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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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At least 451 records · Page 25
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NASA NTRSDate not supplied

TBIRD, a rapid prototyping approach for design, assembly, and test of a LEO-to-ground lasercom CubeSat

The TeraByte InfraRed Delivery (TBIRD) system is a 3U payload on a 6U CubeSat launched in May 2022 which has now demonstrated space to ground links of >1 Terabyte (TB) per pass at a max data rate of 200Gbps. As a CubeSat mission, the development of the TBIRD payload was focused on low SWaP and a “rapid prototyping” approach which accepted higher risks to accelerate the schedule and reduce costs. The optomechanical design process followed standard in-house processes to develop a system that would be robust to LEO environmental loads, with a focus on the stability of the transmit (Tx) and receive (Rx) channel performance metrics. The driving requirement of maintaining 20μrad pointing error between the TX and Rx channels forced specific attention to thermal and mechanical load changes over operational conditions, which drove major design decisions. This paper describes some of engineering challenges overcome and approaches used to make TBIRD a successful program, as well as some of the tradeoffs of rapid prototyping precision optical payloads. TBIRD successfully met and exceeded the total downlink requirements listed above, with a bandwidth of 200Gbps and a total downlink of 4.8TB of information in a single pass.

TBIRD↗
NASA NTRS2014

Application of Sequential Quadratic Programming to Minimize Smart Active Flap Rotor Hub Loads

In an analytical study, SMART active flap rotor hub loads have been minimized using nonlinear programming constrained optimization methodology. The recently developed NLPQLP system (Schittkowski, 2010) that employs Sequential Quadratic Programming (SQP) as its core algorithm was embedded into a driver code (NLP10x10) specifically designed to minimize active flap rotor hub loads (Leyland, 2014). Three types of practical constraints on the flap deflections have been considered. To validate the current application, two other optimization methods have been used: i) the standard, linear unconstrained method, and ii) the nonlinear Generalized Reduced Gradient (GRG) method with constraints. The new software code NLP10x10 has been systematically checked out. It has been verified that NLP10x10 is functioning as desired. The following are briefly covered in this paper: relevant optimization theory; implementation of the capability of minimizing a metric of all, or a subset, of the hub loads as well as the capability of using all, or a subset, of the flap harmonics; and finally, solutions for the SMART rotor. The eventual goal is to implement NLP10x10 in a real-time wind tunnel environment.

HUB LOADS↗
NASA NTRS1991

A rule-based software test data generator

Rule-based software test data generation is proposed as an alternative to either path/predicate analysis or random data generation. A prototype rule-based test data generator for Ada programs is constructed and compared to a random test data generator. Four Ada procedures are used in the comparison. Approximately 2000 rule-based test cases and 100,000 randomly generated test cases are automatically generated and executed. The success of the two methods is compared using standard coverage metrics. Simple statistical tests showing that even the primitive rule-based test data generation prototype is significantly better than random data generation are performed. This result demonstrates that rule-based test data generation is feasible and shows great promise in assisting test engineers, especially when the rule base is developed further.

Deason, William H.↗
NASA NTRS1995

Defining a Mechanism of Educational Interface Between NASA Life Sciences the Nation's Students

Harnessing our greatest national resource, as represented by the nation's students, will require a thoughtful, well developed and administered program that includes precise, executable strategies and valid evaluation tools. Responding to a national education outreach priority, the National Aeronautics and Space Administration's Life and Biomedical Sciences and Applications Division has initiated a process or organizing and implementing various strategies through a steering committee that includes representatives from Headquarters and three field centers with major Life Sciences programs. The mandate of the Life Sciences Education Outreach Steering Committee is to develop ways of communicating space life science issues to America's students through the nation's teachers by curriculum enhancement and direct participation in the education process with an emphasis in the primary and secondary schools. Metrics are also developed for each individually defined process so that the mechanis can be continuously refined and improved.

Chamberland, D.↗
NASA NTRS2016

Design and Stability of an On-Orbit Attitude Control System Using Reaction Control Thrusters

Basic principles for the design and stability of a spacecraft on-orbit attitude control system employing on-off Reaction Control System (RCS) thrusters are presented. Both vehicle dynamics and the control system actuators are inherently nonlinear, hence traditional linear control system design approaches are not directly applicable. This paper has two main aspects: It summarizes key RCS design principles from earlier NASA vehicles, notably the Space Shuttle and Space Station programs, and introduces advances in the linear modelling and analyses of a phase plane control system derived in the initial development of the NASA's next upper stage vehicle, the Exploration Upper Stage (EUS). Topics include thruster hardware specifications, phase plane design and stability, jet selection approaches, filter design metrics, and RCS rotational maneuver logic.

Hall, Robert A.↗
NASA NTRS2017

The Relationships Between the Trends of Mean and Extreme Precipitation

This study provides a better understanding of the relationships between the trends of mean and extreme precipitation in two observed precipitation data sets: the Climate Prediction Center Unified daily precipitation data set and the Global Precipitation Climatology Program (GPCP) pentad data set. The study employs three kinds of definitions of extreme precipitation: (1) percentile, (2) standard deviation and (3) generalize extreme value (GEV) distribution analysis for extreme events based on local statistics. Relationship between trends in the mean and extreme precipitation is identified with a novel metric, i.e. area aggregated matching ratio (AAMR) computed on regional and global scales. Generally, more (less) extreme events are likely to occur in regions with a positive (negative) mean trend. The match between the mean and extreme trends deteriorates for increasingly heavy precipitation events. The AAMR is higher in regions with negative mean trends than in regions with positive mean trends, suggesting a higher likelihood of severe dry events, compared with heavy rain events in a warming climate. AAMR is found to be higher in tropics and oceans than in the extratropics and land regions, reflecting a higher degree of randomness and more important dynamical rather than thermodynamical contributions of extreme events in the latter regions.

global warming↗
NASA NTRS2008

Strategic Analysis Overview

NASA s Constellation Program employs a strategic analysis methodology in providing an integrated analysis capability of Lunar exploration scenarios and to support strategic decision-making regarding those scenarios. The strategic analysis methodology integrates the assessment of the major contributors to strategic objective satisfaction performance, affordability, and risk and captures the linkages and feedbacks between all three components. Strategic analysis supports strategic decision making by senior management through comparable analysis of alternative strategies, provision of a consistent set of high level value metrics, and the enabling of cost-benefit analysis. The tools developed to implement the strategic analysis methodology are not element design and sizing tools. Rather, these models evaluate strategic performance using predefined elements, imported into a library from expert-driven design/sizing tools or expert analysis. Specific components of the strategic analysis tool set include scenario definition, requirements generation, mission manifesting, scenario lifecycle costing, crew time analysis, objective satisfaction benefit, risk analysis, and probabilistic evaluation. Results from all components of strategic analysis are evaluated a set of pre-defined figures of merit (FOMs). These FOMs capture the high-level strategic characteristics of all scenarios and facilitate direct comparison of options. The strategic analysis methodology that is described in this paper has previously been applied to the Space Shuttle and International Space Station Programs and is now being used to support the development of the baseline Constellation Program lunar architecture. This paper will present an overview of the strategic analysis methodology and will present sample results from the application of the strategic analysis methodology to the Constellation Program lunar architecture.

Cirillo, William M.↗
NASA NTRSDate not supplied

Uneven Inflation Load Share Trends in Clusters

The use of parachute clusters for payload recovery is still seeing widespread use ever since the early days of WWII. By involving the (near) simultaneous deployment of several smaller and identical canopies connected to the payload, cluster systems offer flexibility in tailoring to needed descent rates and load management, as well as providing robustness against individual canopy deployment or opening failure. Their downside, of course, resides in the possibility of differing inflation rates by each cluster member as caused by deployment variability, canopy-to-canopy interference, etc. Such variability leads to the lead-lag phenomenon, which causes uneven loading among the parachutes, often times leaving a single canopy to take up a significant portion of the system’s inflation loads. Herein we investigate how serious such an effect can be in terms of the number N of cluster members, underinflation drag of the lagging canopies, inflation swiftness of the leader in comparison to the laggards’, disreefing cutter activation staggering and pre-disreefing drag area. Two new metrics are used to highlight load share unevenness, namely, the peak and average leader canopy riser load in comparison to the leader’s drag during no-lead-lag; and leader peak load, as compared to total peak load. Results are calculated from data collected in NASA’s Orion/CPAS test program, as well as from simple algebraic expressions informing leader drag as sustained in different cluster systems (i.e., of different N) and varying leader inflation time relative to the laggards. Generally, using large-N cluster systems confers better load sharing among canopies. However, and in deployments where significant lead-lag occur, large-N systems may feature greater leader overload excursions, oftentimes in excess of 50% the no-lead-lag levels. These excursions are particularly made worse when cutter activation among the members are far from simultaneous and the laggards’ pre-disreefing drag area is small in comparison to the leader’s.

parachutes↗
NASA NTRS2017

NASA's Space Launch System: SmallSat Deployment to Deep Space

Leveraging the significant capability it offers for human exploration and flagship science missions, NASA's Space Launch System (SLS) also provides a unique opportunity for lower-cost deep-space science in the form of small-satellite secondary payloads. Current plans call for such opportunities to begin with the rocket's first flight; a launch of the vehicle's Block 1 configuration, capable of delivering 70 metric tons (t) to Low Earth Orbit (LEO), which will send the Orion crew vehicle around the moon and return it to Earth. On that flight, SLS will also deploy 13 CubeSat-class payloads to deep-space destinations. These secondary payloads will include not only NASA research, but also spacecraft from industry and international partners and academia. The payloads also represent a variety of disciplines including, but not limited to, studies of the moon, Earth, sun, and asteroids. While the SLS Program is making significant progress toward that first launch, preparations are already under way for the second, which will see the booster evolve to its more-capable Block 1B configuration, able to deliver 105t to LEO. That configuration will have the capability to carry large payloads co-manifested with the Orion spacecraft, or to utilize an 8.4-meter (m) fairing to carry payloads several times larger than are currently possible. The Block 1B vehicle will be the workhorse of the Proving Ground phase of NASA's deep-space exploration plans, developing and testing the systems and capabilities necessary for human missions into deep space and ultimately to Mars. Ultimately, the vehicle will evolve to its full Block 2 configuration, with a LEO capability of 130 metric tons. Both the Block 1B and Block 2 versions of the vehicle will be able to carry larger secondary payloads than the Block 1 configuration, creating even more opportunities for affordable scientific exploration of deep space. This paper will outline the progress being made toward flying smallsats on the first flight of SLS, and discuss future opportunities for smallsats on subsequent flights.

Robinson, Kimberly F.↗
NASA NTRS2017

NASA's Space Launch System: SmallSat Deployment to Deep Space

Leveraging the significant capability it offers for human exploration and flagship science missions, NASA's Space Launch System (SLS) also provides a unique opportunity for lower-cost deep-space science in the form of small-satellite secondary payloads. Current plans call for such opportunities to begin with the rocket's first flight; a launch of the vehicle's Block 1 configuration, capable of delivering 70 metric tons (t) to Low Earth Orbit (LEO), which will send the Orion crew vehicle around the moon and return it to Earth. On that flight, SLS will also deploy 13 CubeSat-class payloads to deep-space destinations. These secondary payloads will include not only NASA research, but also spacecraft from industry and international partners and academia. The payloads also represent a variety of disciplines including, but not limited to, studies of the moon, Earth, sun, and asteroids. While the SLS Program is making significant progress toward that first launch, preparations are already under way for the second, which will see the booster evolve to its more-capable Block 1B configuration, able to deliver 105t to LEO. That configuration will have the capability to carry large payloads co-manifested with the Orion spacecraft, or to utilize an 8.4-meter (m) fairing to carry payloads several times larger than are currently possible. The Block 1B vehicle will be the workhorse of the Proving Ground phase of NASA's deep-space exploration plans, developing and testing the systems and capabilities necessary for human missions into deep space and ultimately to Mars. Ultimately, the vehicle will evolve to its full Block 2 configuration, with a LEO capability of 130 metric tons. Both the Block 1B and Block 2 versions of the vehicle will be able to carry larger secondary payloads than the Block 1 configuration, creating even more opportunities for affordable scientific exploration of deep space. This paper will outline the progress being made toward flying smallsats on the first flight of SLS, and discuss future opportunities for smallsats on subsequent flights.

Robinson, Kimberly F.↗
NASA NTRS1993

Control system design for flexible structures using data models

The dynamics and control of flexible aerospace structures exercises many of the engineering disciplines. In recent years there has been considerable research in the developing and tailoring of control system design techniques for these structures. This problem involves designing a control system for a multi-input, multi-output (MIMO) system that satisfies various performance criteria, such as vibration suppression, disturbance and noise rejection, attitude control and slewing control. Considerable progress has been made and demonstrated in control system design techniques for these structures. The key to designing control systems for these structures that meet stringent performance requirements is an accurate model. It has become apparent that theoretically and finite-element generated models do not provide the needed accuracy; almost all successful demonstrations of control system design techniques have involved using test results for fine-tuning a model or for extracting a model using system ID techniques. This paper describes past and ongoing efforts at Ohio University and NASA MSFC to design controllers using 'data models.' The basic philosophy of this approach is to start with a stabilizing controller and frequency response data that describes the plant; then, iteratively vary the free parameters of the controller so that performance measures become closer to satisfying design specifications. The frequency response data can be either experimentally derived or analytically derived. One 'design-with-data' algorithm presented in this paper is called the Compensator Improvement Program (CIP). The current CIP designs controllers for MIMO systems so that classical gain, phase, and attenuation margins are achieved. The center-piece of the CIP algorithm is the constraint improvement technique which is used to calculate a parameter change vector that guarantees an improvement in all unsatisfied, feasible performance metrics from iteration to iteration. The paper also presents a recently demonstrated CIP-type algorithm, called the Model and Data Oriented Computer-Aided Design System (MADCADS), developed for achieving H(sub infinity) type design specifications using data models. Control system design for the NASA/MSFC Single Structure Control Facility are demonstrated for both CIP and MADCADS. Advantages of design-with-data algorithms over techniques that require analytical plant models are also presented.

Irwin, R. Dennis↗
NASA NTRS2000

Low-Cost Approaches to Deep Space Missions

The past decade has brought about a radical transformation in NASA's planetary exploration program. At the beginning of this decade, NASA was focused on the Cassini mission to Saturn. Following on the heels of the successful Voyager and Galileo missions, Cassini represents the culmination of an evolution towards successively larger, more complex, and more expensive spacecraft. The Cassini spacecraft weighs in at over 5 metric tons, and carries an entry probe and a sophisticated suite of sensors supporting 27 different science investigations enabling a comprehensive scientific investigation of Saturn with a single spacecraft. The cost of this spacecraft exceeded $2B, including the cost of the large Titan IV launch vehicle. During Cassini development, NASA realized that it could no longer afford these "flagship" missions, and the agency moved aggressively towards a "faster, better, cheaper" design philosophy of focused science goals and simpler, rapidly-developed spacecraft, allowing much more frequent launches of smaller, lower-cost missions. The Mars Global Surveyor, launched in November 1996, is an example of this new paradigm. Developed in less than 3-years, MGS is only one-fifth the mass of Cassini, and only cost on the order of $220M. The reduced spacecraft mass allows use of the smaller, lower cost Delta launch vehicle. Currently in orbit about Mars, MGS carries a focused suite of six science instruments that are currently returning high-resolution remote sensing of the Martian surface. The future calls for continued even more aggressive mass and cost targets. Examples of these next-generation goals are embodied in the Mars Micromission spacecraft concept, targeted for launch in 2003. With a mass of only 200kg, this lightweight bus can be tailored to carry a variety of payloads to Mars or other inner-planet destinations. The design of the Micromission spacecraft enable them to be launched at extremely low cost as a secondary "piggyback" payload.

Squibb, G. F.↗
DOE OSTI2024

Challenges in Tracking Waste Reduction Performance Improvement in Manufacturing Plants

The recently released Circularity Gap Report 2023 by Circle Economy Foundation found that the circularity score for the global economy is declining. This indicates that material extraction from virgin sources is climbing over earlier years. As per data released by US Geological Survey, material use in the US economy has increased exponentially with the expanding US economy over last century. EPA tracked municipal solid waste from 1960 to 2018 and found that 50% of the waste is destined for landfills. EPA estimates that US industry is responsible for 2.7 billion ton of solid non-hazardous waste annually in our mostly linear economy model. The circular economy framework aims at decoupling economic value generation from virgin materials extraction from nature. The linear model of material extraction and disposal at end of life is highly unsustainable. Manufacturing companies have realized this and in their commitments to sustainability are adopting ambitious waste reduction targets. Through Better Plants program US Department of Energy has established Waste Reduction Network where it is offering technical assistance to partners to achieve these ambitious waste reduction goals. Basic requirements of establishing a target include identifying a baseline, quantifying waste performance, and measuring progress over time. One problem faced by industry is the unstandardized metrics to quantify waste performance that may not be well suited to demonstrate progress. In this paper, we research methods traditionally used to measure waste performance and highlight advantages, gaps and limitations of each method. Suitability of the methods applicable to different manufacturing circumstances are also examined. Finally, we present a case study of a large manufacturer that faced inconsistencies in their tracked measurement metric. A solution was proposed to alter the methodology to enable more accurate waste performance tracking against a baseline.

Chaudhari, Subodh↗
NASA NTRS1990

Dynamics and control of multipayload platforms - The Middeck Active Control Experiment (MACE)

A flight experiment entitled the Middeck Active Control Experiment (MACE) proposed by the Space Engineering Research Center (SERC) at the Massachusetts Institute of Technology is described. The objective of this program is to investigate and validate the modeling of the dynamics of an actively controlled flexible, articulating, multibody platform free floating in zero gravity. A rationale and experimental approach for the program are presented. The rationale shows that on-orbit testing, coupled with ground testing and a strong analytical program, is necessary in order to fully understand both how flexibility of the platform affects the pointing problem, as well as how gravity perturbs this structural flexibility causing deviations between 1-and 0-gravity behavior. The experimental approach captures the essential physics of multibody platforms, by identifying the appropriate attributes, tests, and performance metrics of the test article, and defines the tests required to successfully validate the analytical framework.

Miller, David W.↗
NASA NTRS1990

The MODE family of on-orbit experiments: The Middeck Active Control Experiment (MACE)

A flight experiment entitled the Middeck Active Control Experiment (MACE), proposed by the Space Engineering Research Center (SERC) at the Massachusetts Institute of Technology, is described. This is the second in a family of flight experiments being developed at MIT. The first is the Middeck 0-Gravity Dynamics Experiment (MODE) which investigates the nonlinear behavior of contained fluids and truss structures in zero gravity. The objective of the MACE program is to investigate and validate the modeling of the dynamics of an actively controlled flexible, articulating, multibody platform free floating in zero gravity. A rationale and experimental approach for the program are presented. The rationale shows that on-orbit testing, coupled with ground testing and a strong analytical program, is necessary in order to fully understand both how flexibility of the platform affects the pointing problem, as well as how gravity perturbs this structural flexibility causing deviations between 1- and 0-gravity behavior. The experimental approach captures the essential physics of multibody platforms, by identifying the appropriate attributes, tests, and performance metrics of the test article and defines the tests required to successfully validate the analytical framework.

Crawley, Edward F.↗
NASA NTRS1992

Object-oriented productivity metrics

Software productivity metrics are useful for sizing and costing proposed software and for measuring development productivity. Estimating and measuring source lines of code (SLOC) has proven to be a bad idea because it encourages writing more lines of code and using lower level languages. Function Point Analysis is an improved software metric system, but it is not compatible with newer rapid prototyping and object-oriented approaches to software development. A process is presented here for counting object-oriented effort points, based on a preliminary object-oriented analysis. It is proposed that this approach is compatible with object-oriented analysis, design, programming, and rapid prototyping. Statistics gathered on actual projects are presented to validate the approach.

Connell, John L.↗
NASA NTRS1994

The Evolution of Technology in the Deep Space Network: A History of the Advanced Systems Program

The Deep Space Network (DSN) of 1995 might be described as the evolutionary result of 45 years of deep space communication and navigation, together with the synergistic activities of radio science and radar and radio astronomy. But the evolution of the DSN did not just happen - it was carefully planned and created. The evolution of the DSN has been an ongoing engineering activity, and engineering is a process of problem solving under constraints, one of which is technology. In turn, technology is the knowledge base providing the capability and experience for practical application of various areas of science, when needed. The best engineering solutions result from optimization under the fewest constraints, and if technology needs are well anticipated (ready when needed), then the most effective engineering solution is possible. Throughout the history of the DSN it has been the goal and function of DSN advanced technology development (designated the DSN Advanced Systems Program from 1963 through 1994) to supply the technology needs of the DSN when needed, and thus to minimize this constraint on DSN engineering. Technology often takes considerable time to develop, and when that happens, it is important to have anticipated engineering needs; at times, this anticipation has been by as much as 15 years. Also, on a number of occasions, mission malfunctions or emergencies have resulted in unplanned needs for technology that has, in fact, been available from the reservoir of advanced technology provided by the DSN Advanced Systems Program. Sometimes, even DSN engineering personnel fail to realize that the organization of JPL permits an overlap of DSN advanced technology activities with subsequent engineering activities. This can result in the flow of advanced technology into DSN engineering in a natural and sometimes almost unnoticed way. In the following pages, we will explore some of the many contributions of the DSN Advanced Systems Program that were provided to DSN Engineering and Implementation. These contributions are, for the most part, unique capabilities that have met the requirements of flight projects for 45 years. These unique capabilities include not only the world's best deep-space communications system, but also outstanding competency in the fields of radio metric measurement, radar and radio astronomy, and radio science.

Layland, J. W.↗
NASA NTRS2002

System Level Uncertainty Assessment for Collaborative RLV Design

A collaborative design process utilizing Probabilistic Data Assessment (PDA) is showcased. Given the limitation of financial resources by both the government and industry, strategic decision makers need more than just traditional point designs, they need to be aware of the likelihood of these future designs to meet their objectives. This uncertainty, an ever-present character in the design process, can be embraced through a probabilistic design environment. A conceptual design process is presented that encapsulates the major engineering disciplines for a Third Generation Reusable Launch Vehicle (RLV). Toolsets consist of aerospace industry standard tools in disciplines such as trajectory, propulsion, mass properties, cost, operations, safety, and economics. Variations of the design process are presented that use different fidelities of tools. The disciplinary engineering models are used in a collaborative engineering framework utilizing Phoenix Integration's ModelCenter and AnalysisServer environment. These tools allow the designer to join disparate models and simulations together in a unified environment wherein each discipline can interact with any other discipline. The design process also uses probabilistic methods to generate the system level output metrics of interest for a RLV conceptual design. The specific system being examined is the Advanced Concept Rocket Engine 92 (ACRE-92) RLV. Previous experience and knowledge (in terms of input uncertainty distributions from experts and modeling and simulation codes) can be coupled with Monte Carlo processes to best predict the chances of program success.

Charania, A. C.↗