Motivation

In structural materials the microstructure formation is triggered using specific thermal- or thermo-chemical heat treatment cycles. The final microstructure derived from a heat treatment is a result of subsequent and parallel transformations which mostly are transient and/or temperature driven. In this IUC, a research data management framework for experimental data with domain-specific semantics is to be designed. Semantic structured data processed in the framework is based on experimental data from different transformation characterizing schemes. Workflows for experimental procedure and data acquisition to data representation will be developed. An ontological representation encompassing both heat treatment courses and material transformation is designed in order to provide a common and unified description. Moreover, scalability from lab size experimental data derived from, e.g., dilatometry and technical furnace equipment is represented.

Overview

Main requirements:
- Ontology for representation of heat treatment courses and transformation in structural materials
- Workflow management systems that can be adapted during use (e.g., primary data acquisition, assertion augmentation, heterogeneous post-processing)
- Tools for automated data assembly
- Data augmentation and condensation for advanced data handling
Main Task Area: TA-OMS
Other related Task Areas: TA-WSD
Possible connections within NFDI: NFDI4Ing
Material/Data: High strength structural materials / time-temperature-transformation relations to microstructures
Main Success Scenario: Users can utilize a knowledge graph populated by process and material data to predict microstructures and their alteration by thermochemical heat treatments. Using a graph-based experimental data structure enables a FAIR data storage to allow for a new level of reproducibility and comparability of experimental results from different experimental setups and groups.
Added value for the MatWerk community: Concepts for the combined ontologies will be developed, combining thermochemical processing and materials transformation. This provides a general framework for heat treatment representation and the resulting erroneous and intended experimental impacts on materials microstructure.

Goals

  • Develop Ontology for Heat Treatment: Create an ontology to represent heat treatment processes and material transformations in structural materials.
  • Design Workflow Management: Develop adaptable workflow management systems for data acquisition, processing, and representation.
  • Automate Data Assembly: Implement tools for automated assembly and handling of experimental data.
  • Enhance Data Augmentation: Develop methods for data augmentation and condensation to support advanced data handling and analysis.

Related Participant Projects

All Infrastructure Use Cases

NFDI-MatWerk
Funded by the German Research Foundation (DFG) under the National Research Data Infrastructure – NFDI 38/1 – 460247524

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