Statistical Characteristics and Correlation Analysis for Control Index of Soil-Aggregate Mixture

2013 ◽  
Vol 718-720 ◽  
pp. 1872-1877 ◽  
Author(s):  
Xu Xi Chang ◽  
Xie Jian Ming ◽  
Jiang Ling Fa ◽  
Chen Shan Xiong
Keyword(s):  
Grain Size ◽  
Correlation Analysis ◽  
Normal Distribution ◽  
Large Scale ◽  
Soil Aggregate ◽  
Site Preparation ◽  
Statistical Characteristics ◽  
Coarse Grain ◽  
Systematic Research ◽  
Large Variability

Currently, the soil-aggregate mixture has been widely used in some large-scale site preparation projects, compaction characteristics has been pay more attention by many engineers and researchers. However, systematic research is insufficient on how to choose the filler. Moreover, some industry regulations are different on the requirements about filler. This paper relies on a certain big site preparation projects, discussing statistical characteristics and correlation on the maximal grain size, contents of the coarse grain, gradation and other parameters of soil-aggregate mixture. The results show that the maximal and the median grain size have small discreteness and normal distribution, indicating site filler is easy to reach the requirement; The coefficient of curvature, coefficient of nonuniformity and the coarse grain content have large discreteness, and dont obey normal distribution, indicating the filler has large variability. The median grain size is highly relevant to the coarse grain content; the maximal grain size isnt relevant to the coefficient of nonuniformity, the coefficient of curvature and the coarse grain content. According to the results of correlation analysis, we suggest that the importance order follow by coarse grain content, the maximum grain size and gradation for the control parameters of filler. This research may be significant to other similar projects.

scholarly journals Risk Assessment of Large-Scale Infrastructure Projects—Assumptions and Context

2020 ◽  
Vol 11 (1) ◽  
pp. 109
Author(s):  
Jana Korytárová ◽  
Vít Hromádka
Keyword(s):  
Risk Assessment ◽  
Economic Efficiency ◽  
Large Scale ◽  
Cash Flows ◽  
Statistical Characteristics ◽  
Individual Risk ◽  
Dependent Variables ◽  
Research Findings ◽  
Input Variables ◽  
Individual Risk Factors

This article deals with the partial outputs of large-scale infrastructure project risk assessment, specifically in the field of road and motorway construction. The Department of Transport spends a large amount of funds on project preparation and implementation, which however, must be allocated effectively, and with knowledge of the risks that may accompany them. Therefore, documentation for decision-making on project financing also includes their analysis. This article monitors the frequency of occurrence of individual risk factors within the qualitative risk analysis, with the support of the national risk register, and identifies dependent variables that represent part of the economic cash flows for determining project economic efficiency. At the same time, it compares these dependent variables identified by sensitivity analysis with critical variables, followed by testing the interaction of the critical variables’ effect on the project efficiency using the Monte Carlo method. A partial section of the research was focused on the analysis of the probability distribution of input variables, especially “the investment costs” and “time savings of infrastructure users” variables. The research findings conclude that it is necessary to pay attention to the setting of statistical characteristics of variables entering the economic efficiency indicator calculations, as the decision of whether or not to accept projects for funding is based on them.

MULTIFRACTAL DETRENDED CROSS-CORRELATION ANALYSIS FOR LARGE-SCALE WAREHOUSE-OUT BEHAVIORS

Fractals ◽  
2015 ◽  
Vol 23 (04) ◽  
pp. 1550044 ◽  
Author(s):  
CAN-ZHONG YAO ◽  
JI-NAN LIN ◽  
XU-ZHOU ZHENG
Keyword(s):  
Correlation Analysis ◽  
Large Scale ◽  
Cross Correlation ◽  
Correlation Property ◽  
Long Term Memory ◽  
Correlation Relationship ◽  
Term Memory ◽  
Wire Rod ◽  
Cross Correlation Analysis

Based on cross-correlation algorithm, we analyze the correlation property of warehouse-out quantity of different warehouses, respectively, and different products of each warehouse. Our study identifies that significant cross-correlation relationship for warehouse-out quantity exists among different warehouses and different products of a warehouse. Further, we take multifractal detrended cross-correlation analysis for warehouse-out quantity among different warehouses and different products of a warehouse. The results show that for the warehouse-out behaviors of total amount, different warehouses and different products of a warehouse significantly follow multifractal property. Specifically for each warehouse, the coupling relationships of rebar and wire rod reveal long-term memory characteristics, no matter for large fluctuation or small one. The cross-correlation effect on long-range memory property among warehouses probably has less to do with product types,and the long-term memory of YZ warehouse is greater than others especially in total amount and wire rod product. Finally, we shuffle and surrogate data to explore the source of multifractal cross-correlation property in logistics system. Taking the total amount of warehouse-out quantity as example, we confirm that the fat-tail distribution of warehouse-out quantity sequences is the main factor for multifractal cross-correlation. Through comparing the performance of the multifractal detrended cross-correlation analysis (MF-DCCA), centered multifractal detrending moving average cross-correlation analysis (MF-X-DMA) algorithms, the forward and backward MF-X-DMA algorithms, we find that the forward and backward MF-X-DMA algorithms exhibit a better performance than the other ones.

Enriching Activity-Based Models using Smartphone-Based Travel Surveys

2018 ◽  
Vol 2672 (42) ◽  
pp. 280-291 ◽  
Author(s):  
Bat-hen Nahmias-Biran ◽  
Yafei Han ◽  
Shlomo Bekhor ◽  
Fang Zhao ◽  
Christopher Zegras ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Large Scale ◽  
Leisure Activities ◽  
Behavior Modeling ◽  
Machine Learning Techniques ◽  
Initial Field ◽  
Activity Data ◽  
Large Variability ◽  
Tel Aviv ◽  
Household Travel Surveys

Smartphone-based travel surveys have attracted much attention recently, for their potential to improve data quality and response rate. One of the first such survey systems, Future Mobility Sensing (FMS), leverages sensors on smartphones, and machine learning techniques to collect detailed personal travel data. The main purpose of this research is to compare data collected by FMS and traditional methods, and study the implications of using FMS data for travel behavior modeling. Since its initial field test in Singapore, FMS has been used in several large-scale household travel surveys, including one in Tel Aviv, Israel. We present comparative analyses that make use of the rich datasets from Singapore and Tel Aviv, focusing on three main aspects: (1) richness in activity behaviors observed, (2) completeness of travel and activity data, and (3) data accuracy. Results show that FMS has clear advantages over traditional travel surveys: it has higher resolution and better accuracy of times, locations, and paths; FMS represents out-of-work and leisure activities well; and reveals large variability in day-to-day activity pattern, which is inadequately captured in a one-day snapshot in typical traditional surveys. FMS also captures travel and activities that tend to be under-reported in traditional surveys such as multiple stops in a tour and work-based sub-tours. These richer and more complete and accurate data can improve future activity-based modeling.

scholarly journals Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data

2019 ◽  
Vol 67 (2) ◽  
pp. 306-319 ◽  
Author(s):  
Charilaos I. Kanatsoulis ◽  
Xiao Fu ◽  
Nicholas D. Sidiropoulos ◽  
Mingyi Hong
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Large Scale ◽  
Large Scale Data ◽  
Scale Data

scholarly journals Bimodal Grain-Size Scaling of Thermal Transport in Polycrystalline Graphene from Large-Scale Molecular Dynamics Simulations

Nano Letters ◽  
2017 ◽  
Vol 17 (10) ◽  
pp. 5919-5924 ◽  
Author(s):  
Zheyong Fan ◽  
Petri Hirvonen ◽  
Luiz Felipe C. Pereira ◽  
Mikko M. Ervasti ◽  
Ken R. Elder ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Grain Size ◽  
Molecular Dynamics Simulations ◽  
Thermal Transport ◽  
Large Scale ◽  
Size Scaling ◽  
Dynamics Simulations ◽  
Bimodal Grain Size

Investigation of Mechanical Properties of Nanostructured Titanium Processed by Warm ECAP Followed Cold Rolling

2014 ◽  
Vol 875-877 ◽  
pp. 63-67 ◽  
Author(s):  
Dinh van Hai ◽  
Nguyen Trong Giang
Keyword(s):  
Mechanical Properties ◽  
Grain Size ◽  
Tensile Strength ◽  
Cold Rolling ◽  
Room Temperature ◽  
Pure Titanium ◽  
Rolling Process ◽  
Coarse Grain ◽  
Nanostructured Titanium

In this work, ECAP technique was combined with cold rolling process in order to enhance mechanical properties and microstructure of pure Titanium. Coarse grain (CG) Titanium with original grain size of 150 μm had been pressed by ECAP at 425oC by 4, 8 and 12 passes, respectively. This process then was followed by rolling at room temperature with 35%, 55%, and 75% rolling strains. After two steps, mechanical properties such as strength, hardness and microstructure of processed Titanium have been measured. The result indicated significant effect of cold rolling on tensile strength, hardness and microstructure of ECAP-Titanium.

scholarly journals Facies Evaluation and Depositional Environments of Carbonates of the Bagh Group, Dhar District, Madhya Pradesh, India

2021 ◽  
Vol 38 (1) ◽  
pp. 33-40
Author(s):  
Sreejita Chatterjee ◽  
Dhiren Kumar Ruidas
Keyword(s):  
Grain Size ◽  
Large Scale ◽  
Energy Condition ◽  
Size Variation ◽  
High Energy ◽  
Depositional Environments ◽  
Small Scale ◽  
Peninsular India ◽  
Sedimentary Structures ◽  
Nodular Limestone

A significant event of marine transgression took place in Central India during Late Turonian-Coniacian. Fossiliferous marine succession of Bagh Group is one of the few carbonate successions exposed in peninsular India which was in focus of the current study for understanding this event. The signatures of this event were identified in the carbonate succession. The carbonates of Bagh Group are composed of two formations: the lower part is represented by Nodular limestone Formation which is overlain by Bryozoan limestone Formation at the top. On the basis of grain size variation and sedimentary structures, the Nodular limestone is divisible into three facies: facies ‘A’, facies ‘B’ and facies ‘C’. A hardground exists between facies B and facies C. Lack of sedimentary structures and high mud content indicates low energy depositional setting for the Nodular limestone Formation. Similarly, Bryozoan limestone Formation is divisible into five facies: facies ‘D’, facies ‘E’, facies ‘F’, facies ‘G’ and facies ‘H’ based on grain size variation and sedimentary structures. All of these five facies are fossiliferous. Glauconites are present within facies ‘G’ and have two modes of occurrence - as infilling within Bryozoan limestone and as altered feldspar. Presence of both small- and large-scale cross-stratification in Bryozoan limestone with lesser mud content are indicative of high energy shallow marine conditions. Large-scale cross-stratifications are possibly representing tidal bars while the small scale cross stratifications are formed in inter bar setting. Presence of reactivation surfaces within facies ‘E’ also supports their tidal origin. Increase in depositional energy condition is also evident from dominated by packstone facies.

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