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rul-prediction-using-lasso-regression

Predicting the Remaining Used Life of Machine parts using LASSO Regression.

rul_estimation_paper_mill

A regression based approach to estimate the Remaining Useful Life (RUL) of a paper mill for a web break prediction problem.

s17-06364

Spring 2017 Chemical and Reaction Engineering

s20-06681

Data science and machine learning in chemical engineering

scientific-computing

Exercises and homework problems to the scientific computing course at Purdue University.

scikit-learn

scikit-learn: machine learning in Python

scithermo

Scientific Thermodynamics in Python

scrreactor

Chemical Engineering Design: Projects 4 - Reactor Design Task

self-driving-car-nd

Udacity's Self-Driving Car Nanodegree project files and notes.

senior-design-project-code

SU unit solver and optimizer with Peng-Robinson EOS and Fischer-Tropsch Reator simulation

separations

Chemical Engineering Separations Library

sim42

Simulator42 is an open source process simulator project with the goal of providing an affordable and accessible chemical process simulator to the chemical engineering community.

simplepfd

A simple Python module for generating process flow diagrams.

simulating-oven-process-conditions

As students of the Final Year Project Team, our project involved Process Development and Simulation of a Bread Manufacturing Plant. As a Chemical Engineer, my focus was to implement proper process selection and developing the process flow diagram. Apart from that, I was instrumental in simulating the Temperature profile of the Bread Oven, in addition to the Moisture Content of the Bread. Sufficient focus was also stressed upon Chemical Project Economics and Site Selection.

simulation_of_rfr

Simulation of Mathematical Modelling on Oxidation Reaction using Reverse Flow Reactor

sksurrogate

SKSurrogate is a suite of tools which implements surrogate optimization for expensive functions based on scikit-learn. The main purpose of SKSurrogate is to facilitate hyperparameter optimization for machine learning models and optimized pipeline design (AutoML).

smrinfbr

Modelling of steame methane reforming (SMR) in a fixed bed reactor (FBR) using orthogonal collocation method

sofc_apu

Modeling for a SOFC aircraft

solaris_tutorials

Tutorials and workshop materials for solaris

solid-surface-adsorption

solidfuelclassification

Hierarchical Classifier Model for Classification of Solid Fuels

sshelly_hx

FAST Research Group Equations for Shell-Side Reactor Heat Exchangers: Python Script for calculation of Shell-Side heat transfer coefficient using correctional factors for Shell-and-Tube bundles based on models found in literature.

stanford-coursera-machine-learning

Course projects and notes from the Stanford Coursera Machine Learning MOOC

steel-plates-fault-diagnosis-using-classification-models

The objective of the project is to classify steel plates fault into 7 different types. The end goal is to train several machine Learning Algorithms for automatic pattern recognition.

stochastic-optimization

A set of examples to optimize process simulators with Python (PSO) - PyConES 2016

storagecode

GAMS and Python scripts underlying paper on how storage affects carbon dioxide emissions from a power system as it decarbonizes.

style-guides

An opinionated guide on how we work.

styrene-reactor-simulation

The dehydrogenation of ethylbenzene to styrene takes place on a promoted iron oxide catalyst in a fixed-bed reactor at high temperature range in the presence of steam. The feed to the reactor consist only of fresh ethylbenzene mixed with superheated vapor. The reactor produces an effluent stream (containing styrene monomer, ethylbenzene, hydrogen, ethylene, toluene, methane, water, CO and CO2).

supercritical-hydrogen-generation

Assessing feasibility of hydrogen production via the electrolysis of supercritical water.

svr-optimizing-tcms

Machine learning in Materials Sciences