Vibration analysis and identification of breathing cracks in beams subjected to single or multiple moving mass using online sequential extreme learning machine

In this paper, a novel approach was presented to vibration analysis and identification of breathing cracks in Timoshenko beam under single or multiple moving mass. Dynamic strain energies (DSEs) and translational accelerations in beam structures under moving mass were used as forward problem and application of an emergent learning algorithm called the online sequential extreme learning machine algorithm as inverse problem to predict crack depths and locations. To demonstrate the potential of the proposed vibration analysis over existing ones, two validation studies have been done. To evaluate the proposed method to identify breathing cracks, two examples, namely, clamped–clamped beam and two span continuous beams have been studied. Also, the effect of the discrepancy in stiffness between the finite-element model and the actual tested dynamic system has been investigated. Another examination has been performed in which moving mass with different speeds are utilized. Also, the effect of multi mass passing through the beam has been studied. The obtained results indicated that the proposed method could identify the breathing cracks existence and severity in the beam under moving mass using DSE and accelerations, which may be noisy or noise free.     

Gaseous Mixtures Separation via Chemically-Activated Nano Silica-Modified Carbon Molecular Sieves

Silicon - The goal of this research was to study the efficiency of the silica-modified, highly selective synthesized carbon molecular sieves for nitrogen separation in the methane purification...     

Electrochemical routes for environmentally friendly recycling of rare-earth-based (Sm–Co) permanent magnets

Journal of Applied Electrochemistry - The consumption of critical raw materials, especially those in permanent magnets of Nd–Fe–B and Sm–Co-type, has significantly grown in the...     

Solvent Influence on the Hydrodeoxygenation of Guaiacol over Pt/SiO2 and Pt/H‐MFI 90 Catalysts

Second generation biofuels are produced in the bioliq® process at the Karlsruhe Institute of Technology via gasification of pyrolysis oil and synthesis of gasoline from the emerging synthesis gas. An alternative strategy is the direct upgrading of the pyrolysis oil by hydrodeoxygenation (HDO). The present study reports on the HDO of guaiacol as one of the phenolic compounds strongly abundant in such mixtures. Special focus was laid on the solvent influence using Pt‐based catalysts. Higher HDO ability was seen using nonpolar solvents and acidic supports. Characterization of the catalysts before and after the test showed that the solvent did not only influence the reactivity, but also the catalyst stability.     

Synergistic reinforcement of NBR by hybrid filler system including organoclay and nano‐CaCO3

Rubber nanocomposites containing one type of nanofiller are common and are widely established in the research field. In this study, nitrile rubber (NBR) based ternary nanocomposites containing modified silicate (Cloisite 30B) and also nano‐calcium carbonate (nano‐CaCO₃) were prepared using a laboratory internal mixer (simple melt mixing). Effects of the hybrid filler system (filler phase have two kind of fillers) on the cure rheometry, morphology, swelling, and mechanical and dynamic–mechanical properties of the NBR were investigated. Concentration of nano‐CaCO₃ [0, 5, 10, and 15 parts per one hundred parts of rubber by weight (phr)] and organoclay (0, 3, and 6 phr) in NBR was varied. The microstructure and homogeneity of the compounds were confirmed by studying the dispersion of nanoparticles in NBR via X‐ray diffraction and field emission scanning electron microscopy. Based on the results of morphology and mechanical properties, the dual‐filler phase nanocomposites (hybrid nanocomposite) have higher performance in comparison with single‐filler phase nanocomposites. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42744.     

Plasma Spray Deposition Enhancement of Titanium Nitride Layer Using Nitrogen-Contained Plasma Irradiation of Titanium Substrate as a Pre-spraying Method

Reactive plasma spray of TiN ceramic coating attracts much attention over the years because of its ability to deposit thick layers on various metal surfaces. However, some mechanical properties of the coating such as its hardness should be improved. In this study, initially a thin layer of titanium nitride was prepared on a titanium substrate during irradiation of titanium substrate by a thermal DC nitrogen-contained plasma jet. Then, during reactive plasma spraying, Ti particles were injected into plasma jet, converted to titanium nitride and huddled on to the substrate. This new hybrid method (primary plasma irradiation and post-reactive plasma spraying) for deposition of TiN coatings would combine the advantages of both plasma-enhanced chemical vapor deposition and reactive plasma spraying methods in part. It resulted in a thick and hard layer of titanium nitride film. Sample produced by this method was analyzed with x-ray diffraction confirming titanium nitride production. Vickers hardness was measured using optical microscopy which was around 1319 H_v300g. To study the cross section of the layer, optical microscopy and scanning electron microscopy (SEM) were used.     

Sensitivity Analysis on Ladder Network Equivalent Circuit Parameters of Power Transformer

In this article, novel methods and ideas are introduced, which altogether lead to an accurate model of power transformer windings. First, by the determination of non-dominant (hidden) resonances from frequency-response tests, a ladder model is proposed. Next, it is improved by assigning different values for similar elements of each section of the model. The parameters are obtained by minimizing the error function via a genetic algorithm. Sensitivity analysis is then applied to the obtained model to achieve further examinations and tests. Measurements have been driven from the windings of a 20/0.4-kV, 1600-kVA transformer. Modeling, methodologies, and sensitivity analysis in this article can be very useful for future research aiming to find internal faults of the transformer with the frequency response analysis.     

FeO0.7F1.3/C Nanocomposite as a High‐Capacity Cathode Material for Sodium‐Ion Batteries

Searching high capacity cathode materials is one of the most important fields of the research and development of sodium‐ion batteries (SIBs). Here, we report a FeO_0.7F_1.3/C nanocomposite synthesized via a solution process as a new cathode material for SIBs. This material exhibits a high initial discharge capacity of 496 mAh g^?1 in a sodium cell at 50 °C. From the 3^rd to 50^th cycle, the capacity fading is only 0.14% per cycle (from 388 mAh g^?1 at 3^rd the cycle to 360 mAh g^?1 at the 50^th cycle), demonstrating superior cyclability. A high energy density of 650 Wh kg^?1 is obtained at the material level. The reaction mechanism studies of FeO_0.7F_1.3/C with sodium show a hybridized mechanism of both intercalation and conversion reaction.     

Application of carbon nanostructures toward SO2 and SO3 adsorption: a comparison between pristine graphene and N-doped graphene by DFT calculations

We studied the adsorption of SO_x (x?=?2,3) molecules on the surface of pristine graphene (PG) and N-doped graphene (NDG) by density functional theory (DFT) calculations at the B3LYP/6-31G(d) level. We used Mulliken and NBO charge analysis to calculate the net charge transfer of adsorbed SO_x on pristine and defected graphene systems. Our calculations reveal much higher adsorption energy and higher net charge transfer by using NDG instead of pristine graphene. Furthermore, the density of state (DOS) graphs point to major orbital hybridization between the SO_x and NDG, while there is no evidence of hybridization by using pristine graphene. Based on our results, it is found that SO₂ and SO₃ molecules can be adsorbed on the surface of NDG physically and chemically with adsorption energies (E_ads) of ?27.5 and 65.2?kJ?mol^?1 (19.6 and 51.4?kJ?mol^?1 BSSE), respectively, while low adsorption energies were calculated in the case of using pristine graphene. So we introduced NDG as a sensitive adsorbent/sensor for detection of SO₂ and SO₃.