Peak Ground Acceleration Estimation by Linear and Nonlinear Models with Reduced Order Monte Carlo Simulation

Abstract: Estimation of the peak ground acceleration (PGA) is one of the main tasks in civil and earthquake engineering practice since it is an important factor for the design spectrum. The Boore–Joyner–Fumal (BJF) and the Crouse–McGuire formula are well‐known empirical models by estimating the PGA with the magnitude of earthquake, the fault‐to‐site distance, and the site foundation properties. It is obvious that a predictive model class with more effective free parameters often fit the data better. However, this does not imply that the complicated formula is more realistic since overfitting may happen when the formula has too many free parameters. In this article, 32 linear and 16 nonlinear predictive model classes are constructed and investigated. The Bayesian model class selection approach is utilized to obtain the most suitable predictive model class for the seismic attenuation formula. In this approach, each predictive model class is evaluated by the plausibility conditional on the data and it is proportional to the evidence which involves a high‐dimensional integral. This integral has closed‐form solution for the linear model classes. Analytic work was done to improve the original asymptotic expansion in this study. For the nonlinear model classes, the evidence integral can be reduced to two‐dimensional and then Monte Carlo simulation is utilized to evaluate the double integral. The most plausible model class is robust in the sense that it balances between the data‐fitting capability and the sensitivity to noise. A database of 266 strong‐motion records, obtained from the China Earthquake Data Center, is utilized for the analysis. The most plausible predictive model class and its updated model parameters are determined. It turns out that the most plausible model class is generally simpler than the full BJF empirical formula. In the case where no single model class has dominant plausibility, one can utilize the multi‐model predictive formula that is a plausibility‐weighted average of the prediction of different predictive models.     

The stability of hydrogen evolution activity and corrosion behavior of NiCu coatings with long-term electrolysis in alkaline solution

In this study, NiCu composite coating was electrochemically deposited on a copper electrode (Cu/NiCu) and tested for hydrogen evolution reaction (HER) in 1 M KOH solution for long-term electrolysis with the help of cathodic current–potential curves and electrochemical impedance spectroscopy (EIS) techniques. The bulk and surface composition of the coating was determined using atomic absorption spectroscopy (AAS) and energy dispersive X-ray (EDX) analysis. The surface morphology was investigated by scanning electron microscopy (SEM). The effect of electrolysis on the corrosion behavior of the Cu/NiCu electrode was also reported. It was found that the NiCu coating had a compact and porous structure with good time stability. The HER activity of the coating was stable over 120 h electrolysis and the HER mechanism was not modified during the operation. The corrosion tests showed that the corrosion resistance of the Cu/NiCu electrode changed when a cathodic current was applied to the electrolysis system.     

Detecting stock-price manipulation in an emerging market: The case of Turkey

This paper aims to develop methods that are capable of detecting manipulation in the Istanbul Stock Exchange. We take the difference between manipulated stock’s and index’s average daily return, average daily change in trading volume and average daily volatility and used these statistics as explanatory variables. The data in post-manipulation and pre-manipulation periods are used as non-manipulated instances while the data in the manipulation period are used as manipulated instances. Test performance of classification accuracy, sensitivity and specificity statistics for Artificial Neural Networks (ANN) and Support Vector Machine (SVM) are compared with the results of discriminant analysis and logistics regression (logit). We found that the data mining techniques (ANN and SVM) are better suited to detect stock-price manipulation than multivariate statistical techniques (discriminant analysis, logistics regression) as the performances of the data mining techniques in terms of total classification accuracy and sensitivity statistics are better than those of multivariate techniques. We also found that unit change in difference between average daily return of manipulated stock and the index has the largest effect while unit change in difference between average daily change in trading volume of manipulated stock and index has the least effect on multivariate classifiers’ decision functions.     

Energy-efficient directional routing between partitioned actors in wireless sensor and actor networks

Actor?actor communication is an important part of the functioning of wireless sensor?actor networks and enables the actor nodes to take coordinated action on a given event. Owing to various reasons such as actor mobility and low actor density, the actor network tends to get partitioned. The authors propose to use the underlying sensor nodes, which are more densely deployed, to heal these partitions. In order to maximise the utilisation of the limited energy available with the sensor nodes, a new routing protocol for actor?actor communication using directional antennas on the actor nodes is proposed. The authors contribution is threefold. First, using simulations they show that the problem of partitioning in the actor networks is significant and propose an architecture with directional antennas on actor nodes and sensor bridges to heal these partitions. Second, they identify the routing problem for this architecture based on a theoretical framework and propose centralised as well as distributed solutions to it. Third, they develop a routing protocol based on the distributed solution and show, using network simulations, that the proposed protocol not only heals the network partitions successfully, but also achieves high throughput and fairness across different flows, in addition to maximising the network lifetime.     

Contaminant transport with adsorption and their inverse problems

In Constales et al. (water Resources Res. 39(30), 1303, 2003) dual-well tests are used to reconstruct the flow and dispersion parameters in contaminant transport. A tracer is introduced by the injection well, which is considered to be in steady-state regime with the extraction well. Then, from measurements of the time evolution of the extracted tracer (breakthrough curve) the required model data has been recovered. In Constales et al. (water Resources Res. 39(30), 1303, 2003), a very precise numerical method has been developed for the solution of the direct problem. In Kačur et al. (Comput. Meth. Appl. Mech. Engo. 194(2–5), 479–489, 2005); Remešiková (J. Comp. Appl. Math. 169(1), 101–116, 2004) an extension has been discussed which adds adsorption terms to the model. The inverse problem of determination of sorption isotherms in nonequilibrium mode was solved by a Levenberg–Marquardt iteration method. In the present paper we develop the adjoint system to evaluate the sensitivity of the solution (via the breakthrough curve) on the sorption parameters in equilibrium and nonequilibrium modes. Possible use of the adjoint system in determining the several parameters occuring in the model is a crucial point for iteration methods. The obtained model parameters then can be used in a 3D flow and transport model with adsorption. The numerical experiments we present, justify the used method.     

Efficient Monitoring Algorithm for Fast News Alerts

Recently, there has been a dramatic increase in the use of XML data to deliver information over the Web. Personal Weblogs, news Web sites, and discussion forums are now publishing RSS feeds for their subscribers to retrieve new postings. As the popularity of personal Weblogs and RSS feeds grows rapidly, RSS aggregation services and blog search engines have appeared, which try to provide a central access point for simpler access and discovery of new content from a large number of diverse RSS sources. In this paper, we study how the RSS aggregation services should monitor the data sources to retrieve new content quickly using minimal resources and to provide its subscribers with fast news alerts. We believe that the change characteristics of RSS sources and the general user access behavior pose distinct requirements that make this task significantly different from the traditional index refresh problem for Web search engines. Our studies on a collection of 10,000 RSS feeds reveal some general characteristics of the RSS feeds and show that, with proper resource allocation and scheduling, the RSS aggregator provides news alerts significantly faster than the best existing approach.     

Designing of a powder compressing device with vibration and investigation of compressibility of MgO powders with this device

One of metal matrix composite (MMC) production methods is infiltration of liquid metal into preformed reinforcement. In this method, MMCs are produced by infiltration of liquid metal into preformed reinforcement using one of pressure, vacuum or pressureless (free) infiltration methods. For infiltration purposes, reinforcement materials in different figuration are preformed in desired shape and reinforcement volume ratio. In this study a vibration apparatus has been designed to compress the particulate reinforcement in a tube so that pressure or vacuum infiltration can be carried out. The compressibility of MgO powders with different sizes with this apparatus has also been investigated. It has been found that with this apparatus, it is possible to compress desired number of specimens uniformly at the same time and at the same ratio. It has also been determined that MgO powders can be compressed in different ratio due to particle sizes with this device. Compressing time of 3 min is enough to reach maximum compression ratio in MgO powders.     

A Novel Control Unit for a Friction Welding Machine Based on Computer

Typical friction welds are made by holding a non-rotating sample in contact with a rotating sample under constant or gradually increasing pressure until the interface reaches the welding temperature and then stopping pressure rotating to complete the weld. This process requires additional time and is labor intensive. Recently, several control systems have been introduced to the industry for improving the welding process such as conventional automatic control, microcontroller control, and Programmable Logic Controller (PLC). However, these processes have limitations either on materials selection or on visualization. In this study, continuous monitoring, control and recording are implemented. Computer-controlled platform for the simulation and control of mechanisms is based on a Microsoft Visual Basic environment. Welding parameters such as friction time, forge time and breaking time are entered with a keyboard and can be saved and used again. To show the feasibility and versatility of the study, the evaluation is used for sample joining. It has been observed that this system works successfully and gives good performance.     

Modeling of Discharge Lamp Characteristics by Using Floating Memristor Circuit Emulator with Tunable Threshold

Abstract

A gas discharge lamp is a device, which operates as a light source by producing electrical discharge in ionized gaseous medium. Discharge lamps are commonly used in the market and according to their physical properties they can be mainly classified in three different categories: high pressure, low pressure and high-intensity lamps. Ionized gases have tendency to produce ongoing discharges and finally electrical arcs, which exhibit memristor characteristics proposed by Leon Chua. This paper introduces a novel fully floating memristor circuit emulator with tunable threshold characteristics which mimic discharge lamp characteristics. In order to investigate discharge lamp characteristics a test set-up is designed and commercially available discharge lamps are tested. The proposed memristor circuit displays distinctive characteristics in contrast to well-known smooth switching memristor characteristics in terms of hard switching capability. Proposed memristor has unique switching behavior and fully capable of modeling discharge lamps since it satisfies required zero-crossing, pinched hysteresis and frequency dependent characteristics of the discharge lamps. The comparisons of the current-voltage characteristics for both memristor and discharge lamps are supplied and investigated.     

Failure Analysis of Two-Dimensional Carbon-Epoxy Composite Plate Pinned Joint

The aim of this study is to investigate failure strength and failure mode of a mechanically fastened carbon-epoxy composite plate of arbitrary orientation. The failure load and the failure mode are analyzed numerically and experimentally. The numerical method includes two steps. First, the stress distribution in the plate is calculated by the use of finite-element method. Second, the failure load and the failure mode are predicted by means of Tsai-Hill and fiber tensile-compressive failure criteria. A computer program was developed which can be used to calculate the failure load, the failure mode, and the propagation of failure. The distance-to-diameter, E/D , and width-to-diameter, W/D , ratios in the plate are changed from 1 to 5 and 2 to 5, respectively. It is found that full bearing strength is developed when E/D and W/D ratios are equal to or greater than 4.