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Related Concept Videos

Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

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The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
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Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Design Consideration01:22

Design Consideration

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Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
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Manipulation and Analysis01:21

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GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
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Stress Concentrations01:24

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Stress concentration is when stress intensifies near discontinuities such as holes or abrupt cross-sectional changes in a structural member. This localized stress can often surpass the average stress within the member. The stress distribution in flat bars, either with a circular hole or varying widths connected by fillets, can be determined experimentally using a photoelastic method. The results are based on ratios of geometric parameters like the ratio of the hole's radius to the smaller...
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A user exposure based approach for non-structural road network vulnerability analysis.

Lei Jin1,2, Haizhong Wang2, Binglei Xie1

  • 1School of Architecture and Urban Planning, Harbin Institute of Technology, Shenzhen, Guangdong, P.R. China.

Plos One
|November 28, 2017
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Summary
This summary is machine-generated.

This study introduces a new framework to assess urban road network vulnerability, focusing on non-structural impacts like travel time increases during heavy snow. The findings highlight significant disruptions caused by weather events.

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Area of Science:

  • Urban planning
  • Transportation engineering
  • Network analysis

Background:

  • Dense urban road networks face risks from non-structural disruptions.
  • Existing vulnerability assessments often overlook indirect consequences.
  • Weather events like heavy snow can severely impact urban mobility.

Purpose of the Study:

  • To propose a novel framework for analyzing non-structural road network vulnerability.
  • To develop metrics for negative consequences considering varied road conditions.
  • To introduce a new vulnerability index incorporating user exposure.

Main Methods:

  • Developed a non-structural road network vulnerability analysis framework.
  • Defined metrics for negative consequences accounting for road conditions.
  • Introduced a user-exposure-based vulnerability index.
  • Applied the methodology to the Sioux Falls network under heavy snow conditions.

Main Results:

  • Identified the vulnerability ranking of road network links during heavy snow.
  • Quantified significant increases in generalized travel time costs.
  • Demonstrated the framework's ability to capture network degeneration impacts.

Conclusions:

  • The proposed framework effectively assesses non-structural road network vulnerability.
  • Non-structural consequences lead to substantial increases in travel time costs.
  • The methodology provides insights into urban network resilience during adverse events.