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A Modified Fully Convolutional Network for Crack Damage Identification Compared with Conventional Methods
Large-scale structural health monitoring and damage detection of concealed underwater structures are always the urgent and state-of-art problems to be solved in the field of civil engineering. With the development of artificial intelligence especially the combination of deep learning and computer vision, greater advantages have been brought to the concrete crack detection based on convolutional neural network (CNN) over the traditional methods. However, these machine learning (ML) methods still have some defects, such as it being inaccurate or not strong, having poor generalization ability, or the accuracy still needs to be improved, and the running speed is slow. In this article, a modified fully convolutional network (FCN) with more robustness and more effectiveness is proposed, which makes it convenient and low cost for long-term structural monitoring and inspection compared with other methods. Meanwhile, to improve the accuracy of recognition and prediction, innovations were conducted in this study as follows. Moreover, differed from the common simple deconvolution, it also includes a subpixel convolution layer, which can greatly reduce the sampling time. Then, the proposed method was verified its practicability with the overall recognition accuracy reaching up to 97.92% and 12% efficiency improvement.
New Robust Part-Based Model with Affine Transformations for Facial Landmark Localization and Detection in Big Data
In this paper, we developed a new robust part-based model for facial landmark localization and detection via affine transformation. In contrast to the existing works, the new algorithm incorporates affine transformations with the robust regression to tackle the potential effects of outliers and heavy sparse noises, occlusions and illuminations. As such, the distorted or misaligned objects can be rectified by affine transformations and the patterns of occlusions and outliers can be explicitly separated from the true underlying objects in big data. Moreover, the search of the optimal parameters and affine transformations is cast as a constrained optimization programming. To mitigate the computations, a new set of equations is derived to update the parameters involved and the affine transformations iteratively in a round-robin manner. Our way to update the parameters compared to the state of the art of the works is relatively better, as we employ a fast alternating direction method for multiplier (ADMM) algorithm that solves the parameters separately. Simulations show that the proposed method outperforms the state-of-the-art works on facial landmark localization and detection on the COFW, HELEN, and LFPW datasets.
Digital Modeling of Heat Transfer during the Baking Process
Numerical modeling and analysis of the baking process are challenging biochemical processes occurring in bread. These changes result from mass engineering tasks, usually characterized by the complex chain of chemical, physical, and heat transfer processes impacting the baking at the same time primarily caused by a variation of two dominating factors: (i) the heat and (ii) the internal moisture content at different temperatures and during the time’s process. This study presents an analysis of the 1-D computational fluid dynamics model for simultaneous heat transfer within a cylindrical bread sample. The numerical simulations were performed using the finite difference model (FDM) and the finite element model (FEM). In the first case, the proposed numerical model considered radiation and convection during sample heating and described the sample’s simultaneous heat, water, and vapor diffusion mechanisms. The calculations indicated that the FDM was susceptible to the time step; consequently, the range of 10 s and 100 s yielded the only relevant results. In the second case, the FEM was used to describe the phenomena of transportation during baking. Results obtained by the FEM showed a large temperature gradient near the surface. The study showed the presence of some critical cases that are considered the most influential on the stages of bread production. The first critical value is the time when the baking temperature reaches 100° C. The second critical value is the time when the liquid water content in the baking medium reaches its peak. The boundary conditions were examined and illustrated by figures in the center and the surface of the bread.
Novel Nonlinear Control and Optimization Strategies for Hybrid Renewable Energy Conversion System
This article deals with a hybrid renewable energy conversion system (HRECS) interconnected to the three-phase grid in association with their power conversion components, i.e., AC/DC rectifier and DC/AC inverter. The HRECS is built around a permanent magnet synchronous wind turbine generator and a photovoltaic energy conversion system. Comparing to traditional control methods, a new multiobjective control strategy is developed to enhance system performances. This makes it possible to account in addition to optimal turbine speed regulation and PV-MPPT and three other important control objectives such as DC-link voltage regulation and the injected reactive power in the grid. To achieve these objectives, a novel control strategy is developed, based on a nonlinear model of the whole “converters-generators” association. The robustness and the stability analysis of the system have been proved using the Lyapunov theory and precisely the backstepping control and the sliding mode control. The performances of the proposed controllers are formally analyzed with respect to standard control solutions illustrated through simulation.
Crashworthy Examination of a Newly Proposed Impact Attenuator Design: Experimental Testing and Numerical Analysis
The impact attenuator is a safety vehicle system designed to absorb the kinetic energy from a collision that is converted into deformation and ensures the deceleration level acting on the human body remains low. In this paper, we propose that the impact attenuator be fabricated with used cans, which are easy to obtain. Compared to fabricating cylinders through machining and other production processes using new material, the application of used cans may reduce production costs by approximately IDR 500,000 (USD 34.50) for one attenuator structure, while the attenuator still meets the weight criterion, i.e., it has to be light to improve acceleration and fuel efficiency. As a type of metal waste product, food cans are often fabricated from aluminum and other metal alloys. These products are widely used in our lives; if they are not recycled, they can potentially pollute the environment as waste. Given these problems and considering the use of environmentally friendly materials, lightweight used cans were chosen as materials for the proposed impact attenuator design. In the initial study, the verification and validation tests of the impact attenuator shell and used cans show good agreement between the numerical and experimental impact tests. The proposed impact attenuator design under the predetermined parameters showed that used cans of aluminum 6063 series can be recommended as an alternative material in this system.
Soil-Structure Interaction of Flexible Temporary Trench Box: Parametric Studies Using 3D FE Modelling
This paper presents the results of two parametric finite-element studies that were carried out using the PLAXIS-3D finite element (FE) computer code. The following objectives and corresponding parameters were considered: (i) to evaluate the soil pressure on the steel trench box shield; the parameters studied were related to soil type and material, and the study considered till, dry sand, wet sand, and sensitive clay soil; (ii) to assess the effect of trench box material and geometry on earth pressure; the parameters studied were related to trench box material (steel versus aluminum) as well as geometry (plate thickness and strut diameter). These studies included simulation of two steel (or aluminum) trench box shields stacked upon each other to cover the total 6 m (20 ft) deep trench. A Mohr-Coulomb (MC) constitutive material model was chosen for FE analysis (FEA). The FEA results were compared to empirical apparent earth pressure diagrams for a sensitive clay. Comparisons showed that the parameters related to the soil and the trench box have a significant influence on earth pressures.