scholarly journals Prediction on Water-flowing Fractured Region Based on 3D Simulation Technology

2016 ◽  
Vol 10 (1) ◽  
pp. 349-360
Author(s):  
Cai Zi-Zhao ◽  
Zhang Fa-Wang ◽  
Xu Wei ◽  
Chen Li
Keyword(s):  
Interpolation Method ◽  
Three Dimensional ◽  
Simulated Data ◽  
Simulation Technology ◽  
Study Region ◽  
Fractured Zone ◽  
Stratigraphic Model ◽  
Caving Zone ◽  
Drilling Technology ◽  
Information System Technology

Caving zone and fractured zone both appear in the Changzhi Basin in China as the a large number of coal are mined from the area. Based on ore cluster mining and on GIS (Geographic Information System) technology, in the paper, it combines the 3-D (three dimensional) simulation technology and adopts the spacial interpolation method to develop the 3-D stratigraphic model of the studied region, the 3D stratigraphic model and the division idea which is applicable for the study region are obtained. The virtual drilling technology is applied to obtain precise stratigraphic data and calculate the heights of the caving zone and fractured zone of Changzhi Basin, their relative locations to the overlying aquifer and the water-flowing fractured region of influence based on computer-simulated data are both analyzed. In addition, it also puts forward the concept of effective water-flowing fractured rate, which lays a solid foundation for further study on the heterogeneous evolution of the spatial structure of regional aquifers after the coal mining which also can provide a data support for future studies on the heterogeneous evolution features of water-bearing media.

scholarly journals UAV-Assisted Three-Dimensional Spectrum Mapping Driven by Spectrum Data and Channel Model

Symmetry ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2308
Author(s):  
Xiaofu Du ◽  
Qiuming Zhu ◽  
Guoru Ding ◽  
Jie Li ◽  
Qihui Wu ◽  
...  
Keyword(s):  
Spatial Data ◽  
Channel Model ◽  
Interpolation Method ◽  
Three Dimensional ◽  
Simulated Data ◽  
Reconstruction Algorithm ◽  
Decision Mechanism ◽  
Spectrum Scarcity ◽  
Distance Weighted ◽  
Spectrum Data

As the number of civil aerial vehicles increase explosively, spectrum scarcity and security become an increasingly challenge in both the airspace and terrestrial space. To address this difficulty, this paper presents an unmanned aerial vehicle-assisted (UAV-assisted) spectrum mapping system and a spectrum data reconstruction algorithm driven by spectrum data and channel model are proposed. The reconstruction algorithm, which includes a model-driven spectrum data inference method and a spectrum data completion method with uniformity decision mechanism, can reconstruct limited and incomplete spectrum data to a three-dimensional (3D) spectrum map. As a result, spectrum scarcity and security can be achieved. Spectrum mapping is a symmetry-based digital twin technology. By employing an uniformity decision mechanism, the proposed completion method can effectively interpolate spatial data even when the collected data are unevenly distributed. The effectiveness of the proposed mapping scheme is evaluated by comparing its results with the ray-tracing simulated data of the campus scenario. Simulation results show that the proposed reconstruction algorithm outperforms the classical inverse distance weighted (IDW) interpolation method and the tensor completion method by about 12.5% and 92.3%, respectively, in terms of reconstruction accuracy when the collected spectrum data are regularly missing, unevenly distributed and limited.

Application of Three-Dimensional Interpolation Methods in Contaminated Site Evaluation

2014 ◽  
Vol 878 ◽  
pp. 782-790 ◽  
Author(s):  
Wen Xia Wei ◽  
Teng Quan ◽  
Yan Wang ◽  
Hai Jian Wang ◽  
Pei Zhong Li
Keyword(s):  
Prediction Model ◽  
Nearest Neighbor ◽  
Interpolation Method ◽  
Three Dimensional ◽  
Lead Contamination ◽  
Contaminated Sites ◽  
Contaminated Site ◽  
Interpolation Methods ◽  
Kriging Interpolation Method ◽  
Stratigraphic Model

Contaminated sites remediation is one of the hot points in environmental protection fields. Therefore, an important research project is how to expediently determine the bound and level of pollution of contaminated sites. This may help to decide on a timely and accurate rescue plan so as to minimize the costs and to improve the effect of restoration. This is also the basis of contaminated sites remediation acceptance. There are many influencing factors to confirm the remediation areas on contaminated sites. Studies show that three-dimensional interpolation method is effective tool to delimit the pollution scope. Different three-dimensional interpolation methods have different results in contaminate distribution prediction and directly affect the boundary of contamination. This paper selects one specific case with heavy metal lead contamination to study three-dimensional interpolation methods. The three-dimensional stratigraphic model is established for uncertainty analysis and error analysis in the grid through KrigingIDW(Shepard) and nearest neighbor interpolation method. Results show that 40m*40m grids have the highest accuracy of stratigraphic simulation. Nearest neighbor interpolation method is most suitable for stratigraphic model building. Kriging interpolation method is more suitable for constructing three-dimensional pollutant prediction model. On the basis of above, this text established one distribution prediction model of soil lead contamination, and calculated the contaminated earthwork quantity under different remediation goals. Finally, the paper achieved three-dimensional visualization of the site soil contamination. This study can be directly applied to the actual site remediation decision process, and is helpful for the contaminated sites evaluation and restoration in the future.

scholarly journals A Novel LOS Decision Technique Reflecting 3D DTED for Modeling an Electronic Warfare Environment

2021 ◽  
Vol 11 (1) ◽  
pp. 409
Author(s):  
Jaejoong Lee ◽  
Chiho Lee ◽  
Hyeon Hwi Lee ◽  
Kyung Tae Park ◽  
Hyun-Kyo Jung ◽  
...  
Keyword(s):  
Interpolation Method ◽  
Three Dimensional ◽  
Superior Performance ◽  
Line Of Sight ◽  
Electronic Warfare ◽  
Decision Algorithm ◽  
Elevation Data ◽  
The Republic ◽  
Point Distance ◽  
Terrain Elevation

A new line-of-sight (LOS) decision algorithm applicable to simulation of electronic warfare (EW) is developed. For accurate simulation, the digital terrain elevation data (DTED) of the region to be analyzed must be reflected in the simulation, and millions of datasets are necessary in the EW environment. In order to obtain real-time results in such an environment, a technology that determines line-of-sight (LOS) quickly and accurately is very important. In this paper, a novel algorithm is introduced for determining LOS that can be applied in an EW environment with three-dimensional (3D) DTED. The proposed method shows superior performance as compared with the simplest point-to-point distance calculation method and it is also 50% faster than the conventional interpolation method. The DTED used in this paper is the data applied as level 0 for the Republic of Korea, and the decision of the LOS at approximately 1.8 million locations viewed by a reconnaissance plane flying 10 km above the ground is determined within 0.026 s.

scholarly journals How Stereological Analysis of Vascular Morphology Can Quantify the Blood Volume Fraction as a Marker for Tumor Vasculature: Comparison with Magnetic Resonance Imaging

2011 ◽  
Vol 32 (3) ◽  
pp. 489-501 ◽  
Author(s):  
Adriana T Perles-Barbacaru ◽  
Boudewijn PJ van der Sanden ◽  
Regine Farion ◽  
Hana Lahrech
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Rat Brain ◽  
Blood Volume ◽  
Volume Fraction ◽  
Three Dimensional ◽  
Simulated Data ◽  
Tumor Model ◽  
Tumor Vasculature ◽  
Resonance Imaging

To assess angiogenesis noninvasively in a C6 rat brain tumor model, the rapid-steady-state- T1 (RSST1) magnetic resonance imaging (MRI) method was used for microvascular blood volume fraction (BVf) quantification with a novel contrast agent gadolinium per (3,6 anhydro) α-cyclodextrin (Gd-ACX). In brain tissue contralateral to the tumor, equal BVfs were obtained with Gd-ACX and the clinically approved gadoterate meglumine (Gd-DOTA). Contrary to Gd-DOTA, which leaks out of the tumor vasculature, Gd-ACX was shown to remain vascular in the tumor tissue allowing quantification of the tumor BVf. We sought to confirm the obtained tumor BVf using an independent method: instead of using a ‘standard’ two-dimensional histologic method, we study here how vascular morphometry combined with a stereological technique can be used for three-dimensional assessment of the vascular volume fraction ( VV). The VV is calculated from the vascular diameter and length density. First, the technique is evaluated on simulated data and the healthy rat brain vasculature and is then applied to the same C6 tumor vasculature previously quantified by RSST1-MRI with Gd-ACX. The mean perfused VV and the BVf obtained by MRI in tumor regions are practically equal and the technique confirms the spatial heterogeneity revealed by MRI.

Evaluation of Actual Geometric Tolerances Using Coordinate Measuring Machine Data

1989 ◽  
Author(s):  
W. H. ElMaraghy ◽  
Z. Wu ◽  
H. A. ElMaraghy
Keyword(s):  
Three Dimensional ◽  
Measurement Data ◽  
Simulated Data ◽  
Coordinate Measuring Machine ◽  
Optimization Techniques ◽  
Test Cases ◽  
Tolerance Zone ◽  
Geometric Tolerances ◽  
Measuring Machine

Abstract This paper focuses on the development of a procedure and algorithms for the systematic comparison of geometric variations of measured features with their specified geometric tolerances. To automate the inspection of mechanical parts, it is necessary to analyze the measurement data captured by coordinate measuring machines (CMM) in order to detect out-of-tolerance conditions. A procedure for determining the geometric tolerances from the measured three dimensional coordinates on the surface of a cylindrical feature is presented. This procedure follows the definitions of the geometric tolerances used in the current Standards, and is capable of determining the value of each geometric tolerance from the composite 3-D data. The developed algorithms adopt the minimum tolerance zone criterion. Nonlinear numerical optimization techniques are used to fit the data to the minimum tolerance zone. Two test cases are given in the paper which demonstrate the successful determination of geometric tolerances from given simulated data.

Abstract 224: A Deep Learning Approach to Left-Ventricular Chamber Quantification for Fully Automated Three Dimensional Strain Analysis in Cardiotoxicity

2020 ◽  
Vol 127 (Suppl_1) ◽  
Author(s):  
Bryant M Baldwin ◽  
Shane Joseph ◽  
Xiaodong Zhong ◽  
Ranya Kakish ◽  
Cherie Revere ◽  
...  
Keyword(s):  
Deep Learning ◽  
Interpolation Method ◽  
Three Dimensional ◽  
Strain Analysis ◽  
Correlation Coefficients ◽  
Semantic Segmentation ◽  
Left Ventricular ◽  
Breast Cancer Patients ◽  
Left Ventricular Chamber ◽  
Longitudinal Strains

This study investigated MRI and semantic segmentation-based deep-learning (SSDL) automation for left-ventricular chamber quantifications (LVCQ) and low longitudinal strain (LLS) determination, thus eliminating user-bias by providing an automated tool to detect cardiotoxicity (CT) in breast cancer patients treated with antineoplastic agents. Displacement Encoding with Stimulated Echoes-based (DENSE) myocardial images from 26 patients were analyzed with the tool’s Convolution Neural Network with underlying Resnet-50 architecture. Quantifications based on the SSDL tool’s output were for LV end-diastolic diameter (LVEDD), ejection fraction (LVEF), and mass (LVM) (see figure for phase sequence). LLS was analyzed with Radial Point Interpolation Method (RPIM) with DENSE phase-based displacements. LVCQs were validated by comparison to measurements obtained with an existing semi-automated vendor tool (VT) and strains by 2 independent users employing Bland-Altman analysis (BAA) and interclass correlation coefficients estimated with Cronbach’s Alpha (C-Alpha) index. F1 score for classification accuracy was 0.92. LVCQs determined by SSDL and VT were 4.6 ± 0.5 vs 4.6 ± 0.7 cm (C-Alpha = 0.93 and BAA = 0.5 ± 0.5 cm) for LVEDD, 58 ± 5 vs 58 ± 6 % (0.90, 1 ± 5%) for LVEF, 119 ± 17 vs 121 ± 14 g (0.93, 5 ± 8 g) for LV mass, while LLS was 14 ± 4 vs 14 ± 3 % (0.86, 0.2 ± 6%). Hence, equivalent LV dimensions, mass and strains measured by VT and DENSE imaging validate our unique automated analytic tool. Longitudinal strains in patients can then be analyzed without user bias to detect abnormalities for the indication of cardiotoxicity and the need for therapeutic intervention even if LVEF is not affected.

scholarly journals Effect of DEM Interpolation Neighbourhood on Terrain Factors

2019 ◽  
Vol 8 (1) ◽  
pp. 30 ◽  
Author(s):  
Ying Zhu ◽  
Xuejun Liu ◽  
Jing Zhao ◽  
Jianjun Cao ◽  
Xiaolei Wang ◽  
...  
Keyword(s):  
Interpolation Method ◽  
Simulated Data ◽  
Topographic Features ◽  
Structure And Morphology ◽  
Digital Elevation ◽  
Different Types ◽  
Slope Error ◽  
Elevation Model ◽  
The Impact ◽  
Mls Method

Topographic factors such as slope and aspect are essential parameters in depicting the structure and morphology of a terrain surface. We study the effect of the number of points in the neighbourhood of a digital elevation model (DEM) interpolation method on mean slope, mean aspect, and RMSEs of slope and aspect from the interpolated DEM. As the moving least squares (MLS) method can maintain the inherent properties and other characteristics of a surface, this method is chosen for DEM interpolation. Three areas containing different types of topographic features are selected for study. Simulated data from a Gauss surface is also used for comparison. First, the impact of the number of points on the DEM root mean square error (RMSE) is analysed. The DEM RMSE in the three study areas decreases gradually with the number of points in the neighbourhood. In addition, the effect of the number of points in the neighbourhood on mean slope and mean aspect was studied across varying topographies through regression analysis. The two variables respond differently to changes in terrain. However, the RMSEs of the slope and aspect in all study areas are logarithmically related to the number of points in the neighbourhood and the values decrease uniformly as the number of points in the neighbourhood increases. With more points in the neighbourhood, the RMSEs of the slope and aspect are not sensitive to topography differences and the same trends are observed for the three studied quantities. Results for the Gauss surface are similar. Finally, this study analyses the spatial distribution of slope and aspect errors. The slope error is concentrated in ridges, valleys, steep-slope areas, and ditch edges while the aspect error is concentrated in ridges, valleys, and flat regions. With more points in the neighbourhood, the number of grid cells in which the slope error is greater than 15° is gradually reduced. With similar terrain types and data sources, if the calculation efficiency is not a concern, sufficient points in the spatial autocorrelation range should be analysed in the neighbourhood to maximize the accuracy of the slope and aspect. However, selecting between 10 and 12 points in the neighbourhood is economical.

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