Research & Development

MatchID originates from a university environment and still has a substantial focus on research involvement. Our ambition is not only to be a leading software provider for the next generation of DIC-based engineering, but also a valuable R&D partner to help our customers realise the full potential of the wealth of data and opportunities provided by our tools.

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Ongoing projects

This project is led by Prof. Sam Coppieters (KU Leuven Ghent campus) and also involves Prof. Miroslav Halilovič (University of Llubljana). The goal is to develop an integrated mechanical test combining heterogeneous strain states, Digital Image Correlation and inverse identification (Virtual Fields Method) able to identify complex anisotropic plastic yield surfaces from a single test, with a view to future commercialization. The underpinning idea is to simplify the use of this technology, denoted ‘Material Testing 2.0’. MatchID’s role in the project is to integrate a new stress reconstruction algorithm named ‘Nice’ and developed by the team of Prof. Halilovič, and provide the expertise to integrate hardware and software to create the final product.

Funding : Vlaio, Innovation mandate, HBC.2024.0807, 2025-2027
We are involved in a Flemish Sim-Icon project entitled “Resonant-based material characterization for metal Additive Manufacturing (AM)” led by Materialise and encompassing Siemens Industry Software, KU Leuven and the University of Ghent as other partners. The objective of this 3-year project is to study the mechanisms and origins of variability in AM part quality. The effect of modifying printing conditions on the AM material is investigated with vibrational NDT techniques as well as with various traditional material characterization techniques (metallography, X-CT, …). The goal is to aim at faster qualification of the print process parameters as well as better AM material qualification. A key objective of MatchID here is to explore DIC-based solutions for a continuously expanding AM market. This involves extension of our existing tools to higher frequency vibrations and in-depth integration with finite element packages.

Funding: VLAIO, Research project, HBC.2021.0798, 2022-2026
This project is at the heart of MatchID’s vision consisting in promoting the integration of DIC with mechanical post-processing. The PhD project of Vahid Firouzbakht, one of our application engineers, aims at formalizing a procedure to perform quantitative validation of finite element structural models with DIC. The project is articulated around a set of case studies with increasing levels of complexity. As illustrated in the figure on the side, qualitative validation would be more than satisfied by just looking at the two left hand-side plots, measurement and model on the same strain scale. However, the difference between the two, scaled in terms of strain noise floor, leads to about one third of the points to be outside the +-3sigma interval where sigma is the strain noise floor. The project aims at unravelling these differences and understanding DIC uncertainties and errors in depth for validation that can be trusted by engineers. Problems related to unobservable boundary conditions or material models are of particular interest. The project should lead to a guide of good practice for model validation with DIC data.

Funding : Vlaio, Baekeland mandate (V. Firouzbakht), HBC.2024.0235, 2024-2028

Past projects

Numerical simulations are now essential in engineering design and material processing. In the automotive sector alone, the simulation market exceeds €1 billion. Yet, obtaining reliable input data—especially material behaviour across temperatures and strains—remains a major challenge. A solution is urgently needed by both simulation users and providers.

To address this, a €2.5 million European project was launched on July 1st, 2020, aiming to improve the accuracy, confidence, and robustness of steel part simulations. Over four years, it brought together five countries, four universities, three industrial partners, and more than twenty researchers. The project, entitled “Toward Virtual Forming and Design: Thermomechanical Characterization of Advanced High Strength Steels through Full-Field Measurements and a Single Designed Test,” involved the University of Aveiro (Portugal), Université de Bretagne Sud (France), KU Leuven (Belgium), Università Politecnica delle Marche (Italy), along with MatchID and OCAS (Belgium), and DAF Trucks (Netherlands). Funded by the EU’s Research Fund for Coal and Steel (RFCS-RPJ 2019), the project focused on improving simulation calibration methods to produce stiffer, stronger, lighter, and safer industrial parts. Results are available on the project website.

MatchID’s role was to develop and integrate a large database of anisotropic elast-plastic models in its Virtual Fields Method (VFM) module, as well as ensure simultaneous calibration of thermal infrared and white light cameras.

Funding: European Union, RFCS programme, Grant #888153, 2020-2024
The goal of this project was to improve both structure-borne and airborne tire noise prediction capabilities by creating novel test and simulation solutions and as such, support automotive OEMs and tire manufacturers for their vehicle NVH assessment and design, particularly in response to increasing importance of rolling noise in the electrification era. A hybrid approach has been adopted via integration of test and CAE tools for the capture of various stages of the rolling noise transfer chain. In this project, our main objective was twofold: (1) benchmark our multicamera DIC solution for sidewall 3D vibration measurements of rotating tires (2) make in-depth FEA validation studies via our FEVAL module.

Funding: VLAIO, Research project, HBC.2018.2266, 2019-2023
Many manufacturing industries still rely on experience gained through years of trial and error. Current simulation tools often require complex workflows across multiple environments, creating major bottlenecks. This project addresses two key challenges:

Usability: It aims to create an integrated, end-to-end simulation solution for selected material-process combinations to improve tool accessibility and industry adoption.

Physical accuracy: It moves beyond empirical, top-down methods by linking manufacturing conditions (e.g. thermal history), material behaviour (e.g. microstructural changes), and final part performance (e.g. strength).

By resolving these issues, the project enables more efficient, accurate assessments of manufacturing processes and delivers operational and economic benefits to industries working with thermoplastic materials, including composites. It also eliminates the need to manage a complex toolchain of separate software for material, process, and performance simulation.

In this project, MatchID has extended its live-recording capabilities towards in-situ thickness reduction measurements for quality inspection of vacuum forming process e.g. Secondly, thermal data was complementary integrated within our measurement and validation chain, including FEDEF and FEVAL modules.

Funding: VLAIO, Research project, HBC.2019.0094, 2020-2024