Artificial intelligence algorithms for prediction of cyclic stress ratio of soil for environment conservation-Reference-Cited by-同舟云学术

Artificial intelligence algorithms for prediction of cyclic stress ratio of soil for environment conservation

Published:2023-08 Issue: Volume:12 Page:100730
ISSN:2667-0100
Container-title:Environmental Challenges
language:en
Short-container-title:Environmental Challenges

Author:

Pawar Aman,Jolly Aman,Pandey Vikas,Chaurasiya Prem Kumar,Verma Tikendra Nath,Meshram Kundan

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Pollution,Waste Management and Disposal,Environmental Engineering,Global and Planetary Change

Reference22 articles.

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2. ASTM D3999 - Standard Test Methods for the Determination of the Modulus and Damping Properties of Soils Using the Cyclic Triaxial Apparatus;Standards,2014

3. LEAP 2017: Soil Characterization and Element Tests For Ottawa F65 Sand;El Ghoraiby,2017

4. Cyclic triaxial test to measure strain-dependent shear modulus of unsaturated sand;Ghayoomi;Int. J. Geomech.,2017

5. Model tests and numerical simulations of liquefaction and lateral spreading;Ghoraiby;Model Test. Numer. Simul. Liquefact. Later. Spread.,2020

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