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At least 1,045 records · Page 58

Advanced technology development for image gathering, coding, and processing

Three overlapping areas of research activities are presented: (1) Information theory and optimal filtering are extended to visual information acquisition and processing. The goal is to provide a comprehensive methodology for quantitatively assessing the end-to-end performance of image gathering, coding, and processing. (2) Focal-plane processing techniques and technology are developed to combine effectively image gathering with coding. The emphasis is on low-level vision processing akin to the retinal processing in human vision. (3) A breadboard adaptive image-coding system is being assembled. This system will be used to develop and evaluate a number of advanced image-coding technologies and techniques as well as research the concept of adaptive image coding.

Huck, Friedrich O.↗

Expert System Control of Plant Growth in an Enclosed Space

The Expert System is an enclosed, controlled environment for growing plants, which incorporates a computerized, knowledge-based software program that is designed to capture the knowledge, experience, and problem-solving skills of one or more human experts in a particular discipline. The Expert System is trained to analyze crop/plant status, to monitor the condition of the plants and the environment, and to adjust operational parameters to optimize the plant-growth process. This system is intended to provide a way to remotely control plant growth with little or no human intervention. More specifically, the term control implies an autonomous method for detecting plant states such as health (biomass) or stress and then for recommending and implementing cultivation and/or remediation to optimize plant growth and to minimize consumption of energy and nutrients. Because of difficulties associated with delivering energy and nutrients remotely, a key feature of this Expert System is its ability to minimize this effort and to achieve optimum growth while taking into account the diverse range of environmental considerations that exist in an enclosed environment. The plant-growth environment for the Expert System could be made from a variety of structures, including a greenhouse, an underground cavern, or another enclosed chamber. Imaging equipment positioned within or around the chamber provides spatially distributed crop/plant-growth information. Sensors mounted in the chamber provide data and information pertaining to environmental conditions that could affect plant development. Lamps in the growth environment structure supply illumination, and other additional equipment in the chamber supplies essential nutrients and chemicals.

May, George↗

Development of metallization process: FSA project, cella and module formation research area

The optimization, evaluation, and demonstration of a novel metallization applied by a screen printing process is examined. Based on previous results of High Resolution, Low Cost Solar Cell Contact Development, a paste consisting of molybdenum, tin, and titanium hydride was selected as the promising composition. No satisfactory cells were made using any of the molybdenum/tin pastes used as a complete replacement for conventional silver pastes. The major problem is the inability to form a bond between the pastes and silicon that withstands soldering.

Garcia, A., III↗

An Optimized Multicolor Point-Implicit Solver for Unstructured Grid Applications on Graphics Processing Units

In the field of computational fluid dynamics, the Navier-Stokes equations are often solved using an unstructuredgrid approach to accommodate geometric complexity. Implicit solution methodologies for such spatial discretizations generally require frequent solution of large tightly-coupled systems of block-sparse linear equations. The multicolor point-implicit solver used in the current work typically requires a significant fraction of the overall application run time. In this work, an efficient implementation of the solver for graphics processing units is proposed. Several factors present unique challenges to achieving an efficient implementation in this environment. These include the variable amount of parallelism available in different kernel calls, indirect memory access patterns, low arithmetic intensity, and the requirement to support variable block sizes. In this work, the solver is reformulated to use standard sparse and dense Basic Linear Algebra Subprograms (BLAS) functions. However, numerical experiments show that the performance of the BLAS functions available in existing CUDA libraries is suboptimal for matrices representative of those encountered in actual simulations. Instead, optimized versions of these functions are developed. Depending on block size, the new implementations show performance gains of up to 7x over the existing CUDA library functions.

Zubair, Mohammad↗

Advanced technologies in the ASI MLRO towards a new generation laser ranging system

Matera Laser Ranging Observatory (MLRO) is a high performance, highly automated optical and astronomical observatory currently under design and development by AlliedSignal for the Italian Space Agency (ASI). It is projected to become operational at the Centro Geodesia Spaziale in Matera, Italy, in 1997. MLRO, based on a 1.5-meter astronomical quality telescope, will perform ranging to spacecraft in earthbound orbits, lunar reflectors, and specially equipped deep space missions. The primary emphasis during design is to incorporate state-of-the-art technologies to produce an intelligent, automated, high accuracy ranging system that will mimic the characteristic features of a fifth generation laser ranging system. The telescope has multiple ports and foci to support future experiments in the areas of laser communications, lidar, astrometry, etc. The key features providing state-of-the-art ranging performance include: a diode-pumped picosecond (50 ps) laser, high speed (3-5 GHz) optoelectronic detection and signal processing, and a high accuracy (6 ps) high resolution (less than 2 ps) time measurement capability. The above combination of technologies is expected to yield millimeter laser ranging precision and accuracy on targets up to 300,000 km, surpassing the best operational instrument performance to date by a factor of five or more. Distributed processing and control using a state-of-the-art computing environment provides the framework for efficient operation, system optimization, and diagnostics. A computationally intelligent environment permits optimal planning, scheduling, tracking, and data processing. It also supports remote access, monitor, and control for joint experiments with other observatories.

Varghese, Thomas↗

OPTIMIZING MEASUREMENTS OF THE NEAR-SURFACE WATER CYCLE ON MARS: INSIGHTS FOR HABITABILITY.

The Martian regolith may act as a sink and source of water vapor for the lower atmosphere through processes such as frost formation, physisorption, solid-state hydration, and brine formation [e.g., 1- 12]. These processes are all dependent on temperature and humidity, as well as regolith properties such as porosity, tortuosity, and composition. In particular, the salty nature of the Martian regolith may increase its role in atmosphere-regolith interactions as hygroscopic salts interact with the ambient water vapor. Although to date experimental works near Mars-relevant conditions have constrained some of the potential effects of a salty regolith on water vapor exchange processes [e.g., 13-18], vital in situ measurements are lacking to link these to the near-surface water cycle on Mars. This is because previous and ongoing environmental payloads for landed Mars missions were not designed to investigate atmosphere-regolith exchange processes [12, 19-20]. Resolving the Martian near-surface water cycle is relevant to both climatic processes and astrobiology. There is the potential to presently form (meta)stable brines on Mars; their stability would be largely controlled by water vapor exchange processes [9, 21]. Here we argue for optimizing in situ measurements of water vapor exchange processes and regolith properties to advance our understanding of the local scale Martian water cycle and inform habitability studies.

E G Rivera-Valentin↗

Mechanisms and kinetics of cellulose fermentation for protein production

The development of a process (and ancillary processing and analytical techniques) to produce bacterial single-cell protein of good nutritional quality from waste cellulose is discussed. A fermentation pilot plant and laboratory were developed and have been in operation for about two years. Single-cell protein (SCP) can be produced from sugarcane bagasse--a typical agricultural cellulosic waste. The optimization and understanding of this process and its controlling variables are examined. Both batch and continuous fermentation runs have been made under controlled conditions in the 535 liter pilot plant vessel and in the laboratory 14-liter fermenters.

Dunlap, C. A.↗

Array automated assembly task, phase 2. Low cost silicon solar array project

Several modifications instituted in the wafer surface preparation process served to significantly reduce the process cost to 1.55 cents per peak watt in 1975 cents. Performance verification tests of a laser scanning system showed a limited capability to detect hidden cracks or defects, but with potential equipment modifications this cost effective system could be rendered suitable for applications. Installation of electroless nickel plating system was completed along with an optimization of the wafer plating process. The solder coating and flux removal process verification test was completed. An optimum temperature range of 500-550 C was found to produce uniform solder coating with the restriction that a modified dipping procedure is utilized. Finally, the construction of the spray-on dopant equipment was completed.

Rhee, S. S.↗

Process modeling for carbon-phenolic nozzle materials

A thermochemical model based on the SINDA heat transfer program is developed for carbon-phenolic nozzle material processes. The model can be used to optimize cure cycles and to predict material properties based on the types of materials and the process by which these materials are used to make nozzle components. Chemical kinetic constants for Fiberite MX4926 were determined so that optimization of cure cycles for the current Space Shuttle Solid Rocket Motor nozzle rings can be determined.

Letson, Mischell A.↗

A scheme for handling arrays in data-flow systems

An examination of the effects of atomicity (higher resolution) on the performance of array processors (data-flow computers) is presented. Data-flow principles are reviewed, noting the reliance on parallel processing using functional languages to specify sequencing of the operations. Techniques are described for eliminating the necessity of copying whole arrays between processing steps, thereby reducing the number of store cycles. The method involves setting whole columns to specific values rather than individual elements. The individual column values can be processed in parallel, i.e., a locally optimized condition exists. A drawback of the system is the need for more low level arguments, to identify the appropriate processing sequences, and high system complexity.

Gaudiot, J.-L.↗

Reliability and Maintainability Engineering - A Major Driver for Safety and Affordability

The United States National Aeronautics and Space Administration (NASA) is in the midst of an effort to design and build a safe and affordable heavy lift vehicle to go to the moon and beyond. To achieve that, NASA is seeking more innovative and efficient approaches to reduce cost while maintaining an acceptable level of safety and mission success. One area that has the potential to contribute significantly to achieving NASA safety and affordability goals is Reliability and Maintainability (R&M) engineering. Inadequate reliability or failure of critical safety items may directly jeopardize the safety of the user(s) and result in a loss of life. Inadequate reliability of equipment may directly jeopardize mission success. Systems designed to be more reliable (fewer failures) and maintainable (fewer resources needed) can lower the total life cycle cost. The Department of Defense (DOD) and industry experience has shown that optimized and adequate levels of R&M are critical for achieving a high level of safety and mission success, and low sustainment cost. Also, lessons learned from the Space Shuttle program clearly demonstrated the importance of R&M engineering in designing and operating safe and affordable launch systems. The Challenger and Columbia accidents are examples of the severe impact of design unreliability and process induced failures on system safety and mission success. These accidents demonstrated the criticality of reliability engineering in understanding component failure mechanisms and integrated system failures across the system elements interfaces. Experience from the shuttle program also shows that insufficient Reliability, Maintainability, and Supportability (RMS) engineering analyses upfront in the design phase can significantly increase the sustainment cost and, thereby, the total life cycle cost. Emphasis on RMS during the design phase is critical for identifying the design features and characteristics needed for time efficient processing, improved operational availability, and optimized maintenance and logistic support infrastructure. This paper discusses the role of R&M in a program acquisition phase and the potential impact of R&M on safety, mission success, operational availability, and affordability. This includes discussion of the R&M elements that need to be addressed and the R&M analyses that need to be performed in order to support a safe and affordable system design. The paper also provides some lessons learned from the Space Shuttle program on the impact of R&M on safety and affordability.

Safie, Fayssal M.↗

Cost model relationships between textile manufacturing processes and design details for transport fuselage elements

Textile manufacturing processes offer potential cost and weight advantages over traditional composite materials and processes for transport fuselage elements. In the current study, design cost modeling relationships between textile processes and element design details were developed. Such relationships are expected to help future aircraft designers to make timely decisions on the effect of design details and overall configurations on textile fabrication costs. The fundamental advantage of a design cost model is to insure that the element design is cost effective for the intended process. Trade studies on the effects of processing parameters also help to optimize the manufacturing steps for a particular structural element. Two methods of analyzing design detail/process cost relationships developed for the design cost model were pursued in the current study. The first makes use of existing databases and alternative cost modeling methods (e.g. detailed estimating). The second compares design cost model predictions with data collected during the fabrication of seven foot circumferential frames for ATCAS crown test panels. The process used in this case involves 2D dry braiding and resin transfer molding of curved 'J' cross section frame members having design details characteristic of the baseline ATCAS crown design.

Metschan, Stephen L.↗

A technique for integrating engine cycle and aircraft configuration optimization

A method for conceptual aircraft design that incorporates the optimization of major engine design variables for a variety of cycle types was developed. The methodology should improve the lengthy screening process currently involved in selecting an appropriate engine cycle for a given application or mission. The new capability will allow environmental concerns such as airport noise and emissions to be addressed early in the design process. The ability to rapidly perform optimization and parametric variations using both engine cycle and aircraft design variables, and to see the impact on the aircraft, should provide insight and guidance for more detailed studies. A brief description of the aircraft performance and mission analysis program and the engine cycle analysis program that were used is given. A new method of predicting propulsion system weight and dimensions using thermodynamic cycle data, preliminary design, and semi-empirical techniques is introduced. Propulsion system performance and weights data generated by the program are compared with industry data and data generated using well established codes. The ability of the optimization techniques to locate an optimum is demonstrated and some of the problems that had to be solved to accomplish this are illustrated. Results from the application of the program to the analysis of three supersonic transport concepts installed with mixed flow turbofans are presented. The results from the application to a Mach 2.4, 5000 n.mi. transport indicate that the optimum bypass ratio is near 0.45 with less than 1 percent variation in minimum gross weight for bypass ratios ranging from 0.3 to 0.6. In the final application of the program, a low sonic boom fix a takeoff gross weight concept that would fly at Mach 2.0 overwater and at Mach 1.6 overland is compared with a baseline concept of the same takeoff gross weight that would fly Mach 2.4 overwater and subsonically overland. The results indicate that for the design mission, the low boom concept has a 5 percent total range penalty relative to the baseline. Additional cycles were optimized for various design overland distances and the effect of flying off-design overland distances is illustrated.

Geiselhart, Karl A.↗

Soft-Decision Decoding of Binary Linear Block Codes Based on an Iterative Search Algorithm

This correspondence presents a suboptimum soft-decision decoding scheme for binary linear block codes based on an iterative search algorithm. The scheme uses an algebraic decoder to iteratively generate a sequence of candidate codewords one at a time using a set of test error patterns that are constructed based on the reliability information of the received symbols. When a candidate codeword is generated, it is tested based on an optimality condition. If it satisfies the optimality condition, then it is the most likely (ML) codeword and the decoding stops. If it fails the optimality test, a search for the ML codeword is conducted in a region which contains the ML codeword. The search region is determined by the current candidate codeword and the reliability of the received symbols. The search is conducted through a purged trellis diagram for the given code using the Viterbi algorithm. If the search fails to find the ML codeword, a new candidate is generated using a new test error pattern, and the optimality test and search are renewed. The process of testing and search continues until either the MEL codeword is found or all the test error patterns are exhausted and the decoding process is terminated. Numerical results show that the proposed decoding scheme achieves either practically optimal performance or a performance only a fraction of a decibel away from the optimal maximum-likelihood decoding with a significant reduction in decoding complexity compared with the Viterbi decoding based on the full trellis diagram of the codes.

Lin, Shu↗

Evaluating Lunar Water Processing System Model Configurations for Small Scale Oxygen and Hydrogen Production Within JAXA’s ISRU Technology Demonstration Plant

In-Situ Resource Utilization (ISRU) refers to novel methods of extracting and processing local resources for use in life support and propulsion systems, reducing or eliminating the required consumables to be transferred from Earth. Current estimates of water-ice availability embedded in regolith within the Moon’s permanently shadowed regions (PSR’s)range between 1-5% by weight. However, the composition and characteristics of the “wet” regolith is unknown. Alternate ISRU excavation techniques and Concept of Operations (ConOps) must be explored to optimize surface system operations based on these factors. To assess the feasibility of different ISRU subsystem technologies and compare system architecture configurations, an interchangeable system model was generated to incorporate technologies spanning excavation of raw materials to storage of products and determine optimal arrangement of total system processing needs. Total Mass, Volume, and Power (M/V/P) requirements were computed for 168 design iterations of this water processing plant.

ISRU↗

Managing the Digital Thread for Structural Applications With Fit for Purpose Materials

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Consequently, at NASA Glenn Research Center a robust information management system that manages the digital thread across the full material life (i.e., capture, analysis, maintenance, and dissemination of data) cycle directed at the design of ‘fit-for-purpose materials’ is under development. To this end the Application Table has been incorporated within NASA Glenn Research Center’s ICME Information Management framework within the ANSYS Granta MI tool. The Application Table provides a place where material and structural application information/requirements can be linked to marry the “design-the-material” (structural engineering) and the “design-with-material” (material science) paradigms and thereby enable application-driven design and optimization of materials and structures. In additional several associated toolsets, specifically: AIMAOS (Automated Information Management Across Organizations and Scales), Py MILab, and JARIMIS (Just A Rather Intelligent Material Interrogation System) are also under development to assist in the judicious automation of this process. AIMOAS offers users an interactive graphical user interface for connecting material information management systems with both commercial and in-house simulation tools at various length scales to enable such automation in the handoff across scales and maintenance of material digital twins and the digital thread. Py MILab, is an automatic framework for the capture, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. Finally, JARIMIS is an expert system that integrates various materials informatics tools (e.g., MicroNet, Surrogate ML models, ANSYS Granta MI, etc.) to enable inverse design of materials and facilitate the application of machine learning (ML) and data science with human in the loop decision making to rapidly discover and optimize new materials.

Digital Transformation↗

Parallelization of a Parabolized Navier-Stokes Solver with a Design Optimizer

The design of future supersonic aircraft, such as the High Speed Civil Transport (HSCT), will rely heavily on computational methods for aircraft design and the prediction of the complex aerodynamics encountered in flight. Parabolized Navier-Stokes (PNS) equation flow solvers are recognized as efficient and accurate computational tools for the solution of supersonic and hypersonic flow-fields, while design optimizers have the potential to be valuable tools within the overall design process. Presently, however, the execution of the flow solver in conjunction with a design optimizer presents a computationally intensive and formidable problem. To meet the challenges and increasing demand for multidisciplinary numerical tools which are faster, more robust and provide greater functionality, alternative strategies are explored to increase computational throughput by coupling a design optimizer and flow solver in a parallel processing environment. To address this problem the parallel processing of a PNS flow solver with a nonlinear constraint design optimizer is investigated as an alternative computational method.

Pallis, J. M.↗

On Efficient Multigrid Methods for Materials Processing Flows with Small Particles

Multiscale modeling of materials requires simulations of multiple levels of structural hierarchy. The computational efficiency of numerical methods becomes a critical factor for simulating large physical systems with highly desperate length scales. Multigrid methods are known for their superior efficiency in representing/resolving different levels of physical details. The efficiency is achieved by employing interactively different discretizations on different scales (grids). To assist optimization of manufacturing conditions for materials processing with numerous particles (e.g., dispersion of particles, controlling flow viscosity and clusters), a new multigrid algorithm has been developed for a case of multiscale modeling of flows with small particles that have various length scales. The optimal efficiency of the algorithm is crucial for accurate predictions of the effect of processing conditions (e.g., pressure and velocity gradients) on the local flow fields that control the formation of various microstructures or clusters.

Thomas, James↗