Determination of the Strength Characteristics of Bituminous-Mineral Mixtures

2021 ◽  
Vol 625 (3) ◽  
pp. 39-43
Author(s):  
N. G. Evdokimova ◽  
◽  
N. A. Egorova ◽  
N. N. Luneva ◽  
◽  
...  
Keyword(s):  
Compressive Strength ◽  
Laboratory Method ◽  
Strength Characteristics ◽  
Optimal Parameters ◽  
Adhesive Properties ◽  
Production Technologies ◽  
Mineral Mixtures ◽  
Adhesion Index

The paper presents the results of the development and testing of a laboratory method for determining the strength characteristics of bitumen-mineral mixtures on the Lintel PK-21-01 strength meter. The conditions for testing the strength of bitumen-mineral mixtures are selected. The dependence between the bitumen adhesion index and the compressive strength of samples of bitumen-mineral mixtures based on it, determined according to the developed method, is shown. A decrease in the strength and adhesive properties of the binder was found with an increase in the content of the DST-30-01 polymer in bitumen. It is proposed to evaluate the possibility of performing research for the development of new types of bitumen products, to develop various production technologies and to select the optimal parameters for its production on the basis of standardized methods of testing bitumen and the developed methodology for determining the strength characteristics of bitumen-mineral mixtures.

Determination of Concrete Cube Strength from Used Samples / Určení Krychelné Pevnosti Betonu U Použitých Zkušebních Trámců

2012 ◽  
Vol 12 (2) ◽  
pp. 186-194 ◽  
Author(s):  
Oldřich Sucharda ◽  
David Mikolášek ◽  
Jiří Brožovský
Keyword(s):  
Compressive Strength ◽  
Concrete Beams ◽  
Linear Analysis ◽  
Bending Tests ◽  
Cube Strength ◽  
Non Linear ◽  
Compressive Strength Of Concrete ◽  
Concrete Cube

Abstract This paper deals with the determination of compressive strength of concrete. Cubes, cylinders and re-used test beams were tested. The concrete beams were first subjected to three-point or fourpoint bending tests and then used for determination of the compressive strength of concrete. Some concrete beams were reinforced, while others had no reinforcement. Accuracy of the experiments and calculations was verified in a non-linear analysis.

scholarly journals Machine Learning Approaches for Prediction of the Compressive Strength of Alkali Activated Termite Mound Soil

2021 ◽  
Vol 11 (11) ◽  
pp. 4754
Author(s):  
Assia Aboubakar Mahamat ◽  
Moussa Mahamat Boukar ◽  
Nurudeen Mahmud Ibrahim ◽  
Tido Tiwa Stanislas ◽  
Numfor Linda Bih ◽  
...  
Keyword(s):  
Compressive Strength ◽  
Construction Materials ◽  
Curing Temperature ◽  
Sustainable Construction ◽  
Support Vector ◽  
Learning Approaches ◽  
Artificial Neural Network Ann ◽  
Curing Regime ◽  
Alkali Activated

Earth-based materials have shown promise in the development of ecofriendly and sustainable construction materials. However, their unconventional usage in the construction field makes the estimation of their properties difficult and inaccurate. Often, the determination of their properties is conducted based on a conventional materials procedure. Hence, there is inaccuracy in understanding the properties of the unconventional materials. To obtain more accurate properties, a support vector machine (SVM), artificial neural network (ANN) and linear regression (LR) were used to predict the compressive strength of the alkali-activated termite soil. In this study, factors such as activator concentration, Si/Al, initial curing temperature, water absorption, weight and curing regime were used as input parameters due to their significant effect in the compressive strength. The experimental results depict that SVM outperforms ANN and LR in terms of R2 score and root mean square error (RMSE).

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