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Failure Modes and Effects Analysis to Determine FORGE Target

Thu, 04 March, 2021

The FORGE project aims to create compositionally complex materials (CCM) that will extend the lifetime of severely damaged components of energy-intensive industries, both for current production and future CO2-saving processes. Identifying the most critical components, i.e the ones particularly vulnerable to harsh operating environments and that incur significant costs associated with their maintenance and replacement, is therefore an essential task under this perspective. The FORGE project has been designed to protect the critical components, mainly from corrosion, erosion, hydrogen embrittlement and thermal breakdown damages, through developing high performance compositionally complex alloy (CCA) and compositionally complex ceramic (CCC) coating materials and materials technologies.

We have considered the following components within the energy-intensive industries for analysis:

  1. Components of Carbon Capture, Utilisation and Storage (CCUS) post-combustion capture for the cement and steel industries
  2. Exhaust gas extraction pipe of waste heat recycling (WHR), inner wall, separator blades, flue gas fan blades and roller table of the raw mill in the cement industry
  3. H2 storage pressure vessel and line pipe and tubing for H2 transport in the steel industry
  4. Refractory inner surface of the kiln in the ceramic industry
  5. Extrusion dies in the aluminium industry

Components of Carbon Capture, Utilisation and Storage (CCUS) post-combustion systems applied at locations of significant CO2 emission in steel and cement production plants suffer corrosive damage. Manufacturing the component out of Corrosion Resistant Alloy (CRA) is expensive, therefore the application of a resistant CCA coating over an inexpensive substrate represents a promising solution.

In the cement industry, erosion wear and corrosion from particulates and process gases are the main causes for damaging the exhaust gas extraction pipe, raw and coal mill roller table, plates, and other components. In the ceramic industry, the refractory bricks’ surface can experience corrosion damage and, consequently, surface cracks may appear on the surface. These damages of the refractory kilns mainly occur due to chemical attack from the combustion gases containing acid and alkaline elements to the firebrick surface and depositions on the refractory surface (undesired condensation). This also leads to an increase in heat losses through the kiln walls, thereby increasing energy consumption.

In the steel industry, there is the need to enhance the pressure of stored hydrogen in the compressed gas form, if it is to be used as a fuel for green steel production. The issue is that higher strength steels, required for the highest pressures, are prone to hydrogen embrittlement. Conversely, low alloyed steel, which would be less susceptible to embrittlement, would have to be prepared to an excessive thickness, which would make the overall weight of the pressure vessel unpractical for any application. The FORGE project will investigate CCA coatings on the low-alloyed steels with reduced wall thickness to overcome the problem. In the aluminium industry, damages occur in the solid and open profile of the extrusion dies due to erosion wear, fatigue and creep, limiting the productivity of the plant expecially for high performance Al alloys.

The Failure Mode and Effects Analysis (FMEA) performed within the project, in collaboration with the representative of energy intensive industries of the steel, cement, aluminum and ceramic sector, allowed to classify the problem into four main conceptual categories, defined in the project as Performance Targets (PT):

  1. PT1: Corrosion in CO2 environment for Carbon Capture and Storage (CCS) systems,
  2. PT2: Resistance to H2 embrittlement
  3. PT3: Wear resistance
  4. PT4: Thermal stability

The Machine Learning (ML)-guided material design approach followed in the FORGE project will focus on each of these areas separately throughout the project. At the same time, also the testing environments supporting the ML model have been devised with different objectives for each performance target. The aim is to eventually combine the different parts composing the model to be able to address multiple PTs and outputs as required by the specific harsh environment.

Article Courtesy: TVS, UK