Oxidation and thermal shock behavior of thermal barrier coated 18/10CrNi alloy with coating modifications

In this study, substrates of 18/10CrNi alloy plates were initially sprayed with a Ni-21Cr-10Al-1Y bond coat and then with an yttria stabilized zirconia top coat by plasma spraying. Subsequently, plasma-sprayed Thermal barrier coatings (TBCs) were treated with two different modification methods, namely, vacuum heat treatment and laser glazing. The effects of modifications on the oxidation and thermal shock behavior of the coatings were evaluated. The effect of coat thickness on the bond strength of the coats was also investigated. Results showed enhancement of the oxidation resistance and thermal shock resistance of TBCs following modifications. Although vacuum heat treatment and laser glazing exhibited comparable results as per oxidation resistance, the former generated the best improvement in the thermal shock resistance of the TBCs. Bond strength also decreased as coat thickness increased.     

Zero-dimensional single zone engine modeling of an SI engine fuelled with methane and methane-hydrogen blend using single and double Wiebe Function: A comparative study

Combustion modeling plays a key role in an engine simulation to predict in-cylinder pressure development and engine performance with a high level accuracy. Wiebe function, representing mass fraction burned (MFB) as a function of crank angle position, is widely used to predict the combustion process. The work presents a predictive zero-dimensional (Zero-D) single zone engine modeling of an SI engine fuelled with methane and methane-hydrogen blend. In this work, the single and double forms of Wiebe function were used to estimate the combustion process in the modeling. For this purpose, the single and double-Wiebe functions' parameters were calculated using the least squares method by fitting to the MFB curves calculated from experimental pressure data. These Wiebe functions were, then, introduced to the Zero-D single zone engine model developed for the methane and methane-hydrogen blend fueled SI engine to obtain in-cylinder pressure development and gross indicated mean effective pressure (GIMEP) for the engine performance prediction. The results show that the model with double-Wiebe Function fit better than that with single-Wiebe function. In addition, the fitted double-Wiebe function has a significant improvement in the GIMEP prediction for methane-hydrogen blend fueled SI engine modeling rather than the methane-fueled modeling.     

Effect of heat treatment on the bending behavior of aluminum alloy tubes

Quasistatic experiments and numerical simulations were performed to investigate the three-point bending behavior of different temper AA6082 tubes in this study. The effect of heat treatment on the samples was investigated by microstructural analyses. Temper designations of T6, T4 and O were applied to the samples to study the load-carrying capacity and bendability of AA6082 tubes. The samples with T4 and O tempers show appropriate bendability of up to the punch travel distance of 60 mm under low-punch forces. However, the samples with T6 temper require three times more punch force than the other temper samples. Furthermore, the T6 temper samples cannot hold their structural integrity. Therefore, crack formation occurred at the enhanced bending angle stages. Experimental results were compared with the numerical simulation outputs, and the deformation mechanism was observed with finite element method. In addition, various element formulations in the numerical simulations were compared in terms of bending force and computational time. Based on the numerical results, element formulations exhibit different performances with respect to temper conditions.     

A multi-objective genetic algorithm for the hot mix asphalt problem

Neural Computing and Applications - It is desirable for the work done in any construction process to be both cost-effective and durable. A thorough consideration of the matter reveals that the...     

From potential forecast to foresight of Turkey's renewable energy with Delphi approach

A Delphi Survey is a series of questionnaires that allow experts or people with specific knowledge to develop ideas about potential future developments around an issue. The Delphi questionnaires were developed throughout the foresight process in relation to the responses given by participants in bibliometric and SWOT analysis conducted prior to the Delphi survey. In this paper, Turkey's renewable energy future is evaluated using the Delphi method. A two-round Delphi research study was undertaken to determine and measure the expectations of the sector representatives regarding the foresight of renewable energies. First and second round of Delphi study were carried out by using online surveys. About 382 participants responded in the first round of the Delphi questionnaire yielding a respond rate of 20.1%, whereas 325 participants responded at the second round yielding a respond rate of 84.9%. About 50% of Turkey's energy demand was foresighted to be met by renewable energies around 2030. The results showed that all types of renewable energies would not only provide economic and environmental benefits but also improve living standards.     

Dielectric behavior characterization of a fibrous‐ZnO/PVDF nanocomposite

This study is focused on forming a fibrous‐zinc oxide/polyvinylidine fluoride (ZnO/PVDF) nanocomposite and characterizing its dielectric behavior. The nanocomposite is prepared in two steps. First, a network of nanoscale diameter ZnO fibers is produced by sintering electrospun PVA/Zinc Acetate fibers. Second, the ZnO fibrous nonwoven mat is sandwiched between two PVDF thermoplastic polymer films by hot‐press casting. Scanning electron microscope images of the nanocomposite show that hot‐press casting of the fibrous‐ZnO network breaks the network up into short fibers. The in‐plane distribution of the ZnO fillers (i.e., the short fibers) in the PVDF matrix appears to comply with that of the pristine ZnO fibers before hot‐pressing, indicating that the fillers remain well‐dispersed in the polymer matrix. To the authors' knowledge, the work reported herein is the first demonstration of the use of electrospinning to secure the dispersion and distribution of a network of inorganic fillers. Moreover, processing a fibrous‐ZnO/PVDF flexible composite as described in this report would facilitate material handling and enable dielectric property measurement, in contrast to that on a fibrous mat of pure ZnO. Because of the high surface area of the short ZnO fibers and their polycrystalline structure, interfacial polarization is pronounced in the nanocomposite film. The dielectric constant is enhanced significantly‐up to a factor of 10 at low frequencies compared to the dielectric constant of constituent materials (both bulk ZnO and PVDF), and up to a factor of two compared to a bulk‐ZnO/PVDF composite. POLYM. COMPOS., 2010. © 2009 Society of Plastics Engineers     

ANN and ANFIS performance prediction models for hydraulic impact hammers

Hydraulic impact hammers are mechanical excavators that can be used in tunneling projects economically under geologic conditions suitable for rock breakage by indentation. However, there is relatively less published material in the literature in relation to predicting the performance of that equipment employing rock properties and machine parameters. In tunnel excavation projects, there is often a need for accurate prediction the performance of such machinery. The poor prediction of machine performance can lead to very costly contractual claims. In this study, the application of soft computing methods for data analysis called artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) to predict the net breaking rate of an impact hammer is demonstrated. The prediction capabilities offered by ANN and ANFIS were shown by using field data of obtained from metro tunnel project in Istanbul, Turkey. For this purpose, two prediction models based on ANN and ANFIS were developed and the results obtained from those models were then compared to those of multiple regression-based predictions. Various statistical performance indexes were used to compare the performance of those prediction models. The results suggest that the proposed ANFIS-based prediction model outperforms both ANN model and the classical multiple regression-based prediction model, and thus can be used to produce a more accurate and reliable estimate of impact hammer performance from Schmidt hammer rebound hardness (SHRH) and rock quality designation (RQD) values obtained from the field tests.     

Optimum design of multiple positioned tuned mass dampers for structures constrained with axial force capacity

The stories of structure may have different and limited axial force capacity. In order to passively control the translational movement of structures, a tuned mass damper (TMD) positioned on a story may cause to exceed axial force capacity of a story. The optimum performance is achieved when all additional masses are positioned on the top story. Whereas, the top stories of structure may be constructed with lower axial force capacity than the lower stories. In that case, the maximum allowed TMD mass for upper stories may be low. In that situation, several TMDs may be positioned on several stories. In the current study, the optimum tuning of TMDs positioned on multiple stories of structure is investigated. By using small masses, it is also possible to obtain effective passive control with dampers that have small damping coefficients comparing with a single TMD on the top of the structure. The design variables of the optimization problem such as the period and damping ratio of TMD are tuned according to a metaheuristic algorithm called flower pollination algorithm. The TMD is optimized for near‐fault excitations by using impulsive motions during the optimization process. The proposal was applied to four case studies. According to the results, the multiple positioned TMDs may be a practical and effective option comparing with the use of a single heavy TMDs on the top of a structure.     

Morphological evaluation and phase behavior of PVDF/PEO blends in the presence of graphene nanoplatelets through rheological measurements

In this study, graphene nanoplatelets (GNPs) were incorporated into poly(vinylidene fluoride) (PVDF), poly(ethylene oxide) (PEO), and PVDF/PEO blends using solution casting method in order to achieve binary and ternary polymer nanocomposites. The focus of the work is on the compatibilizing effects of the GNPs on partially miscible PVDF/PEO blends. X-ray diffraction method, rheological measurements, scanning electron microscopy (SEM), and atomic force microscopy observations enabled us to track the dispersion state and localization of the graphene nanosheets in the nanocomposites. The results exhibited that the nanoplatelets were preferentially distributed through the PVDF phase and/or at the interface of the PVDF/PEO phases. Evaluation of the wetting parameter for the PVDF/PEO/GNPs nanocomposite also verified better affinity of the selected nanofiller with the PVDF component. Extend of the miscibility in the nanocomposites was studied by a well-known rheological method. A tangible increment in binodal (T_b) and spinodal (T_s) decomposition temperatures by addition of a very low content of the GNPs (0.5 wt %) revealed well-defined compatibilization effects of the graphene on this binary polymer blend. SEM images at different temperatures confirmed the rheologically determined liquid–liquid phase diagram. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48017.     

Hydrogen is not an utopia for Turkey

The aim of this study was to explore how the future of technological developments in hydrogen will be shaped in Turkey by using a two-round Delphi method undertaken to determine and measure the expectations of the sector representatives through online surveys where a total of 60 experts responded from 18 different locations. The article discusses not only the expert sights on hydrogen technologies but also all bibliometrical approaches. The results showed that the hydrogen economy will enhance innovations as well as economic prosperities with the support of appropriate policies. Formulating such policies requires a timely and detailed understanding of the latest R&D trends and developments in science and technology policy in all developed countries, and the comprehensive analysis of these developments to enable accurate predictions of future science and technology trends. Therefore, we hope that this study can shed a light on the future use of hydrogen technologies, especially for policy makers.