Learn Design And Simulation Of Chemical Plants And Equipment
Learn Design And Simulation Of Chemical Plants And Equipment
Published 11/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 12.68 GB | Duration: 14h 37m
Learn from chemical industry expert. Enhance you market value.
What you'll learn
Whether you're a seasoned professional or a student aspiring to enter the industry, this course is designed to equip you with the knowledge and skills .
In this course, we delve into the key concepts and methodologies of design and simulation.
We start by exploring the fundamentals, differentiating between design and simulation and discussing their respective roles in chemical engineering.
We then explore two fundamental approaches: phenomenological model-based simulation and data-driven machine learning-based simulation.
We take a hands-on approach, utilizing Aspen, a leading simulation software widely used in the industry.
Speaking of machine learning, we delve into its foundations, understanding the key terms and concepts.
Requirements
Preliminary knowledge of Aspen and Matlab is desirable bt not neccessary.
Description
Introducing Learn Design and Simulation of chemical plants and equipment from Industry Expert.Are you ready to take your skills in chemical engineering to the next level? Look no further! We are thrilled to present our comprehensive online course on Design and Simulation of chemical plants and equipment. Whether you're a seasoned professional or a student aspiring to enter the industry, this course is designed to equip you with the knowledge and skills needed to excel in the field.Why learn design and simulation in the chemical industry? The answer is simple: it is the backbone of modern chemical engineering. Simulation allows engineers to predict and optimize process behavior, minimize risks, and improve efficiency. By understanding the principles and techniques of design and simulation, you gain a competitive edge and open up a world of possibilities in your career.In this course, we delve into the key concepts and methodologies of design and simulation. We start by exploring the fundamentals, differentiating between design and simulation and discussing their respective roles in chemical engineering. We then explore two fundamental approaches: phenomenological model-based simulation and data-driven machine learning-based simulation. By understanding the advantages and disadvantages of these approaches, you will be able to choose the most suitable method for different scenarios.We take a hands-on approach, utilizing Aspen, a leading simulation software widely used in the industry. You will be guided through various simulations, starting with property analysis, flash drum simulation, pump and pipeline simulation, heat exchanger simulation, and reactor simulation. We cover both basic and advanced simulations, including plug flow reactors, CSR, batch reactors, industrial ethylene glycol and ethyl acetate reactors, and more.A significant portion of the course is dedicated to distillation column simulation. You will gain an overview of different distillation column models available in Aspen, including DSTWU and Radfrac rigorous distillation simulations. We also provide a comprehensive case study involving six distillation column simulations, including an industrial benzene column simulation. Additionally, we explore how to identify the optimum feed tray location, and we introduce the exciting topic of simulation by machine learning, discussing its relevance and the steps involved.Speaking of machine learning, we delve into its foundations, understanding the key terms and concepts. You will learn how to clean data, detect outliers, handle missing values, and encode data for machine learning purposes. We guide you through the steps of developing a data-driven regression model, including model selection and performance evaluation. Through engaging case studies, such as bioreactors and soft sensors in distillation columns, you will witness the practical application of machine learning in simulation.Course Content: Design and Simulation of chemical plants and equipmentSection 1: Introduction· Why learn design and simulation in the chemical industry?· Understanding the concept of simulation· Differentiating between design and simulation in chemical engineeringSignificance: This section provides an overview of the course, highlighting the importance of design and simulation in the chemical industry. It sets the foundation for understanding the subsequent topics and their practical applications.Section 2: Two Fundamental Approaches of Modeling and Simulation· Phenomenological model-based simulation and its advantages and disadvantages· Data-driven machine learning-based simulation and its advantages and disadvantagesSignificance: This section introduces the two fundamental approaches to modeling and simulation in chemical engineering, allowing learners to understand the strengths and weaknesses of each method. It helps learners make informed decisions about choosing the appropriate approach for specific scenarios.Section 3: Aspen-Based Simulation· Walkthrough of the Aspen software interface· First Aspen-based simulationSignificance: This section familiarizes learners with the popular Aspen simulation software, providing hands-on experience in navigating the interface and conducting their first simulation. It builds confidence and prepares learners for more advanced simulations throughout the course.Section 4: Property Analysis· Understanding the property analysis quick method assistant· Pure component property analysis· Property analysis of binary mixtureSignificance: Property analysis is a crucial step in chemical engineering design and simulation. This section guides learners in analyzing properties efficiently, ensuring accurate simulation results. It covers both single-component and binary mixture analyses.Section 5: Flash Drum Simulation· Separated simulationSignificance: Flash drum simulation is commonly used in chemical processes. This section covers the simulation of flash drums and explores separated simulation techniques, providing learners with practical knowledge in simulating and optimizing these operations.Section 6: Pump and Pipeline Simulation· Simulating pump and pipeline systemsSignificance: Pump and pipeline systems are integral components of chemical processes. This section teaches learners how to simulate and analyze these systems, considering factors such as pressure drop, flow rates, and efficiency.Section 7: Heat Exchanger Simulation· Simple heat exchanger simulation· Rigorous heat exchanger simulationSignificance: Heat exchangers play a vital role in energy transfer within chemical processes. This section covers both simplified and rigorous heat exchanger simulations, enabling learners to optimize heat transfer and improve process efficiency.Section 8: Reactor Simulation· Plug flow reactor simulation· CSR simulation· Batch reactor simulation· Industrial ethylene glycol reactor simulation· Gibbs reactor simulation· Industrial ethyl acetate reactor simulationSignificance: Reactor simulation is crucial for understanding chemical reactions and optimizing reactor designs. This section covers various reactor types and their simulations, allowing learners to analyze reaction kinetics, conversion rates, and select the appropriate reactor configuration for specific applications.Section 9: Distillation Column Simulation· Overview of different models of distillation columns available in Aspen· DSTWU module· Radfrac rigorous distillation simulation· Case study of 6 distillation column simulations, including an industrial benzene column simulation· Identifying optimum feed tray locationSignificance: Distillation is a widely used separation technique in the chemical industry. This section explores different distillation column models and simulations, including rigorous distillation simulations. Learners gain insights into optimizing column design, tray location, and achieving desired separation efficiency.Section 10 : Simulation by Machine Learning· Case study of bioreactors simulation by machine learning· Steps to develop a machine learning model· Regression learner tools· Data preparation for machine learning· Model selection for machine learning simulations· Performance evaluation of the developed model· Visualizing simulation resultsSignificance: This section explores the application of machine learning in simulation. Learners will understand when and how to utilize machine learning techniques for simulation purposes. The case study on bioreactors demonstrates the practical implementation of machine learning models in chemical engineering processes. Learners will gain insights into data preparation, model selection, performance evaluation, and result visualization, enabling them to apply machine learning effectively in their own simulations.Section 11: Case Study to Develop a Soft Sensor in Distillation Column· Developing a soft sensor using simulation data· Understanding the role of soft sensors in distillation columns· Practical implementation of a soft sensor for real-time monitoring and controlSignificance: Soft sensors play a crucial role in distillation column operations, providing real-time monitoring and control. In this case study, learners will learn how to develop a soft sensor using simulation data and understand its significance in optimizing distillation processes.Section 12: Case Study: Industrial Catalytic Reactor Simulation· Simulation of an industrial catalytic reactor· Analyzing reaction kinetics and reactor performance· Optimization of operating conditions for improved productivitySignificance: This case study focuses on simulating an industrial catalytic reactor, allowing learners to explore reaction kinetics, reactor performance, and the optimization of operating conditions. Learners will gain practical knowledge in simulating and improving the efficiency of catalytic reactors.Conclusion:This comprehensive online course on Design and Simulation in Chemical Engineering covers essential topics, techniques, and case studies to equip learners with the knowledge and skills needed to excel in the field. By understanding the principles of design and simulation, as well as gaining hands-on experience using industry-standard software and machine learning techniques, learners will be well-prepared to tackle real-world challenges in chemical engineering. Enroll in this course today and embark on a journey of professional growth and mastery in design and simulation.Join us on this exciting journey as we equip you with the skills to design and simulate chemical engineering processes effectively. Our expert instructors bring years of industry experience and a passion for teaching, ensuring that you receive top-quality instruction and guidance throughout the course. Take the first step towards mastering design and simulation in chemical engineering and enroll in our course today!
Overview
Section 1: Introduction and course overview
Lecture 1 Introduction
Lecture 2 Why to learn design and simulation in the chemical industry?
Section 2: Understanding the concept of design and simulation
Lecture 3 Understanding the concept of simulation
Lecture 4 Differentiating between design and simulation
Section 3: Two Fundamental Approaches of Modeling and Simulation
Lecture 5 Two Fundamental Approaches of Modeling and Simulation
Lecture 6 Comparitive Advantages and Disadvantages
Section 4: Aspen based simulation
Lecture 7 Overview of flowsheet simulation
Lecture 8 Run the first Aspen simulation
Lecture 9 Introduction part2
Lecture 10 Assessing the variable in Aspen
Section 5: Chemical Property Analysis in Aspen for accurate simulation results
Lecture 11 Propert Analysis: What is it?
Lecture 12 Guideline for selecting appropriate proety method
Lecture 13 How to calculate pure component property of any compund?
Lecture 14 How to calculate properties of any binary mixtures?
Lecture 15 How to calculate properties of any ternary mixtures?
Section 6: Simlation of Flash drum and separators
Lecture 16 SImulation of mixer and splitter
Lecture 17 Flash drum simulation
Lecture 18 Simualtion of separator
Section 7: Design of pump ,compressor and pipeline
Lecture 19 Pump
Lecture 20 Pressure changer overview
Lecture 21 Design of pipeline
Section 8: Design and simulation of heat exchanger
Lecture 22 Overview
Lecture 23 Heat exchanger simulation
Lecture 24 heat excahnger simulation2
Lecture 25 Rigorous heatechanger design and simulation
Section 9: Design and simualtion of Reactor
Lecture 26 Reactor overview
Lecture 27 Batch reactor simulation 1
Lecture 28 Batch Reactor simlation 2
Lecture 29 Plug flow reactor
Lecture 30 CSTR
Lecture 31 Gibbs Reactor
Lecture 32 Case study : Ethylene glycol reactor
Lecture 33 Case study : Ethyl acetate reactor
Section 10: Design and SImulation of distillation column
Lecture 34 Overview of distillation column simulation
Lecture 35 Firststep of distillation column design
Lecture 36 Distillation column simulation : casrstudy1
Lecture 37 Distillation column simulation : casrstudy2
Lecture 38 Distillation column simulation : casrstudy3
Lecture 39 Distillation column simulation : casrstudy4
Lecture 40 Distillation column simulation : casrstudy5
Lecture 41 Distillation column simulation : casrstudy6
Lecture 42 Distillation column simulation : Benene column
Lecture 43 Overview of rigoruos distillation simulation
Lecture 44 Radfrac
Lecture 45 Optimum feed tray location
Section 11: Design spec and sensitivity analysis Features in Aspen
Lecture 46 Design spec
Lecture 47 Sensitivity
Lecture 48 Sensitivity 2
Lecture 49 Sensitivity analysis case study
Section 12: Overview of machine learning in design and simulation
Lecture 50 Machine learning : what is it ?
Lecture 51 Regression analysis
Lecture 52 Overfitting and undetfitting
Lecture 53 Definitions and components of machine learning
Section 13: Steps to build model by machine learning
Lecture 54 Steps
Section 14: Data cleaning and data preprocessing
Lecture 55 Data Preprocessing
Lecture 56 Outlier
Lecture 57 Outliers detection
Section 15: How to build ML models?
Lecture 58 Regression model
Lecture 59 Performance of regression
Section 16: How to build machine learning based simulations
Lecture 60 Matlab regression learner app
Lecture 61 Steps
Lecture 62 Import data
Lecture 63 Identify model type
Lecture 64 Rn and evalate performnace
Lecture 65 Result interpretation
Section 17: Casestudy : BioReactor simulation
Lecture 66 Bio reactor simulation part1
Lecture 67 Bio reactor simulation part2
Lecture 68 Bio reactor simulation part3
Lecture 69 Bio reactor simulation part4
Section 18: Data driven catalytic reactor simulation
Lecture 70 catalytic reactor simulation part1
Lecture 71 catalytic reactor simulation part2
Lecture 72 catalytic reactor simulation part3
Section 19: Real life case study to build softsensor for distillation column
Lecture 73 Real life case study to build softsensor for distillation column part1
Lecture 74 Real life case study to build softsensor for distillation column part2
Lecture 75 Real life case study to build softsensor for distillation column part3
Whether you're a seasoned professional or a student aspiring to enter the industry, this course is designed to equip you with the knowledge and skills needed to excel in the field.,Chemical negineering students (under gradate or post graduate),Process engineers working in chemical industry,Chemical engineers working in chemical industry,Supervisors,technicians,operators working in chemical industry,Simulation and design engineers
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