Fiber concrete beam failure observed as rare phenomena

Investigation of various dynamical natural and technical phenomena is closely connected with studying general nonlinear phenomena characterizing the behavior of dynamical systems. In recent years much attention has been paid to studying new nonlinear effects which can be used in vibro-technique, even in simple systems. Such systems happen to have complicated dynamics which has not been studied sufficiently yet. Fiber concrete beam failure always can be observered as rare phenomena because of existence of considerable dispersion of strength. The aim of this paper is to obtain function described stiffness of fiber concrete beam in the first stage (beam without crack) and at post-cracking stage (beam with crack

Fiberconcrete non-linear fracture control through fresh concrete flow numerical simulation

The use of fiber (steel or synthetic) reinforced concrete (FRC) had a considerable increase during the last decades mainly due to its higher resistance to crack formation and simplified casting technique. At the same time fiberconcrete strength properties are non-linear with a high scatter. The paper presents results for fiberconcrete post-cracking behavior control by means of fresh FRC flow numerical simulations and prediction of internal structure (fiber orientation and distribution) formatio

Strength calculation for a tank of the tank-car under repeated loading

В данной работе выполнена оценка усталостной прочности котла вагона- цистерны при циклическом нагружении на основании прочностного расчета, определен характер изменения во времени основных нагрузок и их влияние на появление усталостных трещин котла, выявленных при техническом освидетельствовании вагонов-цистерн. Оценено влияние действия циклических вертикальных (динамика груза), продольных (тяговые, сжимающие) и поперечных (боковая рамная сила) нагрузок на усталостную прочность котла в условиях эксплуатации на Латвийской железной дороге

Fluctuating Nonlinear Spring Model of Mechanical Deformation of Biological Particles

We present a new theory for modeling forced indentation spectral lineshapes of biological particles, which considers non-linear Hertzian deformation due to an indenter-particle physical contact and bending deformations of curved beams modeling the particle structure. The bending of beams beyond the critical point triggers the particle dynamic transition to the collapsed state, an extreme event leading to the catastrophic force drop as observed in the force (F)-deformation (X) spectra. The theory interprets fine features of the spectra: the slope of the FX curves and the position of force-peak signal, in terms of mechanical characteristics --- the Young's moduli for Hertzian and bending deformations E_H and E_b, and the probability distribution of the maximum strength with the strength of the strongest beam F_b^* and the beams' failure rate m. The theory is applied to successfully characterize the $FX$ curves for spherical virus particles --- CCMV, TrV, and AdV

Unsupervised word embeddings capture latent knowledge from materials science literature.

The overwhelming majority of scientific knowledge is published as text, which is difficult to analyse by either traditional statistical analysis or modern machine learning methods. By contrast, the main source of machine-interpretable data for the materials research community has come from structured property databases1,2, which encompass only a small fraction of the knowledge present in the research literature. Beyond property values, publications contain valuable knowledge regarding the connections and relationships between data items as interpreted by the authors. To improve the identification and use of this knowledge, several studies have focused on the retrieval of information from scientific literature using supervised natural language processing3-10, which requires large hand-labelled datasets for training. Here we show that materials science knowledge present in the published literature can be efficiently encoded as information-dense word embeddings11-13 (vector representations of words) without human labelling or supervision. Without any explicit insertion of chemical knowledge, these embeddings capture complex materials science concepts such as the underlying structure of the periodic table and structure-property relationships in materials. Furthermore, we demonstrate that an unsupervised method can recommend materials for functional applications several years before their discovery. This suggests that latent knowledge regarding future discoveries is to a large extent embedded in past publications. Our findings highlight the possibility of extracting knowledge and relationships from the massive body of scientific literature in a collective manner, and point towards a generalized approach to the mining of scientific literature

Tubulin bond energies and microtubule biomechanics determined from nanoindentation in silico

Microtubules, the primary components of the chromosome segregation machinery, are stabilized by longitudinal and lateral non-covalent bonds between the tubulin subunits. However, the thermodynamics of these bonds and the microtubule physico-chemical properties are poorly understood. Here, we explore the biomechanics of microtubule polymers using multiscale computational modeling and nanoindentations in silico of a contiguous microtubule fragment. A close match between the simulated and experimental force-deformation spectra enabled us to correlate the microtubule biomechanics with dynamic structural transitions at the nanoscale. Our mechanical testing revealed that the compressed MT behaves as a system of rigid elements interconnected through a network of lateral and longitudinal elastic bonds. The initial regime of continuous elastic deformation of the microtubule is followed by the transition regime, during which the microtubule lattice undergoes discrete structural changes, which include first the reversible dissociation of lateral bonds followed by irreversible dissociation of the longitudinal bonds. We have determined the free energies of dissociation of the lateral (6.9+/-0.4 kcal/mol) and longitudinal (14.9+/-1.5 kcal/mol) tubulin-tubulin bonds. These values in conjunction with the large flexural rigidity of tubulin protofilaments obtained (18,000-26,000 pN*nm^2), support the idea that the disassembling microtubule is capable of generating a large mechanical force to move chromosomes during cell division. Our computational modeling offers a comprehensive quantitative platform to link molecular tubulin characteristics with the physiological behavior of microtubules. The developed in silico nanoindentation method provides a powerful tool for the exploration of biomechanical properties of other cytoskeletal and multiprotein assemblie

Characterization of mechanical properties by inverse technique for composite reinforced by knitted fabric. Part 2. Experimental evaluation of mechanical properties by frequency eigenvalues method

This paper is the second part of the research work dedicated to evaluation of mechanical properties of polymer composites reinforced by knitted fabric. Three different approaches were applied for the task. Two of them: a) FEM analysis using Solid Works combined with structural modeling based on experimentally-determined mechanical and geometrical properties of the reinforcement and matrix, and b) direct measurement of mechanical properties (described in Part 1). Present investigation (Part 2) is based on application of vibrational analysis. Modal testing in combination with the mathematical optimization procedure were used for evaluation of elastic properties of a layered material. It is worth mentioning that the application of this approach for materials with high damping ability (laminated composites reinforced by knitted fabric) is still poorly investigated. The inverse technique exploited in this work is based on the direct orthotropic plate free vibration measurements and subsequent mathematical optimization procedure (the planning of experiments or response surface technique), which is based on minimization of error functional. Finally, elastic constants established by the inverse technique were discussed and compared with the results obtained in Part 1

Characterization of mechanical properties by inverse technique for composite reinforced by knitted fabric. Part 1. Material modeling and direct experimental evaluation of mechanical properties

Polymer composites reinforced with knitted fabrics are materials with high potential in aerospace and machine building industries [1-6]. Such materials are mechanically non-linear with a high dynamic energy absorption capacity. Accurate prediction of mechanical properties is of great importance for these materials when considering their applications in novel structures. Three different approaches were implemented to this aim in the reported research work and the results are presented in: Part 1- numerical structural modeling (FEM using Solid Works) based on application of experimentally measured mechanical and geometrical properties of reinforcement and matrix, accompanied by direct measurements of mechanical properties; Part 2 - application of inverse method for characterization of mechanical properties by means of vibration modal analysis. The goal was to obtain and predict mechanical behavior of a weft knitted fabric reinforced multilayered composite plate. Results of all three approaches were compared and discussed