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Related Concept Videos

Design Example: Maintaining Level of an Embankment01:19

Design Example: Maintaining Level of an Embankment

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Constructing a roadway embankment over uneven terrain requires precise leveling to ensure stability and proper drainage. Surveyors use a leveling instrument and staff to calculate ground elevations and determine the required fill material at each point along the embankment alignment.The process begins by positioning a leveling instrument near a benchmark with a known elevation. A backsight reading establishes the instrument height, which serves as a reference for subsequent measurements. A...
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Modeling and Similitude01:12

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Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
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Influence of Earth's Curvature and Atmospheric Refraction on Leveling01:26

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During leveling, the Earth's curvature and atmospheric refraction introduce deviations in the line of sight from a true horizontal reference. When the line of sight is leveled, it remains perpendicular to the plumb line only at a single point. Beyond this, it deviates due to the Earth’s curvature, represented by the correction C. For a sight distance D, the deviation can be derived using the relationship:This relationship shows that the deviation increases quadratically with distance.
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Design Example: Creating a Hydraulic Model of a Dam Spillway01:21

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Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.
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Fluid Pressure over Flat Plate of Variable Width01:02

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When a flat plate is submerged in a fluid, the fluid exerts pressure on the plate. This pressure can lead to many different phenomena, including drag and buoyancy. To understand the behavior of the fluid over a flat plate of variable width, it is essential to analyze the distribution of the pressure exerted.
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Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
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Related Experiment Video

Updated: Sep 4, 2025

Evolution of Staircase Structures in Diffusive Convection
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Emulating Ocean Dynamic Sea Level by Two-Layer Pattern Scaling.

Jiacan Yuan1,2,3,4, Robert E Kopp2,3

  • 1Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences Fudan University Shanghai China.

Journal of Advances in Modeling Earth Systems
|July 21, 2022
PubMed
Summary
This summary is machine-generated.

A new two-layer climate emulator accurately projects ocean dynamic sea level (DSL) changes. Lower emission scenarios show a reduced risk of sea level rise through 2300.

Keywords:
ocean dynamic sea levelpattern scalingsea level risethermal expansion

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Area of Science:

  • Climate Science
  • Oceanography
  • Sea Level Rise

Background:

  • Ocean dynamic sea level (DSL) change significantly impacts relative sea level (RSL) change.
  • Atmosphere-ocean general circulation models (GCMs) are typically used for DSL change projections.

Purpose of the Study:

  • To develop a novel two-layer climate emulator for interpolating and extending DSL change projections.
  • To improve the accuracy of DSL projections compared to existing methods.

Main Methods:

  • Development of a two-layer climate emulator to capture DSL evolution.
  • Interpolation between emission scenarios and extension of projections beyond GCM simulation time horizons.
  • Comparison with univariate pattern scaling emulator to assess accuracy improvements.

Main Results:

  • The two-layer emulator accurately reflects GCM behavior, capturing non-linearities and non-stationarities.
  • Significant reduction in global-averaged error (36% in RCP2.6, 24% in RCP4.5, 34% in RCP8.5) during 2271-2290 compared to univariate pattern scaling.
  • Probabilistic ensemble of DSL projections developed through 2300 for four emission scenarios (RCP2.6, RCP4.5, RCP8.5, SSP3-7.0).

Conclusions:

  • Projected DSL changes and associated uncertainties diminish with lower emission scenarios.
  • Low- and moderate-emission scenarios (RCP2.6, RCP4.5) present a reduced hazard of DSL rise compared to high-emission scenarios (SSP3-7.0, RCP8.5).