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At least 829 records · Page 46

Silicon production process evaluations

Chemical engineering analysis was continued for the HSC process (Hemlock Semiconductor Corporation) in which solar cell silicon is produced in a 1,000 MT/yr plant. Progress and status are reported for the primary engineering activities involved in the preliminary process engineering design of the plant base case conditions (96%), reaction chemistry (96%), process flow diagram (85%), material balance (85%), energy balance (60%), property data (60%), equipment design (40%), major equipment list (30%) and labor requirements (10%). Engineering design of the second distillation column (D-02, TCS column) in the process was completed. The design is based on a 97% recovery of the light key (TCS, trichlorosilane) in the distillate and a 97% recovery of the heavy key (TET, silicon tetrachloride) in the bottoms. At a reflux ratio of 2, the specified recovery of TCS and TET is achieved with 20 trays (equilibrium stages, N=20). Respective feed tray locations are 9, 12 and 15 (NF sub 1 = 9, NF sub 2 = 12,, and NF sub 3 = 15). A total condenser is used for the distillation which is conducted at a pressure of 90 psia.

Source record↗

Distribution of Aliphatic Amines in CO, CV, and CK Carbonaceous Chondrites and Relation to Mineralogy and Processing History

The analysis of water-soluble organic compounds in meteorites provides valuable insights into the prebiotic synthesis of organic matter and the processes that occurred during the formation of the solar system. We investigated the concentration of aliphatic monoamines present in hot acid water extracts of the unaltered Antarctic carbonaceous chondrites, Dominion Range (DOM) 08006 (CO3) and Miller Range (MIL) 05013 (CO3), and the thermally altered meteorites, Allende (CV3), LAP 02206 (CV3), GRA 06101 (CV3), Allan Hills (ALH) 85002 (CK4), and EET 92002 (CK5). We have also reviewed and assessed the petrologic characteristics of the meteorites studied here to evaluate the effects of asteroidal processing on the abundance and molecular distributions of monoamines. The CO3, CV3, CK4, and CK5 meteorites studied here contain total concentrations of amines ranging from 1.2 to 4.0 nmol/g of meteorite; these amounts are 1-3 orders of magnitude below those observed in carbonaceous chondrites from the CI, CM, and CR groups. The low-amine abundances for CV and CK chondrites may be related to their extensive degree of thermal metamorphism and/or to their low original amine content. Although the CO3 meteorites, DOM 08006 and MIL 05013, do not show signs of thermal and aqueous alteration, their monoamine contents are comparable to those observed in moderately/extensively thermally altered CV3, CK4, and CK5 carbonaceous chondrites. The low content of monoamines in pristine CO carbonaceous chondrites suggests that the initial amounts, and not asteroidal processes, play a dominant role in the content of monoamines in carbonaceous chondrites. The primary monoamines, methylamine, ethylamine, and n-propylamine constitute the most abundant amines in the CO3, CV3, CK4, and CK5 meteorites studied here. Contrary to the predominance of n-x-amino acid isomers in CO3 and thermally altered meteorites, there appears to be no preference for the larger n-amines.

mineralogy↗

XV-15 Tilt Rotor Research Aircraft Photogrammetry and Metrology Measurement

A new measurement capability was created by combining photogrammetry and metrology techniques to accurately measure one half of the XV-15 Tilt Rotor Research Aircraft at the Smithsonian’s Udvar-Hazy museum. The challenges imposed by the fuselage and surrounding environment at Udvar-Hazy were overcome by careful application of photogrammetry and metrology techniques. Data analyses and processing included the use of multiple reverse engineering programs to accurately generate a complete 3-dimensional water-tight geometry of the aircraft and rotor blade. This paper describes the photogrammetry and metrology measurement systems, technology and hardware set-up, data analysis and processing methods, future work, and lessons learned. In addition, selected measurement results of the fuselage and rotor blade are presented.

XV-15↗

Analysis of Jimsphere pairs for use in assessing Space Vehicle ascent capability

A data base of paired detailed wind profiles was developed for use in evaluating Shuttle Transportation System (STS) ascent capability. Since launch decision is based on a wind measured about 3.5 hr before launch, a data base of paired detailed profiles is needed. Method and technique on the reduction process and analysis is also presented. Guidelines used in selecting the pairs of profiles were established to insure a valid and representative data base. Sigma-U values for 3.5 hr at 12 km altitude show 8 percent increase from the transition case to the winter case and 18 percent decrease from the transition case to the summer case. Sigma-Values for 3.5 hr at 12 km altitude shows 12 percent increase from the transition case to the winter case and 17 percent decrease from the transition case to the summer case. A special feature of the 7- and 10.5-hr cases is that sigma-V increases by as much as 30 percent from the transition to the winter profiles. This large increase does not appear in the sigma-U data. Comparisons of the calculated values of 3.5 hr standard deviations of U and V with actual component deviations measured during space shuttle launch conditions confirm that the statistical values are representative.

Hill, C. K.↗

Predictability of process resource usage: A measurement-based study of UNIX

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.↗

Predictability of process resource usage - A measurement-based study on UNIX

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient betweeen the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82 percent of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.↗

Conversion-Integration of MSFC Nonlinear Signal Diagnostic Analysis Algorithms for Realtime Execution of MSFC's MPP Prototype System

NASA's advanced propulsion system Small Scale Magnetic Disturbances/Advanced Technology Development (SSME/ATD) has been undergoing extensive flight certification and developmental testing, which involves large numbers of health monitoring measurements. To enhance engine safety and reliability, detailed analysis and evaluation of the measurement signals are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce the risk of catastrophic system failures and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. During the development of SSME, ASRI participated in the research and development of several advanced non- linear signal diagnostic methods for health monitoring and failure prediction in turbomachinery components. However, due to the intensive computational requirement associated with such advanced analysis tasks, current SSME dynamic data analysis and diagnostic evaluation is performed off-line following flight or ground test with a typical diagnostic turnaround time of one to two days. The objective of MSFC's MPP Prototype System is to eliminate such 'diagnostic lag time' by achieving signal processing and analysis in real-time. Such an on-line diagnostic system can provide sufficient lead time to initiate corrective action and also to enable efficient scheduling of inspection, maintenance and repair activities. The major objective of this project was to convert and implement a number of advanced nonlinear diagnostic DSP algorithms in a format consistent with that required for integration into the Vanderbilt Multigraph Architecture (MGA) Model Based Programming environment. This effort will allow the real-time execution of these algorithms using the MSFC MPP Prototype System. ASRI has completed the software conversion and integration of a sequence of nonlinear signal analysis techniques specified in the SOW for real-time execution on MSFC's MPP Prototype. This report documents and summarizes the results of the contract tasks; provides the complete computer source code; including all FORTRAN/C Utilities; and all other utilities/supporting software libraries that are required for operation.

Jong, Jen-Yi↗

Statistical Analysis of CMC Constituent and Processing Data

Ceramic Matrix Composites (CMCs) are the next "big thing" in high-temperature structural materials. In the case of jet engines, it is widely believed that the metallic superalloys currently being utilized for hot structures (combustors, shrouds, turbine vanes and blades) are nearing their potential limits of improvement. In order to allow for increased turbine temperatures to increase engine efficiency, material scientists have begun looking toward advanced CMCs and SiC/SiC composites in particular. Ceramic composites provide greater strength-to-weight ratios at higher temperatures than metallic alloys, but at the same time require greater challenges in micro-structural optimization that in turn increases the cost of the material as well as increases the risk of variability in the material s thermo-structural behavior. to model various potential CMC engine materials and examines the current variability in these properties due to variability in component processing conditions and constituent materials; then, to see how processing and constituent variations effect key strength, stiffness, and thermal properties of the finished components. Basically, this means trying to model variations in the component s behavior by knowing what went into creating it. inter-phase and manufactured by chemical vapor infiltration (CVI) and melt infiltration (MI) were considered. Examinations of: (1) the percent constituents by volume, (2) the inter-phase thickness, (3) variations in the total porosity, and (4) variations in the chemical composition of the Sic fiber are carried out and modeled using various codes used here at NASA-Glenn (PCGina, NASALife, CEMCAN, etc...). The effects of these variations and the ranking of their respective influences on the various thermo-mechanical material properties are studied and compared to available test data. The properties of the materials as well as minor changes to geometry are then made to the computer model and the detrimental effects observed using statistical analysis software. The ultimate purpose of this study is to determine what variations in material processing can lead to the most critical changes in the materials property. The work I have taken part in this summer explores, in general, the key properties needed In this study SiC/SiC composites of varying architectures, utilizing a boron-nitride (BN)

Fornuff, Jonathan↗

A Comprehensive Characterization of Microorganisms and Allergens in Spacecraft Environment

The determination of risk from infectious disease during long-duration missions is composed of several factors including the concentration and the characteristics of the infectious agent. Thus, a thorough knowledge of the microorganisms aboard spacecraft is essential in mitigating infectious disease risk to the crew. While stringent steps are taken to minimize the transfer of potential pathogens to spacecraft, several medically significant organisms have been isolated from both the Mir and International Space Station (ISS). Historically, the method for isolation and identification of microorganisms from spacecraft environmental samples depended upon their growth on culture media. Unfortunately, only a fraction of the organisms may grow on a culture medium, potentially omitting those microorganisms whose nutritional and physical requirements for growth are not met. Thus, several pathogens may not have been detected, such as Legionella pneumophila, the etiological agent of Legionnaire s disease. We hypothesize that environmental analysis using non-culture-based technologies will reveal microorganisms, allergens, and microbial toxins not previously reported in spacecraft, allowing for a more complete health assessment. The development of techniques for this flight experiment, operationally named SWAB, has already provided advances in NASA laboratory processes and beneficial information toward human health risk assessment. The translation of 16S ribosomal DNA sequencing for the identification of bacteria from the SWAB experiment to nominal operations has increased bacterial speciation of environmental isolates from previous flights three fold compared to previous conventional methodology. The incorporation of molecular-based DNA fingerprinting using repetitive sequence-based polymerase chain reaction (rep-PCR) into the capabilities of the laboratory has provided a methodology to track microorganisms between crewmembers and their environment. Both 16S ribosomal DNA identification and bacterial fingerprinting have improved NASA s capability to better understand spacecraft environments and determine the source of contamination events. Preflight sampling has been completed for air, surface, and water samples. In-flight sample collection has been completed for a total of 8 air and surface sample collection sessions. In-flight hardware has performed well and the surface sampling device received positive feedback from the crew for its ease of use. While processing and analysis continue for these samples, early results have begun to provide information on the spacecraft environment. Using a method called Denaturing Gradient Gel Electrophoresis (DGGE), several air and samples were evaluated to determine the types of organisms that were present. Using only molecular techniques, DGGE does not depend on any microbial growth on culture media, allowing a more comprehensive assessment of the spacecraft interior. Preliminary results have identified several microorganisms that would not have been isolated using current technology, though none of these organisms would be considered medically significant. Interestingly, the isolation of Gram negative organisms is greater using DGGE than conventional media based isolation. The cause of this finding is unclear, though it may be the result of the technique s ability to isolate both viable and non-viable bacteria. The next phase of the SWAB sample analysis is the use of quantitative polymerase chain reaction (QPCR) to look for specific medically significant organisms. While not as broad as DGGE, QPCR is much more sensitive and may reveal findings that were not seen during the initial evaluation. Together, this information will lead toward an accurate microbial risk assessment to help set flight requirements to protect the safety, health, and performance of the crew.

Castro, V.A.↗

Rocketdyne PSAM: In-house enhancement/application

The development was initiated of the Probabilistic Design Analysis (PDA) Process for rocket engines. This will enable engineers a quantitative assessment of calculated reliability during the design process. The PDA will help choose better designs, make them more robust, and help decide on critical tests to help demonstrate key reliability issues to aid in improving the confidence of the engine capabilities. Rockedyne's involvement with the Composite Loads Spectra (CLS) and Probabilistic Structural Analysis Methodology (PSAM) contracts started this effort and are key elements in the on-going developments. Internal development efforts and hardware applications complement and extend the CLS and PSAM efforts. The completion of the CLS option work and the follow-on PSAM developments will also be integral parts of this methodology. A brief summary of these efforts is presented.

Newell, J. F.↗

Analysis of physical-chemical processes governing SSME internal fluid flows

In order to aid the development of current and future SSME type engines, it is necessary to improve the understanding of basic issues related with physical-chemical processes of SSME internal flows. Accomplishments under each of the following specific objectives are described herein: (1) supplying a state-of-the-art CFD code and graphics package; (2) demonstrating code usage on SSME-related problems to NASA MSFC personnel; and (3) performance computations and analysis of problems relevant to current and future SSME's.

Singhal, A. K.↗

The Prevalence of Precipitation from Polar Supercooled Clouds

Supercooled clouds substantially impact polar surface energy budgets but large-scale models often underestimate their occurrence, which motivates accurately establishing metrics of basic processes. An analysis of long-term measurements at Utqiaġvik, Alaska, and McMurdo Station, Antarctica, combines lidar-validated use of soundings to identify supercooled cloud layers and colocated ground-based profiling radar measurements to quantify cloud base precipitation. We find that more than 85 % (75 %) of sampled supercooled layers are precipitating over the Arctic (Antarctic) site, with more than 75 % (50 %) precipitating continuously to the surface. Such high frequencies can be reconciled with substantially lesser spaceborne estimates by considering differences in radar hydrometeor detection sensitivity. While ice precipitation into supercooled clouds from aloft is common, we also find that the great majority of supercooled cloud layers without ice falling into them are themselves continuously generating precipitation. Such sustained primary ice formation is consistent with continuous activation of immersion-mode ice nucleating particles (INPs), suggesting that supercooled cloud formation is a principal gateway to ice formation at temperatures greater than ~ −38 °C over polar regions. The prevalence of weak precipitation fluxes is also consistent with supercooled cloud longevity, and with well-observed and widely simulated case studies. An analysis of colocated microwave radiometer retrievals suggests that weak precipitation fluxes can be nonetheless consequential to moisture budgets for supercooled clouds owing to small liquid water paths. Finally, we suggest that these ground-based precipitation rate statistics offer valuable guidance for improving the representation of polar cloud processes in large-scale models.

Polar clouds↗

A Procedure for Structural Weight Estimation of Single Stage to Orbit Launch Vehicles (Interim User's Manual)

This is an interim user's manual for current procedures used in the Vehicle Analysis Branch at NASA Langley Research Center, Hampton, Virginia, for launch vehicle structural subsystem weight estimation based on finite element modeling and structural analysis. The process is intended to complement traditional methods of conceptual and early preliminary structural design such as the application of empirical weight estimation or application of classical engineering design equations and criteria on one dimensional "line" models. Functions of two commercially available software codes are coupled together. Vehicle modeling and analysis are done using SDRC/I-DEAS, and structural sizing is performed with the Collier Research Corp. HyperSizer program.

Martinovic, Zoran N.↗

Multispectral Photography

Model II Multispectral Camera is an advanced aerial camera that provides optimum enhancement of a scene by recording spectral signatures of ground objects only in narrow, preselected bands of the electromagnetic spectrum. Its photos have applications in such areas as agriculture, forestry, water pollution investigations, soil analysis, geologic exploration, water depth studies and camouflage detection. The target scene is simultaneously photographed in four separate spectral bands. Using a multispectral viewer, such as their Model 75 Spectral Data creates a color image from the black and white positives taken by the camera. With this optical image analysis unit, all four bands are superimposed in accurate registration and illuminated with combinations of blue green, red, and white light. Best color combination for displaying the target object is selected and printed. Spectral Data Corporation produces several types of remote sensing equipment and also provides aerial survey, image processing and analysis and number of other remote sensing services.

Source record↗

A Preliminary Analysis of Precipitation Properties and Processes during NASA GPM IFloodS

The Iowa Flood Studies (IFloodS) is a NASA Global Precipitation Measurement (GPM) ground measurement campaign, which took place in eastern Iowa from May 1 to June 15, 2013. The goals of the field campaign were to collect detailed measurements of surface precipitation using ground instruments and advanced weather radars while simultaneously collecting data from satellites passing overhead. Data collected by the radars and other ground instruments, such as disdrometers and rain gauges, will be used to characterize precipitation properties throughout the vertical column, including the precipitation type (e.g., rain, graupel, hail, aggregates, ice crystals), precipitation amounts (e.g., rain rate), and the size and shape of raindrops. The impact of physical processes, such as aggregation, melting, breakup and coalescence on the measured liquid and ice precipitation properties will be investigated. These ground observations will ultimately be used to improve rainfall estimates from satellites and in particular the algorithms that interpret raw data for the upcoming GPM mission's Core Observatory satellite, which launches in 2014. The various precipitation data collected will eventually be used as input to flood forecasting models in an effort to improve capabilities and test the utility and limitations of satellite precipitation data for flood forecasting. In this preliminary study, the focus will be on analysis of NASA NPOL (S‐band, polarimetric) radar (e.g., radar reflectivity, differential reflectivity, differential phase, correlation coefficient) and NASA 2D Video Disdrometers (2DVDs) measurements. Quality control and processing of the radar and disdrometer data sets will be outlined. In analyzing preliminary cases, particular emphasis will be placed on 1) documenting the evolution of the rain drop size distribution (DSD) as a function of column melting processes and 2) assessing the impact of range on ground‐based polarimetric radar estimates of DSD properties.

Carey, Lawrence↗

Developing a Logistics Data Process for Support Equipment for NASA Ground Operations

The United States NASA Space Shuttle has long been considered an extremely capable yet relatively expensive rocket. A great part of the roughly US $500 million per launch expense was the support footprint: refurbishment and maintenance of the space shuttle system, together with the long list of resources required to support it, including personnel, tools, facilities, transport and support equipment. NASA determined to make its next rocket system with a smaller logistics footprint, and thereby more cost-effective and quicker turnaround. The logical solution was to adopt a standard Logistics Support Analysis (LSA) process based on GEIA-STD-0007 http://www.logisticsengineers.org/may09pres/GEIASTD0007DEXShortIntro.pdf which is the successor of MIL-STD-1388-2B widely used by U.S., NATO, and other world military services and industries. This approach is unprecedented at NASA: it is the first time a major program of programs, Project Constellation, is factoring logistics and supportability into design at many levels. This paper will focus on one of those levels NASA ground support equipment for the next generation of NASA rockets and on building a Logistics Support Analysis Record (LSAR) for developing and documenting a support solution and inventory of resources for. This LSAR is actually a standards-based database, containing analyses of the time and tools, personnel, facilities and support equipment required to assemble and integrate the stages and umbilicals of a rocket. This paper will cover building this database from scratch: including creating and importing a hierarchical bill of materials (BOM) from legacy data; identifying line-replaceable units (LRUs) of a given piece of equipment; analyzing reliability and maintainability of said LRUs; and therefore making an assessment back to design whether the support solution for a piece of equipment is too much work, i.e., too resource-intensive. If one must replace or inspect an LRU too much, perhaps a modification of the design of the equipment can make such operational effort unnecessary. Finally, this paper addresses processes of tying resources to a timeline of tasks performed in ground operations: this enables various overarching analyses, e.g., a summarization of all resources used for a given piece of equipment. Quality Control of data will also be discussed: importing and exporting data from product teams, including spreadsheets-todatabase or data exchange between databases.

Chakrabarti, Suman↗

The Severe Storms Observation Satellite /SSOS/

The objective of the Severe Storms Observation Satellite (SSOS) is to continuously observe meteorological phenomena from geosynchronous altitude and to acquire data whose analysis will lead to a better understanding, early detection, and prediction of severe storms and other significant mesoscale events such as dust storms. Details are discussed as to the Advanced Atmospheric Sounding and Imaging Radiometer designed for SSOS, the use of a special spacecraft for an R&D mission, data acquisition, and data processing and analysis. The required accurate vertical temperature and moisture profiles as well as high temporal and spatial resolution images can best be obtained by a three-axis stabilized system, which offers approximately an order of magnitude sensing improvement over a comparable spinning system due to its capability to continuously view the earth. A block diagram of the severe storm analysis system is included.

Shenk, W. E.↗

Assisted Authoring of Model-Based Systems Engineering Documents

In systems engineering practices system design and analysis have historically been performed using a document-centric approach where stakeholders produce a number of documents that represent their views on a system under development. Given the ad-hoc, disparate, and informal nature of natural language documents, these views become quickly inconsistent. Rigor in engineering work is also lost in the transition from model based engineering design and analysis to engineering documents. Once the documents are delivered, the engineering portion of the work is disconnected. In the Open Model Based Engineering Environment (OpenMBEE), Cross-References (aka transclusions) synthesize data for engineering when the information is not simply hyperlinked, but referenced in place in a document, upgrading a document-based process with model-based engineering technology. Those Cross-References are nowadays partially created manually, putting a burden on the engineer who is authoring the document.This paper presents an approach which can assist the engineer by providing machine-generated suggestions for Cross-References using language processing, graph analysis, and clustering technologies on model data managed by the OpenMBEE infrastructure.

Gomes, Ivan↗