Statistical analysis of the V-tool bending process parameters in the bending of HC260Y steel

This paper presents statistical analysis of the parameters in the V-tool bending process of the HC260Y steel. Assessment of the mathematical model and analysis of variance (ANOVA) were performed within the design of experiments. The hydraulic testing machine Amsler and the developed V-tool were used in the experiments

Mechanical clinching process stress and strain in the clinching of EN-AW5754 (AlMg3), and EN AW-5019 (AlMg5) metal plates

This paper presents the results of Finite Element Method numerical simulation performed onEN-AW5754(AlMg3), EN AW-5019 (AlMg5) plates subjected to mechanical clinching. The goal was to observe differences between aluminum plates in the same tool; and to determine the possibility of using the constructed tool for the clinching of Al-Al material combinations. This tool construction is to be produced and tested in laboratory conditions, to elaborate prospective results, and reach additional conclusions

Statistical analysis of different mathematical models for stress-strain curves of AISI 321 stainless steel

This paper presents statistical analysis of data obtained by uniaxial tensile testing of AISI 321 stainless steel. This data is required as material input in numerical software, such as Abaqus, Ansys, MSC Marc, Nastran, etc. This data can be provided in the software as a set of points (piecewise linear model) that is cumbersome to enter, or it can be provided as a mathematical model, in the case of which the Finite Element Method (FEM) software calculates desired points directly from the mathematical model. Various mathematical models can be used to approximate tensile test data depending on the material loading state (linear, elasto-plastic, plastic). In this paper, the same uniaxial test data is analyzed, and curve fitting parameters are shown for each mathematical model

Effect of spring-back in v-tool bending of high-strength steel sheet metal plates

This paper deals with the effects of technological parameters used in the V-die bending process, on the obtained product properties and dimensions. By variation of the tool geometry, several cases of steel sheet bending process are observed through the FEM simulations. Also by variation of different mechanical material properties, effects on product geometry are observed. Since the automobile manufacturers mostly use the high strength steel sheet metal plates, there is a need for the successful tool construction and optimization in order to produce quality products

AllenRV: an Extensible Monitor for Multiple Complex Specifications with High Reactivity

International audienceAllenRV is a tool for monitoring temporal specifications, designed for ensuring good scalability in terms of size and number of formulae, and high reactivity. Its features reflect this design goal. For ensuring scalability in the number of formulae, it can simultaneously monitor a set of formulae written in past and future, next-free LTL, with some metric extensions; their efficient simultaneous monitoring is supported by a let construct allowing to share computations between formulae. For ensuring scalability in the size of formulae, it allows defining new abstractions as user-defined operators, which take discrete time boolean signals as arguments, but also constant parameters such as delays. For ensuring high reactivity, its monitoring algorithm does not require clock tick events, unlike many other tools. This is achieved by recomputing output signals both upon input signals changes and upon internally generated timeout events relative to such changes. As a consequence, monitoring remains efficient on arbitrarily fine-grained time domains. AllenRV is implemented by extending the existing Allen language and compiler, initially targeting ubiquitous applications using binary sensors, with temporal logic operators and a comprehensive library of user-defined operators on top of them. The most complex of these operators, including a complete adaptation of Allen-logic relations as selection operators, are proven correct with respect to their defined semantics. Thus, AllenRV offers an open platform for cooperatively developing increasingly complex libraries of high level, general or domain-specific, temporal operators and abstractions, without compromising correctness

Routine Modeling with Time Series Metric Learning

version éditeur : https://rd.springer.com/chapter/10.1007/978-3-030-30484-3_47International audienceTraditionally, the automatic recognition of human activities is performed with supervised learning algorithms on limited sets of specific activities. This work proposes to recognize recurrent activity patterns, called routines, instead of precisely defined activities. The modeling of routines is defined as a metric learning problem, and an architecture, called SS2S, based on sequence-to-sequence models is proposed to learn a distance between time series. This approach only relies on inertial data and is thus non intrusive and preserves privacy. Experimental results show that a clustering algorithm provided with the learned distance is able to recover daily routines

A novel application of motion analysis for detecting stress responses in embryos at different stages of development.

Motion analysis is one of the tools available to biologists to extract biologically relevant information from image datasets and has been applied to a diverse range of organisms. The application of motion analysis during early development presents a challenge, as embryos often exhibit complex, subtle and diverse movement patterns. A method of motion analysis able to holistically quantify complex embryonic movements could be a powerful tool for fields such as toxicology and developmental biology to investigate whole organism stress responses. Here we assessed whether motion analysis could be used to distinguish the effects of stressors on three early developmental stages of each of three species: (i) the zebrafish Danio rerio (stages 19 h, 21.5 h and 33 h exposed to 1.5% ethanol and a salinity of 5); (ii) the African clawed toad Xenopus laevis (stages 24, 32 and 34 exposed to a salinity of 20); and iii) the pond snail Radix balthica (stages E3, E4, E6, E9 and E11 exposed to salinities of 5, 10 and 15). Image sequences were analysed using Sparse Optic Flow and the resultant frame-to-frame motion parameters were analysed using Discrete Fourier Transform to quantify the distribution of energy at different frequencies. This spectral frequency dataset was then used to construct a Bray-Curtis similarity matrix and differences in movement patterns between embryos in this matrix were tested for using ANOSIM

Quantifying the Dynamics of Coupled Networks of Switches and Oscillators

Complex network dynamics have been analyzed with models of systems of coupled switches or systems of coupled oscillators. However, many complex systems are composed of components with diverse dynamics whose interactions drive the system's evolution. We, therefore, introduce a new modeling framework that describes the dynamics of networks composed of both oscillators and switches. Both oscillator synchronization and switch stability are preserved in these heterogeneous, coupled networks. Furthermore, this model recapitulates the qualitative dynamics for the yeast cell cycle consistent with the hypothesized dynamics resulting from decomposition of the regulatory network into dynamic motifs. Introducing feedback into the cell-cycle network induces qualitative dynamics analogous to limitless replicative potential that is a hallmark of cancer. As a result, the proposed model of switch and oscillator coupling provides the ability to incorporate mechanisms that underlie the synchronized stimulus response ubiquitous in biochemical systems