In computational physics proton transfer phenomena could be viewed as pattern classification problems based on a set of input features allowing classification of the proton motion into two categories： transfer ＇occu...In computational physics proton transfer phenomena could be viewed as pattern classification problems based on a set of input features allowing classification of the proton motion into two categories： transfer ＇occurred＇ and transfer ＇not occurred＇. The goal of this paper is to evaluate the use of artificial neural networks in the classification of proton transfer events, based on the feed-forward back propagation neural network, used as a classifier to distinguish between the two transfer cases. In this paper, we use a new developed data mining and pattern recognition tool for automating, controlling, and drawing charts of the output data of an Empirical Valence Bond existing code. The study analyzes the need for pattern recognition in aqueous proton transfer processes and how the learning approach in error back propagation （multilayer perceptron algorithms） could be satisfactorily employed in the present case. We present a tool for pattern recognition and validate the code including a real physical case study. The results of applying the artificial neural networks methodology to crowd patterns based upon selected physical properties （e.g., temperature, density） show the abilities of the network to learn proton transfer patterns corresponding to properties of the aqueous environments, which is in turn proved to be fully compatible with previous proton transfer studies.展开更多
Refined non-linear static or dynamic analyses of reinforced concrete structures require the knowledge of the actual force-displacement or bending moment-rotation curves of each structural member, which depend on the c...Refined non-linear static or dynamic analyses of reinforced concrete structures require the knowledge of the actual force-displacement or bending moment-rotation curves of each structural member, which depend on the crack widths and on the crack pattern, and after all on the slip between concrete and reinforcing steel. For this reason the definition of improved local models taking into account all these local aspects is a fundamental prerequisite for advanced assessment of r.c. structures. A numerical procedure which allows to predict the relative displacement between steel reinforcement and the surrounding concrete in a reinforced concrete element, once assigned the stress in the naked steel bar and the bond-slip law is discussed. The method provides as final outcomes the sequence of crack openings and the individual crack widths, regardless of the particular bond-slip correlation adopted. The proposed procedure is implemented referring to two relevant experimental case studies, demonstrating that it is able to predict satisfactorily actual strain fields and slips along the investigated reinforced concrete elements.展开更多
Kissing bonds are defects in the adhesive bonds with intimate contact of touching surface but considerably lowered shear strength. Their detection specifically in the aerospace area is so not satisfactory. Usually, ki...Kissing bonds are defects in the adhesive bonds with intimate contact of touching surface but considerably lowered shear strength. Their detection specifically in the aerospace area is so not satisfactory. Usually, kissing bonds are inconspicuous in ultrasonic C-scans. However, the determination of attributes in the time domain and the frequency domain of an ultrasound signal provides the opportunity to derive a pattern for bonded area. Deviations from the pattern found in inconspicuous bonding areas indicate kissing bonds. The survey described here deals with the manufacturing of adhesively joint samples that purposefully include kissing bonds, as well as potential solutions for detecting them through ultrasonic testing combined with pattern recognition. The properties of the epoxy-based adhesive were varied by changing the mixing ratios between resin and hardener. Samples with a mixing ratio far apart from the manufacturer’s recommendation with an inconspicuous appearance in a C-scan, but low shear strength values were taken for further evaluation. After a definition and learning phase, a 100 percent hit rate to separate good bondings from kissing bonds could be derived in a blind test. The discriminating feature found is due to the frequency shift between good and kissing bonds as well as the relative amplitude of the second peak.展开更多
Convex polyhedral cuprate clusters are being formed through lateral frustration when the a and c lattice parameters of the tetragonal ACuO2 infinite layer structure will become identical by substitution of a large cat...Convex polyhedral cuprate clusters are being formed through lateral frustration when the a and c lattice parameters of the tetragonal ACuO2 infinite layer structure will become identical by substitution of a large cation (A = Ba2+). However, the corner-shared CuO2 plaquettes of the infinite network suffer a topotactic rearrangement forming edge-connected units, for instance Cu18O24 cages (polyhedron notation [4641238]) with 2 compound (space group P4/ nmm) will be discussed. The possibility to construct a cuprate super-cage with m3m symmetry (polyhedron notation [4641242438]) is being reported. This super-cage still consists of edge-connected CuO2 plaquettes when fully decorated with copper ions, but with different curvatures, arranged in circles of 9.39 ? of diameter with 139.2° Cu-O-Cu antiferromagnetic super-exchange interaction. On the one hand, the realization of such a quite stable cuprate super-cage as a candidate for high-Tc superconductivity depends on whether a template of suitable size such as the cation or C(CH3)4 enables its formation, and on the other hand the cage can further be stabilized by highly charged cations located along the [111] direction. Synthesis options will be proposed based on suggested cage formation pathways. An X-ray powder pattern was calculated for a less dense cluster structure of Im3m space group with a lattice parameter of a = 14.938 ? and two formula units of Cu46O51 to facilitate future identification. Characteristic X-ray scattering features as identification tool were obtained when the electron distribution of the hollow polyhedron was approximated with electron density in a spherical shell.展开更多
基金Dr. Steve Jones, Scientific Advisor of the Canon Foundation for Scientific Research (7200 The Quorum, Oxford Business Park, Oxford OX4 2JZ, England). Canon Foundation for Scientific Research funded the UPC 2013 tuition fees of the corresponding author during her writing this article
文摘In computational physics proton transfer phenomena could be viewed as pattern classification problems based on a set of input features allowing classification of the proton motion into two categories： transfer ＇occurred＇ and transfer ＇not occurred＇. The goal of this paper is to evaluate the use of artificial neural networks in the classification of proton transfer events, based on the feed-forward back propagation neural network, used as a classifier to distinguish between the two transfer cases. In this paper, we use a new developed data mining and pattern recognition tool for automating, controlling, and drawing charts of the output data of an Empirical Valence Bond existing code. The study analyzes the need for pattern recognition in aqueous proton transfer processes and how the learning approach in error back propagation （multilayer perceptron algorithms） could be satisfactorily employed in the present case. We present a tool for pattern recognition and validate the code including a real physical case study. The results of applying the artificial neural networks methodology to crowd patterns based upon selected physical properties （e.g., temperature, density） show the abilities of the network to learn proton transfer patterns corresponding to properties of the aqueous environments, which is in turn proved to be fully compatible with previous proton transfer studies.
文摘Refined non-linear static or dynamic analyses of reinforced concrete structures require the knowledge of the actual force-displacement or bending moment-rotation curves of each structural member, which depend on the crack widths and on the crack pattern, and after all on the slip between concrete and reinforcing steel. For this reason the definition of improved local models taking into account all these local aspects is a fundamental prerequisite for advanced assessment of r.c. structures. A numerical procedure which allows to predict the relative displacement between steel reinforcement and the surrounding concrete in a reinforced concrete element, once assigned the stress in the naked steel bar and the bond-slip law is discussed. The method provides as final outcomes the sequence of crack openings and the individual crack widths, regardless of the particular bond-slip correlation adopted. The proposed procedure is implemented referring to two relevant experimental case studies, demonstrating that it is able to predict satisfactorily actual strain fields and slips along the investigated reinforced concrete elements.
文摘Kissing bonds are defects in the adhesive bonds with intimate contact of touching surface but considerably lowered shear strength. Their detection specifically in the aerospace area is so not satisfactory. Usually, kissing bonds are inconspicuous in ultrasonic C-scans. However, the determination of attributes in the time domain and the frequency domain of an ultrasound signal provides the opportunity to derive a pattern for bonded area. Deviations from the pattern found in inconspicuous bonding areas indicate kissing bonds. The survey described here deals with the manufacturing of adhesively joint samples that purposefully include kissing bonds, as well as potential solutions for detecting them through ultrasonic testing combined with pattern recognition. The properties of the epoxy-based adhesive were varied by changing the mixing ratios between resin and hardener. Samples with a mixing ratio far apart from the manufacturer’s recommendation with an inconspicuous appearance in a C-scan, but low shear strength values were taken for further evaluation. After a definition and learning phase, a 100 percent hit rate to separate good bondings from kissing bonds could be derived in a blind test. The discriminating feature found is due to the frequency shift between good and kissing bonds as well as the relative amplitude of the second peak.
文摘Convex polyhedral cuprate clusters are being formed through lateral frustration when the a and c lattice parameters of the tetragonal ACuO2 infinite layer structure will become identical by substitution of a large cation (A = Ba2+). However, the corner-shared CuO2 plaquettes of the infinite network suffer a topotactic rearrangement forming edge-connected units, for instance Cu18O24 cages (polyhedron notation [4641238]) with 2 compound (space group P4/ nmm) will be discussed. The possibility to construct a cuprate super-cage with m3m symmetry (polyhedron notation [4641242438]) is being reported. This super-cage still consists of edge-connected CuO2 plaquettes when fully decorated with copper ions, but with different curvatures, arranged in circles of 9.39 ? of diameter with 139.2° Cu-O-Cu antiferromagnetic super-exchange interaction. On the one hand, the realization of such a quite stable cuprate super-cage as a candidate for high-Tc superconductivity depends on whether a template of suitable size such as the cation or C(CH3)4 enables its formation, and on the other hand the cage can further be stabilized by highly charged cations located along the [111] direction. Synthesis options will be proposed based on suggested cage formation pathways. An X-ray powder pattern was calculated for a less dense cluster structure of Im3m space group with a lattice parameter of a = 14.938 ? and two formula units of Cu46O51 to facilitate future identification. Characteristic X-ray scattering features as identification tool were obtained when the electron distribution of the hollow polyhedron was approximated with electron density in a spherical shell.
