Carbonation is one of the most critical deterioration phenomena to concrete structures exposed to high concentration, sheltered from rain. Lots of researches have been performed on evaluation of carbonation depth and changes in hydrate compositions, however carbonation modeling is limitedly carried out due to complicated carbonic reaction and diffusion coefficient.
Learn MorePapadrakakis, M. and Papadopoulos, V. "A computationally efficient method for the limit analysis of space frames", Journal of Computational Mechanics, 16(2), pp. 132-141, 1995. Papadrakakis, M., Papadopoulos, V. and Lagaros, N. "Structural reliability analysis of elastoplastic structures using neural networks and Monte Carlo simulation", Computer Methods in Applied Mechanics and
Learn Moreof carbonation depth that can describe all conditions of concrete carbonation, on account of the complexity of carbonation process. On the other hand, when the prior knowledge of the behavior of concrete carbonation is not available, the conventional model cannot be employed either. In such situations, artificial neural network (ANN) is a viable
Learn MoreA δ value (weight) of 1.00 is assigned to studies that use random effect analysis, whereas studies that use fixed effects analysis are assigned a ∂ value of 0.75 (Kober et al., ). A Monte Carlo simulation with 5000 iterations was used to determine the threshold for statistical significance, that is, the proportion that exceeds the whole
Learn MoreGeometrically nonlinear analysis of laminate composite plates and shells using the eight-node hexahedral element with one-point integration. Composite Structures, Vol. 79, No. 4. Solution strategy and rigid element for nonlinear analysis of elastically structures based on updated Lagrangian formulation.
Learn MoreSelf-healing properties of HDFRC. Analysis on tensile behavior. - Micromechanics-based fiber bridging analysis. - Fiber distribution evaluation in FRCCs using image processing techniques. - Tensile behavior simulation of FRCCs. Development of special version of FRCC for infra-structure application. Fig. Tensile behavior of construction materials.
Learn MoreNeural Turing Machines. A Neural Turing Machine is made up of two components : a controller and a memory bank. The controller "controls" the inputs and outputs of the cell while the memory is
Learn MoreThe experimental program consisted of the evaluation of compressive strength, pH profiling, measurement of carbonation depth, X-ray diffraction (XRD), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), and chemical composition measurements in order to study the extent of carbonation.
Learn MoreThis paper discusses the combined application of two different techniques, Neural Networks (NN) and Principal Component Analysis (PCA), for improved prediction of concrete properties. The combination of these approaches allowed the development of six neural networks models for predicting slump and compressive strength of concrete with mineral
Learn MorePrediction of Efficiency Factor of Ground-Granulated Blast-Furnace Slag of Concrete Using Artificial Neural Network. Aci Materials Journal, 2011. Mohamed Ghrici. Arezki Tagnit-hamou. Bakhta Boukhatem. Said KENAI. Mohamed Ghrici. Arezki Tagnit-hamou. Bakhta Boukhatem.
Learn MoreZhang, Li, Huang, and Huang considered an array of linearly coupled memristor-based neural networks with time-varying delay by using an intermittent control technique and obtained stability and synchronization criteria for these networks. Synchronization is an important collective behavior in nature, and some work has addressed synchronization
Learn Morebamboo-reinforced concrete beams from the experimental results data using artificial neural networks (ANNs). The number of beam test specimens were 25 pieces with a size of 75 mm 150 mm 1100 mm. The testing method uses the four-point method with simple support. The results of the analysis
Learn MoreAnalysis of neural coding of rational thoughts. (A) Encoding: Neurally derived beliefs b ̌ match behaviorally derived beliefs b ^ based on IRC. Cross-validated neural beliefs are estimated from testing neural responses r using a linear estimator, b ̌ = W r + c, with the weight matrix fitted from
Learn MoreBrain scans of 9- to 11-year-olds offer clues about aggressive, antisocial behavior Two new papers, one about gray matter, the other about reward behavior, suggest that at the neural level not all conduct problems look the same.
Learn MoreThe concrete industry is a contributor to the global carbon cycle particularly with respect to the contribution of carbon dioxide in the manufacturing of cement (calcination). The reverse reaction of carbonation is known to occur in concrete, but is usually limited to exterior surfaces exposed to carbon dioxide and humidity in the air. As alternate concrete uses expand which have more surface
Learn MoreAn artificial neural network (ANN) based approach for the assessment of damage in prestressed concrete (PSC) beams using its present stiffness and natural frequency as the test inputs to the ANN has been proposed.
Learn MoreNon-destructive strength evaluation of concrete: Analysis of some key factors using synthetic simulations. Construction and Building Materials, 99, 235-245. 19. Topcu, I. B., Sarıdemir, M. ( ). Prediction of compressive strength of concrete containing fly ash using artificial neural networks and fuzzy logic.
Learn MoreSmall-sample artificial neural network based response surface method for reliability analysis of concrete bridges D. Lehký & M. Šomodíková Impact of building's lifespan on the life cycle assessment Z. Stránská & K. Struhala Rapid testing method for air-permeability of concrete in structure using borehole A. Nonaka & N. Yuasa
Learn MoreTogether, these examples emphasize the task-dependence of model-free and model-based behavior and highlight the benefits of using computer simulations to determine what pattern of results to expect from both model-free and model-based agents performing a given two-stage decision task in order to design choice paradigms and analysis strategies
Learn Morephenomenon involved in concrete degradation, such as understanding microstructure of concrete before and during degradation. c) Semi empirical models: These tend to use more simple mathematical expressions than mechanistic model, predictions are made by fitting parameters based on data from field and laboratory tests and analysis.
Learn More1. Introduction. Corrosion is the main pathological manifestation in reinforced concrete structures and has great influence on the composite material behavior throughout its lifespan , .The carbon dioxide (CO 2) diffusion in concrete, a process denominated carbonation, is the main cause of reinforcement depassivation of concrete elements in urban environments .
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