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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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The implementation of direct access storage devices for LACIE is discussed with emphasis on the storage and retrieval of image data. Topics covered include the definition of the problem, the solution methodology (design decisions), the initial operational structure, and the modifications which were incorporated. Some conclusions and projections of future problems to be solved are also presented.
An experiment on melting and directional crystallization of an antimony (Sb) doped germanium silicon (GeSi) solid solution was designed for the Apollo-Soyuz Test Project (ASTP) to study the possibility of using zero-g conditions for obtaining solid-solution monocrystals with uniformly distributed components. Crystallization in the zero-g environment did not occur under ideal stationary growth and segregation conditions. Crystallization under zero-g conditions revealed the heterogeneous nature of Si and Sb distribution in the cross sections of crystals. The presence of the radial thermal gradient in the multipurpose furnace could be one of the reasons for such Si and Sb distribution. The structure of space-grown crystals correlates with the nature of heterogeneities of Si and Sb distribution in crystals. The type of surface morphology and the contour observed in space-grown crystals were never observed in ground-based crystals and indicate the absence of wetting of the graphitized walls of the ampoule by the melt during melting and crystallization.
This report describes the preliminary results of an investigation on component reliability analysis and reliability-based design optimization of thin-walled circular composite cylinders with average diameter and average length of 15 inches. Structural reliability is based on axial buckling strength of the cylinder. Both Monte Carlo simulation and First Order Reliability Method are considered for reliability analysis with the latter incorporated into the reliability-based structural optimization problem. To improve the efficiency of reliability sensitivity analysis and design optimization solution, the buckling strength of the cylinder is estimated using a second-order response surface model. The sensitivity of the reliability index with respect to the mean and standard deviation of each random variable is calculated and compared. The reliability index is found to be extremely sensitive to the applied load and elastic modulus of the material in the fiber direction. The cylinder diameter was found to have the third highest impact on the reliability index. Also the uncertainty in the applied load, captured by examining different values for its coefficient of variation, is found to have a large influence on cylinder reliability. The optimization problem for minimum weight is solved subject to a design constraint on element reliability index. The methodology, solution procedure and optimization results are included in this report.
The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) has proposed a set of spacecraft flying in close formation around the Earth in order to measure the behavior of the auroras. The mission, named Auroral Lites, consists of four spacecraft configured to start at the vertices of a tetrahedron, flying over three mission phases. During the first phase, the distance between any two spacecraft in the formation is targeted at 10 kilometers (km). The second mission phase is much tighter, requiring satellite interrange spacing targeted at 500 meters. During the final phase of the mission, the formation opens to a nominal 100-km interrange spacing. In this paper, we present the strategy employed to initialize and model such a close formation during each of these phases. The analysis performed to date provides the design and characteristics of the reference orbit, the evolution of the formation during Phases I and II, and an estimate of the total mission delta-V budget. AI Solutions' mission design tool, FreeFlyer, was used to generate each of these analysis elements. The tool contains full force models, including both impulsive and finite duration maneuvers. Orbital maintenance can be fully modeled in the system using a flexible, natural scripting language built into the system. In addition, AI Solutions is in the process of adding formation extensions to the system facilitating mission analysis for formations like Auroral Lites. We will discuss how FreeFlyer is used for these analyses.
The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) has proposed a set of spacecraft flying in close formation around the Earth in order to measure the behavior of the auroras. The mission, named Auroral Lites, consists of four spacecraft configured to start at the vertices of a tetrahedron, flying over three mission phases. During the first phase, the distance between any two spacecraft in the formation is targeted at 10 kilometers (km). The second mission phase is much tighter, requiring satellite interrange spacing targeted at 500 meters. During the final phase of the mission, the formation opens to a nominal 100-km interrange spacing. In this paper, we present the strategy employed to initialize and model such a close formation during each of these phases. The analysis performed to date provides the design and characteristics of the reference orbit, the evolution of the formation during Phases I and II, and an estimate of the total mission delta-V budget. AI Solutions' mission design tool, FreeFlyer(R), was used to generate each of these analysis elements. The tool contains full force models, including both impulsive and finite duration maneuvers. Orbital maintenance can be fully modeled in the system using a flexible, natural scripting language built into the system. In addition, AI Solutions is in the process of adding formation extensions to the system facilitating mission analysis for formations like Auroral Lites. We will discuss how FreeFlyer(R) is used for these analyses.
An approximate axisymmetric method has been developed which can reliably calculate nonequilibrium fully viscous hypersonic flows over blunt-nosed bodies. By substituting Maslen's second-order pressure expression for the normal momentum equation, a simplified form of the viscous shock layer (VSL) equations is obtained. This approach can solve both the subsonic and supersonic regions of the shock layer without a starting solution for the shock shape. This procedure is significantly faster than the parabolized Navier-Stokes and VSL solvers and would be useful in a preliminary design environment. Solutions have been generated for air flows over several analytic body shapes. Surface heat transfer and pressure predictions are comparable to VSL results. Computed heating rates are in good agreement with experimental data. The present technique generates its own shock shape as part of its solution, and therefore could be used to provide more accurate initial shock shapes for higher-order procedures which require starting solutions.
TAWFIVE computer program calculates transonic flow over transport-type wing and fuselage. Combines multigrid acceleration technique in iterative solution of potential equation with use of integral-form boundary-layer equations to provide software tool computationally efficient, yet accurate enough for use in design. Simplifies solution process by breaking problem into loosely coupled set of modified equations. Inviscid-flow method, using standard inviscid-flow equations, valid in "outer" region away from wing, whereas boundary-layer equations valid in thin region near solid surface of wing. Written in FORTRAN 77.
A report presents background and historical information, as of August 1998, on the Advanced Design Technologies Testbed (ADTT) at Ames Research Center. The ADTT is characterized as an activity initiated to facilitate improvements in aerospace design processes; provide a proving ground for product-development methods and computational software and hardware; develop bridging methods, software, and hardware that can facilitate integrated solutions to design problems; and disseminate lessons learned to the aerospace and information technology communities.
Design and development of Shape Memory Alloy (SMA) Tires is a difficult and challenging problem. A “build and test” approach isn’t practical due to both the expense and time associated with taking such an approach. The multiple iterations that would be required to close requirements space for a space flight hardware program makes this approach infeasible. Hence, details regarding GRC’s SMA modeling approach to solving this challenging problem will be highlighted and used to showcase the power associated with leveraging an SMA modeling framework during design.
Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.
Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.
Electric Sails (E-Sails) are a promising propulsion technology that seek to enable high characteristic propellentless acceleration for spacecraft to reach distant and/or difficult to reach orbits such as rapid transit to heliopause. The E-Sail system exchanges momentum by using positively charged electrostatic tethers to repel solar wind photons to push it through space. This concept was first theorized by Pekka Janhunen in 2004 with further developments occurring including a NASA Innovative Advanced Concepts Phase 1 and Phase 2 hosted out of NASA’s Marshall Space Flight Center (MSFC). These developments led to further maturation of the overall system, and this paper is designed to help identify different design sensitivities of an integrated Electric Sail system. To approach this, a small team at MSFC took an in-house developed three degrees of freedom (3DoF) simulation tool and a trajectory modelling tool to look at different design parameters and to determine a potential ideal E-Sail configuration. An E-Sail system has different design architectures including a barbell design, hub and spoke design, and a potential hybrid solution. The barbell design features two equally massed satellites that spin around a central point in the tether system. The hub and spoke design features a large central spacecraft with small end spacecraft to aid in formation control of the overall E-Sail system. Leveraging elements from both the hub and spoke, and barbell design, a hybrid option exists where one could have a larger central mass and one or two tethers extended to a smaller end mass [2]. In summary, the hub and spoke design is the ideal configuration for E-Sail with tethers spanning kilometers to achieve the designed design characteristic acceleration of at least one mm/s2 with this architecture being the focus of this study. Different key design parameters were varied as part of this study. These parameters include the total number of tethers, the length of the tethers, spin rate, relative spacecraft mass, tether voltage, inertia per tether, and impact of slew rate changes. These results started from an internal MSFC technology demonstration mission design and then the parameters were varied with engineering judgement to ensure that the results were consistent with expected results. These were varied in the MSFC 3DoF tool and compared to baseline results to generate a candidate ideal E-Sail design system. These results were then used to help inform the mission analysis design for the system. The 3DoF trajectory optimization was performed in the Astrodynamics and Space Science Enabling Toolbox (ASSET) and utilized collocation optimization of control vector pointing with the objective function being transfer duration. A representative model of the E-Sail force was derived as a function of the Sun-pointing vector direction. This model was initialized with a zero Sun Incidence Angle (SIA) trajectory for the initial guess generation, then with a portion of the mission optimized SIA time history for fast outbound transfers. After the trajectory is hyperbolic relative to a heliocentric frame, the SIA is maintained at 0 degrees except for any needed trajectory correction maneuvers. This trajectory optimization looked at different characteristic acceleration values to analyze the impact it had on mission performance. As a result of this study, the team can best inform mission designers and technology development efforts to mature the E-Sail system. This study will allow mission designers to have defined rules-of-thumb to design an E-Sail system to meet desired mission needs as well as providing several sample mission profiles. These design drivers will inform maturation efforts on which design requirements to consider for an integrated E-Sail design.
A rapid technique for solving the blade-to-blade turbomachinery flow problem was developed. Approximate governing flow equations, which include the effects of compressibility, radius change, rotation, and variable stream sheet thickness are solved using a panel method. The development and solution of these equations are described. Sample calculations are presented to illustrate the method's capabilities and accuracy.
A rapid technique for solving the blade-to-blade turbomachinery flow problem was developed. Approximate governing flow equations, which include the effects of compressibility, radius change, rotation, and variable stream sheet thickness are solved using a panel method. The development and solution of these equations are described. Sample calculations are presented to illustrate the method's capabilities and accuracy. Previously announced in STAR as N83-13077
Described here are the results of a study to develop a conceptual design for an experimental closed loop fluid handling system capable of monitoring, controlling, and supplying nutrient solution to higher plants. The Plant Feeder Experiment (PFE) is designed to be flight tested in a microgravity environment. When flown, the PFX will provide information on both the generic problems of microgravity fluid handling and the specific problems associated with the delivery of the nutrient solution in a microgravity environment. The experimental hardware is designed to fit into two middeck lockers on the Space Shuttle, and incorporates several components that have previously been flight tested.
Using STM(Science, Technology, Engineering, Math) education, this emerging workforce will have the chance to creatively solve one of Virginia's biggest challenges: TRANSPORTATION. - Students will be asked to develop alternative transportation systems for the state. This competition will enable teams to work with business mentors to design creative solutions for regional gridlocks and develop other transportation systems to more easily and expediently reach all parts of the Commonwealth.
This paper describes the results of a study to develop a conceptual design for an experimental, closed-loop fluid handling system capable of monitoring, controlling, and supplying nutrient solution to higher plants. The Plant Feeder Experiment (PFX) is designed to be flight tested in a micro-gravity (micro-g) environment and was developed under NASA's In-Space Technology Experiments Program (INSTEP). When flown, PFX will provide information on both the generic problems of micro-g fluid handling and the specific problems associated with the delivery of nutrient solution in a micro-g environment. The experimental hardware is designed to fit into two middeck lockers on the Space Shuttle, and incorporates several components that have previously been flight tested.
Structural optimization is a field of research that has experienced noteworthy growth for many years. Researchers in this area have developed optimization tools to successfully design and model structures, typically minimizing mass while maintaining certain deflection and stress constraints. Numerous optimization studies have been performed to minimize mass, deflection, and stress on a benchmark cantilever truss problem. Predominantly traditional optimization theory is applied to this problem. The cross-sectional area of each member is optimized to minimize the aforementioned objectives. This Technical Publication (TP) presents a structural optimization technique that has been previously applied to compliant mechanism design. This technique demonstrates a method that combines topology optimization, geometric refinement, finite element analysis, and two forms of evolutionary computation: genetic algorithms and differential evolution to successfully optimize a benchmark structural optimization problem. A nontraditional solution to the benchmark problem is presented in this TP, specifically a geometrically refined topological solution. The design process begins with an alternate control mesh formulation, multilevel geometric smoothing operation, and an elastostatic structural analysis. The design process is wrapped in an evolutionary computing optimization toolset.