TPS3: A privacy preserving data collection protocol for smart grids

Smart grid (SG) allows for two-way communication between the utility and its consumers and hence they are considered as an inevitable future of the traditional grid. Since consumers are the key component of SGs, providing security and privacy to their personal data is a critical problem. In this paper, a security protocol, namely TPS3, is based on Temporal Perturbation and Shamir’s Secret Sharing (SSS) schemes that are proposed to ensure the privacy of SG consumer’s data. Temporal perturbation is employed to provide temporal privacy, while the SSS scheme is used to ensure data confidentiality. Temporal perturbation adds random delays to the data collected by smart meters, whereas the SSS scheme fragments these data before transmitting them to the data collection server. Joint employment of both schemes makes it hard for attackers to obtain consumer data collected in the SG. The proposed protocol TPS3 is evaluated in terms of privacy, reliability, and communication cost using two different SG topologies. The performance evaluation results clearly show that the TPS3 protocol ensures the privacy and reliability of consumer data in SGs. The results also show that the tradeoff between the communication cost and security of TPS3 is negligible.     

Novel glazing technologies to mitigate energy consumption in low‐carbon buildings: a comparative experimental investigation

Buildings play a key role in total world energy consumption as a consequence of poor thermal insulation characteristics of facade materials. Among the elements of a typical building envelope, windows are responsible for the greatest energy loss because of their notably high overall heat transfer coefficients. About 60% of heat loss through the building fabric can be attributed to the glazed areas. In this respect, novel cost‐effective glazing technologies are needed to mitigate energy consumption, and thus to achieve the latest targets toward low/zero carbon buildings. Therefore in this study, three unique glazing products called vacuum tube window, heat insulation solar glass and solar pond window which have recently been developed at the University of Nottingham are introduced, and thermal performance analysis of each glazing technology is done through a comparative experimental investigation for the first time in literature. Standardized co‐heating test methodology is performed, and overall heat transfer coefficient (U‐value) is determined for each glazing product following the tests carried out in a calibrated environmental chamber. The research essentially aims at developing cost‐effective solutions to mitigate energy consumption because of windows. The results indicate that each glazing technology provides very promising U‐values which are incomparable with conventional commercial glazing products. Among the samples tested, the lowest U‐value is obtained from the vacuum tube window by 0.40 W/m²K, which corresponds to five times better thermal insulation ability compared to standard air filled double glazed windows. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

Visible Light Photocatalysis of Ni-Deposited TiO_2 Nanotubes for Methyl Orange Degradation in Alkaline Medium

The photocatalysis of Ti O2nanotubes(Ti/TNT) and Ni-deposited Ti O2nanotubes(Ti/TNT–Ni) for methyl orange degradation was investigated.Methyl orange was selected as the model pollutant,and its photocatalytic degradation was determined in 1 mol/L KOH solution.Ti/TNT was produced by anodizing method,and the electrodeposition of nickel on TNT was performed galvanostatically.The characterization of electrodes was performed by scanning electron microscopy,energy-dispersive X-ray spectroscopy and X-ray diffraction analysis.The electrochemical behavior of the electrodes was determined by cyclic voltammetry and electrochemical impedance spectroscopy.The irradiation was applied by visible light source(k = 635 nm) for 48 h.UV/vis spectroscopy was used for determination of the concentration of methyl orange.Furthermore,after 48-h irradiation,the solutions were analyzed by Fourier transform infrared spectroscopy.Results showed that the concentration of methyl orange decreased from 100 ppm(10-6) to 16 ppm,after48-h irradiation with the photocatalysis of Ti/TNT–Ni.     

A complementary study on novel PdAuCo catalysts: Synthesis,characterization, direct formic acid fuel cell application,and exergy analysis

At present, Pd containing (10–40 wt%) multiwall carbon nanotube (MWCNT) supported Pd monometallic, Pd:Au bimetallic, and PdAuCo trimetallic catalysts are prepared via NaBH₄ reduction method to examine their formic acid electrooxidation activities and direct formic acid fuel cell performances (DFAFCs) when used as anode catalysts. These catalysts are characterized by advanced analytical techniques as N₂ adsorption and desorption, XRD, SAXS, SEM-EDX, and TEM. Electronic state of Pd changes by the addition of Au and Co. Moreover, formic acid electrooxidation activities of these catalysts measured by CV indicates that particle size changes in wide range play a major role in the formic acid electrochemical oxidation activity, ascribed the strong structure sensitivity of formic acid electrooxidation reaction. PdAuCo (80:10:10)/MWCNT catalyst displays the most significant current density increase. On the other hand, lower CO stripping peak potential obtained for PdAuCo (80:10:10)/MWCNT catalyst, attributed to the awakening of the Pd-adsorbate bond strength down to its optimum value, which favors higher electrochemical activity. DFAFCs performance tests and exergy analysis reveal that fuel cell performances increase with the addition of Au and Co which can be attributed to synergetic effect. Furthermore, temperature strongly influences the performance of formic acid fuel cell.     

Processing and properties of modified polyamide 66-organoclay nanocomposites

Binary polyamide 66 nanocomposites containing 2 wt % organoclay, polyamide 66 blend containing 5 wt % impact modifier, and ternary polyamide 66 nanocomposites containing 2 wt % organoclay and 5 wt % impact modifier were prepared by melt compounding method. The effects of E-GMA and the types of the organoclays on the interaction between the organoclay and the polymer, dispersion of the organoclay, morphology, mechanical, flow, and thermal properties of the nanocomposites were investigated. Partial exfoliation and improved mechanical properties are observed for Cloisite® 15A and Cloisite® 25A nanocomposites. On the other hand, the organoclay was intercalated or in the form of tactoids in Cloisite® 30B nanocomposites. Components of the nanocomposites containing Cloisite® 15A and Cloisite® 25A were compounded in different addition orders. Mixing sequence of the components affected both the dispersion of the organoclay and the mechanical properties drastically. SEM analyses revealed that homogeneous dispersion of the organoclay results in a decrease in the domain sizes and promotes the improvements in the toughness of the materials. Melt viscosity was also found to have a profound effect on the dispersion of the organoclay according to MFI and XRD results. Crystallinity of the nanocomposites did not change significantly. It is only the type of the constituents and their addition order what dramatically influence the nanocomposite properties. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci 2008     

An investigation of Al2O3–ZrO2 ceramic composite-coated engine parts using plasma spray method on a diesel engine

ABSTRACT

In this study, the surfaces of the piston, cylinder head and valve parts of the combustion chambers for a single-cylinder diesel engine were coated at 250?µm thick ceramic composite Al₂O₃–ZrO₂ (20–80%) main coating material and 100?µm NiCrAl interlayer material. Also, B6 and B12 biodiesel fuels were produced. Fuel blends were tested on a diesel engine with thermal barrier-coated surfaces for 50?h under the same conditions. When the SEM images and the EDS analysis results of the pistons covered with the ceramic composite main coating material are examined, it has been seen that the coating material permeates the surfaces in a very homogeneous manner and allows to work with high performance without causing any deterioration on the surfaces during working. At high temperatures, the working periods of 50?h and the formation of smoke did not cause any damage to the main material and the coating material.     

Force Transmission Error Analysis for a High-Pressure Single-Sinker Magnetic Suspension Densimeter

The magnetic suspension densimeter (MSD) is a sophisticated, state-of-the-art device that provides extremely accurate results for density measurements. The MSD uses a magnetic technique to couple a mass inside a measurement cell with an external mass balance for mass measurement. This article presents a force transmission error (FTE) analysis for a high-pressure, single-sinker MSD. Due to the magnetic working principle of the apparatus, magnetic properties of the high-pressure cell and external magnetic fields affect the measurements slightly. For the analysis, McLinden et al. suggest making measurements using two different sinkers, a titanium sinker and a copper sinker, having the same mass. The measurements cover densities for methane, ethane, carbon dioxide and nitrogen over the temperature range from 265 K to 450 K (±5 mK stability) up to 180 MPa (uncertainty of 0.01 % full scale: 200 MPa). Comparing and manipulating the measurements permit determination of apparatus and fluid specific effects that contribute to the FTE. For this MSD, the apparatus effect is about 200 ppm, which effectively masks any fluid specific effect. A comprehensive analysis of the FTE produces a uniform deviation for density values of about 0.05 % at 2σ across the full range of pressure.