Volodymyr Kozachynskyi

Project: Machine Learning in Chemical Engineering (DFG priority programme 2331) • Commissioning of the vapor-liquid equilibrium measurement laboratory setup. • Use of parameter estimation (PE) and optimal experimental design (OED) optimization methods for steady-state VLE, methanol synthesis, and dynamic esterification reaction experiments. • Development of pattern recognition tool with GUI. • Maintenance and customer support of the mopeds Python package (https://mopeds.readthedocs.io/).

Project: Integrated Chemical Processes in Liquid Multiphase Systems (SFB InPROMPT) • Process design, HAZOP, and electrical and mechanical modification of an existing mini-plant. • Development of a methodology for optimal experimental design and parameter estimation optimization problems and its implementation in Python package mopeds (https://pypi.org/project/mopeds/). • Development of an OPC-UA based solution for online use of advanced process control tools and its implementation in Python.

• Development of the dynamic pressure-driven model of the column

• Created images, slides, and teaching materials for Process Simulation class at Technische Universität Berlin. • Developed new content for Process Simulation exercises using Aspen Plus and gPROMS.

• Utilized data reconciliation methods to close the mass balance of a chemical plant, reducing raw material costs. • Developed a VBA-based tool for automatic measurement error determination of categorized equipment like flow and temperature sensors.

• Managed supermarket refrigeration and air conditioning control systems, optimizing energy costs. • Developed graphical interfaces for monitoring systems to enhance efficiency. • Designed piping layouts in AutoCAD with cost estimates.

German, Energy Economics, Energy Engineering

Physics, Thermodynamics, Refrigeration, HVAC