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Related Concept Videos

Quality of Water01:19

Quality of Water

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In concrete preparation, the quality of water is paramount as it affects the strength and durability of the concrete. Potable water is usually preferred; however, it must not have excessive sodium or potassium to prevent compromising the concrete's integrity. Water quality is typically evaluated based on impurities such as dissolved solids, chlorides, and sulfates, and its pH value is ideally between 6 and 8. Even slightly acidic natural water may be acceptable unless it contains harmful...
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Testing Water Quality01:14

Testing Water Quality

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When the quality of water for concrete preparation is uncertain, its impact on the setting time of cement and compressive strength of mortar is assessed by comparison with de-ionized or distilled water benchmarks. American Society for Testing and Materials (ASTM) C1602 requires the setting times to be within 90 minutes of the control, British Standard (BS) 3146:1980 allows a 30-minute variance in the initial setting, while British Standards European Norm (BS EN) 1008 specifies initial setting...
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Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

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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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Typical Model Studies01:30

Typical Model Studies

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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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Modeling and Similitude01:12

Modeling and Similitude

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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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Design Example: Creating a Hydraulic Model of a Dam Spillway01:21

Design Example: Creating a Hydraulic Model of a Dam Spillway

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Watershed Planning within a Quantitative Scenario Analysis Framework
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A cloud model-based approach for water quality assessment.

Dong Wang1, Dengfeng Liu1, Hao Ding1

  • 1Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, School of Earth Sciences and Engineering, State Key Laboratory of Pollution Control and Resource Reuse, Nanjing University, Nanjing 210046, China.

Environmental Research
|March 21, 2016
PubMed
Summary
This summary is machine-generated.

A new cloud model approach enhances water quality assessment by integrating randomness and fuzziness. This method accurately evaluates lake eutrophication, offering a reliable alternative to existing techniques.

Keywords:
Analytic hierarchy processCloud modelFuzzinessInformation entropyMulti-criteria decision-makingRandomness

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Area of Science:

  • Environmental Science
  • Information Science
  • Water Resource Management

Background:

  • Water quality assessment is a complex multi-criteria decision-making process.
  • Existing methods struggle to adequately account for qualitative and quantitative uncertainties like randomness and fuzziness.

Purpose of the Study:

  • To propose a novel cloud model-based approach for water quality assessment.
  • To address uncertainties in randomness and fuzziness inherent in water quality evaluations.

Main Methods:

  • Utilized a cognitive cloud model to bridge qualitative concepts and quantitative data.
  • Incorporated a bilateral boundary formula for parameter estimation and a hybrid entropy-analytic hierarchy process for weight calculation.
  • Employed repeated simulations to determine the degree of final certainty.

Main Results:

  • The cloud model approach was successfully applied to assess the eutrophication status of 12 Chinese lakes and reservoirs.
  • Compared the proposed method against Scoring Index, Variable Fuzzy Sets, Hybrid Fuzzy and Optimal, and Neural Networks methods.
  • The cloud model approach provided membership information for each water quality status, leading to accurate final assessments.

Conclusions:

  • The proposed cloud model-based approach is accurate and representative of alternative assessment methods.
  • This method offers a robust framework for handling uncertainties in water quality evaluation.
  • The approach demonstrates significant potential for practical application in water resource management.