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Design Example: Managing Concrete Workability

Design Example: Managing Concrete Workability

This example deals with managing the workability of concrete for a raft foundation project under hot weather conditions. Workability is crucial for ensuring the concrete is easy to place, compact, and finish. In this scenario, a slump test — a common method to measure the workability of fresh concrete — initially indicated low workability. This was attributed to the rapid water loss from the concrete mix, exacerbated by the high temperatures causing the course aggregates to heat up.
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Effects of Air-entrainment in Concrete

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Workability of Concrete

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The workability of concrete is a crucial property that affects its handling, placing, and finishing during construction. It describes the ease with which concrete can be mixed, placed, compacted, and finished. Workability is primarily concerned with the concrete's movement and its ability to resist internal friction and external resistance from molds and reinforcements during the application process.
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Segregation in Fresh Concrete

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Segregation in fresh concrete is a phenomenon where the components of the concrete mix separate, leading to uneven distribution and compromised structural integrity. This separation typically occurs when concrete is subjected to excessive horizontal movement within forms, or when it is dropped from considerable heights or forced through narrow, winding paths. As a result, heavier coarse aggregate particles settle at the bottom, while lighter, finer materials such as cement and water rise to the...

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Related Experiment Video

Updated: Jun 13, 2026

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Published on: January 5, 2024

Multi-objective optimization of low-noise pervious concrete using a stacking ensemble learning and NSGA-II approach.

Fan Yu^1,2, Haoyun Zhang^1,2, SiYe Zhang³

¹College of Civil Engineering and Architecture, China Three Gorges University, Yichang, 443002, China.

Scientific Reports

|June 11, 2026

Summary

This study optimizes pervious concrete mix designs for low-noise pavements using Stacking ensemble learning and NSGA-II. The method balances acoustic, mechanical, and hydraulic properties, significantly improving sound absorption.

Keywords:

Multi-objective optimization NSGA-II algorithm Pervious concrete Sound absorption performance Stacking ensemble learning

Related Experiment Videos

Last Updated: Jun 13, 2026

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Published on: January 5, 2024

Area of Science:

Materials Science
Civil Engineering
Acoustics

Background:

Pervious concrete faces performance conflicts between acoustic, mechanical, and hydraulic properties, hindering its use in low-noise pavements.
Optimizing mix proportions is crucial to balance these competing characteristics.

Purpose of the Study:

To develop a multi-objective optimization method for pervious concrete mix proportions.
To enhance sound absorption while maintaining permeability and compressive strength.

Main Methods:

Established a comprehensive database for training a Stacking ensemble learning model for sound absorption prediction.
Integrated sound absorption, compressive strength, and permeability models into the NSGA-II genetic algorithm for multi-objective optimization.
Validated optimization results through experimental testing.

Main Results:

Aggregate gradation significantly impacts sound absorption, with a 95.7% improvement in optimal vs. poorest gradations.
The Stacking ensemble model achieved R²=0.97, surpassing individual models.
The optimized mix proportion (O3) met permeability and strength standards while exceeding single-sized aggregate sound absorption.

Conclusions:

The proposed optimization framework effectively resolves performance conflicts in pervious concrete.
Optimized pervious concrete demonstrates superior sound absorption, permeability, and strength.
The Stacking ensemble learning and NSGA-II approach provides a reliable method for material performance optimization.