Structure and Applications of Surfactants

Surfactant molecules have two parts, a lipophilic (apolar) part that retains fat and a hydrophilic (polar) part that is miscible with water. The lipophilic portion consists of one or more aliphatic, straight or branched or aromatic or even alkylaromatic hydro- or fluorocarbon chains. The hydrophilic portion or polar head consists of one or more polar groups, ionic or nonionic. Surfactants have a wide variety of applications that include membrane permeabilization and dissolution, inclusion body solubilization, as well as membrane protein solubilization, biochemistry, crystallization, and manipulation. The behavior of these molecules is directly related to the aversion to water of the nonpolar groups, whereas the polar moieties tend to be highly hydrated. Their surfactant properties are therefore essentially based on the balance between the hydrophilic and hydrophobic parts of the molecule, called HLB (Hydrophile-Lipophile Balance)

Watermarking for the Secure Transmission of the Key into an Encrypted Image

Ensuring the confidentiality of any data exchanged always presents a great concern for all communication instances. Technically, encryption is the ideal solution for this task. However, this process must deal with the progress of the cryptanalysis that aims to disclose the information exchanged. The risk increases due to the need for a dual transmission that includes the encrypted medium and the decryption key. In a context of chaotic encryption of images, we propose to insert the decryption key into the encrypted image using image watermarking. Thus, only the watermarked encrypted image will be transmitted. Upon reception, the recipient extracts the key and decrypts the image. The cryptosystem proposed is based on an encryption using a dynamic Look-Up Table issued from a chaotic generator. The obtained results prove the efficiency of our method to ensure a secure exchange of images and keys

Mechanical characterization and constitutive parameter identification of anisotropic tubular materials for hydroforming applications

This paper aims to identify the constitutive parameters of anisotropic tubular materials and to verify the accuracy of models' prediction. The identification of the constitutive parameters is based on information obtained from tensile tests, performed on samples cut from the tubes, and from the free tubular bulge test, using a home-developed bulge forming machine. Two tubular materials exhibiting different anisotropic behaviour and work hardening characteristics are investigated: a mild steel S235 seamed tube and an aluminium alloy AA6063 extruded tube. It is shown that advanced phenomenological yield functions, including a large number of anisotropy parameters, can accurately describe the plastic flow of highly anisotropic tubular materials during the tube hydroforming process. However, parameter identification procedure of advanced yield criteria requires a high number of experimental tests. Thus, in order to enable the parameter identification of these yield criteria when using a reduced set of experimental results, the present study develops a method that combines tensile tests with (i) a free bulge test, which is used to characterize the biaxial stress state experienced by the tube during the bulge testing, and (ii) some generated artificial input data. Finally, the proposed method shows an excellent agreement between numerical predictions and experimental results.The authors gratefully acknowledge the financial support of the Portuguese Foundation for Science and Technology (FCT) via the projects PTDC/EMS-TEC/1805/2012 and PEst-C/EME/UI0285/2013 and by FEDER funds through the program COMPETE – Programa Operacional Factores de Competitividade, under the project CENTRO-07-0224-FEDER-002001 (MT4MOBI). The first author is also grateful for the Post-Doc grant.info:eu-repo/semantics/publishedVersio

Machine learning for predicting fracture strain in sheet metal forming

Machine learning models are built to predict the strain values for which edge cracking occurs in hole expansion tests. The samples from this test play the role of sheet metal components to be manufactured, in which edge cracking often occurs associated with a uniaxial tension stress state at the critical edges of components. For the construction of the models, a dataset was obtained experimentally for rolled ferritic carbon steel sheets of different qualities and thicknesses. Two types of tests were performed: tensile and hole expansion tests. In the tensile test, the yield stress, the tensile strength, the strain at maximum load and the elongation after fracture were determined in the rolling and transverse directions. In the hole expansion test, the strain for which edge cracking occurs, was determined. It is intended that the models can predict the strain at fracture in this test, based on the knowledge of the tensile test data. The machine learning algorithms used were Multilayer Perceptron, Gaussian Processes, Support Vector Regression and Random Forest. The traditional polynomial regression that fits a 2nd order polynomial function was also used for comparison. It is shown that machine learning-based predictive models outperform the traditional polynomial regression method; in particular, Gaussian Processes and Support Vector Regression were found to be the best machine learning algorithms that enable the most robust predictive models.publishe

Influence of the characteristics of the experimental data set used to identify anisotropy parameters

This work presents an investigation into the effect of the number and type of experimental input data used in parameter identification of Hill’48, Barlat’91 (Yld91) and Cazacu and Barlat’2001 (CB2001) yield criteria on the accuracy of the finite element simulation results. Different sets of experimental data are used to identify the anisotropy parameters of two metal sheets, exhibiting different anisotropic behaviour and hardening characteristics: a mild steel (DC06) and an aluminium alloy (AA6016-T4). Although it has been shown that the CB2001 yield criterion can lead to an accurate description of anisotropic behaviour of metallic sheets, its calibration requires a large set of experimental input data. A calibration procedure is proposed for CB2001 based on a reduced set of experimental data, i.e. where the results are limited to three uniaxial tensile tests, combined with artificial data obtained using the Barlat’91 yield criterion. Evaluation of the predictive capacity of the studied yield criteria, calibrated using different sets of experimental data, is made by comparing finite element simulation results with experimental results for the deep drawing of a crossshaped part. A satisfying agreement is observed between experimental and numerical thickness distributions, with a negligible effect of the number and type of experimental data for the Hill’48 and Yld91 yield criteria. On the contrary, CB2001 calibration is quite sensitive to the experimental data available, particularly biaxial values. Nevertheless, CB2001 calibration based on the combination of effective and artificial experimental data achieves satisfying results, which in the worst case are similar to the ones obtained with the Yld91.The authors gratefully acknowledge the financial support of the Portuguese Foundation for Science and Technology (FCT) via the projects PTDC/EMS-TEC/1805/2012 and PEst-C/EME/UI0285/2013 and by FEDER funds through the program COMPETE – Programa Operacional Factores de Competitividade, under the project CENTRO-07-0224-FEDER-002001 (MT4MOBI). The first author is also grateful for the Post-Doc grant.info:eu-repo/semantics/publishedVersio

Identification des lois de comportemement élastoplastiques par essais inhomogènes et simulations numériques

The subject of the thesis deals with the anisotropy elastoplastic constitutive behavior law identification in the aim of its use for the numerical simulation of the metal sheet deep drawing processes. Essentially, we have contributed to the definition and the application of constitutive behavior identification techniques and strategies from experimental tests. The classical tests used for the identification: Simple tensile test, in the axes and off-axes, plane tensile test and the bulge test are presented and analyzed from the point of view of the deformation homogeneity to outcome to the stress-strain relation grom the globales measurements force-displacement. The identification of the behaviorlaws from homogeneous tests needs numerical simulation coupled with an optimisation procedure (simplex method) for minimizing the difference between measured results and model responses calculated by finite element method. We have identified anisotropy elastoplastic behaviour laws with isotropy hardening law. These laws are based on the choice of the constitutive functions" equivalent stress" which defines the yield locus and plasticity potential( non associated plasticity) that has the same form as the yield function. Several quadratic and non quadratic yield loci are then used. We have developed a specific sensitivity analysis method of the tests in relation to the identified behaviour law parameters. This method is applied on practical examples.Le sujet de thèse que nous abordons concerne l'identification des lois de comportement élastoplastiques anisotropes en vue de leur utilisation pour la simulation numérique des procédés de mise en forme par déformation plastique de tôles minces métalliques d'emboutissage. Nous avons essentiellement contribué à la définition et à la mise en oeuvre de stratégies et techniques d'identification des lois de comportement à partir d'essais expérimentaux. Les essais classiquement utilisés pour l'identification des modèles : la traction simple dans les axes et hors axes, la traction plane et le gonfelement hydraulique sont présentés et analysés du point de vue homogénéité des déformations pour aboutir à la relation contrainte-déformation à partir des mesures globales force-déplacement. L'identification des modèles de comportement à partir des essais inhomogènes nécessite une simulation numérique couplée avec une méthode d'optimisation (méthode du Simplexe) pour minimiser l'écart entre les résultats expérimentaux et la réponse du modèle calculée par une méthode d'élements finis. Nous avons identifié des lois de comportement élastoplastiques anisotropes avec écrouissage isotrope. Ces lois sont basées en particulier sur le choix d'une ou deux fonctions "contrainte équivalente" définissant le critère de plasticité et le potentiel plastique (cadre de la normalité non associée) ayant la même structure que la fonction seuil. Plusieurs critères quadratiques et non quadratiques sont alors utilisés. Nous avons développé une technique spécifique d'analyse de sensibilité des essais par rapport aux differents paramètres à identifier de la loi de comportement. Cette technique est mise en oeuvre sur des exemples pratiques

The Pandemic Discourse: A Cross-Cultural Case Study

The paper examines speech samples of 5 politicians, namely the presidents of Sudan, Brazil, United States, Indonesia and the British queen. Samples are taken from and specifically focused on public speech related to the events regarding the COVID-19 Pandemic. The goal of the research is to make a cross-cultural linguistic comparison based on the qualitative data. The methodology is anchored in discourse analysis of the speech samples and their interpretation. The examination has shown there are considerable individual and cultural differences between the studied subjects, which can be seen from the point of view of discourse analysis, especially in the context of power and media influence. Additionally, the paper suggests further possible points of view from which other disciplines might be used in order to build a more comprehensive understanding of the studied matter