Deep Learning for Accelerated Seismic Reliability Analysis of Transportation Networks

To optimize mitigation, preparedness, response, and recovery procedures for infrastructure systems, it is essential to use accurate and efficient means to evaluate system reliability against probabilistic events. The predominant approach to quantify the impact of natural disasters on infrastructure systems is the Monte Carlo approach, which still suffers from high computational cost, especially when applied to large systems. This article presents a deep learning framework for accelerating seismic reliability analysis, on a transportation network case study. Two distinct deep neural network surrogates are constructed and studied: (1) a classifier surrogate that speeds up the connectivity determination of networks and (2) an end‐to‐end surrogate that replaces modules such as roadway status realization, connectivity determination, and connectivity averaging. Numerical results from k‐terminal connectivity analysis of a California transportation network subject to a probabilistic earthquake event demonstrate the effectiveness of the proposed surrogates in accelerating reliability analysis while achieving accuracies of at least 99%.     

Mesoporous silica coated gold nanorods: a multifunctional theranostic platform for radiotherapy and X-ray imaging

Journal of Porous Materials - The development of theranostic nanostructures is one of the most advanced branches of pharmaceutical and medical sciences in the world today. Due to the unique...     

Controller Design Based On Wavelet Neural Adaptive Proportional Plus Conventional Integral-Derivative For Bilateral Teleoperation Systems With Time-Varying Parameters

International Journal of Control, Automation and Systems - In this study, a new controller method based on wavelet neural adaptive proportional plus conventional integral-derivative (WNAP+ID)...     

Adaptive robust control-based energy management of hybrid PV-Battery systems with improved transient performance

Energy management of hybrid photovoltaic (PV)-battery systems still serve as a challenging task owing to their complex and nonlinear characteristics, multicomponent structures, and the extensive range of environmental factors disturbing their nominal performance. The hybrid energy system developed in this study encompasses PV arrays, a battery component, one boost converter, and one bidirectional boost converter. In this paper, we propose a novel adaptive robust control framework for the optimal energy management of the PV-battery systems under many operating conditions and subject to unmodelled dynamics. An improved exponential-like adaptive integral sliding mode (EISM) control coupled to neural network approximator is introduced using a multi-rate convergence tweaking mechanism for the sliding surface to improve the transient performance of the closed-loop system. Furthermore, the entire dynamics of the hybrid energy system is considered unknown, unlike the previous studies that only assumed the parametric uncertainties. The global asymptotic stability of the system is guaranteed, and the effectiveness of this novel framework is compared to benchmark studies.     

Castor oil-based polyurethane coatings containing benzyl triethanol ammonium chloride: synthesis,characterization, and biological properties

In the present work, benzyl triethanol ammonium chloride (BTEAC) was employed as a reactive bactericidal additive for preparing of polyurethane coatings. In this regard, castor oil as a renewable resource-based polyol, polyethylene glycol (PEG1000), and BTEAC were reacted with toluene diisocyanate. Physical, mechanical, and thermal characteristics as well as biocompatibility and antibacterial properties of polyurethanes were evaluated. The prepared polyurethanes showed two-phase structure with soft and hard segments glass transition temperature transitions in the range of 18–70 and 85–153 °C, respectively. Initial modulus and tensile strength were improved for coatings with higher BTEAC content, while elongation at break and thermal stability were decreased. Hydrophilicity of coatings was increased for polyurethanes based on higher content of BTEAC and PEG1000. Polyurethanes with higher BTEAC content showed better cytocompatibility for mouse L929 fibroblast cells. Moreover, coatings with higher hydrophilicity and BTEAC content displayed superior antibacterial activity against both Escherichia coli and Staphylococcus aureus bacteria.     

Memory-efficient real-time map building using octree of planes and points

This paper presents an octree-based map building algorithm for mobile home-service robots. The robot is equipped with a time-of-flight camera, which produces point clouds of the environment surfaces. Given the successive input of point clouds, a 3D map is incrementally computed in real time. The map is accurate and memory-efficient because the octree nodes containing points on a plane are merged and represented simply by an index to the plane. The real-time performance is achieved largely due to the parallel processing capability of the many-core Graphics Processing Unit used for plane extraction.     

Design equations for prediction of pressuremeter soil deformation moduli utilizing expression programming systems

Providing precise estimations of soil deformation modulus is very difficult due to its dependence on many factors. In this study, gene expression programming (GEP) and multi-expression programming (MEP) systems are presented to derive empirical equations for the prediction of the pressuremeter soil deformation modulus. The employed expression programming (EP) systems formulate the soil deformation modulus in terms of the soil physical properties. Selection of the best models is on the basis of developing and controlling several models with different combinations of the affecting parameters. The proposed EP-based models are established upon 114 pressuremeter tests on different soil types conducted in this study. The generalization capabilities of the models are verified using several statistical criteria. Contributions of the variables influencing the soil modulus are evaluated through a sensitivity analysis. The GEP and MEP approaches accurately characterize the soil deformation modulus resulting in a very good prediction performance. The result indicates that moisture content and soil dry unit weight can efficiently represent the initial state and consolidation history of soil for determining its modulus.     

Failure of silver nanowire transparent electrodes under current flow

Silver nanowire transparent electrodes have received much attention as a replacement for indium tin oxide, particularly in organic solar cells. In this paper, we show that when silver nanowire electrodes conduct current at levels encountered in organic solar cells, the electrodes can fail in as little as 2 days. Electrode failure is caused by Joule heating which causes the nanowires to breakup and thus create an electrical discontinuity in the nanowire film. More heat is created, and thus failure occurs sooner, in more resistive electrodes and at higher current densities. Suggestions to improve the stability of silver nanowire electrodes are given.     

Study of inhibition effect of carboxylic salt derivative on corrosion of C1010 carbon steel in saline solution

In the present work, sodium 4-[(4-formylbenzylidene) amino] benzoiate (4) was synthesized and its structure was confirmed using spectroscopic techniques. Prepared compound was successfully applied as a corrosion inhibitor for C1010 carbon steel in 3.5% NaCl solution at 25°C. Different electrochemical measurements such as linear polarization resistance (LPR), potentiodynamic polarization (PDP), and electrochemical impedance spectroscopy (EIS) were used to evaluate the suggested inhibitor (4). The results of different electrochemical measurements show that inhibition efficiencies obtained from EIS curves are in consistence with the results of potentiodynamic polarization and LPR measurements due to increase corrosion inhibition efficiency by increasing the concentration of organic inhibitor (4). Semi-empirical calculations with PM3 method were used to find relationship between molecular structure and inhibiting effect of suggested inhibitor (4).     

Preparation of novel 2-(2-oxo-2H-chromen-4-yl)-3- arylthiazolidin-4-one derivatives using an efficient ionic liquid catalyst

An eco-friendly procedure for synthesis of 2-(2-oxo-2H-chromen-4-yl)-3-arylthiazolidin-4-one derivatives by three-component reaction of 2-oxo-2H-chromene-4-carbaldehydes, aromatic amines and thioglycolic acid, with tetramethylbutane-1,4-diammonium acetate as a low-cost ionic liquid catalyst under reflux condition is described. The use of an ionic liquid as a catalyst has the advantages of high yields, short reaction time and environmentally friendly reaction media.