New buildings and bridges can be made from reclaimed steel. This requires the mechanical material properties (yield stress, fracture toughness, etc.) to be known. Aim is to derive a method for estimating these properties by combining destructive and non-destructive tests with prior knowledge from data collected of similar steels.
Project aimLarge quantities of steel become available from disassembled or destroyed structures. The vast majority of this quantity is suited for re-use, yet only a fraction (approximately 5%) is being re-used. One of the hurdles of reusing is addressed in this proposal: What are the mechanical properties of the reclaimed components that are relevant for re-use? How can these properties be obtained with a minimum number of tests at an acceptable level of uncertainty? This is the topic that you will focus on.
BackgroundReclaimed steel elements are usually between 20 and 50 and sometimes up to 100 years old. Mechanical material properties might deviate from that of modern steels, especially in case of structural steels older than 50 years, because of different production processes and the presence of tramp elements. This affects the ductility and strength and, more importantly, the fracture toughness. Not only the base metal but also the welds and the heat affected zones have properties that differ between current and old production processes. This needs to be accounted for if reclaimed components are used in new structures. It is possible to extract specimens and conduct tests on each reclaimed components for obtaining the material properties, but this is uneconomic and time-consuming. You will therefore develop a probabilistic framework that combines a minimum number of destructive tests with non-destructive tests and prior knowledge from a database that you will set-up, consisting of mechanical properties as a function of production process, production time and use collected from literature and own tests.
Your approachYou will:
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Determine correlations between non-destructive testing (NDT) and mechanical properties based on literature. In addition to conventional techniques, emerging and promising new NDT will be considered.
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Collect test data on mechanical material properties from the literature and the project partners. Data collection should include mechanical properties, chemo-physical properties, composition, production processes, application area, time and country of production. Correlate the properties to production process, time, and use by applying Analysis of Variance (ANOVA). Establish a categorized database of structural properties as a function of production process, time, and use.
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Develop a Bayesian updating procedure to update the distribution parameters of each material property based on a limited number of NDT or DT for a specific batch. Use a combination of NDT methods to obtain an as good characterization of mechanical properties as possible. Determine lower bound estimates following from the procedure depending on the prior information of Step 2 and the tests of Step 3. Tests are done at our Structures Laboratory TU/e https://www.tue.nl/en/research/research-labs/structures-laboratory. This activity forms the core of the study.
- Collect data of material certificates of existing structures, to determine the variation in material properties between components of the same batch, different batches, and different structures. Conduct additional tests for older structures. Evaluate these data and determine how similar elements must be to obtain a representative estimate of the material properties by testing only one element.
- Develop a Bayesian updating procedure (based on 3 and 4) to do DT and NDT to a minimum number of components from a single structure. Quantify the probability of different material properties despite this procedure (i.e., quantify the uncertainty of this procedure).
You will be embedded in the Metal Structures group of TU/e, see
https://www.tue.nl/en/research/research-groups/structural-engineering-and-design/steel-structures and
https://www.tue.nl/en/research/research-groups/structural-engineering-and-design/aluminium-structures. The group has approximately 10 PhD students. Your project is part of a cross-university project involving more than 70 PhD students and Postdocs, all working on decarbonization and circularity of steel and steel structures, see
https://groeienmetgroenstaal.nl/en/.