Causes of Collapse and Damage to Low-Rise RC Buildings in Recent Turkish Earthquakes

This study assesses performance objectives defined in the Turkish Earthquake Code (TEC) in order to make a realistic evaluation related to heavy damage and collapse reasons of reinforced concrete (RC) buildings that experienced severe earthquakes in Turkey. A series of three-dimensional RC buildings with different characteristics and representing low-rise structures damaged and collapsed in the earthquake areas is designed according to Turkish codes (Turkish Design Standards and Turkish Earthquake Code). Pushover analyses are carried out to determine nonlinear behavior of the buildings under earthquake loads. Building performances are determined by using the displacement coefficients method, which is a commonly used nonlinear static evaluation procedure for different seismic hazard levels defined in the TEC. The stipulated performance objectives in the TEC are checked in terms of plastic rotations and maximum story drift. From the results of this research, it can be concluded that low-rise RC buildings designed according to Turkish codes sufficiently provide for the performance objectives stipulated in the TEC. Reasons for the heavy damages and collapses of RC buildings during severe earthquakes are explained by commonly occurring themes (i.e., project errors, poor quality of construction, modifications of buildings, etc.).     

Two-level and hybrid ensembles of decision trees for high performance concrete compressive strength prediction

Accurate prediction of high performance concrete (HPC) compressive strength is very important issue. In the last decade, a variety of modeling approaches have been developed and applied to predict HPC compressive strength from a wide range of variables, with varying success. The selection, application and comparison of decent modeling methods remain therefore a crucial task, subject to ongoing researches and debates. This study proposes three different ensemble approaches: (i) single ensembles of decision trees (DT) (ii) two-level ensemble approach which employs same ensemble learning method twice in building ensemble models (iii) hybrid ensemble approach which is an integration of attribute-base ensemble method (random sub-spaces RS) and instance-base ensemble methods (bagging Bag, stochastic gradient boosting GB). A decision tree is used as the base learner of ensembles and its results are benchmarked to proposed ensemble models. The obtained results show that the proposed ensemble models could noticeably advance the prediction accuracy of the single DT model and for determining average determination of correlation, the best models for HPC compressive strength forecasting are GB–RS DT, RS–GB DT and GB–GB DT among the eleven proposed predictive models, respectively. The obtained results show that the proposed ensemble models could noticeably advance the prediction accuracy of the single DT model and for determining determination of correlation (R²_max), the best models for HPC compressive strength forecasting are GB–RS DT (R²=0.9520), GB–GB DT (R²=0.9456) and Bag–Bag DT (R²=0.9368) among the eleven proposed predictive models, respectively.     

Discrete time/cost trade-off problem: A decomposition-based solution algorithm for the budget version

This paper investigates the budget variant of the discrete time/cost trade-off problem (DTCTP). This multi-mode project scheduling problem requires assigning modes to the activities of a project so that the total completion time is minimized and the budget and the precedence constraints are satisfied. This problem is often encountered in practice as timely completion of the projects without exceeding the budget is crucial. The contribution of this paper to the literatures is to describe an effective Benders Decomposition-based exact algorithm to solve the DTCTP instances of realistic sizes. Although Benders Decomposition often exhibits a very slow convergence, we have included several algorithmic features to enhance the performance of the proposed tailored approach. Computational results attest to the efficacy of the proposed algorithm, which can solve large-scale instances to optimality.     

Development of flame retardancy properties of new halogen‐free phosphorous doped SiO2 thin films on fabrics

In this study, flame retardancy properties of fabrics treated with phosphorous (P) doped and undoped SiO₂ thin films were developed by sol–gel technique. As to this aim, P‐doped and undoped SiO₂ film were coated on cotton fabric from the solutions prepared from P, Si‐based precursors, solvent, and chelating agent at low temperature in air using sol–gel technique. To determine solution characteristics, which affect thin film structure, turbidity, pH values, and rheological properties of the prepared solutions were measured using a turbidimeter, a pH meter, and a rheometer machines before coating process. The thermal, structural, and microstructural characterization of the coating were done using differential thermal analysis/thermograviometry, fourier transform infrared spectroscopy, X‐ray diffractometry, and scanning electron microscopy. In addition, tensile strength, wash fastness, flame retandancy, and lightness properties of the coated fabrics were determined. To compensate the slight loss of tensile strength of samples, which occurred at the treated fabrics with P‐doped Si‐based solutions, the cotton fabrics were coated with polyurethane films during second step. In conclusion, the flame retardant cotton fabric with durability of washing as halogen‐free without requiring after treatment with formaldehyde was fabricated using sol–gel processing for the first time. Moreover the cotton fabrics, which were treated with P‐doped Si‐based solutions and then coated with polyurethane at second step, still has got nonflammable property. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007     

A receding contact problem between a functionally graded layer and two homogeneous quarter planes

In this paper, the plane problem of a frictionless receding contact between an elastic functionally graded layer and two homogeneous quarter planes is considered when the graded layer is pressed against the quarter planes. The top of the layer is subjected to normal tractions over a finite segment. The graded layer is modeled as a non-homogeneous medium with a constant Poisson’s ratio and exponentially varying shear modules. The problem is converted into the solution of a Cauchy-type singular integral equation in which the contact pressure and the receding contact half-length are the unknowns using integral transforms. The singular integral equation is solved numerically using Gauss–Jacobi integration. The corresponding receding contact half-length that satisfies the global equilibrium condition is obtained using an iterative procedure. The effect of the material non-homogeneity parameter on the contact pressure and on the length of the receding contact is investigated.     

The modification of the characteristics of ZnO nanofibers by TCNQ doping content

In this study, the electrical properties of an Al/p-Si metal/semiconductor photodiodes with Tetracyanoquinodimethane–Polyvinyl chloride (TCNQ–PVC) and PVC–TCNQ:ZnO interfacial layers were investigated. Growing of the interfacial layers on p-Si were fulfilled using electrospinning method as a fiber form. Al metallic and ohmic contacts were deposited via physical vapor deposition method. Scanning electron microscopy (SEM) pictures of the devices were captured to examine the morphology of the structure. Within the scope of electrical characterization, I–V measurements of the Al/PVC–TCNQ/p-Si and Al/PVC–TCNQ:ZnO/p-Si devices were accomplished both in the dark and under illumination conditions. Various device parameters, such as ideality factor and barrier height values were determined from I–V characteristics. Although the ideality factor values were obtained as 8.47 and 6.85 for undoped and ZnO-doped Al/PVC–TCNQ/p-Si diodes, the barrier height values were calculated as 0.84 for both devices. When a comparison was made between ZnO doped and undoped Al/PVC–TCNQ/p-Si diodes, it was evaluated that the rectification and photoresponse properties of the heterojunction diode was improved with ZnO dopant.

     

A discrete artificial bee colony algorithm for single machine scheduling problems

This paper presents a discrete artificial bee colony algorithm for a single machine earliness–tardiness scheduling problem. The objective of single machine earliness–tardiness scheduling problems is to find a job sequence that minimises the total sum of earliness–tardiness penalties. Artificial bee colony (ABC) algorithm is a swarm-based meta-heuristic, which mimics the foraging behaviour of honey bee swarms. In this study, several modifications to the original ABC algorithm are proposed for adapting the algorithm to efficiently solve combinatorial optimisation problems like single machine scheduling. In proposed study, instead of using a single search operator to generate neighbour solutions, random selection from an operator pool is employed. Moreover, novel crossover operators are presented and employed with several parent sets with different characteristics to enhance both exploration and exploitation behaviour of the proposed algorithm. The performance of the presented meta-heuristic is evaluated on several benchmark problems in detail and compared with the state-of-the-art algorithms. Computational results indicate that the algorithm can produce better solutions in terms of solution quality, robustness and computational time when compared to other algorithms.     

Sub-nanomolar sensing of ionic mercury with polymeric electrospun nanofibers

Ethyl cellulose (EC) based electrospun nanofibers were exploited for sub-nanomolar level optical chemical sensing of ionic mercury. An azomethine ionophore was used as Hg (I) and Hg (II) sensing material. Ethyl cellulose nanofibers with varying amounts of the ionic liquid; 1-ethyl-3-methylimidazolium tetrafluoroborate (EMIMBF₄) were prepared and characterized. The nanofibers were fabricated by electrospinning technique. The offered chemosensor allow determination of mercury ions in a large linear working range between 1.0 × 10⁻¹⁰ and 1.0 × 10⁻⁴ mol L⁻¹. Limit of detection was found to be 0.07 nM which makes this technique alternative to cold-vapor atomic absorption spectrometry (CV-AAS), flame emission methods and to inductively coupled plasma-mass spectrometry (ICP-MS).     

Neuro-fuzzy control of antilock braking system using sliding mode incremental learning algorithm

A neuro-fuzzy adaptive control approach for nonlinear dynamical systems, coupled with unknown dynamics, modeling errors, and various sorts of disturbances, is proposed and used to design a wheel slip regulating controller. The implemented control structure consists of a conventional controller and a neuro-fuzzy network-based feedback controller. The former is provided both to guarantee global asymptotic stability in compact space and as an inverse reference model of the response of the controlled system. Its output is used as an error signal by an incremental learning algorithm to update the parameters of the neuro-fuzzy controller. In this way the latter is able to gradually replace the conventional controller from the control of the system. The proposed new learning algorithm makes direct use of the variable structure systems theory and establishes a sliding motion in terms of the neuro-fuzzy controller parameters, leading the learning error toward zero. In the simulations and in the experimental studies, it has been tested on the control of antilock breaking system model and the analytical claims have been justified under the existence of uncertainty and large nonzero initial errors.