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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Bayesian Approach for In-Situ Stress Prediction and Uncertainty Quantification for Subsurface Engineering

Many subsurface engineering applications require accurate knowledge of the in-situ state of stress for their safe design and operation. Existing methods to meet this need primarily include field measurements for estimating one or more of the principal stresses from a borehole, or optimization methods for constructing a 3D geomechanical model in terms of geophysical measurements. These methods, however, often contain considerable uncertainty in estimating the state of stress. Here, in this paper, we build on a Bayesian approach to quantify uncertainty in stress estimations for subsurface engineering applications. This approach can provide an estimate of the 3D distribution of stress throughout the volume of interest and provide an estimate of the uncertainty arising from the stress measurement, the rheology parameters, and a paucity of measurements. The value of this approach is demonstrated using stress measurements from the In Salah carbon storage site, which was one of the world’s first industrial carbon capture and storage projects. This demonstration shows the application of this Bayesian approach for estimating the initial state of stress for In Salah and quantifying the uncertainty in the estimated stress. Also, an assessment of a maximum injection pressure to prevent geomechanical risks from CO 2 injection pressures is provided in terms of the probability distribution of the minimum principal stress quantified by the approach. With the In Salah case study, this paper demonstrates that using the Bayesian approach can provide additional insights for site explorations and/or project operations to make informed-site decisions for subsurface engineering applications.

58 GEOSCIENCES↗
DOE OSTI2018

Automated Segmentation and Quantification of Drusen in Fundus and Optical Coherence Tomography Images for Detection of ARMD

Age-related macular degeneration (ARMD) is one of the most common retinal syndromes that occurs in elderly people. Different eye testing techniques such as fundus photography and optical coherence tomography (OCT) are used to clinically examine the ARMD-affected patients. Many researchers have worked on detecting ARMD from fundus images, few of them also worked on detecting ARMD from OCT images. However, there are only few systems that establish the correspondence between fundus and OCT images to give an accurate prediction of ARMD pathology. In this paper, we present fully automated decision support system that can automatically detect ARMD by establishing correspondence between OCT and fundus imagery. The proposed system also distinguishes between early, suspect and confirmed ARMD by correlating OCT B-scans with respective region of the fundus image. In first phase, proposed system uses different B-scan based features along with support vector machine (SVM) to detect the presence of drusens and classify it as ARMD or normal case. In case input OCT scan is classified as ARMD, region of interest from corresponding fundus image is considered for further evaluation. The analysis of fundus image is performed using contrast enhancement and adaptive thresholding to detect possible drusens from fundus image and proposed system finally classified it as early stage ARMD or advance stage ARMD. The proposed system is tested on local data set of 100 patients with100 fundus images and 6800 OCT B-scans. Proposed system detects ARMD with the accuracy, sensitivity, and specificity ratings of 98.0, 100, and 97.14%, respectively.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Bayesian merging of numerical modeling and remote sensing for saltwater intrusion quantification in the Vietnamese Mekong Delta

Saltwater intrusion has become one of the most concerning issues in the Vietnamese Mekong Delta (VMD) due to its increasing impacts on agriculture and food security of Vietnam. Reliable estimation of salinity plays a crucial role to mitigate the impacts of saltwater intrusion. Here, this study developed a hybrid technique that merges satellite imagery with numerical simulations to improve the estimation of salinity in the VMD. The salinity derived from Landsat images and by numerical simulations was fused using the Bayesian inference technique. The results indicate that our technique significantly reduces the uncertainties and improves the accuracy of salinity estimates. The Nash–Sutcliffe coefficient is 0.74, which is much higher than that of numerical simulation (0.63) and Landsat estimation (0.6). The correlation coefficient between the ensemble and measured salinity is relatively high (0.88). The variance of the ensemble salinity errors (5.0 ppt 2 ) is lower than that of Landsat estimation (10.4 ppt 2 ) and numerical simulations (9.6 ppt 2 ). The proposed approach shows a great potential to combine multiple data sources of a variable of interest to improve its accuracy and reliability wherever these data are available.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Application of Genetic Algorithm (GA) Assisted Partial Least Square (PLS) Analysis on Trilinear and Non-trilinear Fluorescence Data Sets to Quantify the Fluorophores in Multifluorophoric Mixtures: Improving Quantification Accuracy of Fluorimetric Estimations of Dilute Aqueous Mixtures

Excitation-emission matrix fluorescence (EEMF) and total synchronous fluorescence spectroscopy (TSFS) are the 2 fluorescence techniques that are commonly used for the analysis of multifluorophoric mixtures. These 2 fluorescence techniques are conceptually different and provide certain advantages over each other. The manual analysis of such highly correlated large volume of EEMF and TSFS towards developing a calibration model is difficult. Partial least square (PLS) analysis can analyze the large volume of EEMF and TSFS data sets by finding important factors that maximize the correlation between the spectral and concentration information for each fluorophore. However, often the application of PLS analysis on entire data sets does not provide a robust calibration model and requires application of suitable pre-processing step. The present work evaluates the application of genetic algorithm (GA) analysis prior to PLS analysis on EEMF and TSFS data sets towards improving the precision and accuracy of the calibration model. The GA algorithm essentially combines the advantages provided by stochastic methods with those provided by deterministic approaches and can find the set of EEMF and TSFS variables that perfectly correlate well with the concentration of each of the fluorophores present in the multifluorophoric mixtures. The utility of the GA assisted PLS analysis is successfully validated using (i) EEMF data sets acquired for dilute aqueous mixture of four biomolecules and (ii) TSFS data sets acquired for dilute aqueous mixtures of four carcinogenic polycyclic aromatic hydrocarbons (PAHs) mixtures. In the present work, it is shown that by using the GA it is possible to significantly improve the accuracy and precision of the PLS calibration model developed for both EEMF and TSFS data set. Hence, GA must be considered as a useful pre-processing technique while developing an EEMF and TSFS calibration model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Quantification of Porosity in Ceramic Matrix Composites Using Thermography

Thermography is one of the Non-Destructive Evaluation methods used to qualitatively estimate the amount of porosity in as-manufactured ceramic matrix composite (CMC) parts. Through-transmission (TT) thermography allows for comparison of thermal diffusivity caused by differences in material density and porosity at different locations in the part. In this study, volume fraction of pores and its distribution in CMC samples containing different amounts of porosity was quantified using optical microscopy and X-ray computed tomography scans. TT thermography was done on the same specimens and images were analyzed to determine the distribution of thermal diffusivity. Comparison of porosity measurements and thermal diffusivity images shows an inverse correlation. A simple two-phase analytical model describing this relationship is derived for composites and its solution is shown to compare favorably with experimental data. In the absence of porosity data, the model can be used to estimate porosity directly from thermal diffusivity data.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Quantification of the Interaction Field in Arrays of Magnetic Nanowires from the Remanence Curves

A method is presented that allows quantifying the average value of the interaction field in arrays of magnetic nanowires from the field difference between the isothermal remanence (IRM) and the DC demagnetizing (DCD) remanence curves when the normalized magnetization is equal to one third. Arrays of magnetic nanowires of different diameters and packing fractions are used to experimentally test the method. The results have been compared with those obtained using the method based on the difference between the remanence coercivity fields and with a mean-field expression for the interaction field, providing a very good agreement and thus validating the method. Additionally, it is shown that both the position (m{sub 0}) and the shift along the magnetization axis of the intersection between the remanence curves with respect to the value of one third (δm = m{sub 0} − 1/3) provide qualitative information about the interaction field. The former indicates the type of interaction depending if the intersection is above (m{sub 0} > 1/3) or below (m{sub 0} < 1/3), which corresponds to a ferro or anti-ferro magnetic interaction, respectively. While for the latter, it is shown that the maximum deviation of the Delta-M plot from zero (ΔM{sub max}) corresponds to three times the shift (ΔM{sub max} = 3δm).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Quantification techniques of mass-separation and ion yield for the detection of radioactive isotopes

This research demonstrates two methods of quantifying isotope separation efficiency using an inductively coupled plasma mass spectrometer. One method measured the accumulated charge on a conductive collection substrate in real-time while the second method performed a chemical dissolution of the substrate with subsequent post-processing and analysis. Our previous results demonstrated and compared these methods with a multi-element standard of stable isotopes. This research applies these methods to quantifying radioactive isotopes utilizing measurements of the stable isotope at the same mass-to-charge ratio. The mass-separated radioactive isotope were fission products produced from thermal neutron irradiation of a highly enriched 235U foil. The two methods are explained and the results of this new separation methodology are compared to available cumulative fission yields.

Dion, Michael P.↗
DOE OSTI2018

Trace impurity analysis in uranium oxide via hybrid quantification techniques—gravimetric standard addition and isotope dilution mass spectrometry

Measurement methods for the analysis of trace impurities in uranium materials, essential in nuclear fuel production and nuclear forensics, are continuously improving. Analytical methods were developed with the goal of lowering uncertainties of next generation certified uranium oxide reference materials for trace impurity concentrations. Through addition of a traceable standard directly into the sample, gravimetric standard addition and isotope dilution followed by analysis on an inductively coupled plasma mass spectrometer can achieve lower uncertainties. In conclusion, results for 28 impurities in CRM 124-1 and 124-6 from NBL Program Office were used for validation of accuracy and comparisons of uncertainties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantification of uranium metal and total uranium in U-UO 2 mixtures using H 3 PO 4 -HCl

Here, the selective dissolution of uranium metal from its mixtures with UO 2 was studied to establish a simple and rapid quantitative method. Uranium metal was found to selectively dissolve as U(IV) into a solution of phosphoric and hydrochloric acids, with quantitative dissolution occurring within 1 h. Total dissolution of uranium as U(VI) could then be obtained by nitric acid addition and heating for 0.5–1 h. Analysis of the resulting U(IV) and U(VI) solutions by ICP-OES or UV–Vis spectroscopy yielded uranium metal-to-UO 2 ratios with an accuracy of ± 10% or better. Accuracy of the ICP-OES method was slightly better than UV–Vis, but the simplicity of the latter makes it an attractive option for some applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Remote quantification of Cm(III) and HNO 3 by fluorescence spectroscopy and chemometrics

A unique approach to remotely quantify Cm(III) (0–100 µg mL −1 ) in HNO 3 (1–12 M) using steady-state laser fluorescence spectroscopy and multivariate regression models was developed. Photoluminescence is amenable to remote measurements using fiber-optic cables and is sensitive to numerous lanthanide and actinide species. In-line measurements can provide feedback to support complex processing in harsh environments (e.g., hot cells) to help guide and optimize radiochemical separations. In this work, Cm(III) spectra were acquired remotely in a glove box as a function of HNO 3 concentration to better understand spectral characteristics and evaluate the utility of multivariate regression models in this system. Furthermore, the Cm(III) fluorescence peak shape, width, position, and intensity changed significantly as a function of HNO 3 concentration, likely because of the displacement of emission quenching inner-sphere water molecules and complexation with nitrate ions. Despite significant covariance and nonlinearity in the data, a D-optimal design strategy successfully minimized training set sample size and was used to build effective partial least squares regression models for Cm(III) and HNO 3 concentrations without a priori knowledge of solution conditions. Chemometrics for modeling complex fluorescence spectra are promising and may find widespread applicability for online analysis in numerous chemical systems found in the nuclear field.

Actinide↗
DOE OSTI2018

A single external cavity laser-based sensor for simultaneous detection and quantification of atmospheric methane and water vapor

A single external cavity diode laser (ECDL)-based sensor system was developed for simultaneous measurements of methane and water vapor in the atmospheric air. A home-made continuous wave (CW) ECDL with a wavelength of ∼ 1325 nm was employed to cover two absorption lines for different gas species. A high-finesse optical cavity composed of two high-reflectivity mirrors (R=0.99927) was used to enhance the gas absorption in a space of 0.5 l. An isolated methane absorption line at 7552.74 cm{sup −1} and a common (non-isolated) absorption line of water vapor and methane 7552.81cm{sup −1} were utilized for simultaneous detection. A method was developed to calculate the water vapor concentration from these lines. To our knowledge, the method and the absorption lines used in the present paper were used for the first time for simultaneous measurement of the concentrations of atmospheric methane and water vapor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Liquid Inclusion Distortion by Lens Shape Effect: In Situ Observation and Quantification on LCAK Steels Using HT-CSLM

Because of interfacial and surface tension, micron-sized liquid oxide droplets are expected to change from spherical (when fully immersed in liquid steel) to lens shape on top of steel. Inclusion sizes were measured by automated analysis of polished sections of calcium-treated aluminum-killed steel. A sample of the same steel was remelted and observed using confocal scanning laser microscopy. Droplets on the steel surface appear to have approximately twice the diameter of fully immersed spherical inclusions.

36 MATERIALS SCIENCE↗