Parametric Identification of Rotating Cavitation in a Three-Bladed Axial Inducer

2021 ◽  
Author(s):  
Antonio Costanzo ◽  
Dario Valentini ◽  
Giovanni Pace ◽  
Ruzbeh Hadavandi ◽  
Lucio Torre ◽  
...  
Keyword(s):  
High Performance ◽  
Statistical Significance ◽  
Likelihood Estimation ◽  
Parametric Identification ◽  
Flow Instabilities ◽  
Model Parameters ◽  
Promising Tool ◽  
Dual Sensor ◽  
Stationary Frame

Abstract The article illustrates the application of Bayesian estimation to the identification of flow instabilities, with special reference to rotating cavitation, in a three-bladed axial inducer using the unsteady pressure readings of a single transducer mounted on the casing just behind the leading edges of the impeller blades. The typical trapezoidal pressure distribution in the blade channels is parametrized and modulated in time and space for theoretically reproducing the expected pressure generated by known forms of cavitation instabilities (cavitation auto-oscillations, n-lobed rotating cavitation, higher-order surge/rotating cavitation modes). The Fourier spectra of the theoretical pressure so obtained in the rotating frame are transformed in the stationary frame, frequency broadened to better approximate the experimental results, and parametrically fitted by maximum likelihood estimation to the measured auto-correlation spectra. Each form of instability generates a characteristic distribution of sidebands in addition to its fundamental frequency. The identification makes use of this information for effective detection and characterization of multiple simultaneous flow instabilities with intensities spanning over about 20 dB down to about 4 dB signal-to-noise ratios. The same information also allows for effectively bypassing the aliasing limitations of traditional cross-correlation methods in the discrimination of multiple-lobed azimuthal instabilities from dual-sensor measurements on the same axial station of the machine. The method returns both the estimates of the model parameters and their standard deviations, providing the information needed for the assessment of the statistical significance of the results. The proposed approach represents therefore a promising tool for experimental research on flow instabilities in high-performance turbopumps.

scholarly journals Probabilistic Inference Coupled with Possibilistic Reasoning for Robust Estimation of Hydrologic Parameters and Piecewise Characterization of Interactive Uncertainties

2016 ◽  
Vol 17 (4) ◽  
pp. 1243-1260 ◽  
Author(s):  
S. Wang ◽  
G. H. Huang ◽  
B. W. Baetz ◽  
W. Huang
Keyword(s):  
Expert Knowledge ◽  
Probability Distributions ◽  
Statistical Significance ◽  
Probabilistic Inference ◽  
Hydrologic Model ◽  
Factorial Analysis ◽  
Model Parameters ◽  
Xiangxi River ◽  
Parametric Interactions

Abstract This paper presents a factorial possibilistic–probabilistic inference (FPI) framework for estimation of hydrologic parameters and characterization of interactive uncertainties. FPI is capable of incorporating expert knowledge into the parameter adjustment procedure for enhancing the understanding of the nature of the calibration problem. As a component of the FPI framework, a Monte Carlo–based fractional fuzzy–factorial analysis (MFA) method is also proposed to identify the best parameter set and its underlying probability distributions in a fuzzy probability space. Factorial analysis of variance (ANOVA) coupled with its multivariate extensions are performed to explore potential interactions among model parameters and among hydrological metrics in a systematic manner. The proposed methodology is applied to the Xiangxi River watershed by using the conceptual hydrological model (HYMOD) to demonstrate its validity and applicability. Results reveal that MFA is capable of deriving probability density functions (PDFs) of hydrologic model parameters. Moreover, the sequential inferences derived from the F test and its multivariate approximations disclose the statistical significance of parametric interactions affecting individual and multiple hydrological metrics, respectively. The findings presented here indicate that parametric interactions are complex in a fuzzy stochastic environment, and the magnitude and direction of interaction effects vary in different regions of the parameter space as well as vary temporally because of the dynamic behavior of hydrologic systems.

scholarly journals Non-Gaussian models of diffusion weighted imaging for detection and characterization of prostate cancer: a systematic review and meta-analysis

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
V. Brancato ◽  
C. Cavaliere ◽  
M. Salvatore ◽  
S. Monti
Keyword(s):  
Prostate Cancer ◽  
Systematic Review ◽  
Diffusion Weighted Imaging ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Gaussian Model ◽  
Model Parameters ◽  
Diffusion Weighted ◽  
Non Gaussian

AbstractThe importance of Diffusion Weighted Imaging (DWI) in prostate cancer (PCa) diagnosis have been widely handled in literature. In the last decade, due to the mono-exponential model limitations, several studies investigated non-Gaussian DWI models and their utility in PCa diagnosis. Since their results were often inconsistent and conflicting, we performed a systematic review of studies from 2012 examining the most commonly used Non-Gaussian DWI models for PCa detection and characterization. A meta-analysis was conducted to assess the ability of each Non-Gaussian model to detect PCa lesions and distinguish between low and intermediate/high grade lesions. Weighted mean differences and 95% confidence intervals were calculated and the heterogeneity was estimated using the I2 statistic. 29 studies were selected for the systematic review, whose results showed inconsistence and an unclear idea about the actual usefulness and the added value of the Non-Gaussian model parameters. 12 studies were considered in the meta-analyses, which showed statistical significance for several non-Gaussian parameters for PCa detection, and to a lesser extent for PCa characterization. Our findings showed that Non-Gaussian model parameters may potentially play a role in the detection and characterization of PCa but further studies are required to identify a standardized DWI acquisition protocol for PCa diagnosis.

Preparation and Characterization of NH2-Terminal Fibrinogen Bβ Fragments from N-DSK of Human Fibrinogen

1984 ◽  
Vol 51 (01) ◽  
pp. 016-021 ◽  
Author(s):  
S Birken ◽  
G Agosto ◽  
B Lahiri ◽  
R Canfield
Keyword(s):  
High Performance ◽  
Gel Filtration ◽  
Ion Exchange Chromatography ◽  
Exchange Chromatography ◽  
Reverse Phase ◽  
Human Fibrinogen ◽  
Human Volunteers ◽  
Cnbr Cleavage ◽  
Two Peaks

SummaryIn order to investigate the early release of NH2-terminal plasmic fragments from the Bβ chain of fibrinogen, substantial quantities of Bβ 1-42 and Bβ 1-21 are required as immunogens, as radioimmunoassay standards and for infusion into human volunteers to determine the half-lives of these peptides. Towards this end methods that employ selective proteolytic cleavage of these fragments from fibrinogen have been developed. Both the N-DSK fragment, produced by CNBr cleavage of fibrinogen, and Bβ 1-118 were employed as substrates for plasmin with the finding of higher yields from N-DSK. Bβ 1-42 and Bβ 1-21 were purified by gel filtration and ion-exchange chromatography on SP-Sephadex using volatile buffers. When the purified preparation of Bβ 1-42 was chromatographed on reverse-phase high performance liquid chromatography, two peaks of identical amino acid composition were separated, presumably due either to pyroglutamate or to amide differences.

Preparation and Characterization of the High Molecular Weight [3H]Hyaluronic Acid

1992 ◽  
Vol 57 (10) ◽  
pp. 2151-2156 ◽  
Author(s):  
Peter Chabreček ◽  
Ladislav Šoltés ◽  
Hynek Hradec ◽  
Jiří Filip ◽  
Eduard Orviský
Keyword(s):  
Molecular Weight ◽  
Hyaluronic Acid ◽  
High Molecular Weight ◽  
Methyl Bromide ◽  
High Performance ◽  
Hydrogen Atoms ◽  
Isolation And Characterization ◽  
Labelling Procedure ◽  
Enzymatic Depolymerization

Two methods for the preparation of high molecular weight [3H]hyaluronic acid were investigated. In the first one, hydrogen atoms in the molecule were replaced by tritium. This isotopic substitution was performed in aqueous solution using Pd/CaCO3 as the catalyst. In the second method, the high molecular weight hyaluronic acid was alkylated with [3H]methyl bromide in liquid ammonia at a temperature of -33.5 °C. High-performance gel permeation chromatographic separation method was used for the isolation and characterization of the high molecular weight [3H]hyaluronic acid. Molecular weight parameters for the labelled biopolymers were Mw = 128 kDa, Mw/Mn = 1.88 (first method) and Mw = 268 kDa, Mw/Mn = 1.55 (second method). The high molecular weight [3H]hyaluronic acid having Mw = 268 kDa was degraded further by specific hyaluronidase. Products of the enzymatic depolymerization were observed to be identical for both, labelled and cold biopolymer. This finding indicates that the described labelling procedure using [3H]methyl bromide does not induce any major structural rearrangements in the molecule.

scholarly journals Development and characterization of Nb3Sn/Al2O3 superconducting multilayers for particle accelerators

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chris Sundahl ◽  
Junki Makita ◽  
Paul B. Welander ◽  
Yi-Feng Su ◽  
Fumitake Kametani ◽  
...  
Keyword(s):  
High Performance ◽  
High Energy ◽  
Particle Accelerators ◽  
Quality Factors ◽  
Critical Fields ◽  
Linear Accelerators ◽  
Cross Sectional ◽  
Low Field ◽  
Superconducting Radio Frequency

AbstractSuperconducting radio-frequency (SRF) resonator cavities provide extremely high quality factors > 1010 at 1–2 GHz and 2 K in large linear accelerators of high-energy particles. The maximum accelerating field of SRF cavities is limited by penetration of vortices into the superconductor. Present state-of-the-art Nb cavities can withstand up to 50 MV/m accelerating gradients and magnetic fields of 200–240 mT which destroy the low-dissipative Meissner state. Achieving higher accelerating gradients requires superconductors with higher thermodynamic critical fields, of which Nb3Sn has emerged as a leading material for the next generation accelerators. To overcome the problem of low vortex penetration field in Nb3Sn, it has been proposed to coat Nb cavities with thin film Nb3Sn multilayers with dielectric interlayers. Here, we report the growth and multi-technique characterization of stoichiometric Nb3Sn/Al2O3 multilayers with good superconducting and RF properties. We developed an adsorption-controlled growth process by co-sputtering Nb and Sn at high temperatures with a high overpressure of Sn. The cross-sectional scanning electron transmission microscope images show no interdiffusion between Al2O3 and Nb3Sn. Low-field RF measurements suggest that our multilayers have quality factor comparable with cavity-grade Nb at 4.2 K. These results provide a materials platform for the development and optimization of high-performance SIS multilayers which could overcome the intrinsic limits of the Nb cavity technology.

scholarly journals Enzymatic Synthesis and Characterization of Different Families of Chitooligosaccharides and Their Bioactive Properties

2021 ◽  
Vol 11 (7) ◽  
pp. 3212
Author(s):  
Noa Miguez ◽  
Peter Kidibule ◽  
Paloma Santos-Moriano ◽  
Antonio O. Ballesteros ◽  
Maria Fernandez-Lobato ◽  
...  
Keyword(s):  
High Performance ◽  
Chemical Characterization ◽  
Amperometric Detection ◽  
Anion Exchange Chromatography ◽  
Exchange Chromatography ◽  
Enzymatic Production ◽  
Bioactive Properties ◽  
Substrate Properties ◽  
Chitin Hydrolysis

Chitooligosaccharides (COS) are homo- or hetero-oligomers of D-glucosamine (GlcN) and N-acetyl-D-glucosamine (GlcNAc) that can be obtained by chitosan or chitin hydrolysis. Their enzymatic production is preferred over other methodologies (physical, chemical, etc.) due to the mild conditions required, the fewer amounts of waste and its efficiency to control product composition. By properly selecting the enzyme (chitinase, chitosanase or nonspecific enzymes) and the substrate properties (degree of deacetylation, molecular weight, etc.), it is possible to direct the synthesis towards any of the three COS types: fully acetylated (faCOS), partially acetylated (paCOS) and fully deacetylated (fdCOS). In this article, we review the main strategies to steer the COS production towards a specific group. The chemical characterization of COS by advanced techniques, e.g., high-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD) and MALDI-TOF mass spectrometry, is critical for structure–function studies. The scaling of processes to synthesize specific COS mixtures is difficult due to the low solubility of chitin/chitosan, the heterogeneity of the reaction mixtures, and high amounts of salts. Enzyme immobilization can help to minimize such hurdles. The main bioactive properties of COS are herein reviewed. Finally, the anti-inflammatory activity of three COS mixtures was assayed in murine macrophages after stimulation with lipopolysaccharides.

scholarly journals Industrial Plume Properties Retrieved by Optimal Estimation Using Combined Hyperspectral and Sentinel-2 Data

2021 ◽  
Vol 13 (10) ◽  
pp. 1865
Author(s):  
Gabriel Calassou ◽  
Pierre-Yves Foucher ◽  
Jean-François Léon
Keyword(s):  
Matched Filter ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Model Parameters ◽  
Surface Reflectance ◽  
Sequential Method ◽  
Modal Radius ◽  
Sentinel 2

Stack emissions from the industrial sector are a subject of concern for air quality. However, the characterization of the stack emission plume properties from in situ observations remains a challenging task. This paper focuses on the characterization of the aerosol properties of a steel plant stack plume through the use of hyperspectral (HS) airborne remote sensing imagery. We propose a new method, based on the combination of HS airborne acquisition and surface reflectance imagery derived from the Sentinel-2 Multi-Spectral Instrument (MSI). The proposed method detects the plume footprint and estimates the surface reflectance under the plume, the aerosol optical thickness (AOT), and the modal radius of the plume. Hyperspectral surface reflectances are estimated using the coupled non-negative matrix factorization (CNMF) method combining HS and MSI data. The CNMF reduces the error associated with estimating the surface reflectance below the plume, particularly for heterogeneous classes. The AOT and modal radius are retrieved using an optimal estimation method (OEM), based on the forward model and allowing for uncertainties in the observations and in the model parameters. The a priori state vector is provided by a sequential method using the root mean square error (RMSE) metric, which outperforms the previously used cluster tuned matched filter (CTMF). The OEM degrees of freedom are then analysed, in order to refine the mask plume and to enhance the quality of the retrieval. The retrieved mean radii of aerosol particles in the plume is 0.125 μμm, with an uncertainty of 0.05 μμm. These results are close to the ultra-fine mode (modal radius around 0.1 μμm) observed from in situ measurements within metallurgical plant plumes from previous studies. The retrieved AOT values vary between 0.07 (near the source point) and 0.01, with uncertainties of 0.005 for the darkest surfaces and above 0.010 for the brightest surfaces.

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