, NASA and the broader propulsion community are working to address remaining gaps in hardware development, reliability, performance, unique operational considerations, and risk mitigations for high value scientific assets.

Henry W. Mulkey↗
NASA NTRSDate not supplied

High School Citizen Scientists Use AI/ML to Predict Intra-Ocular Pressure From Gene Expression Data for Spaceflown Mice

Artificial Intelligence (AI) and Machine Learning (ML) have increasingly become pivotal in biological and biomedical research, largely due to the culture of open data sharing and its associated benefits. The methodologies inherent in AI/ML are particularly adept at identifying and forecasting biological phenotypes from the vast amounts of data generated by next-generation sequencing technologies. These techniques offer substantial promise for advancing research in space biosciences and for the development of automated systems for monitoring space health. Nevertheless, there are crucial aspects to consider when training, validating, and testing machine learning models in both biological research and clinical contexts. It is essential that Open Science principles, including data sharing and the availability of open-source code, are complemented by high-quality, publicly accessible training resources. These resources should focus on best practices and include modules based on real-world scientific cases and data to ensure that future AI/ML practitioners gain practical experience with genuine problems. Addressing this knowledge gap, we have designed, developed, and delivered both interactive and self-paced training programs for citizen scientists worldwide, enabling them to utilize AI/ML for space biology research. This initiative was made possible through generous funding from a Transformation to Open Science Training grant. The interactive training sessions, conducted this summer, utilized AI/ML techniques to analyze data from the Open Science Data Repository, specifically targeting the effects of spaceflight on ocular structure and function. The dataset OSD-583, from the Rodent Research 9 mission, provides experimental data detailing the ocular responses of mice subjected to a 35-day spaceflight, compared with ground control counterparts. Using OSD-583 as observational data, our summer training participants applied AI/ML methods to predict intraocular pressure from RNA-seq data and identify the genes most predictive of the observed responses. Further analysis through pathway enrichment and gene set enrichment revealed that these genes are involved in molecular and cellular processes contributing to retinal degeneration.

James Casaletto↗
NASA NTRSDate not supplied

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

machine learning↗