Justin Dirrenberger

Evaluation of morphological representative sample sizes for nanolayered polymer blends

The size of representative microstructural samples obtained from atomic force microscopy is addressed in this paper. The case of an archetypal one‐dimensional nanolayered polymer blend is considered. Image analysis is performed on micrographs obtained through atomic force microscopy, yielding statistical data concerning morphological properties of the material. The variability in terms of microstructural morphology is due to the thermomechanical processing route. The statistical data is used in order to estimate sample size representativity, based on an asymptotic relationship relating the inherent point variance of the indicator function of one material phase to the statistical, size‐dependent, ensemble variance of the same function. From the study of nanolayered material systems, the statistical approach was found to be an effective mean for discriminating and characterizing multiple scales of heterogeneity.

Calorimetric Studies and Self-Heating Measurements for a Dual-Phase Steel Under Ultrasonic Fatigue Loading

The objective of the present research is to study the self-heating behavior of a dual-phase (DP) steel under ultrasonic fatigue loading and to investigate the effect of frequency on intrinsic heat dissipation of the material. The steel studied in this work is DP600 commercial DP steel. Fatigue tests were conducted using an ultrasonic fatigue machine at a testing frequency of 20 kHz with flat specimens. An infrared camera was used to measure the mean temperature evolution during the tests. A specific form of heat diffusion equation was adopted in this work to calculate the heat dissipation per cycle from temperature measurements. The variation of this dissipation versus stress amplitude in cyclic loading was also studied.

From Architectured Materials to Large-Scale Additive Manufacturing

The classical material-by-design approach has been extensively perfected by materials scientists, while engineers have been optimising structures geometrically for centuries. The purpose of architectured materials is to build bridges across the microscale of materials and the macroscale of engineering structures, to put some geometry in the microstructure. This is a paradigm shift. Materials cannot be considered monolithic anymore. Any set of materials functions, even antagonistic ones, can be envisaged in the future. In this paper, we intend to demonstrate the pertinence of computation for developing architectured materials, and the not-so-incidental outcome which led us to developing large-scale additive manufacturing for architectural applications.