This study investigates the topography evolution of a calibrated surface on a rectangular column 316L stainless steel specimen during a robotic PEMEC (French acronym Polissage Electro-MEcano-Chimique, electrochemical-mechanical polishing) process. The robotic PEMEC equipment consists of a six-axis robot mounted with the 316L specimen and a rotating tank filled with a mixture with abrasive media and electrolyte. A robotic motion strategy was developed to efficiently expose the specimen to the mixture flow of by targeting one surface of the specimen. The results showed the surface roughness of the target surface improved from 13.4 µm to 0.3 µm Ra during a 30-minute PEMEC process. Surface topography changes, material removal, and edge profile evolution between conventional and robotic PEMEC are compared, and possible causes of these evolutions are discussed.
The relationship between surface integrity, particularly residual stresses, and fatigue life is well-established. A model known as the "3D hybrid multi-pass model" has been previously developed to predict the 3D residual stress fields generated by longitudinal turning over multiple revolutions until a steady state is reached. This model simulates the generation of residual stresses by accounting for equivalent 3D thermo-mechanical loads, which are calibrated using cutting force measurements, as they move over the machined surface. The aim of this paper is to adapt this methodology for surface milling, where multiple cutting edges generate the surface at a much higher frequency. A case study on the surface milling of 15-5PH martensitic stainless steel is presented.
This study focuses on assessing the thermomechanical behavior of cold mix asphalt (CMA) at young age using the Impact Resonance Test (IRT). Several IRTs were performed during the curing of two emulsion-based CMA samples at constant temperature, and the complex modulus was determined using both numerical and analytical back analysis methods. The material properties vary considerably in the first week, stabilizing during the following week. One sample was subjected to IRT 13 days after compaction at different temperatures. The obtained complex modulus were plot in the Cole-Cole plane, showing that the material follows the Time-Temperature Superposition Principle (TTSP).
Accurate prediction of vibrational energy transmission in slender structures is essential for the analysis and design of modern mechanical systems, particularly at micro-and nano-scales and in mid-to-high frequency regimes. In this work, an energy-based vibroacoustic framework for onedimensional viscoelastic rods and Euler-Bernoulli beams is developed using second strain gradient theory. Energy methods are especially suitable in this frequency range, where displacement-based numerical approaches become computationally inefficient and less robust, while physically relevant quantities such as energy density, energy flux, and injected power govern the system response. By incorporating higher-order strain terms, second strain gradient theory enables more accurate modeling of microstructural features and small-scale heterogeneities that are not captured by conventional continuum formulations. Analytical expressions for strain and kinetic energy densities and energy flux are derived within the SSG framework. Numerical investigations illustrate the influence of second strain gradient effects on wave propagation characteristics and vibrational energy distribution, highlighting the enhanced predictive capability of the proposed approach for mid-to-high frequency vibroacoustic analysis of one-dimensional media.
Biocompatibility of a biosensor can be achieved by grafting polymer brushes onto a solid surface. These brushes must be able to attract specific analytes or repel unwanted entities. This is obtained with weak polyelectrolyte polymer brushes that shrink or swell depending on external stimuli. In this study, the conformation of polyacrylic acid (PAA) and polyethylene oxide (PEO) polymer brushes was characterized as a function of pH and ionic strength using Atomic Force Microscopy (AFM) in spectroscopic mode. Instead of colloidal tips classically used to measure the mechanical behavior of the brush, force curves were performed with conventional tips for better sensitivity to the interaction between ions and polymer, which is responsible for their conformation. Since force mapping experiments generate thousands of curves, a statistical representation was employed to define the general trend of the curves and facilitate their interpretation. As expected, the neutral PEO is not affected by changes in solution pH and salinity. In contrast, PAA exhibits behaviors depending on the ions present in the solution and increasing salinity; the brush shrinks at low pH with H3O+ ions and swells with the addition of Na+ and K+ ions. The originality of the study also lies in the implementation of an Artificial Intelligence (AI) clustering model applied to force curves to specifically study a 50% PAA/50% PEO mixed polymer brush. This AI model makes it possible to distinguish areas of the surface where only one type of polymer has been grafted and to identify its nature according to its force curve.
