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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Flammability Configuration Analysis for Spacecraft Applications

Fire is one of the many potentially catastrophic hazards associated with the operation of crewed spacecraft. A major lesson learned by NASA from the Apollo 204 fire in 1966 was that ignition sources in an electrically powered vehicle should and can be minimized, but can never be eliminated completely. For this reason, spacecraft fire control is based on minimizing potential ignition sources and eliminating materials that can propagate fire. Fire extinguishers are always provided on crewed spacecraft, but are not considered as part of the fire control process. "Eliminating materials that can propagate fire" does not mean eliminating all flammable materials - the cost of designing and building spacecraft using only nonflammable materials is extraordinary and unnecessary. It means controlling the quantity and configuration of such materials to eliminate potential fire propagation paths and thus ensure that any fire would be small, localized, and isolated, and would self-extinguish without harm to the crew. Over the years, NASA has developed many solutions for controlling the configuration of flammable materials (and potentially flammable materials in commercial "off-the-shelf" hardware) so that they can be used safely in air and oxygen-enriched environments in crewed spacecraft. This document describes and explains these design solutions so payload customers and other organizations can use them in designing safe and cost-effective flight hardware. Proper application of these guidelines will produce acceptable flammability configurations for hardware located in any compartment of the International Space Station or other program crewed vehicles and habitats. However, use of these guidelines does not exempt hardware organizations of the responsibility for safety of the hardware under their control.

Pedley, Michael D.↗
NASA NTRS2016

Implementation of a Multichannel Serial Data Streaming Algorithm using the Xilinx Serial RapidIO Solution

In the current world of applications that use reconfigurable technology implemented on field programmable gate arrays (FPGAs), there is a need for flexible architectures that can grow as the systems evolve. A project has limited resources and a fixed set of requirements that development efforts are tasked to meet. Designers must develop robust solutions that practically meet the current customer demands and also have the ability to grow for future performance. This paper describes the development of a high speed serial data streaming algorithm that allows for transmission of multiple data channels over a single serial link. The technique has the ability to change to meet new applications developed for future design considerations. This approach uses the Xilinx Serial RapidIO LOGICORE Solution to implement a flexible infrastructure to meet the current project requirements with the ability to adapt future system designs.

RapidIO↗
NASA NTRS2001

Multiobjective Optimization of Rocket Engine Pumps Using Evolutionary Algorithm

A design optimization method for turbopumps of cryogenic rocket engines has been developed. Multiobjective Evolutionary Algorithm (MOEA) is used for multiobjective pump design optimizations. Performances of design candidates are evaluated by using the meanline pump flow modeling method based on the Euler turbine equation coupled with empirical correlations for rotor efficiency. To demonstrate the feasibility of the present approach, a single stage centrifugal pump design and multistage pump design optimizations are presented. In both cases, the present method obtains very reasonable Pareto-optimal solutions that include some designs outperforming the original design in total head while reducing input power by one percent. Detailed observation of the design results also reveals some important design criteria for turbopumps in cryogenic rocket engines. These results demonstrate the feasibility of the EA-based design optimization method in this field.

Oyama, Akira↗
NASA NTRS2010

On the Minimum Induced Drag of Wings

Of all the types of drag, induced drag is associated with the creation and generation of lift over wings. Induced drag is directly driven by the span load that the aircraft is flying at. The tools by which to calculate and predict induced drag we use were created by Ludwig Prandtl in 1903. Within a decade after Prandtl created a tool for calculating induced drag, Prandtl and his students had optimized the problem to solve the minimum induced drag for a wing of a given span, formalized and written about in 1920. This solution is quoted in textbooks extensively today. Prandtl did not stop with this first solution, and came to a dramatically different solution in 1932. Subsequent development of this 1932 solution solves several aeronautics design difficulties simultaneously, including maximum performance, minimum structure, minimum drag loss due to control input, and solution to adverse yaw without a vertical tail. This presentation lists that solution by Prandtl, and the refinements by Horten, Jones, Kline, Viswanathan, and Whitcomb

Bowers, Albion H.↗
NASA NTRS2011

On the Minimum Induced Drag of Wings

Of all the types of drag, induced drag is associated with the creation and generation of lift over wings. Induced drag is directly driven by the span load that the aircraft is flying at. The tools by which to calculate and predict induced drag we use were created by Ludwig Prandtl in 1903. Within a decade after Prandtl created a tool for calculating induced drag, Prandtl and his students had optimized the problem to solve the minimum induced drag for a wing of a given span, formalized and written about in 1920. This solution is quoted in textbooks extensively today. Prandtl did not stop with this first solution, and came to a dramatically different solution in 1932. Subsequent development of this 1932 solution solves several aeronautics design difficulties simultaneously, including maximum performance, minimum structure, minimum drag loss due to control input, and solution to adverse yaw without a vertical tail. This presentation lists that solution by Prandtl, and the refinements by Horten, Jones, Kline, Viswanathan, and Whitcomb.

Bowers, Albion H.↗
NASA NTRS2011

On the Minimum Induced Drag of Wings -or- Thinking Outside the Box

Of all the types of drag, induced drag is associated with the creation and generation of lift over wings. Induced drag is directly driven by the span load that the aircraft is flying at. The tools by which to calculate and predict induced drag we use were created by Ludwig Prandtl in 1903. Within a decade after Prandtl created a tool for calculating induced drag, Prandtl and his students had optimized the problem to solve the minimum induced drag for a wing of a given span, formalized and written about in 1920. This solution is quoted in textbooks extensively today. Prandtl did not stop with this first solution, and came to a dramatically different solution in 1932. Subsequent development of this 1932 solution solves several aeronautics design difficulties simultaneously, including maximum performance, minimum structure, minimum drag loss due to control input, and solution to adverse yaw without a vertical tail. This presentation lists that solution by Prandtl, and the refinements by Horten, Jones, Kline, Viswanathan, and Whitcomb.

Bowers, Albion H.↗
DOE OSTI2020

Morphological–Electrical Property Relation in Cu(In,Ga)(S,Se) 2 Solar Cells: Significance of Crystal Grain Growth and Band Grading by Potassium Treatment

Abstract Solution‐processed Cu(In,Ga)(S,Se) 2 (CIGS) has a great potential for the production of large‐area photovoltaic devices at low cost. However, CIGS solar cells processed from solution exhibit relatively lower performance compared to vacuum‐processed devices because of a lack of proper composition distribution, which is mainly instigated by the limited Se uptake during chalcogenization. In this work, a unique potassium treatment method is utilized to improve the selenium uptake judiciously, enhancing grain sizes and forming a wider bandgap minimum region. Careful engineering of the bandgap grading structure also results in an enlarged space charge region, which is favorable for electron–hole separation and efficient charge carrier collection. Besides, this device processing approach has led to a linearly increasing electron diffusion length and carrier lifetime with increasing the grain size of the CIGS film, which is a critical achievement for enhancing photocurrent yield. Overall, 15% of power conversion efficiency is achieved in solar cells processed from environmentally benign solutions. This approach offers critical insights for precise device design and processing rules for solution‐processed CIGS solar cells.

Kim, Joo‐Hyun↗
DOE OSTI2024

Continuous automatic polarization channel stabilization from heterodyne detection of coexisting dim reference signals

Quantum networking continues to encode information in polarization states due to ease and precision. The variable environmental polarization transformations induced by deployed fiber need correction for deployed quantum networking. Here, we present a method for automatic polarization compensation (APC) and demonstrate its performance on a metropolitan quantum network. Designing an APC involves many design decisions as indicated by the diversity of previous solutions in the literature. Our design leverages heterodyne detection of wavelength-multiplexed dim classical references for continuous high-bandwidth polarization measurements used by newly developed multi-axis (non-)linear control algorithm(s) for complete polarization channel stabilization with no downtime. This enables continuous relatively high-bandwidth correction without significant added noise from classical reference signals. We demonstrate the performance of our APC using a variety of classical and quantum characterizations. Finally, we use C-band and L-band APC versions to demonstrate continuous high-fidelity entanglement distribution on a metropolitan quantum network with an average relative fidelity of 0.94 ± 0.03 for over 30 hrs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1996

Variational Methods in Sensitivity Analysis and Optimization for Aerodynamic Applications

Variational methods (VM) sensitivity analysis, which is the continuous alternative to the discrete sensitivity analysis, is employed to derive the costate (adjoint) equations, the transversality conditions, and the functional sensitivity derivatives. In the derivation of the sensitivity equations, the variational methods use the generalized calculus of variations, in which the variable boundary is considered as the design function. The converged solution of the state equations together with the converged solution of the costate equations are integrated along the domain boundary to uniquely determine the functional sensitivity derivatives with respect to the design function. The determination of the sensitivity derivatives of the performance index or functional entails the coupled solutions of the state and costate equations. As the stable and converged numerical solution of the costate equations with their boundary conditions are a priori unknown, numerical stability analysis is performed on both the state and costate equations. Thereafter, based on the amplification factors obtained by solving the generalized eigenvalue equations, the stability behavior of the costate equations is discussed and compared with the state (Euler) equations. The stability analysis of the costate equations suggests that the converged and stable solution of the costate equation is possible only if the computational domain of the costate equations is transformed to take into account the reverse flow nature of the costate equations. The application of the variational methods to aerodynamic shape optimization problems is demonstrated for internal flow problems at supersonic Mach number range. The study shows, that while maintaining the accuracy of the functional sensitivity derivatives within the reasonable range for engineering prediction purposes, the variational methods show a substantial gain in computational efficiency, i.e., computer time and memory, when compared with the finite difference sensitivity analysis.

Ibrahim, A. H.↗
DOE OSTI2021

An Approach to Bayesian Optimization for Design Feasibility Check on Discontinuous Black-Box Functions

The paper presents a novel approach to applying Bayesian Optimization (BO) in predicting an unknown constraint boundary, also representing the discontinuity of an unknown function, for a feasibility check on the design space, thereby representing a classification tool to discern between a feasible and infeasible region. Bayesian optimization is a low-cost black-box global optimization tool in the Sequential Design Methods where one learns and updates knowledge from prior evaluated designs, and proceeds to the selection of new designs for future evaluation. However, BO is best suited to problems with the assumption of a continuous objective function and does not guarantee true convergence when having a discontinuous design space. This is because of the insufficient knowledge of the BO about the nature of the discontinuity of the unknown true function. In this paper, we have proposed to predict the location of the discontinuity using a BO algorithm on an artificially projected continuous design space from the original discontinuous design space. The proposed approach has been implemented in a thin tube design with the risk of creep-fatigue failure under constant loading of temperature and pressure. The stated risk depends on the location of the designs in terms of safe and unsafe regions, where the discontinuities lie at the transition between those regions; therefore, the discontinuity has also been treated as an unknown creep-fatigue failure constraint. The proposed BO algorithm has been trained to maximize sampling toward the unknown transition region, to act as a high accuracy classifier between safe and unsafe designs with minimal training cost. The converged solution has been validated for different design parameters with classification error rate and function evaluations at an average of <1% and ~150, respectively. Finally, the performance of our proposed approach in terms of training cost and classification accuracy of thin tube design is shown to be better than the existing machine learning (ML) algorithms such as Support Vector Machine (SVM), Random Forest (RF), and Boosting.

Engineering↗
NASA NTRS2017

Initial Results of Heuristic Guided Orbit Selection for a Low Frequency Radio Interferometric Spacecraft Constellation

A constellation of radio telescope spacecraft can leverage interferometry to accurately image distant objects throughout the universe, but mission design must balance among many interrelated constraints. In particular, the number of craft and the selection of time-varying orbital parameters play a pivotal role in determining what interferometric baselines are feasible with respect to different targets, and thus drives the breadth and quality of data available to the constellation. The large combinatorial orbit configuration space and competing concerns present a challenging problem that is not well addressed by traditional mission design processes. This paper describes application of automated optimization methods to help direct mission design effort to the most promising dynamic constellation geometries: those that achieve broad interferometric coverage but remain cost-effective and resilient to failures. Several automatic heuristic-driven optimization algorithms representing complementary search strategies were created to explore among concrete constellation configuration plans. Evaluation of each candidate constellation plan was accelerated by efficiently combining precomputed caches of orbital and interferometric data. Results indicate that leveraging automated optimization for constellation mission design is both practical and illuminating: generated solutions provided both evidence for existing design intuitions as well as fresh insights into novel configurations.

Hernandez, Sonia↗
DOE OSTI2026

Control co-design under uncertainty for offshore wind farms: Optimizing grid integration, energy storage, and market participation

Offshore wind farms (OWFs) are set to significantly contribute to global decarbonization efforts. Developers often use a sequential approach to optimize design variables and market participation for grid-integrated offshore wind farms. However, this method can lead to sub-optimal system performance, and uncertainties associated with renewable resources are often overlooked in decision-making. Here, this paper proposes a control co-design approach, optimizing design and control decisions for integrating OWFs into the power grid while considering energy market and primary frequency market participation. Additionally, we introduce optimal sizing solutions for energy storage systems deployed onshore to enhance revenue for OWF developers over time. This framework addresses uncertainties related to wind resources and energy prices. We analyze five U.S. west-coast offshore wind farm locations and potential interconnection points, as identified by the Bureau of Ocean Energy Management (BOEM). Results show that optimized control co-design solutions can increase market revenue by 3.2% and provide flexibility in managing wind resource uncertainties.

Control Co-design↗
NASA NTRS2014

Path Toward a Unifid Geometry for Radiation Transport

The Direct Accelerated Geometry for Radiation Analysis and Design (DAGRAD) element of the RadWorks Project under Advanced Exploration Systems (AES) within the Space Technology Mission Directorate (STMD) of NASA will enable new designs and concepts of operation for radiation risk assessment, mitigation and protection. This element is designed to produce a solution that will allow NASA to calculate the transport of space radiation through complex computer-aided design (CAD) models using the state-of-the-art analytic and Monte Carlo radiation transport codes. Due to the inherent hazard of astronaut and spacecraft exposure to ionizing radiation in low-Earth orbit (LEO) or in deep space, risk analyses must be performed for all crew vehicles and habitats. Incorporating these analyses into the design process can minimize the mass needed solely for radiation protection. Transport of the radiation fields as they pass through shielding and body materials can be simulated using Monte Carlo techniques or described by the Boltzmann equation, which is obtained by balancing changes in particle fluxes as they traverse a small volume of material with the gains and losses caused by atomic and nuclear collisions. Deterministic codes that solve the Boltzmann transport equation, such as HZETRN [high charge and energy transport code developed by NASA Langley Research Center (LaRC)], are generally computationally faster than Monte Carlo codes such as FLUKA, GEANT4, MCNP(X) or PHITS; however, they are currently limited to transport in one dimension, which poorly represents the secondary light ion and neutron radiation fields. NASA currently uses HZETRN space radiation transport software, both because it is computationally efficient and because proven methods have been developed for using this software to analyze complex geometries. Although Monte Carlo codes describe the relevant physics in a fully three-dimensional manner, their computational costs have thus far prevented their widespread use for analysis of complex CAD models, leading to the creation and maintenance of toolkit-specific simplistic geometry models. The work presented here builds on the Direct Accelerated Geometry Monte Carlo (DAGMC) toolkit developed for use with the Monte Carlo N-Particle (MCNP) transport code. The workflow for achieving radiation transport on CAD models using MCNP and FLUKA has been demonstrated and the results of analyses on realistic spacecraft/habitats will be presented. Future work is planned that will further automate this process and enable the use of multiple radiation transport codes on identical geometry models imported from CAD. This effort will enhance the modeling tools used by NASA to accurately evaluate the astronaut space radiation risk and accurately determine the protection provided by as-designed exploration mission vehicles and habitats

Lee, Kerry↗
NASA NTRS1995

Design and development of an F/A-18 inlet distortion rake: A cost and time saving solution

An innovative inlet total pressure distortion measurement rake has been designed and developed for the F/A-18 A/B/C/D aircraft inlet. The design was conceived by NASA and General Electric Aircraft Engines personnel. This rake has been flight qualified and flown in the F/A-18 High Alpha Research Vehicle at NASA Dryden Flight Research Center, Edwards, California. The eight-legged, one-piece, wagon wheel design of the rake was developed at a reduced cost and offered reduced installation time compared to traditional designs. The rake features 40 dual-measurement ports for low- and high-frequency pressure measurements with the high-frequency transducer mounted at the port. This high-frequency transducer offers direct absolute pressure measurements from low to high frequencies of interest, thereby allowing the rake to be used during highly dynamic aircraft maneuvers. Outstanding structural characteristics are inherent to the design through its construction and use of lightweight materials.

Yuhas, Andrew J.↗
DOE OSTI2024

Design of a high-temperature cell for cobalt-60 irradiations of aqueous solutions with in situ UV–visible spectroscopy

To understand the speciation of solutes in aqueous solutions in high temperature radiation environments, we report the design and fabrication of a custom-built, high temperature (≤300 °C) titanium irradiation cell with in situ optical spectroscopy capabilities, as afforded by coupled fiber optic cables. The wetted surfaces of the 8-inch tall cylindrical cell with 3.5 in. diameter are entirely made of titanium, sapphire, and gold, which are chemically and radiolytically inert. The initial benchmarking results are reported, including the baseline spectrum of deionized water as a function of temperature, the stability of a spectrum over 4 h at 100 °C, and an irradiated Fricke dosimetry solution under ambient irradiator temperature conditions (27.0 ± 0.5 °C). Further, the average gamma radiation dose rate in the cell in its current configuration is 26.1 ± 1.3 Gy min -1 . This cell has application in studying several processes throughout the nuclear fuel cycle, including the reactor coolant behavior.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS2003

Binary-Phase Fourier Gratings for Nonuniform Array Generation

We describe a design method for a binary-phase Fourier grating that generates an array of spots with nonuniform, user-defined intensities symmetric about the zeroth order. Like the Dammann fanout grating approach, the binary-phase Fourier grating uses only two phase levels in its grating surface profile to generate the final spot array. Unlike the Dammann fanout grating approach, this method allows for the generation of nonuniform, user-defined intensities within the final fanout pattern. Restrictions governing the specification and realization of the array's individual spot intensities are discussed. Design methods used to realize the grating employ both simulated annealing and nonlinear optimization approaches to locate optimal solutions to the grating design problem. The end-use application driving this development operates in the near- to mid-infrared spectrum - allowing for higher resolution in grating specification and fabrication with respect to wavelength than may be available in visible spectrum applications. Fabrication of a grating generating a user-defined nine spot pattern is accomplished in GaAs for the near-infrared. Characterization of the grating is provided through the measurement of individual spot intensities, array uniformity, and overall efficiency. Final measurements are compared to calculated values with a discussion of the results.

Keys, Andrew S.↗
NASA NTRS2016

Trajectory Design Employing Convex Optimization for Landing on Irregularly Shaped Asteroids

Mission proposals that land on asteroids are becoming popular. However, in order to have a successful mission the spacecraft must reliably and softly land at the intended landing site. The problem under investigation is how to design a fuel-optimal powered descent trajectory that can be quickly computed on- board the spacecraft, without interaction from ground control. An optimal trajectory designed immediately prior to the descent burn has many advantages. These advantages include the ability to use the actual vehicle starting state as the initial condition in the trajectory design and the ease of updating the landing target site if the original landing site is no longer viable. For long trajectories, the trajectory can be updated periodically by a redesign of the optimal trajectory based on current vehicle conditions to improve the guidance performance. One of the key drivers for being completely autonomous is the infrequent and delayed communication between ground control and the vehicle. Challenges that arise from designing an asteroid powered descent trajectory include complicated nonlinear gravity fields, small rotating bodies and low thrust vehicles. There are two previous studies that form the background to the current investigation. The first set looked in-depth at applying convex optimization to a powered descent trajectory on Mars with promising results.1, 2 This showed that the powered descent equations of motion can be relaxed and formed into a convex optimization problem and that the optimal solution of the relaxed problem is indeed a feasible solution to the original problem. This analysis used a constant gravity field. The second area applied a successive solution process to formulate a second order cone program that designs rendezvous and proximity operations trajectories.3, 4 These trajectories included a Newtonian gravity model. The equivalence of the solutions between the relaxed and the original problem is theoretically established. The proposed solution for designing the asteroid powered descent trajectory is to use convex optimization, a gravity model with higher fidelity than Newtonian, and an iterative solution process to design the fuel optimal trajectory. The solution to the convex optimization problem is the thrust profile, magnitude and direction, that will yield the minimum fuel trajectory for a soft landing at the target site, subject to various mission and operational constraints. The equations of motion are formulated in a rotating coordinate system and includes a high fidelity gravity model. The vehicle's thrust magnitude can vary between maximum and minimum bounds during the burn. Also, constraints are included to ensure that the vehicle does not run out of propellant, or go below the asteroid's surface, and any vehicle pointing requirements. The equations of motion are discretized and propagated with the trapezoidal rule in order to produce equality constraints for the optimization problem. These equality constraints allow the optimization algorithm to solve the entire problem, without including a propagator inside the optimization algorithm.

Pinson, Robin M.↗