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At least 271 records · Page 15

Geometric conditions for saturating the data processing inequality

Abstract The data processing inequality (DPI) is a scalar inequality satisfied by distinguishability measures on density matrices. For some distinguishability measures, saturation of the scalar DPI implies an operator equation relating the arguments of the measure. These results are typically derived using functional analytic techniques. In a complementary approach, we use geometric techniques to derive a formula that gives an operator equation from DPI saturation for any distinguishability measure; moreover, for a broad class of distinguishability measures, the derived operator equation is sufficient to imply saturation as well. Our operator equation coincides with known results for the sandwiched Rényi relative entropies, and gives new results for α - z Rényi relative entropies and a family of of quantum f -divergences, which we compute explicitly.

Physics↗

On the prediction of critical flutter conditions from subcritical response data and some related wind-tunnel experience

Methods of interpreting response measurements which could be amenable to flight flutter testing procedures were studied analytically and in the wind tunnel. One suggested scheme, which requires evaluation, is an iterative technique in which derivatives obtained from subcritical response data are used to indicate the approach to flutter. A simplification of this procedure was considered by examining the manner in which a single characteristic of the subcritical response behaves in relation to variations of the density or dynamic pressure in the approach to flutter. The use of this single parameter scheme was examined for random excitation as well as for sinusoidal forcing. The feasibility of the method is illustrated by several examples and the relative merits of random and sinusoidal excitation are discussed.

Houbolt, J. C.↗

Radar remote sensing for crop classification and canopy condition assessment: Ground-data documentation

A vegetation and soil-moisture experiment was conducted in order to examine the microwave emission and backscattering from vegetation canopies and soils. The data-acquisition methodology used in conjunction with the mobile radar scatterometer (MRS) systems is described and associated ground-truth data are documented. Test fields were located in the Kansas River floodplain north of Lawrence, Kansas. Ten fields each of wheat, corn, and soybeans were monitored over the greater part of their growing seasons. The tabulated data summarize measurements made by the sensor systems and represent target characteristics. Target parameters describing the vegetation and soil characteristics include plant moisture, density, height, and growth stage, as well as soil moisture and soil-bulk density. Complete listings of pertinent crop-canopy and soil measurements are given.

Ulaby, F. T.↗

Design of test specimens and procedures for generating material properties of Douglas fir/epoxy laminated wood composite material: With the generation of baseline data at two environmental conditions

In support of the design of wind turbine generator airfoils/blades utilizing Douglas Fir/West System Epoxy laminated composite material, a program was undertaken to define pertinent material properties utilizing small scale test specimens. Task 1 was the development of suitable monotonic tension, compression, short beam shear and full reversed cyclic specimen designs and the companion grips and testing procedures. Task 2 was the generation of the material properties at two environmental conditions utilizing the specimens and procedures developed in Task 1. The monotonic specimens and procedures generated results which compare favorably with other investigators while the cyclic results appear somewhat conservative. Adding moisture and heat or scarf joints degraded the monotonic performance but had a more nebulus effect with cyclic loading.

Johnson, Paul E.↗

The reduction of airplane flight test data to standard atmosphere conditions

This report was prepared for the National Advisory Committee for Aeronautics in order to supply the need of practical methods of reducing observed performance to standard conditions with a minimum of labor. The first part gives a very simple approximate method of reducing performance in climb, and is particularly adapted to work not requiring extreme accuracy. The second part gives a somewhat more elaborate and more accurate method which is well suited to general flight test reduction. The third part gives the conventional method of calibrating air-speed indicators and reducing the indicated speeds to true air speeds. An appendix gives working tables and charts for the standard atmosphere. (author)

Diehl, Walter S↗

Protecting Astronaut Medical Privacy: Review of Presentations and Publications for Attributability

Retrospective research and medical data collected on astronauts can be a valuable resource for researchers. This data can be requested from two separate NASA Archives. The Lifetime Surveillance of Astronaut Health (LSAH) holds astronaut medical data, and the Life Sciences Data Archive (LSDA) holds research data. One condition of use of astronaut research and medical data is the requirement that all abstracts, publications and presentations using this data must be reviewed for attributability. All final versions of abstracts, presentations, posters, and manuscripts must be reviewed by LSDA/LSAH prior to submission to a conference, journal, or other entities outside the Principal Investigator (PI) laboratory [including the NASA Export Control Document Availability Authorization (DAA) system]. If material undergoes multiple revisions (e.g., journal editor comments), the new versions must also be reviewed by LSDA/LSAH prior to re-submission to the journal. The purpose of this review is to ensure that no personally identifiable information (PII) is included in materials that are presented in a public venue or posted to the public domain. The procedures for submitting materials for review will be outlined. The process that LSAH/LSDA follows for assessing attributability will be presented. Characteristics and parameter combinations that often prompt attributability concerns will be identified. A published case report for a National Football League (NFL) player will be used to demonstrate how, in a population of public interest, a combination of information can result in inadvertent release of private or sensitive information.

Wear, M. L.↗

Development of physics-consistent conditional diffusion model to overcome data scarcity in critical heat flux

Deep generative modeling provides a powerful pathway to overcome data scarcity in energy-related applications where experimental data are often limited. By learning the underlying probability distribution of the training dataset, deep generative models, such as the diffusion model, can generate high-fidelity synthetic samples that statistically resemble the training data. Such synthetic data generation can significantly enrich the size and diversity of the available training data, and more importantly, improve the robustness of downstream machine learning models in predictive tasks. The objective of this paper is to investigate the effectiveness of diffusion models for overcoming data scarcity in nuclear energy applications. By leveraging a public dataset on critical heat flux which covers a wide range of commercial nuclear reactor operational conditions, we developed a diffusion model that can generate an arbitrary amount of synthetic samples. Since a vanilla diffusion model can only generate samples randomly, we also developed a conditional diffusion model capable of generating targeted critical heat flux data under user-specified thermal-hydraulic conditions. The performance of the diffusion model was evaluated based on its ability to capture empirical feature distributions and pair-wise correlations, as well as to maintain physical consistency. The results showed that both the diffusion model and conditional diffusion model can successfully generate realistic and physics-consistent critical heat flux data. Furthermore, uncertainty quantification results demonstrate that the conditional diffusion model is highly effective in augmenting critical heat flux data while maintaining acceptable levels of uncertainty.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The parameter-level performance of covariance matrix conditioning in cosmic microwave background data analyses

Empirical estimates of the band power covariance matrix are commonly used in cosmic microwave background (CMB) power spectrum analyses. While this approach easily captures correlations in the data, noise in the resulting covariance estimate can systematically bias the parameter fitting. Conditioning the estimated covariance matrix, by applying prior information on the shape of the eigenvectors, can reduce these biases and ensure the recovery of robust parameter constraints. In this work, we use simulations to benchmark the performance of four different conditioning schemes, motivated by contemporary CMB analyses. The simulated surveys measure the TT, TE, and EE power spectra over the angular multipole range 300 ≤ ℓ ≤ 3500 in Δℓ = 50 wide bins, for temperature map-noise levels of 10, 6.4, and $2\, \mu$K arcmin. We divide the survey data into N real = 30, 50, or 100 uniform subsets. We show the results of different conditioning schemes on the errors in the covariance estimate, and how these uncertainties on the covariance matrix propagate to the best-fitting parameters and parameter uncertainties. The most significant effect we find is an additional scatter in the best-fitting point, beyond what is expected from the data likelihood. For a minimal conditioning strategy, N real = 30, and a temperature map-noise level of 10$\, \mu$K arcmin, we find the uncertainty on the recovered best-fitting parameter to be ×1.3 larger than the apparent posterior width from the likelihood (×1.2 larger than the uncertainty when the true covariance is used). Stronger priors on the covariance matrix reduce the misestimation of parameter uncertainties to $\lt 1{{\ \rm per\ cent}}$. As expected, empirical estimates perform better with higher N real , ameliorating the adverse effects on parameter constraints.

79 ASTRONOMY AND ASTROPHYSICS↗

Outdoor flat-plate collector performance prediction from solar simulator test data

Solar collector performance data obtained from tests with a simulator was modified for real-life conditions. The data obtained with the simulator was corrected for the variable conditions of ambient temperature, wind, incident angle, flow rate, etc., that are encountered outdoors. Modification of simulator data was accomplished by combining experiment with theory. The technique was demonstrated by application to a spectrally selective and a nonselective type of collector. This kind of modified simulator collector performance data should be valuable in solar systems analysis and for collector performance ranking based on all-day calculated conditions.

Simon, F. F.↗

Pollutant emissions from and within a model gas turbine combustor at elevated pressures and temperatures

Conventional and advanced gas turbine engines are coming under increased scrutiny regarding pollutant emissions. This, in turn, has created a need to obtain in-situ experimental data at practical conditions, as well as exhaust data, and to obtain the data in combustors that reflect modern designs. The in-situ data are needed to (1) assess the effects of design modifications on pollutant formation, and (2) develop a detailed data base on combustor performance for the development and verification of computer modeling. This paper reports on a novel high pressure, high temperature facility designed to acquire such data under controlled conditions and with access (optical and extractive) for in-situ measurements. To evaluate the utility of the facility, a model gas turbine combustor was selected which features practical hardware design, two rows of jets (primary and dilution) with four jets in each row, and advanced wall cooling techniques with laser drilled effusive holes. The dome is equipped with a flat-vaned swirler with vane angles of 60 degrees. Data are obtained at combustor pressures ranging from 2 to 10 atmospheres of pressure, levels of air preheat to 427 C, combustor reference velocities from 10.0 to 20.0 m/s, and an overall equivalence ratio of 0.3. Exit plane and in-situ measurements are presented for HC, O2, CO2, CO, and NO(x). The exit plane emissions of NO(x) correspond to levels reported from practical combustors and the in-situ data demonstrate the utility and potential for detailed flow field measurements.

Drennan, S. A.↗

From Machine Learning to Machine Reasoning: A Model-based Approach to Analyze Equipment Reliability Data

In current nuclear power plants (NPPs) a large amount of condition-based data which can be used to assess and monitor component health and performance. Assessing component health from such data can be performed with a large variety of methods. While the analysis of numeric data can be performed with several methods, the extraction of information from textual data remains a challenge. Currently employed natural language processing (NLP) methods do not really provide quantitative information that might be contained in IRs. In addition, the integration of numeric and textual data to identify possible causal relationships between data elements is still an unresolved challenge. This paper presents an approach to extract information from textual (e.g., incident or maintenance reports) and numeric data that relies on model based system engineer (MBSE) models. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence while semantic analysis is designed to analyze the logic structure of a sentence. An innovative element of our approach is that semantic analysis uses MBSE models to identify links between textual elements. Similarly, numeric data is directly linked to elements of the MBSE models in order to map which functions are being monitored.

97 - MATHEMATICS AND COMPUTING↗

Photosynthetic modulation during the diurnal cycle in a unicellular diazotrophic cyanobacterium grown under nitrogen-replete and nitrogen-fixing conditions

Abstract Cyanobacteria are the only oxygenic photosynthetic organisms that can fix nitrogen. In diazotrophic cyanobacteria, the regulation of photosynthesis during the diurnal cycle is hypothesized to be linked with nitrogen fixation and involve the D1 protein isoform PsbA4. The amount of bioavailable nitrogen has a major impact on productivity in aqueous environments. In contrast to low- or nitrogen-fixing (−N) conditions, little data on photosynthetic regulation under nitrogen-replete (+ N) conditions are available. We compared the regulation of photosynthesis under −N and + N conditions during the diurnal cycle in wild type and a psbA4 deletion strain of the unicellular diazotrophic cyanobacterium Cyanothece sp. ATCC 51142. We observed common changes to light harvesting and photosynthetic electron transport during the dark in + N and −N conditions and found that these modifications occur in both diazotrophic and non-diazotrophic cyanobacteria. Nitrogen availability increased PSII titer when cells transitioned from dark to light and promoted growth. Under −N conditions, deletion of PsbA4 modified charge recombination in dark and regulation of PSII titer during dark to light transition. We conclude that darkness impacts the acceptor-side modifications to PSII and photosynthetic electron transport in cyanobacteria independently of the nitrogen-fixing status and the presence of PsbA4.

59 BASIC BIOLOGICAL SCIENCES↗