Subsurface Characterization at Ground Failure Sites in Adapazari, Turkey

Ground failure in Adapazari, Turkey during the 1999 Kocaeli earthquake was severe. Hundreds of structures settled, slid, tilted, and collapsed due in part to liquefaction and ground softening. Ground failure was more severe adjacent to and under buildings. The soils that led to severe building damage were generally low plasticity silts. In this paper, the results of a comprehensive investigation of the soils of Adapazari, which included cone penetration test (CPT) profiles followed by borings with standard penetration tests (SPTs) and soil index tests, are presented. The effects of subsurface conditions on the occurrence of ground failure and its resulting effect on building performance are explored through representative case histories. CPT- and SPT-based liquefaction triggering procedures adequately identified soils that liquefied if the clay-size criterion of the Chinese criteria was disregarded. The CPT was able to identify thin seams of loose liquefiable silt, and the SPT (with retrieved samples) allowed for reliable evaluation of the liquefaction susceptibility of fine-grained soils. A well-documented database of in situ and index testing is now available for incorporating in future CPT- and SPT-based liquefaction triggering correlations.     

Revisiting Slotted ALOHA: Density Adaptation in FANETs

Unmanned aerial vehicles have been widely used in many areas of life. They communicate with each other or infrastructure to provide ubiquitous coverage or assist cellular and sensor networks. They construct flying ad hoc networks. One of the most significant problems in such networks is communication among them over a shared medium. Using random channel access techniques is a useful solution. Another important problem is that the variations in the density of these networks impact the quality of service and introduce many challenges. This paper presents a novel density-aware technique for flying ad hoc networks. We propose Density-aware Slotted ALOHA Protocol that utilizes slotted ALOHA with a dynamic random access probability determined using network density in a distributed fashion. Compared to the literature, this paper concentrates on proposing a three-dimensional, easily traceable model and stabilize the channel utilization performance of slotted ALOHA with an optimized channel access probability to its maximum theoretical level, 1/e, where e is the Euler’s number. Monte-Carlo simulation results validate the proposed approach leveraging aggregate interference density estimator under the simple path-loss model. We compare our protocol with two existing protocols, which are Slotted ALOHA and Stabilized Slotted ALOHA. Comparison results show that the proposed protocol has 36.78% channel utilization performance; on the other hand, the other protocols have 24.74% and 30.32% channel utilization performances, respectively. Considering the stable results and accuracy, this model is practicable in highly dynamic networks even if the network is sparse or dense under higher mobility and reasonable non-uniform deployments.

     

The production of graphene nano layers by using milling—exfoliation hybrid process

Even though high quality graphene can be produced through chemical exfoliation of Graphite or Expanded graphite (EG), the amount of acquired products is limited. Graphite powders were subjected to a pre-milling process with prevailing shear stress in order to increase the amount of products. Therefore, separation of hexagonal layers through pre-separation process was targeted. The milled powders were firstly mixed in the saturated acid mixture containing H₂SO₄ and HNO₃, and then heated to 950°C. At the end of process, the distance between layers was expanded and the structure called as expanded graphite was obtained. Separation of layers and formation of graphene were provided by stirring expanded graphite within a chemical solvent for a while. The obtained samples were examined by using X-ray analysis, electron microscopy analysis, and Raman spectroscopy analysis. Despite the fact that there is a production method for graphene by chemical exfoliation, addition of the milling into steps of this process is an unusual step. Although a great amount of amorphous structures occurred in the structure at the end of milling process in this study, there were still graphitic structures preserving its hexagonality in the sample even if just a little. Most of amorphous carbon was removed from the structure as a result of applying further steps of process to milled graphite. A great part of graphitic structures apart from amorphous carbon structures were transformed into graphene. Even though amorphous carbon structures and defects were still found in the product, the obtained graphenes were relatively qualified and of high amount.     

An assessment of total RMR classification system using unified simulation model based on artificial neural networks

Engineering design has great importance in the cost and safety of engineering structures. Rock mass rating (RMR) system has become a reliable and widespread pre-design system for its ease of use and variety in engineering applications such as tunnels, foundations, and slopes. In RMR system, six parameters are employed in classifying a rock mass: uniaxial compressive strength of intact rock material (UCS), rock quality designation (RQD), spacing of discontinuities (SD), condition of discontinuities (CD), condition of groundwater (CG), and orientation of discontinuities (OD). The ratings of the first three parameters UCS, RQD, and SD are determined via graphic readings where the last three parameters CD, CG, and OD are estimated by the tables that are composed of interval valued linguistic expressions. Because of these linguistic expresions, the estimated rating values of the last three become fuzzy especially when the related conditions are close to border of any two classes. In such cases, these fuzzy situations could lead up incorrect rock class estimations. In this study, an empirical database based on the linguistic expressions for CD, CG, and OD is developed for training Artificial Neural Network (ANN) classifiers. The results obtained from graphical readings and ANN classifiers are unified in a simulation model (USM). The data obtained from five different tunnels, which were excavated for derivation purpose, are used to evaluate classification results of conventional method and proposed model. Finally, it is noted that more accurate and realistic ratings are reached by means of proposed model.     

The synthesis,characterisation and molecular structure of a new hetarylazoindole dye studied by X‐ray diffraction,spectral analysis and density functional theory calculation

1,2‐Dimethyl‐3‐(5‐methylisoxazol‐3‐yldiazenyl)‐1H‐indole was obtained by coupling 3‐amino‐5‐methylisoxazole with diazotised 1,2‐dimethylindole. It was characterised by proton and carbon nuclear magentic resonance, ultraviolet–visible, infrared and Raman spectra, and the X‐ray single crystal diffraction method. On the theoretical side, the molecular geometry, chemical shifts and the fundamental vibrational frequencies were evaluated using density functional theory. Time‐dependent density functional theory was used to evaluate the electronic excitation spectra. In addition, the scaled quantum mechanical approach was used to study the total energy distributions of the vibrational modes of the molecule. The results showed that the general agreement between experimental and calculated geometric parameters, chemical shifts and λ_max values are good. Excellent agreement was found between the calculated and experimental vibrational frequencies.     

Analyzing the behaviors of virtual cells (VCs) and traditional manufacturing systems: Ant colony optimization (ACO)-based metamodels

The aim of this paper is two fold. First we investigate the three different types of systems, namely cellular layout (CL), process layout (PL) and virtual cells (VCs). VCs are addressed by using family-based scheduling rule, developed by a part allocation algorithm in a PL. Simulation is used to compare three types of systems under the performance metrics such as mean flow time and mean tardiness. Results indicate that VCs have better responsiveness in terms of the performance metrics. Second we develop a new ant colony optimization-based metamodels fed by existing simulation runs to represent the prospective simulation runs, which require a lot of time and effort. Regression metamodels, which allow us to obtain much faster results, are seen to be promising to estimate the systems behaviors.     

UV-visible technique for studying powder coatings and their dissolution

UV-Visible (UVV) technique used to monitor powder coating and its dissolution processes from hard latex particles. Three sets of latex coatings were prepared from poly(methyl methacrylate) (PMMA) particles. The first set of coatings was annealed at elevated temperatures in various time intervals during which reflected photon intensity, I_rf, was measured. The second set of coatings was annealed at various temperatures in 10 min time intervals during which transmitted intensity, I_tr, was measured. I_rf first decreased and then increased as the annealing temperature was increased. Decrease in I_rf was explained with the void closure mechanism due to viscous flow. Increase in I_tr and I_rf against time and temperature were attributed to an increase in crossing density at the junction surface. The activation energy of viscous flow, ΔH, was measured and found to be around 8 kcal/mol and the back and forth activation energies (ΔE_rf and ΔE_tr) were measured and found to be around 49 and 53 kcal/mol for a reptating polymer chain across the junction surface. Diffusion of solvent molecules (chloroform) into the annealed latex coatings was followed by desorption of PMMA chains for the third set of films. Desorption of pyrene, P, labeled PMMA chains was monitored in real-time by the absorbance change of pyrene in the polymer-solvent mixture. A diffusion model with a moving boundary was employed to quantify real-time UVV data. Diffusion coefficients of desorbed PMMA chains were measured and found to be between 2 and 0.6 × 10⁻¹¹ cm² s⁻¹ in the 100 and 275°C temperature range. Presented at the 2000 Spring Meeting of the PMSE Div. of the American Chemical Society, March 26–30, 2000, San Francisco, CA. Dept. of Physics, Maslak 80626 Istanbul, Turkey. Dept. of Physics, 22030 Edirne, Turkey.     

Myoglobin adsorption onto poly(glycidyl methacrylate) microbeads with surface functionalized iminodiacetic acid

In this study, poly(glycidyl methacrylate) [PGMA] microbeads with surface modified iminodiacetic acid (IDA) were used for myoglobin (Mb) adsorption from buffer solutions at different pHs and ionic strengths in a packed-bed column. Attenuated Total Reflectance Fourier Transformed Infrared (ATR-FTIR) spectroscopy and scanning electron microscopy (SEM) measurements before and after the adsorption process confirmed the structural stability of adsorbed Mb. The effects of initial concentration, flow-rate, pH and ionic strength on the adsorption were investigated. The results showed that the maximum amount of protein was adsorbed at a pH 7.0, which is the protein isoelectric point. The adsorption is rationalized in terms of local electrostatic forces acting between the protein and the IDA modified PGMA surface as well as hydrophobic interactions close to the protein isoelectric point, whereas at low pH the global changes give rise to protein–protein repulsion and at high pH protein-support material repulsion.     

Collaborative and Cognitive Network Platforms: Vision and Research Challenges

In this paper, we present a visionary concept referred to as Collaborative and Cognitive Network Platforms (CCNPs) as a future-proof solution for creating a dependable, self-organizing and self-managing communication substrate for effective ICT solutions to societal problems. CCNP creates a cooperative communication platform to support critical services across a range of business sectors. CCNP is based on the personal network (PN) technology which is an inherently cooperative environment prototyped in the Dutch Freeband PNP2008 and the European Union IST MAGNET projects. In CCNP, the cognitive control plane strives to exploit the resources to better satisfy the requirements of networked applications. CCNP facilitates collaboration inherently. Through cognition in the cognitive control plane, CCNP becomes a self-managed substrate. The self-managed substrate, in this paper, is defined as cognitive and collaborative middleware on which future applications run without user intervention. Endemic sensor networks may be incorporated into the CCNP concept to feed its cognitive control plane. In this paper, we present the CCNP concept and discuss the research challenges related to collaboration and cognition.