Computational Sci & Eng

Codes, Examples, and Theory Manuals of a Wide Spectrum of Programs for Computational Science and Engineering

Glass-Box Physics Rule Learner for Nano Science

Raw data are from

Qiang Li, In Ho Cho, Rana Biswas, and Jaeyoun Kim, 2019. Nano Letters [10.1021/acs.nanolett.8b04038]

Raw training data of nano-scale electric potentials on three-dimensional point clouds.

Nano Letters 2019


Data-Driven and Computational Earthquake Engineering

Cell network-based stiffness reduction calculation of U-shaped walls

Based on the work of

Yicheng Yang, Sai Yemmaleni, Ikkyun Song, and In Ho Cho, 2018. Earthquake Spectra (in press) [doi.org/10.1193/010317EQS003M]

Perform variable selection for best prediction capability using the Generalized Additive Model (GAM) in R and Rmpi.

(1) serial version using R

(2) parallel version using R and Rmpi

Based on the work of

Ikkyun Song, In Ho Cho, and Raymond Wong, 2018. An Advanced Statistical Approach to Data-Driven Earthquake Engineering, Journal of Earthquake Engineering (in press). [doi.org/10.1080/13632469.2018.1461713].


Matlab Codes and manual of

Cell Network for U walls

R & Rmpi Codes

GAM for Earthquake Eng

General RC Wall auto-meshing program in portable Matlab (under construction)

Can help model three-dimensional body and entire reinforcements of any shape of RC shear wall including

U-shaped wall, T-shaped wall, Box-shaped wall with opening as well as simple rectangular wall

Based on the work of

In Ho Cho, 2013.

Virtual Earthquake Engineering Laboratory Capturing Nonlinear Shear, Localized Damage and Progressive Buckling of Bar, Earthquake Spectra 29(1), 103-126. [doi: http://dx.doi.org/10.1193/1.4000095].

Program and manual

Auto-meshing program

(1) Matlab package (can be installed and run on Window 64 bit)

(2) manual (written by graduate student Hongtao Dang)

Multi-target prediction of capacity curve of complex RC structures (under construction)

Based on the work of

Yicheng Yang and In Ho Cho, 2018. Earthquake Spectra (in preparation)

Hybrid dataset of structural performances based on experiments and high-fidelity simulations

Training Dataset of Complex RC structures