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Related Concept Videos

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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

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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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Related Experiment Video

Updated: Dec 12, 2025

Experimental Methods for Investigation of Shape Memory Based Elastocaloric Cooling Processes and Model Validation
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Hindered and compression solid settling functions - Sensor data collection, practical model identification and

Benedek G Plósz1, Javier Climent2, Christopher T Griffin3

  • 1Department of Chemical Engineering, University of Bath, Claverton Down, Bath, BA2 7AY, UK; Dept. of Environmental Engineering, Technical University of Denmark, Bygningstorvet, Building 115, 2800, Kgs. Lyngby, Denmark.

Water Research
|August 7, 2020
PubMed
Summary

Accurate modeling of activated sludge settling velocity is crucial for water resource recovery facilities. This study identifies new settling functions and optimal sensor data for reliable predictions, even during challenging conditions like filamentous bulking.

Keywords:
Compression solid concentration and effective solid stressComputational fluid dynamics (CFD)Hindered and compression solid settling velocityOne-dimensional modelPractical model identificationSettling column sensor

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Area of Science:

  • Environmental Engineering
  • Water Treatment
  • Wastewater Treatment

Background:

  • Secondary settling tanks (SSTs) are critical but hydraulically sensitive in activated sludge water resource recovery facilities (WRRFs).
  • Predictive models for activated sludge settling velocity contain irreducible epistemic uncertainty, necessitating regular calibration.
  • Accurate settling velocity models are vital to prevent process failures, especially under high flow or filamentous bulking conditions.

Purpose of the Study:

  • To determine if constitutive functions for hindered and compression settling allow unique parameter estimation.
  • To establish the optimal sensor data requirements for developing reliable settling velocity functions.
  • To improve the predictive capacity of activated sludge models for WRRFs.

Main Methods:

  • Utilized innovative settling column sensor technology and full-scale operational data.
  • Developed and validated an amended Vesilind function for hindered settling.
  • Formulated and validated a novel exponential function for compression settling velocity.
  • Employed one-dimensional and computational fluid dynamics (CFD) simulations for analysis.

Main Results:

  • Demonstrated practical model identifiability for settling velocity parameters under both well-settling and filamentous bulking scenarios.
  • Validated new constitutive functions for hindered and compression settling.
  • Provided insights into the sensor data requirements for accurate model calibration.

Conclusions:

  • The study successfully identified and validated new settling velocity functions, enhancing model reliability.
  • Unique parameter estimation is achievable for hindered and compression settling under tested conditions.
  • The findings contribute to more robust process control and capacity prediction in wastewater treatment plants.