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NH₃ Removal from NH₃ Cracking Gas
ML-based Optimization of TSA Configurations for NH₃ Removal from NH₃ Cracking Gas
ANN for H₂ Recovery and CO₂ Capture from Hydrogen Tail Gas
Dynamic-model-based Artificial Neural Network for H₂ Recovery and CO₂ Capture from Hydrogen Tail Gas
Deep Reinforcement Learning Optimization Framework
DRLOF for Power Generation Plant considering Performance & Environmental Issues
CO₂ Capture Capability using Deep Learning
CO₂ Capture Capability of 0.5 MW MEA Demo Plant using Three Different DL Pipelines
DNN-based Analysis & Optimization
Techno-economic Analysis & Optimization using DNN Model for CO₂ Absorption
Deep Reinforcement Learning to find Optimal Operating Conditions
Actor-critic Reinforcement Learning using DNN Model to determine Optimal Operating Conditions of Hydrocracking
SMR Physics based Model with Machine Learning
Integrating Mathematical Modelling & Machine Learning for Steam Methane Reformer
ANN-based Optimization for Integrated Separation Process
ANN-based Optimization for Low-carbon H₂ Production via SESMR integrated with Separation Process
ML model for Simulated Moving Bed
ML Model of Commercial Scale SMB for Multi-component N-paraffin Separation
Various Bed Reactor Guideline using optimization techniques
Design Guideline for CO₂ to Methanol Conversion supported by Generic Model of Bed Reactors
Wet CO₂ to Methanol Integrated Process ML Model
Novel Process for Wet CO₂ to Methanol using Catalytic Fluidized Bed Reactor integrated with Separators
DNN-based Surrogate Model for Solid Propellant
DNN-based Surrogate Model for Dynamic Behaviors & Performance of Solid Propellant Combustion
Advanced Cartridge Design using CFD
Advanced Cartridge Design using CFD for Gas Respiratory Protection System
CO₂ Capture & Methanol Conversion using ML
Optimizing CO₂ Capture and Methanol Conversion with Advanced Integration and Machine Learning
Blended-Amine CO₂ Capture for Syngas
Stripper-Free Blended-Amine CO₂ Capture for High-Pressure Syngas
CO₂ Capture for Blue H₂ from SMR
Amine-Based Pre-Combustion CO₂ Capture for Blue H₂ from SMR
Predicting CO₂ Solubility
Predicting CO₂ Solubility in Electrolyte Solutions up to 709 Bar
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Tailor-made ML solution for Hydrocracking Plant
Hybrid Simulator for Fine Chemical Plant
CFD Models for Three-phase Reactor
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About
Company
Industries
Customers
News
AI Software
Tailor-made ML Technology
Real data-based ML Technology
Model-based ML Technology
Physics-based ML Technology
R&DD
NH₃ Removal from NH₃ Cracking Gas
ANN for H₂ Recovery and CO₂ Capture from Hydrogen Tail Gas
Deep Reinforcement Learning Optimization Framework
CO₂ Capture Capability using Deep Learning
DNN-based Analysis & Optimization
Deep Reinforcement Learning to find Optimal Operating Conditions
SMR Physics based Model with Machine Learning
ANN-based Optimization for Integrated Separation Process
ML model for Simulated Moving Bed
Various Bed Reactor Guideline using optimization techniques
Wet CO₂ to Methanol Integrated Process ML Model
DNN-based Surrogate Model for Solid Propellant
Advanced Cartridge Design using CFD
CO₂ Capture & Methanol Conversion using ML
Blended-Amine CO₂ Capture for Syngas
CO₂ Capture for Blue H₂ from SMR
Predicting CO₂ Solubility
Project
Tailor-made ML solution for Hydrocracking Plant
Hybrid Simulator for Fine Chemical Plant
CFD Models for Three-phase Reactor
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서울특별시 서대문구 연희로 81-5, 4층 F05호
㈜도그우드에이아이 (연희동, 평화빌딩)
F05 DogWoodAI 4F, 81-5 Yeonhui-ro, Seodaemun-gu, Seoul, Republic of Korea (03708)
T. +82 10 6278 0184
M. dogwoodai@naver.com
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