scholarly journals Random Material Property Fields of 3D Concrete Microstructures Based on CT Image Reconstruction

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1423
Author(s):  
George Stefanou ◽  
Dimitrios Savvas ◽  
Panagiotis Metsis
Keyword(s):  
Random Fields ◽  
Volume Fraction ◽  
Concrete Specimen ◽  
Elasticity Tensor ◽  
Statistical Characteristics ◽  
Moving Window ◽  
Window Method ◽  
Ct Image Reconstruction ◽  
Random Material Property ◽  
Spatially Varying

The purpose of this paper is to determine the random spatially varying elastic properties of concrete at various scales taking into account its highly heterogeneous microstructure. The reconstruction of concrete microstructure is based on computed tomography (CT) images of a cubic concrete specimen. The variability of the local volume fraction of the constituents (pores, cement paste and aggregates) is quantified and mesoscale random fields of the elasticity tensor are computed from a number of statistical volume elements obtained by applying the moving window method on the specimen along with computational homogenization. Based on the statistical characteristics of the mesoscale random fields, it is possible to assess the effect of randomness in microstructure on the mechanical behavior of concrete.

scholarly journals PPT-NS: Prioritized Progressive Trend Based Navigational System on GPS data with Artifacts

2019 ◽  
Vol 9 (2) ◽  
pp. 621-630
Keyword(s):  
Global Positioning System ◽  
Gps Data ◽  
Moving Window ◽  
Location Service ◽  
Window Method ◽  
Global Positioning ◽  
Trajectory Mapping ◽  
Coefficient Corrélation ◽  
Navigational System ◽  
Processing Techniques

The Global Positioning System is extensively used in the various context and location service-based applications. Any kind of abnormalities requires an efficient and suitable pre-processing algorithm to be implemented on the data which provides accurate results when used in the application synchronizations. This paper illustrates a framework for various pre-processing techniques applied to the real-time GPS data and its effect on trajectory mapping. The technique used includes Prioritized pattern-based, Savitzky-Golay filtering, outlier elimination, de-trending, and coefficient correlation. The performance assessment of methods discussed in this study is calculated in terms of accuracy with the original and re-created trajectory after the pre-processing and found that the best result is given by moving window method.

scholarly journals Conducting statistical analysis of the three-dimensional juvenile model angiofibromas of the base of the human skull for planning purposes surgical treatment of the tumor

2012 ◽  
Vol 16 (5) ◽  
pp. 55-61
Author(s):  
S.M. Alhіmova ◽  
V.P. YAcenko
Keyword(s):  
Surgical Treatment ◽  
Blood Loss ◽  
Volume Fraction ◽  
Three Dimensional ◽  
3D Models ◽  
Statistical Characteristics ◽  
Vascular Volume ◽  
Juvenile Angiofibroma ◽  
Human Skull ◽  
Massive Blood Loss

The usage possibility of statistical characteristics for anatomical 3D-models of tumor is considered in the solutions the problem to predict the risk of massive blood loss during surgical tumors removal. This problem is considered on Juvenile Angiofibroma example. Results of experiments are given which confirm the dependence of statistical characteristics' values on such perfusion characteristics as relative vascular volume fraction of tumors tissue. Correlation analysis found relationship between statistical characteristics' values and specific volume of blood loss, that was obtained according to Juvenile Angiofibromas removal surgery data

scholarly journals Numerical Simulation of Water Based Ferrofluid Flows along Moving Surfaces

Processes ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 830
Author(s):  
Gabriella Bognár ◽  
Krisztián Hriczó
Keyword(s):  
Volume Fraction ◽  
Solid Volume Fraction ◽  
Skin Friction Coefficient ◽  
Zn Ferrite ◽  
Water Based ◽  
Dimensional Boundary ◽  
Layer Flow ◽  
Spatially Varying ◽  
The Impact ◽  
Similarity Method

The steady two-dimensional boundary layer flow past a stretching flat sheet in a water-based ferrofluid is investigated. The spatially varying magnetic field is created by two line currents. The similarity method is applied to transform the governing equations into a system of coupled ordinary differential equations. Numerical investigations are performed for ferrofluids, the suspensions of water, and three types of ferroparticles (magnetite, cobalt ferrite, and Mn-Zn ferrite). The impact of the solid volume fraction, the surface stretching parameter, and the ferromagnetic coefficient on the dimensionless velocity and temperature profiles, the skin friction coefficient, and the local Nusselt number are analysed for the three types of ferrofluid.

scholarly journals Concatenation of the Moving Window Technique for Auditory-Perceptual Analysis of Voice Quality

2018 ◽  
Vol 27 (4) ◽  
pp. 1426-1433
Author(s):  
Benjamin Ehrlich ◽  
Liyu Lin ◽  
Jack Jiang
Keyword(s):  
Sensitivity And Specificity ◽  
Characteristic Curve ◽  
Voice Quality ◽  
Moving Window ◽  
Perceptual Analysis ◽  
Perceptual Evaluation ◽  
Window Method ◽  
Window Technique ◽  
Pathological Voice ◽  
Higher Sensitivity

Purpose The purpose of this study is to develop a program to concatenate acoustic vowel segments that were selected with the moving window technique, a previously developed technique used to segment and select the least perturbed segment from a sustained vowel segment. The concatenated acoustic segments were compared with the nonconcatenated, short, individual acoustic segments for their ability to differentiate normal and pathological voices. The concatenation process sometimes created a clicking noise or beat, which was also analyzed to determine any confounding effects. Method A program was developed to concatenate the moving window segments. Listeners with no previous rating experience were trained and, then, rated 20 normal and 20 pathological voice segments, both concatenated (2 s) and short (0.2 s) for a total of 80 segments. Listeners evaluated these segments on both the Grade, Roughness, Breathiness, Asthenia, and Strain scale (GRBAS; 8 listeners) and the Consensus Auditory-Perceptual Evaluation of Voice (Kempster, Gerratt, Abbott, Barkmeier-Kraemer, & Hillman, 2009) scale (7 listeners). The sensitivity and specificity of these ratings were analyzed using a receiver-operating characteristic curve. To evaluate if there were increases in particular criteria due to the beat, differences between beat and nonbeat ratings were compared using a 2-tailed analysis of variance. Results Concatenated segments had a higher sensitivity and specificity for distinguishing pathological and normal voices than short segments. Compared with nonbeat segments, the beat had statistically similar increases for all criteria across Consensus Auditory-Perceptual Evaluation of Voice and GRBAS scales, except pitch and loudness. Conclusions The concatenated moving window method showed improved sensitivity and specificity for detecting voice disorders using auditory-perceptual analysis, compared with the short moving window segment. It is a helpful tool for perceptual analytic protocols, allowing for voice evaluation using standardized and automated voice-segmenting procedures. Supplemental Material https://doi.org/10.23641/asha.7100951

scholarly journals Correcting Marine Surface Winds Simulated in Atmospheric Models Using Spatially and Temporally Varying Linear Regression

2014 ◽  
Vol 29 (2) ◽  
pp. 305-330 ◽  
Author(s):  
Tom H. Durrant ◽  
Diana J. M. Greenslade ◽  
Ian Simmonds ◽  
Frank Woodcock
Keyword(s):  
Linear Regression ◽  
Atmospheric Model ◽  
Correction Method ◽  
Wind Forcing ◽  
Moving Window ◽  
Operational Environment ◽  
Atmospheric Models ◽  
Marine Surface ◽  
Spatially Varying ◽  
Self Learning

Abstract This study examines the application of three different variations of linear-regression corrections to the surface marine winds from the Australian Bureau of Meteorology’s recently implemented operational atmospheric model. A simple correction over the entire domain is found to inadequately account for geographical variation in the wind bias. This is addressed by considering corrections that vary in space. Further, these spatially varying corrections are extended to vary in time. In an operational environment, the error characteristics of the wind forcing can be expected to change over time with the evolution of the atmospheric model. This in turn requires any applied correction to be monitored and maintained. Motivated by a desire to avoid this manual maintenance, a self-learning correction method is proposed whereby spatially and temporally varying corrections are calculated in real time from a moving window of historical comparisons between observations and preceding forecasts. This technique is shown to effectively remove both global and regionally varying wind speed biases.

Parametric Modeling Method for Composite Microstructure Virtual Testing

2010 ◽  
Vol 97-101 ◽  
pp. 1661-1664
Author(s):  
Zhen Qing Wang ◽  
Xiao Qiang Wang ◽  
Ji Feng Zhang ◽  
Song Zhou
Keyword(s):  
Function Method ◽  
Volume Fraction ◽  
Parametric Modeling ◽  
Modeling Method ◽  
Window Function ◽  
Moving Window ◽  
Fiber Volume ◽  
Virtual Testing ◽  
Distribution Features ◽  
Composite Microstructure

A method of parametric modeling composite microstructure is proposed. It can be used for composite microstructure virtual testing and optimization procedure. Considering the fiber random distribution features of composite microstructure and the flaw distribution in the fibers, a three dimensional parametric model has been built in this paper. Then, the sizes of the composite representative volume element (RVE) generated by the method are determined by moving-window function method. These models are close to reality and can be used for further virtual testing. Finally, numerical experiment is presented by the secondary development of the finite element packages (ABAQUS) via Python language programming to verify the proposed method. The following conclusions are obtained: (i) fiber volume fraction of the composite structure model reaches 65% by the modeling method, which meets the majority engineering demands; (ii) stress distribution feature of RVE generated by using moving-window function method coincides with general prediction.

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