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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Continued investigation of potential application of Omega navigation to civil aviation

Major attention is given to an analysis of receiver repeatability in measuring OMEGA phase data. Repeatability is defined as the ability of two like receivers which are co-located to achieve the same LOP phase readings. Specific data analysis is presented. A propagation model is described which has been used in the analysis of propagation anomalies. Composite OMEGA analysis is presented in terms of carrier phase correlation analysis and the determination of carrier phase weighting coefficients for minimizing composite phase variation. Differential OMEGA error analysis is presented for receiver separations. Three frequency analysis includes LOP error and position error based on three and four OMEGA transmissions. Results of phase amplitude correlation studies are presented.

Baxa, E. G., Jr.↗
NASA NTRS2022

Optimization Approach for Wind Tunnel Fan Blade Strain Gage Correlation with Test Fixture Unknowns

NASA has a significant maintenance challenge with the aging wind tunnel infrastructure across the Agency. Some wind tunnel fan blades, such as those in the National Transonic Facility at NASA Langley Research Center, have been in use for far longer than their planned 10-year lifetime. No detailed analytical models of the fan blades from their initial fabrication were created. To support the fabrication of either new, nominally identical fan blades or newly designed fan blades, accurate analytical models of the existing fan blades are necessary to demonstrate an understanding of the capabilities of the existing fan blades. Additionally, the existing documentation of the testing of the existing fan blades has gaps. In this report, a process for improving test-analysis correlation for these wind tunnel fan blades is discussed. This process involved a detailed study of unknown parameters in test fixture parameters from the old and incomplete test documentation. To improve correlation, these unknown parameters were used as design variables in an optimization study to minimize the error between test data and computed structural responses. Legacy strain gage data from tests conducted in 1981 were compared with results from a finite element model created in 2019. The use of test data from 1981 was necessary because none of the existing fan blades could be spared for use in destructive structural testing. While this process was demonstrated for wind tunnel fan blades, this process could be utilized for evaluating unknowns in test fixtures for other structural test configurations.

wind tunnel↗
NASA NTRS2001

Evaluation of Test/Analysis Correlation Methods for Crash Applications

A project has been initiated to improve crash test and analysis correlation. The work in this paper concentrated on the test and simulation results for a fuselage section. Two drop tests of the section were conducted. The first test was designed to excite the linear structural response for comparison with finite element modal analysis results. The second test was designed to provide data for correlation with crash simulations. An MSC.Dytran model was developed to generate nonlinear transient dynamic results. Following minor modifications, the same model was executed in MSC.Nastran to generate modal analysis results. The results presented in this paper concentrate on evaluation of correlation methodologies for crash test data and finite element simulation results.

Lyle, Karen H.↗
NASA NTRS1993

Analysis of high vacuum systems using SINDA'85

The theory, algorithms, and test data correlation analysis of a math model developed to predict performance of the Space Station Freedom Vacuum Exhaust System are presented. The theory used to predict the flow characteristics of viscous, transition, and molecular flow is presented in detail. Development of user subroutines which predict the flow characteristics in conjunction with the SINDA'85/FLUINT analysis software are discussed. The resistance-capacitance network approach with application to vacuum system analysis is demonstrated and results from the model are correlated with test data. The model was developed to predict the performance of the Space Station Freedom Vacuum Exhaust System. However, the unique use of the user subroutines developed in this model and written into the SINDA'85/FLUINT thermal analysis model provides a powerful tool that can be used to predict the transient performance of vacuum systems and gas flow in tubes of virtually any geometry. This can be accomplished using a resistance-capacitance (R-C) method very similar to the methods used to perform thermal analyses.

Spivey, R. A.↗
DOE OSTI2016

An Efficient Sampling-Based Method for Sensitivity and Uncertainty Analysis Through RAVEN

Sensitivity analysis (SA) and uncertainty quantification (UQ) are now widely recognized as essential parts of analyses for complex nuclear systems. Plenty of well-established methodologies are already available for performing SA and UQ, such as Monte Carlo analysis, adjoint-based method, and variance decomposition. The focus of this summary is on developing an efficient sampling-based approach to perform SA and UQ through RAVEN. RAVEN (Risk Analysis and Virtual control Environment) is a software framework able to perform SA and UQ, currently under development at the Idaho National Laboratory. In literature, a number of approaches have been developed to accelerate the process of SA and UQ for large complex systems, such as principal component analysis (PCA) of input space, input-output correlation analysis, and intersection subspace methods. The fundamental idea is to identify the dominant active directions in the parameter space prior to conducting SA and UQ. The premise is that the number of active directions is much less than the dimensionality of input space. In this work, the PCA or Karhunen-Loeve expansion or SVD method is implemented in RAVEN to identify the active directions. This approach is also combined with the forward sampling approaches, such as Monte Carlo, Grid, Latin Hypercube, and Response Surface Design sampling approaches that are currently available in RAVEN, to perform SA and UQ more efficiently. The summary is organized as follows. In the following section, we present the PCA-based forward sampling approach. The effectiveness and efficiency are discussed in the numerical results section. The paper then ends with a concluding summary. In this summary, we have presented PCA-based forward sampling approach to perform SA and UQ. The goal is to reduce the computational overhead for repetitive executions of complex nuclear systems that are generally required when performing SA and UQ. The control of correlations between input parameters is implemented in RAVEN to better represent the input relationships. In addition, we are currently examining our implementations with more realistic models, and we are also focusing on implementation of some new high-dimensional input reduction techniques in RAVEN. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Quantification of Prediction Bounds Caused by Model Form Uncertainty

Numerical simulations, irrespective of the discipline or application, are often plagued by arbitrary numerical and modeling choices. Arbitrary choices can originate from kinematic assumptions, for example the use of 1D beam, 2D shell, or 3D continuum elements, mesh discretization choices, boundary condition models, and the representation of contact and friction in the simulation. This works takes a step toward understanding the effect of arbitrary choices and model-form assumptions on the accuracy of numerical predictions. The application is the simulation of the first four resonant frequencies of a one-story aluminum portal frame structure under free-free boundary conditions. The main challenge of the portal frame structure resides in modeling joint connections, for which different modeling assumptions are available. To study this model-form uncertainty, and compare it to other types of uncertainty, two finite element models are developed using solid elements, and with differing representations of the beam-to-column and column-to-base plate connections using: (i) contact stiffness, and (ii) tied nodes. Test-analysis correlation is performed by comparing the range of numerical predictions obtained from parametric studies of the joint modeling strategies to the range of experimentally obtained natural frequencies. The approach proposed is, first, to characterize the experimental variability of the joints by varying the bolt torque, method of bolt tightening, and the sequence in which the bolts are tightened. The second step is to convert what is learned from these experimental studies to models that bound the range of observed bolt behavior. We show that this approach, that combines small-scale experiments, sensitivity analysis studies, and bounding-case models, successfully produces bounds of numerical predictions that match those measured experimentally on the frame structure.

42 ENGINEERING↗
DOE OSTI2012

A Visual Analytics Approach for Correlation, Classification, and Regression Analysis

New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasing complex, multivariate data sets. In this paper, a novel visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today's data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. The current work provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Cell-Edge Detection via Selective Cooperation and Generalized Canonical Correlation

Improving the uplink quality of service for users located around the boundaries between cells is a key challenge in cellular systems. Existing approaches relying on power control throttle the rates of cell-center users, while multi-user detection requires accurate channel estimates for the cell-edge users, which is another challenge due to their low received signal-to-noise ratio (SNR). Utilizing the fact that cell-edge user signals are weak but common (received at roughly equal power) at different base stations (BSs), this paper establishes a connection between cell-edge user detection and generalized canonical correlation analysis (GCCA). It puts forth a GCCA-based method that leverages selective BS cooperation to recover the cell-edge user signal subspace even at low SNR. The cell-edge user signals can then be extracted from the resulting mixture via algebraic signal processing techniques. The paper includes theoretical analysis showing why GCCA recovers the correct subspace containing the cell-edge user signals under mild conditions. The proposed method can also identify the number of cell-edge users in the system, i.e., the common subspace dimension. Simulations reveal significant performance improvement relative to various multiuser detection techniques. Cell-edge detection performance is further studied as a function of how many / which BSs are selected, and it is shown that using the closest three BS is always the best choice.

base station cooperation↗
DOE OSTI2025

Predicting High‐Resolution Spatial and Spectral Features in Mass Spectrometry Imaging with Machine Learning and Multimodal Data Fusion

Recent advancements in molecular Mass Spectrometry Imaging have sparked interest in integrating high spatial resolution methods with molecular mass-spectrometry-based chemical imaging. Fusion-based algorithms have proven effective in generating high spatial-resolution molecular mass spectra. However, a significant challenge stems from the differing physical mechanisms underlying image generation and data upsampling techniques, potentially leading to discrepancies in integrated information channels. Integrating physical constraints into data processing workflows is essential to tackle this issue. In this study, we propose an innovative approach that merges data from Fourier transform ion cyclotron resonance (FTICR), time-of-flight matrix-assisted laser desorption/ionization, and time-of-flight secondary ion mass spectrometry imaging techniques. By leveraging FT-ICR's unparalleled spectral resolution and ToF-SIMS's exceptional spatial resolution, we achieve submicron spatial resolution, enabling the observation of intact molecular species with remarkable spectral precision. Canonical correlation analysis is employed to incorporate physical constraints. Through sophisticated image processing and machine learning techniques, the results of this fusion hold significant promise for advancing our comprehension of complex systems and unveiling concealed molecular intricacies.

canonical correlation analysis↗
DOE OSTI2017

An overlooked nitrogen loss linked to anaerobic ammonium oxidation in estuarine sediments in China

Despite its importance, anammox (anaerobic ammonium oxidation) in estuarine sediment systems remains poorly understood, particularly at the continental scale. This study aimed to understand the abundance, diversity, and activity of anammox bacteria and to determine the main factors influencing the anammox process in estuarine sediments in China. Materials and methods Estuarine sediments were collected from 18 estuaries spanning over 4000 km. Experiments using an (15)Ntracer, quantitative PCR, and clone library construction were used to determine the activity, abundance, and diversity of anammox bacteria. The impact of environmental factors on anammox processes was also determined. Results and discussion The abundance of the anammox-specific hydrazine synthase (hzsB) gene ranged from 1.8 x 105 +/- 3.4 x 104 to 3.6 x 108 +/- 7.5 x 107 copies g(-1) dw. Candidatus Scalindua, Brocadia, Kuenenia, Jettenia, and two novel unidentified clusters were detected, with Scalindua dominating the anammox population. Additionally, the abundances of Scalindua, Kuenenia, and Brocadia were found to be significantly correlated with latitude. The anammox rates ranged from 0.29 +/- 0.15 to 13.68 +/- 3.98 nmol N g(-1) dw h(-1) and contributed to 2.39-82.61% of total N-2 production. Pearson correlation analysis revealed that the anammox rate was positively correlated with total nitrogen, total carbon, and temperature, and was negatively correlated with dissolved oxygen (DO). The key factors influencing the hzsB gene abundance were ammonium concentration, salinity, and DO. Ammonium concentration, pH, temperature, and latitude were main variables shaping the anammox-associated bacterial community. Conclusions Our results suggested that anammox bacteria are ubiquitous in coastal estuaries in China and underline the importance of anammox resulting in N loss at a continental scale.

activity↗
DOE OSTI2018

Copper and zinc levels in soil, water, wheat, and hair of inhabitants of three areas of the Orenburg region, Russia

Highlights: • Soil, water, wheat and hair levels of Zn and Cu in Orenburg region were studied. • Both Zn and Cu levels in the samples were higher in the eastern area. • Higher levels of Zn and Cu in the eastern area may occur due to industrial activities. • Water Zn levels were associated with hair Zn levels. The objective of the present study was to assess the level of zinc and copper in soil, water, wheat and hair of inhabitants of the western, central, and eastern areas of the Orenburg region. A total of 525 water, soil, and wheat samples, as well as 420 hair samples were assessed using atomic absorption spectrometry (water, soil, wheat) and inductively-coupled plasma mass spectrometry (hair). The highest levels of Zn and Cu in water (4.9(4.2–5.1) and 1.0(0.9–1.1) mg/l), soil (23.8(20.7–27.0) and 2.6(1.9–3.1) mg/kg), and wheat (24.7(20.5–31.0) and 4.8(4.2–5.5) mg/kg) were observed in the eastern area (p < 0.001). Hair zinc levels in inhabitants of the western (184(165–198) µg/g) and eastern (224(211–253) µg/g) areas of the region exceeded the respective values from the central area by 32% and 61% (p < 0.001). In turn, hair Cu levels in the central (16.4(14.3–17.8) µg/g) and eastern (17.9(16.4–19.0) µg/g) areas exceeded the values from the western area by 10% and 20%, respectively. Correlation analysis demonstrated that hair Zn levels were positively correlated with water and soil content, whereas wheat Zn levels were associated with soil and water content. For copper significant direct correlation was observed only between soil and water Cu content. In multiple regression models, only water zinc level was significantly associated with hair Zn content, although the general model accounted for 55% of variability of hair Zn content. Higher zinc and copper exposure in the eastern area is presumably associated with higher activity of metal-processing industry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

AIM2 is a potential therapeutic target in human renal carcinoma and suppresses its invasion and metastasis via enhancing autophagy induction

Highlights: • Low AIM2 expression was correlated with RCC patient survival. • AIM2 suppressed the proliferation, migration and invasion of renal cancer cells. • AIM2 enhanced the expression of autophagy-related genes. • AIM2 exerts the anti-tumor effect via enhancing the induction of autophagy. Absent in melanoma 2 (AIM2) as a tumor suppressor is recently recognized to play an important role in many human solid tumors. However, the biological significance and function of AIM2 in renal cell carcinoma (RCC) remain unknown. In this study, we proposed to investigate the clinicopathological and prognostic significance of AIM2 in RCC patient specimens, to analyze the correlation between AIM2 expression and disease progression, and to further investigate the role and mechanism of AIM2 in malignant behaviors of renal carcinoma by cellular and animal models. The correlation analysis showed that low AIM2 expression was significantly correlated with lymph node metastasis, poor 5-year overall (P < 0.05) and disease-specific survival (P < 0.05) in RCC patients. Over-expression of AIM2 in 786-O or OSRC-2 cells suppressed the cell proliferation, migration and invasion as compared with control. The increased AIM2 expression enhanced the expression of autophagy-related genes (Bcl-2, Beclin-1, LC3-Ⅱ, and ATG-5) and increased the ratio of LC3-Ⅱ/LC3-Ⅰin renal carcinoma cells. Of note, the blockade of autophagy by 3-Methyladenine (3-MA) abrogated the inhibition of cell migration and invasion by over-expressing AIM2, indicated that AIM2 suppressed the malignant behaviors of renal carcinoma by enhancing the induction of autophagy. Furthermore, 3-MA abolished the prevention of tumor growth on nude mouse established by AIM2-OSRC-2 cells. Our results suggested that AIM2 might serve as a novel prognostic indicator as well as a potential therapeutic target for renal carcinoma treatment.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1995

Ground-based microwave monitoring of middle atmosphere ozone: Comparison to lidar and Stratospheric and Gas Experiment 2 satellite observations

A dedicated ground-based microwave radiometer was in operation to monitor the middle atmospheric ozone concentration at Table Mountain Facility (TMF) of the Jet Propulsion Laboratory (JPL), California (34.4 deg N, 117.7 deg W) from July 1989 to June 1992, as a part of the Network for Detection of Stratospheric Change. Ozone profiles from 56 to 0.04 mbar (approximately 20 - 70 km) were retrieved from the microwave data. The focus in this paper is to validate the microwave ozone observations from 56 to 1 mbar by comparing the results from a JPL ground-based lidar located at the same site and from the Stratospheric Aerosol and Gas Experiment 2 (SAGE 2) satellite overpasses within 1000 km of TMF and to examine the ability of these instruments to detect short-term, seasonal, and annual variations in ozone. The profile comparison results show that the mean differences of microwave ozone from lidar and SAGE 2 are about 5% or less and the root-mean-square scatter about the mean is mainly from the precision of the instruments. A correlation analysis of ozone time series suggests highly significant correlations up to 2.4 mbar between lidar and microwave measurements and up to 1 mbar between SAGE 2 and microwave. The short-term and seasonal variation of the ozone profile seen in the microwave measurements is shown to be consistent with the observations of lidar and SAGE 2, and the interannual variation of ozone appears to be detectable within an accuracy of a few percent with the microwave instrument.

Tsou, J. J.↗
DOE OSTI2013

A Visual Analytics Approach for Correlation, Classification, and Regression Analysis

New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today s increasing complex, multivariate data sets. In this paper, a visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today s data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. This chapter provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.

Steed, Chad A↗
DOE OSTI2018

Aggregation and data analysis of corrosion studies in molten chloride and fluoride salts

Corrosion studies in molten fluoride and chloride salts were surveyed, and key data were aggregated into a single dataset. Studies were graphed by salt purity, temperature, sample material, container material, and experimental method (loop, capsule, crucible). To elucidate and quantify the factors that affect corrosion in molten salts, a data analysis using a newly-defined corrosion resistance score and a correlation analysis using techniques borrowed from machine learning were performed. It is shown that salt purity had the strongest correlation with corrosion rates in molten chlorides and fluorides. As a result, data analysis across varied works was inconsistent due to the lack of standardization among molten salt corrosion studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

A hybrid approach to test-analysis-model development for large space structures

The present FEM reduction method for the generation of test-analysis-models (TAMs) in test-analysis correlation addresses contentions that the current modal TAM is hypersensitive to differences between test model shapes and analysis mode shapes, thereby generating large off-diagonal terms within the orthogonality and cross-orthogonality matrices employed in test-analysis mode-shape correlation. A hybrid TAM methodology is accordingly developed which combines the exact representation of the FEM target modes from the modal TAM with the more accurate TAM representation of the residual modes; the superior residual dynamics representation of the hybrid TAM is demonstrated for a detailed representation of a large space structure.

Kammer, D. C.↗
NASA NTRS1982

Preliminary sonic boom correlation of predicted and measured levels for STS-1 entry

A preliminary analysis correlating peaks from sonic boom pressure signatures recorded during the descent trajectory of the Orbiter Columbia, which landed in the dry lake bed at Edwards Air Force Base (EAFB), California, with measured wind tunnel signatures extrapolated from flight altitudes to the ground has been made for Mach numbers ranging from 1.3 to 6. The flight pressure signatures were recorded by microphones positioned at ground level near the groundtrack, whereas the wind tunnel signatures were measured during a test of a 0.0041-scale model Orbiter. The agreement between overpressure estimates based on wind tunnel data using preliminary flight trajectory data and oscillograph traces from ground measurements appears reasonable at this time for the range of Mach numbers considered. More detailed studies using final flight trajectory data and digitized ground measured data will be performed.

Garcia, F., Jr.↗
DOE OSTI2019

Low-Frequency Mutational Heterogeneity of Invasive Ductal Carcinoma Subtypes: Information to Direct Precision Oncology

Information regarding the role of low-frequency hotspot cancer-driver mutations (CDMs) in breast carcinogenesis and therapeutic response is limited. Using the sensitive and quantitative Allele-specific Competitor Blocker PCR (ACB-PCR) approach, mutant fractions (MFs) of six CDMs (PIK3CA H1047R and E545K, KRAS G12D and G12V, HRAS G12D, and BRAF V600E) were quantified in invasive ductal carcinomas (IDCs; including ~20 samples per subtype). Measurable levels (i.e., ≥ 1 × 10 -5 , the lowest ACB-PCR standard employed) of the PIK3CA H1047R, PIK3CA E545K, KRAS G12D, KRAS G12V, HRAS G12D, and BRAF V600E mutations were observed in 34/81 (42%), 29/81 (36%), 51/81 (63%), 9/81 (11%), 70/81 (86%), and 48/81 (59%) of IDCs, respectively. Correlation analysis using available clinicopathological information revealed that PIK3CA H1047R and BRAF V600E MFs correlate positively with maximum tumor dimension. Analysis of IDC subtypes revealed minor mutant subpopulations of critical genes in the MAP kinase pathway (KRAS, HRAS, and BRAF) were prevalent across IDC subtypes. Few triple-negative breast cancers (TNBCs) had appreciable levels of PIK3CA mutation, suggesting that individuals with TNBC may be less responsive to inhibitors of the PI3K/AKT/mTOR pathway. These results suggest that low-frequency hotspot CDMs contribute significantly to the intertumoral and intratumoral genetic heterogeneity of IDCs, which has the potential to impact precision oncology approaches.

59 BASIC BIOLOGICAL SCIENCES↗