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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Microstructural Study of Micron-Sized Craters Simulating Stardust Impacts in Aluminum 1100 Targets

Various microscopic techniques were used to characterize experimental micro- craters in aluminium foils to prepare for the comprehensive analysis of the cometary and interstellar particle impacts in aluminium foils to be returned by the Stardust mission. First, SEM (Scanning Electron Microscopy) and EDS (Energy Dispersive X-ray Spectroscopy) were used to study the morphology of the impact craters and the bulk composition of the residues left by soda-lime glass impactors. A more detailed structural and compositional study of impactor remnants was then performed using TEM (Transmission Electron Microscopy), EDS, and electron diffraction methods. The TEM samples were prepared by Focused Ion Beam (FIB) methods. This technique proved to be especially valuable in studying impact crater residues and impact crater morphology. Finally, we also showed that InfraRed microscopy (IR) can be a quick and reliable tool for such investigations. The combination of all of these tools enables a complete microscopic characterization of the craters.

Leroux, Hugues↗
NASA NTRS2021

Sample Return Container Opening Process Concept for Potential Mars Sample Return

Proposed Mars Sample Return (MSR) missions would require a pristine and secure opening method to ensure sample Contamination Control and backward Planetary Protection. In order to reach the samples, a series of five containers would need to be opened inside of a Mars Returned Sample Handling (MRSH) facility. The process would include opening the Containment Assurance Module (CAM) aboard the Earth Entry Vehicle (EEV), the Secondary Containment Vessel (SCV), Primary Containment Vessel (PCV), and the Orbiting Sample (OS) container, and finally removing and opening the Returned Sample Tube Assemblies (RSTA). Some of these containers can be opened by reversing the mechanical assembly process while others would require destructive means. Several containers are still in a conceptual design phase while others are en route to Mars aboard the M2020 rover. In order to inform the design of the containers that are still in the conceptual stages, a study was performed at each level of the containment assembly. The studies were used to determine the least destructive and most robust methods to disassemble and open the containers while minimizing risk to the samples or the personnel. In addition to the envisioned disassembly and breaching method, contingency plans were made for completing the disassembly if damage to the vehicle and containment system occurred.

Liu, Yang↗
NASA NTRS2002

Comparative Results of Using Different Methods for Discovery of Microorganisms in very Ancient Layers of the Central Antarctic Glacier above the Lake Vostok

The ice sheet of the Central Antarctic is considered by the scientific community worldwide, as a model to elaborate on different methods to search for life outside Earth. This became especially significant in connection with the discovery of the underglacial lake in the vicinity of the Russian Antarctic Station Vostok. Lake Vostok is considered by many scientists as an analog of the ice covered seas of Jupiter's satellite Europa. According to the opinion of many researchers there is the possibility that relict forms of microorganisms, well preserved since the Ice Age, may be present in this lake. Investigations throughout the thickness of the ice sheet above Lake Vostok show the presence of microorganisms belonging to different well-known taxonomic groups, even in the very ancient horizons near close to floor of the glacier. Different methods were used to search for microorganisms that are rarely found in the deep ancient layers of an ice sheet. The method of aseptic sampling from the ice cores and the results of controlled sterile conditions in all stages when conducting these investigations, are described in detail in previous reports. Primary investigations tried the usual methods of sowing samples onto different nutrient media, and the result was that only a few microorganisms grew on the media used. The possibility of isolating the organisms obtained for further investigations, by using modern methods including DNA-analysis, appears to be the preferred method. Further investigations of the very ancient layers of the ice sheet by radioisotopic, luminescence, and scanning electron microscopy methods at different modifications, revealed the quantity and morphological diversity of the cells of microorganisms that were distributed on the different horizons. Investigations over many years have shown that the microflora in the very ancient strata of the Antarctic ice cover, nearest to the bedrock, support the effectiveness of using a combination of different methods to search for signs of life in ancient icy formations, which might play a role in the long-term preservation and transportation of microbial life throughout the Universe.

Abyzov, S. S.↗
DOE OSTI2021

A new long-term sampling approach to viruses on surfaces

The importance of virus disease outbreaks and its prevention is of growing public concern but our understanding of virus transmission routes is limited by adequate sampling strategies. While conventional swabbing methods provide merely a microbial snapshot, an ideal sampling strategy would allow reliable collection of viral genomic data over longer time periods. This study has evaluated a new, paper-based sticker approach for collection of reliable viral genomic data over longer time periods up to 14 days and after implementation of different hygiene measures. In contrast to swabbing methods, which sample viral load present on a surface at a given time, the paper-based stickers are attached to the surface area of interest and collect viruses that would have otherwise been transferred onto that surface. The major advantage of one-side adhesive stickers is that they are permanently attachable to a variety of surfaces. Initial results demonstrate that stickers permit stable recovery characteristics, even at low virus titers. Stickers also allow reliable virus detection after implementation of routine hygiene measures and over longer periods up to 14 days. Overall, results for this new sticker approach for virus genomic data collection are encouraging, but further studies are required to confirm anticipated benefits over a range of virus types.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1987

A Modal-Parameter Extraction Procedure

Procedure accommodates multiple input excitations. Improved modalparameter extraction procedure applicable to linear, time-invariant systems derived in 92-page report. Algorithm allows multiple noncoherent input excitations applied to structure and generates consistent set of modal parameters. Procedure extension of simultaneous frequency-domain (SFD) techniques achieved through investigation of two automatic methods for reducing effective problem size while minimizing amount of user interaction. In several sample runs, independentcoordinate reduction method shown more accurate method for small sample size. Principle-component method used to estimate number of modes active in given frequency range.

Kurdila, A. H.↗
DOE OSTI2020

Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis: Version 6.12 Theory Manual

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis: Version 6.12 User's Manual

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis (V.6.14) (Theory Manual)

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis (V.6.14) (User's Manual)

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a users manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.13 Theory Manual

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.13 User's Manual

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user’s manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.15 User's Manual

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Theory Manual (V.6.15)

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis (V.6.16 User's Manual)

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.16 Theory Manual

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of Dakota’s iterative analysis capabilities.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

The role of time and speed in NASA's SUNLITE program

The SUNLITE program of NASA's LaRC aims to demonstrate lower noise and better frequency stability for continuous-wave (CW) solid-state lasers in the microgravity environment of space. The program will utilize laser-diode-pumped nonplanar-ring oscillators regulated by ultra-stable high-finesse Fabry-Perot Spectrometers to produce light beams with phase rate or frequency variations as low as 3 Hz. SUNLITE will use the period-method (P-method) to measure the phase rate and frequency stability of the lasers. The P-method was chosen because it requires less memory space for the raw data, because frequencies can be analyzed on-line in real-time simply by reciprocating the periods (fi = 1/pi), and because the mean and variance of the frequencies can be calculated as fast or faster than they can be with the fastest fast Fourier transformations. Furthermore, for a given signal-to-noise power ratio, the P-method requires less data and less computer time to extract the noise components. Although the P-method does require fast Time Interval Counters, the Fourier transformation method requires comparably fast Sampling Volt meters. For either method, however, time and computer speed play a critical role.

Hafele, Joseph C.↗
DOE OSTI2020

Global analysis peak fitting for chemical spectroscopy data

The present invention relates to methods for analyzing a chemical sample. For instance, the methods herein allow for global analysis of spectroscopy data in order to extract useful chemical properties from complicated multidimensional data. Such analysis can optionally employ data compression to further expedite computer-implemented computation. In particular, the methods herein provide global analysis of data matrices explained by both linear and non-linear terms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1976

Several methods for concentrating bacteria in fluid samples

The sensitivities of the firefly luciferase - ATP flow system and luminol flow system were established as 300,000 E. coli per milliliter and 10,000 E. coli per milliliter respectively. To achieve the detection limit of 1,000 bacteria per milliliter previously established, a method of concentrating microorganisms using a sartorius membrane filter system is investigated. Catalase in 50% ethanol is found to be a stable luminol standard and can be used up to 24 hours with only a 10% loss of activity. The luminol reagent is also stable over a 24 hour period. A method of preparing relatively inexpensive luciferase from desiccated firefly tails is developed.

Thomas, R. R.↗