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Related Concept Videos

Design Example: Managing Concrete Workability01:14

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.
To address...
Design Example: Sustainability in Concrete Building01:26

Design Example: Sustainability in Concrete Building

As the construction industry moves towards more eco-friendly practices, concrete's adaptability and its ability to incorporate sustainable features make it a key material in the drive towards greener building solutions.
There are multiple approaches to achieve sustainability in a commercial concrete building. For instance, construct a concrete parking area under the building, utilizing pervious concrete paver blocks in open areas to facilitate rainwater collection through an underground cistern.
Pozzolans01:21

Pozzolans

Pozzolans are siliceous or aluminous materials blended with Portland cement. They interact with the calcium hydroxide produced during the hydration of Portland cement and contribute to improved strength and durability of concrete. The pozzolanic activity, a measure of a pozzolan's effectiveness, is typically assessed using the strength activity index, as defined in ASTM C 618-93, which calculates the ratio of the compressive strength of cement mixtures with and without pozzolan.
Fly ash is a...
Design Example: Aggregate Gradation01:24

Design Example: Aggregate Gradation

The right type and quality of aggregates are crucial for concrete as they significantly influence its properties, mix proportions, and cost-effectiveness. If different sources are available for sand, the commonly used fine aggregate in concrete, the selection of sand is primarily based on its gradation.
The grading, or particle-size distribution, of sand is determined using sieve analysis, with standard sizes ranging from 150 μm to 10 mm (ASTM No. 100 sieve to 3⁄8 in. sieve). Sand is sampled...
Effects of Air-entrainment in Concrete01:28

Effects of Air-entrainment in Concrete

Air entrainment in concrete significantly enhances the material's durability, especially in environments subjected to freeze-thaw cycles. Introducing small air bubbles into the concrete mix acts as internal voids that accommodate the expansion of water when it freezes, thereby alleviating internal stress and preventing structural cracks. This function is crucial in climates with significant freezing and thawing, as it protects the concrete from repeated stresses that could lead to premature...
Additives and Fillers in Concrete01:29

Additives and Fillers in Concrete

Additives and fillers are integral to enhancing the properties of concrete. Pozzolans and blast-furnace slag are additives or admixtures due to their reactions with calcium hydroxide released during cement hydration. Fillers, which are finely ground and similar in fineness to Portland cement, improve concrete attributes such as workability density, and reduce capillary bleeding or cracking. Some fillers possess hydraulic properties or participate in benign reactions within the cement paste.
The...

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Related Experiment Video

Updated: Jun 30, 2026

Optimization of An Air-Based Heat Management System for Dusty Particulate Matter-Covered Lithium-Ion Battery Packs
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Optimization of An Air-Based Heat Management System for Dusty Particulate Matter-Covered Lithium-Ion Battery Packs

Published on: November 3, 2023

Explainable AI-based optimization framework for sustainable fly ash concrete design.

Morteza Khorshidi1, Pourya Nejatipour2, Amirehsan Teimortashlu3

  • 1Independent Scholar (Applicant to U.S. PhD Programs), Champaign, IL, USA.

Scientific Reports
|June 28, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an AI framework for sustainable fly ash concrete design, optimizing mix proportions for strength and reduced CO2 footprint. NGBoost model achieved best performance, identifying key factors for concrete strength.

Keywords:
CO2 footprintExplainable artificial intelligence (XAI)SHAP analysisSustainable concrete design

Related Experiment Videos

Last Updated: Jun 30, 2026

Optimization of An Air-Based Heat Management System for Dusty Particulate Matter-Covered Lithium-Ion Battery Packs
10:36

Optimization of An Air-Based Heat Management System for Dusty Particulate Matter-Covered Lithium-Ion Battery Packs

Published on: November 3, 2023

Area of Science:

  • Sustainable Materials Science
  • Artificial Intelligence in Engineering
  • Concrete Technology

Background:

  • Fly ash utilization in concrete reduces environmental impact and maintains mechanical properties.
  • Sustainable concrete design requires balancing performance with ecological considerations.
  • Existing methods for concrete mix design lack comprehensive optimization and interpretability.

Purpose of the Study:

  • To develop an explainable AI-based multi-objective framework for sustainable fly ash concrete design.
  • To integrate predictive modeling, feature interpretation, uncertainty assessment, and optimization.
  • To identify optimal concrete mix designs that maximize compressive strength and minimize CO2 footprint.

Main Methods:

  • Compiled a dataset of 1,062 concrete mix samples.
  • Applied outlier detection to the training subset.
  • Trained and compared four AI models (TabNet, SVR, NGBoost, SAINT) for compressive strength prediction.
  • Conducted bootstrap-based uncertainty analysis.
  • Coupled the best predictive model with nature-inspired optimization algorithms.

Main Results:

  • NGBoost demonstrated the best predictive performance (R²=0.92).
  • Cement content, water content, and MCS-28 were identified as key predictors of compressive strength.
  • TabNet and NGBoost showed narrower uncertainty bounds, indicating higher reliability.
  • The framework identified Pareto-optimal concrete mix designs within the dataset domain.

Conclusions:

  • The proposed AI framework offers a data-driven approach for sustainable fly ash concrete mix design.
  • The framework effectively balances compressive strength and CO2 footprint reduction.
  • Future work should incorporate additional practical constraints and larger datasets for enhanced validation.