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At least 757 records · Page 42

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Benchmark Problem Development for Testing Maturity of Intelligent Contingency Management Tools

This paper presents a process used to develop appropriate scenarios and metrics for evaluating the maturity of intelligent contingency management algorithms. A benchmark scenario is a reference point against which something can be measured, compared, or assessed. Creating an accurate benchmark requires considerable research and expertise. The scenario itself is an artificial representation of a real-world event, designed to achieve a set of learning objectives through experiential learning. Designing an effective benchmark simulation scenario requires careful planning, including identification of clear objectives; capability assessment of the algorithm/tool being evaluated; assessment of necessary levels of fidelity; development of a process flow map of events and event interactions; and identification of metrics that map back to objectives. Thus, a benchmark scenarios for contingency management might consist of one or several commonly used functions taken from real world applications, used for evaluation, characterization and performance measurement of a contingency management algorithm. Behavior of the contingency management algorithm under different environmental conditions should then be able to be predicted using a set of benchmark functions. The paper describes the resulting benchmark problem as an illustration of the application of this process.

Jon Holbrook↗

NASA NTRS2005

Characterization of Polymer-Coated MEMS Humidity Sensors for Flight Applications

Under NASA's Aviation Safety Program (AvSP), in addition to wind velocity and temperature, water vapor is considered one key factor in determining aviation weather, which is a substantial contributor to many general aviation (GA) accidents. The conventional and reliable humidity measuring methods such as radiation reflection or absorption have relatively high cost in addition to highly specialized operating and maintenance characteristics. This paper presents characterizations of inexpensive MEMS and capacitance type humidity sensors for their potential use on aircraft. If installed, these sensors are subjected to ambient environmental conditions as well as to different chemicals and deicing fluids used on aircraft. This paper reports the effect of different deicing fluids and chemicals on these inexpensive humidity sensors.

Shams, Qamar A.↗

DOE OSTI2016

Synthesis and characterization of magnesium doped cerium oxide for the fuel cell application

Cerium oxide has attained much attentions in global nanotechnology market due to valuable application for catalytic, fuel additive, and widely as electrolyte in solid oxide fuel cell. Doped cerium oxide has large oxygen vacancies that allow for greater reactivity and faster ion transport. These properties make cerium oxide suitable material for SOFCs application. Cerium oxide electrolyte requires lower operation temperature which shows improvement in processing and the fabrication technique. In our work, we synthesized magnesium doped cerium oxide by the co-precipitation method. With the magnesium doping catalytic reactivity of CeO{sub 2} was increased. Synthesized nanoparticle were characterized by the XRD and UV absorption techniques.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Unsupervised machine learning based on non-negative tensor factorization for analyzing reactive-mixing

Analysis of reactive-diffusion simulations representing complex mixing processes requires a large number of independent model runs. For each high-fidelity model simulation, the model inputs are varied and the predicted mixing behavior is represented by temporal and spatial changes in species concentration. It is then required to discern how the model inputs (such as diffusivity, dispersion, anisotropy, and velocity field properties) impact the mixing process. This task is challenging and typically involves interpretation of large model outputs representing temporal and spatial changes of species concentration within the model domain. Yet, the task can be automated and substantially simplified by applying Machine Learning (ML) methods. Here, we present an application of an unsupervised ML method (called NTF k ) using Non-negative Tensor Factorization (NTF) coupled with a custom clustering procedure based on k-means to reveal the temporal and spatial features in product concentrations. An attractive and unique aspect of the proposed ML method is that it ensures the extracted features are non-negative, which is important to obtain a meaningful deconstruction of the mixing processes. The ML methodology is applied to a large set of high-resolution finite-element model simulations representing anisotropic reaction-diffusion processes in perturbed vortex-based velocity fields. The applied finite-element method ensures that spatial and temporal species concentration are always non-negative, even in the case of high anisotropic contrasts. The simulated reaction is a fast irreversible bimolecular reaction A+B→C , where species A and B react to form species C. The reactive-diffusion model input parameters that control mixing include properties of the velocity field (such as vortex structures), anisotropic dispersion, and molecular diffusion. We demonstrate the applicability of the ML feature extraction method to produce a meaningful deconstruction of model outputs to discriminate between different physical processes impacting the reactants, their mixing, and the spatial distribution of the product C. The introduced ML analysis allowed us to identify additive temporal and spatial features that characterize mixing behavior. The application of the proposed NTF k approach is not limited to reactive-mixing. NTFk can be readily applied to any observed or simulated datasets that can be represented as tensors (multi-dimensional arrays) and have separable latent signatures or features.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Dispersed SiC nanoparticles in Ni observed by ultra-small-angle X-ray scattering

In this paper, a metal-ceramic composite, nickel reinforced with SiC nanoparticles, was synthesized and characterized for its potential application in next-generation molten salt nuclear reactors. Synchrotron ultra-small-angle X-ray scattering (USAXS) measurements were conducted on the composite. The size distribution and number density of the SiC nanoparticles in the material were obtained through data modelling. Scanning and transmission electron microscopy characterization were performed to substantiate the results of the USAXS measurements. Tensile tests were performed on the samples to measure the change in their yield strength after doping with the nanoparticles. Finally, the average interparticle distance was calculated from the USAXS results and is related to the increased yield strength of the composite.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Non-contact Thermophysical Characterization of Solids and Fluids for Gen3 Concentrating Solar Power

In this project, we aim to develop Modulation Photothermal Radiometry (MPR), which is an attractive non-contact tool to evaluate thermophysical properties of high-temperature solids and HTFs that are otherwise time-consuming and difficult to measure and for in-situ testing of these properties. Therefore, the main objective of the project is the development and application of MPR to characterize high temperature thermophysical properties of heat transfer fluids (HTFs) and the solids (tubing and solar absorbing coating) in various components and sub-systems used in CSP plants. The measurements will be first demonstrated on a wide range of materials at UCSD and then the tool will be transferred to other facilities within the Gen3 CSP portfolio.

14 SOLAR ENERGY↗

DOE OSTI2019

Nanowires for Electrochemical Energy Storage

Nanomaterials provide many desirable properties for electrochemicalenergy storage devices due to their nanoscale size effect, which could be significantlydifferent from bulk or micron-sized materials. Particularly, confined dimensions playimportant roles in determining the properties of nanomaterials, such as the kinetics ofion diffusion, the magnitude of strain/stress, and the utilization of active materials.Nanowires, as one of the representative one-dimensional nanomaterials, have greatcapability for realizing a variety of applications in thefields of energy storage since theycould maintain electron transport along the long axis and have a confinement effectacross the diameter. In this review, we give a systematic overview of the state-of-the-artresearch progress on nanowires for electrochemical energy storage, from rational designand synthesis,in situstructural characterizations, to several important applications inenergy storage including lithium-ion batteries, lithium-sulfur batteries, sodium-ionbatteries, and supercapacitors. The problems and limitations in electrochemical energystorage and the advantages in utilizing nanowires to address the issues and improve thedevice performance are pointed out. At the end, we also discuss the challenges and demonstrate the prospective for the futuredevelopment of advanced nanowire-based energy storage devices.

25 ENERGY STORAGE↗

NASA NTRS2004

Photogrammetry and Videogrammetry Methods for Solar Sails and Other Gossamer Structures

Ultra-lightweight and inflatable gossamer space structures are designed to be tightly packaged for launch, then deploy or inflate once in space. These properties will allow for in-space construction of very large structures 10 to 1000 meters in size such as solar sails, inflatable antennae, and space solar power stations using a single launch. Solar sails are of particular interest because of their potential for propellantless propulsion. Gossamer structures do, however, have significant complications. Their low mass and high flexibility make them very difficult to test on the ground. The added mass and stiffness of attached measurement devices can significantly alter the static and dynamic properties of the structure. This complication necessitates an alternative approach for characterization. This paper discusses the development and application of photogrammetry and videogrammetry methods for the static and dynamic characterization of gossamer structures, as four specific solar sail applications demonstrate. The applications prove that high-resolution, full-field, non-contact static measurements of solar sails using dot projection photogrammetry are possible as well as full-field, noncontact, dynamic characterization using dot projection videogrammetry.

Black, Jonathan T.↗

NASA NTRS2005

Preparation and Analysis of Platinum Thin Films for High Temperature Sensor Applications

A study has been made of platinum thin films for application as high temperature resistive sensors. To support NASA Glenn Research Center s high temperature thin film sensor effort, a magnetron sputtering system was installed recently in the GRC Microsystems Fabrication Clean Room Facility. Several samples of platinum films were prepared using various system parameters to establish run conditions. These films were characterized with the intended application of being used as resistive sensing elements, either for temperature or strain measurement. The resistances of several patterned sensors were monitored to document the effect of changes in parameters of deposition and annealing. The parameters were optimized for uniformity and intrinsic strain. The evaporation of platinum via oxidation during annealing over 900 C was documented, and a model for the process developed. The film adhesion was explored on films annealed to 1000 C with various bondcoats on fused quartz and alumina. From this compiled data, a list of optimal parameters and characteristics determined for patterned platinum thin films is given.

Wrbanek, John D.↗

DOE OSTI2025

Machine learning for fundamental spectroscopic and thermodynamic data of actinides and lanthanides

Accurately modeling optical spectra with absolute radiometric intensities is vital for nuclear forensics applications that depend on characterizing optical emissions from energetic nuclear phenomena. This requires precise knowledge of the individual atomic transition probabilities, known as Einstein A-coefficients, for each emission line. Obtaining these values theoretically or experimentally is often impractical due to the complex electronic structures and the number of transitions involved in atoms relevant to nuclear applications. In this study, we explore the use of machine learning to predict the Einstein A coefficients for atomic transitions. Seven models were evaluated that ranged from deep learning to decision tree algorithms, and found that gradient boosting performed best, specifically the Extreme Gradient Boosting (XGB) architecture, achieving a precision of 86% across transitions of 36 elements. Furthermore, the model was cross-validated using published transition probabilities reported in the literature and applied to estimate Pu plasma temperatures from a previous experiment conducted at Savannah River National Laboratory.

Atomic spectroscopy↗

DOE OSTI2016

Calibration of photoelastic modulator based dichrometers: maintaining constant phase across the spectrum

Photoelastic modulators can alter the polarization state of a beam of ultraviolet, visible or infrared photons by means of periodic stress-induced differences in the refractive index of a transparent material that forms the optical element of the device and is isotropic in the absence of stress. Furthermore, they have found widespread application in instruments that characterize or alter the polarization state of a beam in fields as diverse as astronomy, structural biology, materials science and ultraviolet lithography for the manufacture of nano-scale integrated circuits. Measurement of circular dichroism, the differential absorption of left- and right circularly polarized light, and of strain-induced birefringence of optical components are major applications. Instruments using synchrotron radiation and photoelastic modulators with CaF 2 optical elements have extended circular dichroism measurements down to wavelengths of about 130 nm in the vacuum ultraviolet. Maintaining a constant phase shift between two orthogonal polarization states across a spectrum requires that the amplitude of the modulated stress be changed as a function of wavelength. For commercially available photoelastic modulators, the voltage that controls the amplitude of modulation required to produce a specified phase shift, which is a surrogate for the stress modulation amplitude, has been shown to be an approximately linear function of wavelength in the spectral region where the optical element is transparent. But, extrapolations of such straight lines cross zero voltage at a non-zero wavelength, not at zero-wavelength. For modulators with calcium fluoride and fused silica optical elements, the zero-crossing wavelength is always in the spectral region where the optical element of the modulator strongly absorbs the incident radiation, and at a wavelength less than the longest-wavelength apparent resonance deduced from experimental values of the refractive index fit to the Sellmeier equation. Using a model that relates the refractive indices of a stressed optical element to the refractive index of its unstressed state, an expression for the modulator control voltage was derived that closely fits the experimental data. Our result provides a theoretical rational for the apparently linear constant-phase programming voltage, and thus provides theoretical backing for the calibration procedure frequently used for these modulators. Lastly there are other factors that can influence the calibration of a photoelastic modulator, including temperature and atmospheric pressure, are discussed briefly.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2019

Exobiology Through the Lens of Constraint-Based Metabolic Modeling

A focus of many astrobiology questions resides on the interplay between biochemistry and geochemistry. This biotic-abiotic interface is intimately connected to habitability. Computational systems biology provides a paradigm to characterize this interface. Here we describe the application of constraint-based metabolic modeling to characterize photosynthetic microorganisms inhabiting a modern analog to the Earth’s primordial ocean. Biochemistry is captured in a metabolic network that is converted to a mathematical model. Geochemistry results in constraints that limit the capabilities of the metabolic network. The combination of the two within a single framework can elucidate the co-evolution of life and the environment.

Broddrick, Jared T.↗

NASA NTRS2006

Chemical, Physical, and Mechanical Characterization of Isocyanate Cross-linked Amine-Modified Silica Aerogels

We describe a new mechanically strong lightweight porous composite material obtained by encapsulating the skeletal framework of amine-modified silica aerogels with polyurea. The conformal polymer coating preserves the mesoporous structure of the underlying silica framework and the thermal conductivity remains low at 0.041 plus or minus 0.001 W m(sup -1 K(sup -1). The potential of the new cross-linked silica aerogels for load-carrying applications was determined through characterization of their mechanical behavior under compression, three-point bending, and dynamic mechanical analysis (DMA). A primary glass transition temperature of 130 C was identified through DMA. At room temperature, results indicate a hyperfoam behavior where in compression cross-linked aerogels are linearly elastic under small strains (less than 4%) and then exhibit yield behavior (until 40% strain), followed by densification and inelastic hardening. At room temperature the compressive Young's modulus and the Poisson's ratio were determined to be 129 plus or minus 8 MPa and 0.18, respectively, while the strain at ultimate failure is 77% and the average specific compressive stress at ultimate failure is 3.89 x 10(exp 5) N m kg(sup -1). The specific flexural strength is 2.16 x 10(exp 4) N m kg(sup -1). Effects on the compressive behavior of strain rate and low temperature were also evaluated.

Katti, Atul↗

DOE OSTI2021

A multiplexed nanostructure-initiator mass spectrometry (NIMS) assay for simultaneously detecting glycosyl hydrolase and lignin modifying enzyme activities

Lignocellulosic biomass is composed of three major biopolymers: cellulose, hemicellulose and lignin. Analytical tools capable of quickly detecting both glycan and lignin deconstruction are needed to support the development and characterization of efficient enzymes/enzyme cocktails. Previously we have described nanostructure-initiator mass spectrometry-based assays for the analysis of glycosyl hydrolase and most recently an assay for lignin modifying enzymes. Here we integrate these two assays into a single multiplexed assay against both classes of enzymes and use it to characterize crude commercial enzyme mixtures. Application of our multiplexed platform based on nanostructure-initiator mass spectrometry enabled us to characterize crude mixtures of laccase enzymes from fungi Agaricus bisporus (Ab) and Myceliopthora thermophila (Mt) revealing activity on both carbohydrate and aromatic substrates. Using time-series analysis we determined that crude laccase from Ab has the higher GH activity and that laccase from Mt has the higher activity against our lignin model compound. Inhibitor studies showed a significant reduction in Mt GH activity under low oxygen conditions and increased activities in the presence of vanillin (common GH inhibitor). Ultimately, this assay can help to discover mixtures of enzymes that could be incorporated into biomass pretreatments to deconstruct diverse components of lignocellulosic biomass.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Weighted inequalities for quasilinear integral operators on the semi-axis and applications to Lorentz spaces

A precise characterization of inequalities in weighted Lebesgue spaces with positive quasilinear integral operators of iterative type on the half-axis is given. All cases of positive integration parameters are treated, including the case of supremum. Applications to the solution of the well-known problem of the boundedness of the Hardy-Littlewood maximal operator in weighted Lorentz Γ-spaces are given. Bibliography: 41 titles.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1982

Study to perform preliminary experiments to evaluate particle generation and characterization techniques for zero-gravity cloud physics experiments

Methods of particle generation and characterization with regard to their applicability for experiments requiring cloud condensation nuclei (CCN) of specified properties were investigated. Since aerosol characterization is a prerequisite to assessing performance of particle generation equipment, techniques for characterizing aerosol were evaluated. Aerosol generation is discussed, and atomizer and photolytic generators including preparation of hydrosols (used with atomizers) and the evaluation of a flight version of an atomizer are studied.

Katz, U.↗

DOE OSTI2025

What to Support When You’re Compressing

Over the last nearly 20 years, lossy compression has become an essential aspect of HPC applications’ data pipelines, allowing them to overcome limitations in storage capacity and bandwidth and, in some cases, increase computational throughput and capacity. However, with the adoption of lossy compression comes the requirement to assess and control the impact lossy compression has on scientific outcomes. In this work, we take a major step forward in describing the state of practice and by characterizing workloads. We examine applications’ needs and compressors’ capabilities across 9 different supercomputing application domains. We present 24 takeaways that provide best practices for applications, operational impacts for facilities achieving compressed data, and gaps in application needs not addressed by production compressors that point towards opportunities for future compression research.

Error-Bounded Lossy Compression↗

NASA NTRS1997

Microgravity Environment Characterization Program

The Microgravity Science and Applications Division (MSAD), a division within NASA's Office of Life and Microgravity Science and Applications, sponsors a broad range of space-based research in biotechnology, combustion science, fluid physics, fundamental physics, and materials science. To better understand and exploit the orbital environment, MSAD has developed methods and hardware to characterize accelerations on microgravity experiment carriers. MSAD supports research to verify analytically derived acceleration requirements for experiments and provides vibration isolation for sensitive experiments. The Microgravity Measurement and Analysis Project (MMAP), supported by MSAD, incorporates four projects: the Space Acceleration Measurement System (SAMS), the Orbital Acceleration Research Experiment (OARE), the SAMS for International Space Station (SAMS-II), and the Principal Investigator Microgravity Services (PIMS). SAMS was developed to record microgravity accelerations and the OARE was developed to record very low-frequency microgravity accelerations on-board the NASA Orbiters. The SAMS is also used for cooperative investigations on the Russian Mir space station. The SAMS-II is being developed for the same function on-board the International Space Station (ISS). PIMS utilizes microgravity acceleration data to develop a description of each microgravity mission's acceleration environment and to support microgravity investigators in interpreting possible effects of the acceleration environment on their experiments. These elements of the MSAD program will be used to define acceleration requirements for future Orbiter and ISS payloads. This paper describes the MMAP and summarizes the products and services available to principal investigators and other users. This paper also presents some microgravity acceleration characterization results from the last six years of Orbiter microgravity missions.

DeLombard, Richard↗