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At least 847 records · Page 47

Non-Magnetic, Tough, Corrosion- and Wear-Resistant Knives From Bulk Metallic Glasses and Composites

Quality knives are typically fabricated from high-strength steel alloys. Depending on the application, there are different requirements for mechanical and physical properties that cause problems for steel alloys. For example, diver's knives are generally used in salt water, which causes rust in steel knives. Titanium diver's knives are a popular alternative due to their salt water corrosion resistance, but are too soft to maintain a sharp cutting edge. Steel knives are also magnetic, which is undesirable for military applications where the knives are used as a tactical tool for diffusing magnetic mines. Steel is also significantly denser than titanium (8 g/cu cm vs. 4.5 g/cu cm), which results in heavier knives for the same size. Steel is hard and wear-resistant, compared with titanium, and can keep a sharp edge during service. A major drawback of both steel and titanium knives is that they must be ground or machined into the final knife shape from a billet. Since most knives have a mirrored surface and a complex shape, manufacturing them is complex. It would be more desirable if the knife could be cast into a net or near-net shape in a single step. The solution to the deficiencies of titanium, steel, and ceramic knives is to fabricate them using bulk metallic glasses (or composites). These alloys can be cast into net or near-net shaped knives with a combination of properties that exceed both titanium and steel. A commercially viable BMG (bulk metallic glass) or composite knife is one that exhibits one or all of the following properties: It is based on titanium, has a self-sharpening edge, can retain an edge during service, is hard, is non-magnetic, is corrosion-resistant against a variety of corrosive environments, is tough (to allow for prying), can be cast into a net-shape with a mirror finish and a complex shape, has excellent wear resistance, and is low-density. These properties can be achieved in BMG and composites through alloy chemistry and processing. For each desired property for knife fabrication and performance, there is an alloy development strategy that optimizes behavior. Although BMG knives have been demonstrated as far back as 1995, they never found commercial success because they had to be ground (which presented problems because the alloys contained beryllium), they weren't low cost (because they weren't cast to a net-shape), they were brittle (because they were made with a low-quality commercial material), and they had extremely poor corrosion resistance (because corrosion was not well-understood in these materials). Ultimately, these shortcomings prevented the widespread commercialization. In the current work, the inventors have applied more than a decade of research on BMGs from Caltech and JPL to develop a better understanding of how to make BMG knives that exhibit an optimal combination of properties, processing and cost. Alloys have been developed based in titanium (and other metals), that exhibit high toughness, high hardness, excellent corrosion resistance, no ferromagnetism, edge-retaining selfsharpening, and the ability to be cast like a plastic using commercially available casting techniques (currently used by commercial companies such as Liquidmetal Technologies and Visser Precision Casting). The inventors argue that depending on the application (diving, military, tactical, utility, etc.) there is an optimal combination of design and alloy composition. Moreover, with new casting technologies not available at the inception of these materials, net-shaped knives can be cast into complex shapes that require no aftermarket forming, except for sharpening using water-cooled polishing wheel. These combinations of discoveries seek to make low-cost BMG knives commercially viable products that have no equal among metal or ceramic knives. Current work at JPL focuses on net-shape casting of these alloys and testing their mechanical properties versus commercially available knives to demonstrate their benefits.

Hoffman, Douglas C.↗

Study of random process theory aids digital data processing

Study of techniques for all random process technology, including stationary, nonstationary, and Gaussian bivariate, aids digital data processing. It presents material on digital filtering, correlation function, optimal spectral smoothing, deterministic data processing, and nonstationary spectrum and correlation analyses.

Bordner, G. W.↗

Geometry Modeling and Grid Generation for Design and Optimization

Geometry modeling and grid generation (GMGG) have played and will continue to play an important role in computational aerosciences. During the past two decades, tremendous progress has occurred in GMGG; however, GMGG is still the biggest bottleneck to routine applications for complicated Computational Fluid Dynamics (CFD) and Computational Structures Mechanics (CSM) models for analysis, design, and optimization. We are still far from incorporating GMGG tools in a design and optimization environment for complicated configurations. It is still a challenging task to parameterize an existing model in today's Computer-Aided Design (CAD) systems, and the models created are not always good enough for automatic grid generation tools. Designers may believe their models are complete and accurate, but unseen imperfections (e.g., gaps, unwanted wiggles, free edges, slivers, and transition cracks) often cause problems in gridding for CSM and CFD. Despite many advances in grid generation, the process is still the most labor-intensive and time-consuming part of the computational aerosciences for analysis, design, and optimization. In an ideal design environment, a design engineer would use a parametric model to evaluate alternative designs effortlessly and optimize an existing design for a new set of design objectives and constraints. For this ideal environment to be realized, the GMGG tools must have the following characteristics: (1) be automated, (2) provide consistent geometry across all disciplines, (3) be parametric, and (4) provide sensitivity derivatives. This paper will review the status of GMGG for analysis, design, and optimization processes, and it will focus on some emerging ideas that will advance the GMGG toward the ideal design environment.

Samareh, Jamshid A.↗

Experiences with serial and parallel algorithms for channel routing using simulated annealing

Two algorithms for channel routing using simulated annealing are presented. Simulated annealing is an optimization methodology which allows the solution process to back up out of local minima that may be encountered by inappropriate selections. By properly controlling the annealing process, it is very likely that the optimal solution to an NP-complete problem such as channel routing may be found. The algorithm presented proposes very relaxed restrictions on the types of allowable transformations, including overlapping nets. By freeing that restriction and controlling overlap situations with an appropriate cost function, the algorithm becomes very flexible and can be applied to many extensions of channel routing. The selection of the transformation utilizes a number of heuristics, still retaining the pseudorandom nature of simulated annealing. The algorithm was implemented as a serial program for a workstation, and a parallel program designed for a hypercube computer. The details of the serial implementation are presented, including many of the heuristics used and some of the resulting solutions.

Brouwer, Randall Jay↗

Combined design of structures and controllers for optimal maneuverability

Approaches to the combined design of structures and controllers for achieving optimal maneuverability are presented. A maneuverability index which directly reflects the minimum time required to perform a given set of maneuvers is introduced. By designing the flexible appendages, the maneuver time of the spacecraft is minimized under the constraints of structural properties, and post maneuver spillover is kept within a specified bound. The spillover reduction is achieved by making use of an appropriate reduced order model. The distributed parameter design problem is approached using assumed shape functions, and finite element analysis with dynamic reduction. Solution procedures have been investigated. Approximate design methods have been developed to overcome the computational difficulties. Some new constraints on the modal frequencies of the spacecraft are introduced in the original optimization problem to facilitate the solution process. It is shown that the global optimal design may be obtained by tuning the natural frequencies to satisfy specific constraints. Researchers quantify the difference between a lower bound to the solution for maneuver time associated with the original problem and the estimate obtained from the modified problem, for a specified application requirement. Numerical examples are presented to demonstrate the capability of this approach.

Ling, Jer↗

Automated Data Accountability for Missions in Mars Rover Data

As the Mars Curiosity Rover transmits data to the JPL Ground Data System (GDS), it frequently observes data loss and corruption, requiring re-transmits from the rover and Ground Data System Analysts (GDSA) to monitor the downlink process. As new missions are launched, the GDSA team redistributes analysts to these new missions, causing shortages in previous missions. The GDSA team can significantly benefit from the automation and optimization of the downlink process of telemetry data. In fact, there is a need for a better understanding of why the data is corrupted, so that the GDSA team can best determine the root cause of the issues in the GDS. This paper presents machine learning and deep learning based approaches to automate and optimize the detection of data loss. We first created a pipeline to automatically accumulate data from the telemetry databases (MAROS, Telemetry Data Storage, and GDS Elastic Search Database) in the downlink process. With our newly created datasets, we perform feature selection to supplement the GDSA understanding of the downlink process and provide supplemental analysis on the importance of different features. We implement various machine learning and deep learning based models, including support vector machines, ensemble methods, and deep neural networks and evaluate their accuracies in identifying whether a downlink process is complete or incomplete. We utilize fast hyperparameter optimization methods that allow our models to quickly be re-trained, allowing them to quickly be tuned and optimized on daily incoming data in real time. This hyperparameter optimization also allows our methods to be quickly integrated into other JPL missions. Our results show that our best-performing machine learning and deep learning based models outperform the existing GDSA detection software by 6 accuracy points and can aid analysts by providing insights into the data accountability problem. Since these various machine learning and deep learning approaches vary significantly in interpretability, we provide a discussion on the tradeoffs between their performance and trustworthiness in helping detect issues in data transmission.

Divsalar, Dariush↗

Cost studies for commercial fuselage crown designs

Studies were conducted to evaluate the cost and weight potential of advanced composite design concepts in the crown region of a commercial transport. Two designs from each of three design families were developed using an integrated design-build team. A range of design concepts and manufacturing processes were included to allow isolation and comparison of cost centers. Detailed manufacturing/assembly plans were developed as the basis for cost estimates. Each of the six designs was found to have advantages over the 1995 aluminum benchmark in cost and weight trade studies. Large quadrant panels and cobonded frames were found to save significant assembly labor costs. Comparisons of high- and intermediate-performance fiber systems were made for skin and stringer applications. Advanced tow placement was found to be an efficient process for skin lay up. Further analysis revealed attractive processes for stringers and frames. Optimized designs were informally developed for each design family, combining the most attractive concepts and processes within that family. A single optimized design was selected as the most promising, and the potential for further optimization was estimated. Technical issues and barriers were identified.

Walker, T. H.↗

Optimization and design of three-dimensional aerodynamic configurations of arbitrary shape by a vortex lattice method

A new method based on vortex lattice theory has been developed which can be applied to the combined analysis, induced drag optimization, and aerodynamic design of three-dimensional configurations of arbitrary shape. Geometric and aerodynamic constraints can be imposed on both the optimization and the design process. The method is compared with several known analytical solutions and is applied to several different design and optimization problems, including formation flight and wingtip fins for the Boeing KC-135 tanker airplane. Good agreement has been observed between the theoretical predictions and the wind tunnel test results for the KC-135 modification.

Feifel, W. M.↗

Trajectory Optimization Methods and Applications at NASA Goddard

The process of spacecraft trajectory design frequently incorporates an optimization step in which one or more objectives, such as propellant consumption or time of flight, is minimized. Optimization is especially crucial for low-thrust mission design, due to the need to specify a thrust vector at every instant in time along a trajectory. At NASA's Goddard Space Flight Center (GSFC) a number of open-source tools have been developed for spacecraft trajectory optimization that utilize direct shooting and collocation methods. These tools have been effectively applied to cislunar, libration point, and interplanetary mission design for the Lunar IceCube, SWFO, and DAVINCI missions, among others. This presentation outlines the theory underlying these optimization tools along with the details of their application to several trajectory design problems, with a focus on the Lunar IceCube (LIC) mission. The LIC mission required a low-thrust trajectory from a high-energy deployment state to a lunar orbit, and its limited control authority necessitated the use of optimization tools and low-energy trajectory design techniques. The tools discussed demonstrate how the use of optimization methods expands mission capabilities and enables transformational science.

Robert Pritchett↗

Thermodynamic Cycle Analysis of Magnetohydrodynamic-Bypass Airbreathing Hypersonic Engines

Established analyses of conventional ramjet/scramjet performance characteristics indicate that a considerable decrease in efficiency can be expected at off-design flight conditions. This can be explained, in large part, by the deterioration of intake mass flow and limited inlet compression at low flight speeds and by the onset of thrust degradation effects associated with increased burner entry temperature at high flight speeds. In combination, these effects tend to impose lower and upper Mach number limits for practical flight. It has been noted, however, that Magnetohydrodynamic (MHD) energy management techniques represent a possible means for extending the flight Mach number envelope of conventional engines. By transferring enthalpy between different stages of the engine cycle, it appears that the onset of thrust degradation may be delayed to higher flight speeds. Obviously, the introduction of additional process inefficiencies is inevitable with this approach, but it is believed that these losses are more than compensated through optimization of the combustion process. The fundamental idea is to use MHD energy conversion processes to extract and bypass a portion of the intake kinetic energy around the burner. We refer to this general class of propulsion system as an MHD-bypass engine. In this paper, we quantitatively assess the performance potential and scientific feasibility of MHD-bypass airbreathing hypersonic engines using ideal gasdynamics and fundamental thermodynamic principles.

Litchford, Ron J.↗

Processing and plating helical metallic coils

The results of research efforts to develop an optimized nickel cobalt coating suitable as a recording medium are outlined. The coating is to be used directly on a BeCu helical coil substrate of a helical coil NASA recorder. Specifically, efforts were made to: optimize the coating thickness; establish processes and techniques adaptable for the production of finalized plated helical coils; design and fabricate the equipment required for production and testing of the coils; and deliver finalized helical coils to NASA.

Source record↗

A study of enhancing critical current densities (J(sub c)) and critical temperature (T(sub c)) of high-temperature superconductors

The development of pure phase 123 and Bi-based 2223 superconductors has been optimized. The pre-heat processing appears to be a very important parameter in achieving optimal physical properties. The synthesis of pure phases in the Bi-based system involves effects due to oxygen partial pressure, time, and temperature. Orientation/melt-sintering effects include the extreme c-axis orientation of Yttrium 123 and Bismuth 2223, 2212, and 2201 phases. This orientation is conductive to increasing critical currents. A procedure was established to substitute Sr for Ba in Y-123 single crystals.

Vlasse, Marcus↗

Concurrent Probabilistic Simulation of High Temperature Composite Structural Response

A computational structural/material analysis and design tool which would meet industry's future demand for expedience and reduced cost is presented. This unique software 'GENOA' is dedicated to parallel and high speed analysis to perform probabilistic evaluation of high temperature composite response of aerospace systems. The development is based on detailed integration and modification of diverse fields of specialized analysis techniques and mathematical models to combine their latest innovative capabilities into a commercially viable software package. The technique is specifically designed to exploit the availability of processors to perform computationally intense probabilistic analysis assessing uncertainties in structural reliability analysis and composite micromechanics. The primary objectives which were achieved in performing the development were: (1) Utilization of the power of parallel processing and static/dynamic load balancing optimization to make the complex simulation of structure, material and processing of high temperature composite affordable; (2) Computational integration and synchronization of probabilistic mathematics, structural/material mechanics and parallel computing; (3) Implementation of an innovative multi-level domain decomposition technique to identify the inherent parallelism, and increasing convergence rates through high- and low-level processor assignment; (4) Creating the framework for Portable Paralleled architecture for the machine independent Multi Instruction Multi Data, (MIMD), Single Instruction Multi Data (SIMD), hybrid and distributed workstation type of computers; and (5) Market evaluation. The results of Phase-2 effort provides a good basis for continuation and warrants Phase-3 government, and industry partnership.

Abdi, Frank↗

Precision of Sensitivity in the Design Optimization of Indeterminate Structures

Design sensitivity is central to most optimization methods. The analytical sensitivity expression for an indeterminate structural design optimization problem can be factored into a simple determinate term and a complicated indeterminate component. Sensitivity can be approximated by retaining only the determinate term and setting the indeterminate factor to zero. The optimum solution is reached with the approximate sensitivity. The central processing unit (CPU) time to solution is substantially reduced. The benefit that accrues from using the approximate sensitivity is quantified by solving a set of problems in a controlled environment. Each problem is solved twice: first using the closed-form sensitivity expression, then using the approximation. The problem solutions use the CometBoards testbed as the optimization tool with the integrated force method as the analyzer. The modification that may be required, to use the stiffener method as the analysis tool in optimization, is discussed. The design optimization problem of an indeterminate structure contains many dependent constraints because of the implicit relationship between stresses, as well as the relationship between the stresses and displacements. The design optimization process can become problematic because the implicit relationship reduces the rank of the sensitivity matrix. The proposed approximation restores the full rank and enhances the robustness of the design optimization method.

Patnaik, Surya N.↗

Design for Manufacturing Tool for Automated Fiber Placement Structures - Verification and Validation

A tool has been developed to address the growing Design for Manufacturing needs for composite structures, specifically those manufactured with automated fiber placement. This manufacturing approach presents unique challenges associated with puckers and wrinkling, tow overlaps and gaps, fiber deviation, and laminate strength. Achieving a satisfactory laminate design usually requires finding compromises between those four areas. The developed tool, dubbed the Central Optimizer, assists with the process of balancing competing design metrics in automated fiber placement. This tool was developed under the NASA Advanced Composites Consortium with input from industry partners. Under this program, the Central Optimizer has been exercised on three different structures to verify its functionality and validate ability to improve the design process for automated fiber placement structures.

August T Noevere↗

Affordable Development and Optimization of CERMET Fuels for NTP Ground Testing

CERMET fuel materials for Nuclear Thermal Propulsion (NTP) are currently being developed at NASA's Marshall Space Flight Center. The work is part of NASA's Advanced Space Exploration Systems Nuclear Cryogenic Propulsion Stage (NCPS) Project. The goal of the FY12-14 project is to address critical NTP technology challenges and programmatic issues to establish confidence in the affordability and viability of an NTP system. A key enabling technology for an NCPS system is the fabrication of a stable high temperature nuclear fuel form. Although much of the technology was demonstrated during previous programs, there are currently no qualified fuel materials or processes. The work at MSFC is focused on developing critical materials and process technologies for manufacturing robust, full-scale CERMET fuels. Prototypical samples are being fabricated and tested in flowing hot hydrogen to understand processing and performance relationships. As part of this initial demonstration task, a final full scale element test will be performed to validate robust designs. The next phase of the project will focus on continued development and optimization of the fuel materials to enable future ground testing. The purpose of this paper is to provide a detailed overview of the CERMET fuel materials development plan. The overall CERMET fuel development path is shown in Figure 2. The activities begin prior to ATP for a ground reactor or engine system test and include materials and process optimization, hot hydrogen screening, material property testing, and irradiation testing. The goal of the development is to increase the maturity of the fuel form and reduce risk. One of the main accomplishmens of the current AES FY12-14 project was to develop dedicated laboratories at MSFC for the fabrication and testing of full length fuel elements. This capability will enable affordable, near term development and optimization of the CERMET fuels for future ground testing. Figure 2 provides a timeline of the development and optimization tasks for the AES FY15-17 follow on program.

Hickman, Robert R.↗