Chemical Process Simulation Using Dwsim, Scilab & Chemsep
Last updated 9/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 27.06 GB | Duration: 38h 22m
Last updated 9/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 27.06 GB | Duration: 38h 22m
Chemical Process Designing | Process Modelling | Process Simulation | Process Optimization | DWSIM | SCILAB | ChemSep
What you'll learn
Synthesis of Reaction Paths
Synthesis of Heat Exchanger Networks (HENs)
Synthesis of Separation Sequences
Synthesis of Energy Recovery Networks
Requirements
Basic Understanding of Chemical Engineering
Description
Each session shall be of two hours. Sessions 1 through 14 are on Advanced Process Simulations and Sessions 15 through 21 are on Artificial Intelligence in Chemical Process Industry. Sessions 1 through 7, 15 through 21 are contemporary industrial case study learning and sessions 8 through 14 are completely hands on exercises. Special Feature: A complementary session on personal research work on India’s First BioCNG Plant and Green Hydrogen Production shall be delivered at the end.Software to be used: DWSIM SCILAB ChemSepSkills those shall be earned/fostered after the internship: Engineering Fundamentals and Concepts Mathematical Modelling Process Synthesis and Analysis Process Design Process Modelling Process Simulation Process Optimization Process Retrofitting Process Debottlenecking Process Data Analytics Data Modelling Artificial Intelligence Tools Deep Learning using Artificial Neural Networks Industry 4.0 for Process Engineering Contemporary Industrial case studiesAt the end of this course, the participants shall be able to: Review the developments of process design and simulation fostering economy Show how advanced Process Simulators function Share various contemporary industrial simulation case studies with facilitation of ICT enabled tools Encourage use of process simulators for simulation of Chemical Manufacturing processes and plants Apply advanced Computational Intelligence as Process Data Analytics, Artificial Intelligence, Machine Learning with deep learning of Artificial Neural Networks
Overview
Section 1: Introduction
Lecture 1 Engineering Fundamentals and Concepts
Section 2: Mathematical Modelling
Lecture 2 Developing Mathematical Models for Process Simulations
Section 3: Process Synthesis and Analysis
Lecture 3 Synthesis of commercial chemical processes
Section 4: Process Design
Lecture 4 Design of Vinyl Chloride Plant, Heuristics in Design
Section 5: Process Modelling
Lecture 5 Systems for modelling Chemical Engineering processes
Section 6: Process Simulation
Lecture 6 Process Simulation
Section 7: Process Optimization
Lecture 7 Process Optimization
Section 8: Contemporary Industrial case studies Stream Property Data
Lecture 8 Contemporary Industrial case studies Stream Property Data
Section 9: Contemporary Industrial case studies T-xy and VLE Plots
Lecture 9 Generate vapourliquid equilibrium data (VLE) for a binary component system
Section 10: Contemporary Industrial case studies Steam Compressor
Lecture 10 Design Compressor with retrofitting
Section 11: Contemporary Industrial case studies Flash Column
Lecture 11 Develop a simple process flow sheet to estimate the liquid and vapour composit
Section 12: Contemporary Industrial case studies Heat Exchanger
Lecture 12 Develop a simple process flow sheet to determine the heat duty required to hea
Section 13: Contemporary Industrial case studies Fluid Pumping Station Pump, Pipe Segment
Lecture 13 eeeee
Section 14: Industrial case studies Ethanol Distillery Mixer Heater and Flash Drum
Lecture 14 Develop a simple process sheet to distill Ethanol for Rectified Spirit
Section 15: Industrial case studies Full Plant Case Study
Lecture 15 BT Column Sensitivity Analysis
Section 16: Industrial case studies Full Plant Case Study
Lecture 16 Ethanol Acetone Separation
Section 17: Heat Exchanger Design using HTRI
Lecture 17 Industrial Shell and Tube Heat Exchanger Design Methodology
Section 18: Industry 4.0 for Process Engineering
Lecture 18 Tools and Systems in Industry 4.0 specially crafted for Process Industry
Section 19: Process Data Analytics & Data Modelling
Lecture 19 Descriptive and Inferential Statistics, Random sampling, decision process
Section 20: ddddd
Lecture 20 Frequency distribution, Pareto chart, Histogram, Class IntervalsFrequency
Chemical Engineering students