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Boundary lubrication cannot provide long-term protection against scuffing. Therefore, it is fundamental to recognise the breaking point of the boundary layer that activates scuffing. Based on this assumption, three-dimensional (3D) morphologies of surfaces were characterised, and the fundamental conditions of the scuffing process were investigated to identify the transition from boundary lubrication conditions to catastrophic wear.

A series of systematic tribological double-blind experiments were carried out using a poorly lubricated cylinder/plane interface to model the tribological inverse problem in a boundary lubrication situation. Areal morphological analysis was performed, with the help of an optical interferometer, on a millimetric area corresponding to the contact surface during experimental tribological investigations. The statistical correlation between scuffing and the selected morphological parameters was evaluated. This evaluation study consisted of determining the linear, logarithmic, exponential, polynomial (of degree 2) or power dependency between time to scuffing and morphological parameters.

A clear, statistically confirmed relationship was observed between selected morphological parameters of the surface (Spd, Sha, Str, Sz) and its scuffing performance.

3D morphological parameters that best specified the technological scuffing performance of metallic surfaces were selected and proposed.

The present paper aims to explore a computational homogenisation procedure to investigate the full geometric representation of yield surfaces for isotropic porous ductile media. The effects of cell morphology and imposed boundary conditions are assessed. The sensitivity of the yield surfaces to the Lode angle is also investigated in detail.

The microscale of the material is modelled by the concept of Representative Volume Element (RVE) or unit cell, which is numerically simulated through three-dimensional finite element analyses. Numerous loading conditions are considered to create complete yield surfaces encompassing high, intermediate and low triaxialities. The influence of cell morphology on the yield surfaces is assessed considering a spherical cell with spherical void and a cubic RVE with spherical void, both under uniform strain boundary condition. The use of spherical cell is interesting as preferential directions in the effective behaviour are avoided. The periodic boundary condition, which favours strain localization, is imposed on the cubic RVE to compare the results. Small strains are assumed and the cell matrix is considered as a perfect elasto-plastic material following the von Mises yield criterion.

Different morphologies for the cell imply in different yield conditions for the same load situations. The yield surfaces in correspondence to periodic boundary condition show significant differences compared to those obtained by imposing uniform strain boundary condition. The stress Lode angle has a strong influence on the geometry of the yield surfaces considering low and intermediate triaxialities.

The exhaustive computational study of the effects of cell morphologies and imposed boundary conditions fills a gap in the full representation of the flow surfaces. The homogenisation-based strategy allows us to further investigate the influence of the Lode angle on the yield surfaces.

The purpose of this study is to solve the issues of time-consuming and complicated computation of traditional measures, as well as the underutilization of two-dimensional (2D) phase-trajectory projection matrix, so a new set of features were proposed based on the projection of attractors trajectory to characterize the friction-induced attractors and to reveal the tribological behavior during the running-in process.

The frictional running-in experiments were conducted by sliding a ball against a static disk, and the friction coefficient was collected to reconstruct the friction-induced attractors. The projection of the attractors in 2D subspace was then mapped and the distribution of phase points was adapted to conduct the feature extraction.

The evolution of the proposed moment measures could be described as “initial rapid decrease/increase- midterm gradual decrease/increase- finally stable,” which could effectively reveal the convergence degree of the friction-induced attractors. Moreover, the measures could also describe the relative position of the attractors in phase–space domain, which reveal the amplitude evolution of signals to some extent.

The proposed measures could reveal the evolution of tribological behaviors during the running-in process and meet the more precise real-time running-in status identification.

The purpose of this paper is to develop and parameterize a time‐invariant (equilibrium) material mechanical model for segmented polyureas, a class of thermoplastically linked co‐polymeric elastomers, using experimental data available in open literature.

The key components of the model are developed by first constructing a simple molecular‐level microstructure model and by relating the microstructural elements and intrinsic material processes to the material mechanical response. The new feature of the present material model relative to the ones currently used is that the physical origin and the evolution equation for the deformation‐induced softening and inelasticity observed in polyureas are directly linked to the associated evolution of the soft‐matrix/hard segment molecular‐level microstructure of this material. The model is first developed for the case of uniaxial loading, parameterized using one set of experimental results and finally validated using another set of experimental results.

The validation procedure suggested that the model can reasonably well account for the equilibrium mechanical response of polyureas under the simple uniaxial loading conditions.

The present approach enables a more accurate determination of the mechanical behavior of polyurea and related elastomeric materials.

The paper aims to research the applications of topological geometry to the architectural concept design process and their combination with the modern digital technology to find novel architectural spaces and forms which are dynamic, easily adaptable to the context and surroundings.

The article uses the method of studying the existing literature on topological geometry and architectural design theory including design thinking, architectural design methods and architectural compositions to analyze and compare them with architectural practices and suggest new topological design tools and methods. Moreover, the paper tests the proposals with a number of preliminary design research experiments. In addition, graphic design software, parametric design, building information modeling (BIM) and digital development trends in architecture were explored and experienced to reveal the application potential of topological design thinking and methods in the trend of architectural digitization.

The paper has analyzed, synthesized and systematized the basic theories of topological geometry in order to clarify their applications in the architectural concept design process. On that basis, the paper proposes a novel topological design thinking and method for finding rich diversified architectural ideas and forms based on original invariant design constraints. Finally, the paper clarifies the combination as well as the mutual, motivating relationship between topological geometry and modern digital technologies when applied to architectural design.

The research contributes a novel design thinking and method based on topological geometry combined with modern digital technology to the architectural design theory. It will be a valuable tool capable of suggesting architects how to think and innovate in architecture in the era of industrial revolution 4.0.

The purpose of this paper is the numerical assessment of concrete behaviour close to failure, via the development of robust elastoplastic models inclusive of damage effects. If mesoscale investigations are to be considered, the model must take into account the local confinement effects because of the presence of aggregate inclusions in the cement paste and, correspondingly, the possibility to account for local 3D stress states even under uniaxial compression. Additionally, to enhance the predictive capabilities of a mesoscale representation, the reconstructed geometry must accurately follow the real one.

The work provides a procedure that combines a 3D digital image technique with finite element (FE) modelling thus maintaining the original 3D morphology of the composite.

The potentialities of the proposed approach are discussed, giving new insights to a FE modelling (FEM)-based approach applied together with a computer-aided design. Coupled mechanisms of mechanical mismatch and confinement, characterizing the combined cement matrix-aggregates effect, are captured and highlighted via the numerical tests.

The novelty of this research work lies in the proposal of a digitally based methodology for a precise concrete reconstruction together with the adoption of an upgraded elastic–plastic damage model for the cement paste.

Outcome with a novel methodology for online recognition and classification of pieces in robotic assembly tasks and its application into an intelligent manufacturing cell.

The performance of industrial robots working in unstructured environments can be improved using visual perception and learning techniques. The object recognition is accomplished using an artificial neural network (ANN) architecture which receives a descriptive vector called CFD&POSE as the input. Experimental results were done within a manufacturing cell and assembly parts.

Find this vector represents an innovative methodology for classification and identification of pieces in robotic tasks, obtaining fast recognition and pose estimation information in real time. The vector compresses 3D object data from assembly parts and it is invariant to scale, rotation and orientation, and it also supports a wide range of illumination levels.

Provides vision guidance in assembly tasks, current work addresses the use of ANN's for assembly and object recognition separately, future work is oriented to use the same neural controller for all different sensorial modes.

Intelligent manufacturing cells developed with multimodal sensor capabilities, might use this methodology for future industrial applications including robotics fixtureless assembly. The approach in combination with the fast learning capability of ART networks indicates the suitability for industrial robot applications as it is demonstrated through experimental results.

This paper introduces a novel method which uses collections of 2D images to obtain a very fast feature data – ”current frame descriptor vector” – of an object by using image projections and canonical forms geometry grouping for invariant object recognition.

This study aims to review the effect of copper percentage in Sn-based solder alloys (Sn-xCu, x = 0–5 Wt.%) on intermetallic compound (IMC) formation and growth after laser soldering.

This study reviews the interfacial reactions at the solder joint interface, solder joint morphology and the theory on characterizing the formation and growth of IMCs. In addition, the effects of alloying and strengthening mechanism, including wettability, melting and mechanical properties are discussed.

This paper presents a comprehensive overview of the composition of tin-copper (Sn-Cu) solders with a potential to enhance their microstructure, mechanical characteristics and wettability by varying the Cu percentage. The study found that the best Cu content in the Sn-xCu solder alloy was 0.6–0.7 Wt.%; this composition provided high shear strength, vibration fracture life value and ideal IMC thickness. A method of solder alloy preparation was also found through powder metallurgy and laser soldering to improve the solder joint reliability.

This study focuses on interfacial reactions at the solder joint interface, solder joint morphology, modelling simulation of joint strength and the theory on characterising the formation and growth of IMC.

The paper comprehensively summarises the useful findings of the Sn-Cu series. This information will be important for future trends in laser soldering on solder joint formation.

The purpose of this paper is to provide a computational procedure for a novel damage‐coupled material law for semicrystalline polyethylene. Using a damage mechanics approach, the model seeks to gain insight into the mechanical behaviour of polyethylene considering the microstructure and degradation processes occurring under uniaxial tension.

The material morphology is modelled as a collection of inclusions. Each inclusion consists of crystalline material lying in a thin lamella attached to an amorphous layer. The interface region interconnecting the two phases is the plane through which loads are carried and transferred by the tie molecules. It is assumed that the constitutive model contains complete information about the mechanical behaviour and degradation processes of each constituent. After modelling the two phases independently, the inclusion behaviour is found by applying some compatibility and equilibrium restrictions along the interface plane.

The model provides a rational representation of the damage process of the intermolecular bonds holding crystals and of the tie‐molecules connecting neighbouring crystallites. The model is also used to analyze the degree of relationship between some of the material properties and the mechanical responses.

In practice, the numerical model clearly helps to understand the influence of the different microstructure properties on the tensile mechanical behaviour of semicrystalline polyethylene – an issue of particular interest in improving material processability and product performance.

To the authors’ knowledge, a phenomenon such as microstructural degradation of polyethylene has not received much attention in the literature. The proposed model successfully captures aspects of the material behaviour considering crystal fragmentation and tie‐molecule rupture.

The purpose of this study is to quantify the impact of the variation of microstructural features on macroscopic and microscopic fields. The application of multi-scale methods in the context of constitutive modeling of microheterogeneous materials requires the choice of a representative volume element (RVE) of the considered microstructure, which may be based on some idealized assumptions and/or on experimental observations. In any case, a realistic microstructure within the RVE is either computationally too expensive or not fully accessible by experimental measurement techniques, which introduces some uncertainty regarding the microstructural features.

In this paper, a systematical variation of microstructural parameters controlling the morphology of an RVE with an idealized microstructure is conducted and the impact on macroscopic quantities of interest as well as microstructural fields and their statistics is investigated. The study is carried out under macroscopically homogeneous deformation states using the direct micro-macro scale transition approach.

The variation of microstructural parameters, such as inclusion volume fraction, aspect ratio and orientation of the inclusion with respect to the overall loading, influences the macroscopic behavior, especially the micromechanical fields significantly.

The systematic assessment of the impact of microstructural parameters on both macroscopic quantities and statistics of the micromechanical fields allows for a quantitative comparison of different microstructure morphologies and a reliable identification of microstructural parameters that promote failure initialization in microheterogeneous materials.