Classifying High Strength Concrete Mix Design Methods Using Decision Trees.

Materials (Basel)

Department of Civil Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.

Published: March 2022

Concrete mix design methods are used to determine proportions of concrete ingredients needed for certain workability and strength. Each mix design method operates under certain assumptions and suggests slightly different proportions. It is of great importance that site/construction engineers know the method by which the mix was designed. However, it can be difficult to know the designing method based solely on mix proportions. Hence, in this work, a decision trees model was used to classify high strength concrete mix design methods based on their produced concrete mix proportions. It was found that the trained decision tree model is capable of classifying mix design methods with high accuracy. Further, based on dimensionality reduction methods, the amount of cement in a concrete mix was found to be the paramount predictor of the used mix design method. In this work, a novel high-accuracy model for determining a mix design method based only on mix proportion is proposed.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8912015PMC
http://dx.doi.org/10.3390/ma15051950DOI Listing

Publication Analysis

Top Keywords

mix design
28
concrete mix
20
design methods
16
mix
12
design method
12
high strength
8
strength concrete
8
decision trees
8
method based
8
mix proportions
8

Similar Publications

The Impact of the COVID-19 Pandemic on Medical-Legal Partnership Services and Cases.

J Public Health Manag Pract

January 2025

Author Affiliations: Department of Health Promotion, Center for Reducing Health Disparities, College of Public Health, University of Nebraska Medical Center, Omaha, Nebraska (Dr Ramos); Center for Reducing Health Disparities, College of Public Health, University of Nebraska Medical Center, Omaha, Nebraska (Dr Sanchez Roman, Ms Soto Prado, and Ms Schmeits); and Department of Obstetrics/Gynecology, College of Medicine, University of Nebraska Medical Center, Omaha, Nebraska (Dr Rodabaugh).

Context: Medical-legal partnerships (MLPs) are innovative, promising models that integrate legal service providers and medical professionals to prevent, detect, and address legal, social, and economic needs arising from social inequities that may negatively impact health. The COVID-19 pandemic impacted health care systems across the United States. MLP workflows and legal services were also interrupted by COVID-19 infection prevention and control measures such as no-visitor policies, social distancing, and the cancellation of non-emergent or routine health care services.

View Article and Find Full Text PDF

Mix-Charged Nanofiltration Membrane for Efficient Organic Removal from High-Salinity Wastewater: The Role of Charge Spatial Distribution.

Environ Sci Technol

January 2025

State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100190, PR China.

The efficient removal of organic contaminants from high-salinity wastewater is crucial for resource recovery and achieving zero discharge. Nanofiltration (NF) membranes are effective in separating organic compounds and monovalent salts, but they typically exhibit an excessive rejection of divalent salts. Modifying the charge characteristics of NF membranes can improve salt permeation; however, the role of charge spatial distribution in governing salt transport behavior is not fully understood.

View Article and Find Full Text PDF

Ultra-high-performance concrete (UHPC) is widely used in engineering due to its exceptional mechanical properties, particularly compressive strength. Accurate prediction of the compressive strength is critical for optimizing mix proportions but remains challenging due to data dispersion, limited data availability, and complex material interactions. This study enhances the Gaussian Process (GP) model to address these challenges by incorporating Singular Value Decomposition (SVD) and Kalman Filtering and Smoothing (KF/KS).

View Article and Find Full Text PDF

Human exposure to complex, changing, and variably correlated mixtures of environmental chemicals has presented analytical challenges to epidemiologists and human health researchers. There have been a wide variety of recent advances in statistical methods for analyzing mixtures data, with most of these methods having open-source software for implementation. However, there is no one-size-fits-all method for analyzing mixtures data given the considerable heterogeneity in scientific focus and study design.

View Article and Find Full Text PDF

Background: The use of eHealth innovations is becoming increasingly important in improving health outcomes, especially for maternal and newborn health. However, planning and executing these innovations can be challenging due to their complex nature. To provide guidance and clarity on implementation approaches, researchers need to use implementation research (IR) tools.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!