Process Metallurgy

Process simulation for decarbonization

We are excited to announce the commencement of our “Process Simulation for Decarbonization” project, funded by the European Union and the state of NRW. This initiative aims to enhance our capabilities in modeling mass transport, heat transfer, and reaction kinetics, all essential for predicting complex chemical processes. In keeping with the European spirit, our transformation […]

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Navigating the chemical space: Sustainable metallurgy through materials informatics

How can we accelerate the transformation of the iron and steel industry using materials informatics? Computational thermochemistry is fundamental for the transition to sustainable metallurgy. You need to understand thermodynamics to create process models – or to discover new alloy compositions for advanced engineering applications. We face challenges such as the decarbonization of steel metallurgy

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Constructing a Blast Furnace Diagram with FactSage – Part IV

In order to reduce the CO2 emissions caused by the iron & steel industry, there have been initiatives in the last decades to substitute reductants based on carbon by the use of H2 as a reducing agent. These initiatives go from the direct injection of H2 at the tuyeres of the blast furnace [1, 2]

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A Comprehensive Guide: Setting up ChemApp for Python and Converting FactSage Equilibrium Files using Equi2Py

Welcome to our step-by-step guide on setting up ChemApp for Python and converting equilibrium files into Python-compatible formats! In this blog post, we’ll walk you through the process by our video tutorial, ensuring you have all the information you need to get started with ChemApp for Python and make the most out of it. Setup

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Constructing a Blast Furnace Diagram with FactSage – Part II

In the second blog post of this series related to the Blast Furnace Diagram, we explore some variations of the diagram constructed in the first blog post, while sticking to carbon as the only reducing agent in the system. This blog post was written in collaboration with Klaus Hack. The first diagram that we will

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Advanced functionalities of ChemApp for Python: Streams

In this article, some of the features and recent additions to the ChemApp for Python package are introduced and explained. As a brief summary, ChemApp for Python is a Python module that encapsulates the ChemApp thermodynamic calculation library. It does provide different ways to access it. To users that are accustomed to ChemApp from other

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Constructing a Blast Furnace Diagram with FactSage 8.2

The so-called blast-furnace diagram describes which phases are stable in the different regions of the blast furnace, depending on the conditions of temperature and of the atmosphere inside the furnace[1]. It is basically a phase diagram, where the volume fraction of CO is represented on the X-axis and the temperature is represented on the Y-axis,

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Video presentations from the GTT Users’ Meeting 2022 are online

GTT's Logo

The GTT Users‘ Meeting 2022, which took place online, was a huge success with more than 150 participants from all over the world! The final program including the recorded video presentations can be found here: https://gtt-technologies.de/workshop2022/ As you can see, the program contained an excellent mix of theoretical and application-oriented presentations covering topics mainly in

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KilnSimu – Solution for Rotary Kiln Simulation

KilnSimu is a standalone software that can be used for thermodynamic modelling rotary drum furnaces. It is a joint production by VTT and GTT. While it relies on the calculation routines of ChemApp, it is user-friendly and specialized to one specific application. The rotary kiln is concurrently used in several industries. The rotary drum provides

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SimuSage at work

In connection with the Industry 4.0 initiative, tools for process simulation and process optimization are recently gaining in importance. In the context of metallurgy, its digitalization will work as an enabler of the „circular economy“ [1], by a combination of fundamentally-based process models, artificial intelligence, big data approaches and last by not least, guided by

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