Uzay Kafes Yapıların Ateş Böceği Algoritması Yöntemiyle Optimizasyonu

Konferans Bildirisi -- Teorik ve Uygulamalı Mekanik Türk Milli Komitesi, 2015Conference Paper -- Theoretical and Applied Mechanical Turkish National Committee, 2015Hayvan ve böcek türlerinin sürü/koloni/grup davranışlarını taklit eden sezgisel optimizasyon yöntemleri son yıllarda farklı tasarım problemlerinin çözümünde kullanılmıştır. Ateşböceği algoritması, ateşböceklerinin davranışları ve parıldama yoluyla yaptıkları iletişimleri taklit etmektedir. Bu çalışma ile, ateşböceği algoritması yöntemiyle uzay kafes yapıların optimizasyonu yapılacaktır. Optimizasyon probleminde, deplasman ve gerilme sınırlayıcıları altında minimum ağırlıklı kafes yapıların elde edilmesi amaçlanmaktadır. Ateşböceği algoritması yönteminin performansı; daha önce armoni arama, hibrid parçacık sürü optimizasyonu, hibrid parçacık sürü-karınca koloni optimizasyonu, adaptif armoni arama ve ateşböceği algoritması yöntemleriyle optimize edilmiş olan 25 elemanlı uzay kafes yapı üzerinde test edilmiştir. Yapılan kıyaslamalar ateşböceği algoritmasının en az diğer yöntemler kadar güçlü bir optimizasyon yöntemi olduğunu göstermektedir.Meta-heuristic optimization algorithms simulated the behaviour of flock/colony/group have been used for the solving of different design problems. Firefly algorithm (FFA) is a recently developed meta-heuristic optimization algorithm inspired by social behaviour of fireflies and the phenomenon of bioluminescent communication. The main purpose of this study is to implement a robust FFA algorithm for sizing optimization of spatial truss structures. The objective of the study is to obtain the minimum weight truss design under the displacement and stress constraints. The efficiency of the FFA algorithm implemented in this study is tested on weight minimization problem of 25-bar truss structure. The optimization results are compared with those reported in the literature for other state-of-the-art meta-heuristic optimization methods such as harmony search, hybrid particle swarm optimization, hybrid particle swarm ant colony optimization, self-adaptive harmony search algorithm and firefly algorithm. The comparisons showed that firefly algorithm is as powerful as the other meta-heuristic optimization methods

Application of Optical Methods to Electronic Component Stress Analysis

Increasing electronic component reliability is, nowadays, a hot topic both in most advanced applications as well as in electronic devices of common use in everyday life. In fact, requirements in terms of miniaturization of electronics components introduce issues connected with heat dissipation management. Materials, packaging, heat dissipator, and even positioning of the component on the board should be optimized in order to reduce thermal stresses generated in the components, which are one of the most important failure mechanisms of electronics. Thermal stress evaluation is, however, a difficult task due to the size of the elements under testing and to the necessity of measuring small amount of strains. At the same time, any contact with the object under measurement should be avoided not to alter heat capacity of the component itself. In this work, some results of experimental stress analysis gathered using electronic speckle pattern interferometry will be described; it will be pointed out how this approach allows to put in evidence inhomogeneous stress fields undergone by the electronic components and how it is possible to highlight the presence of bad functioning and defects

Spectroscopic and adsorptive studies of a thermally robust pyrazolato-based PCP

The pyrazolato-based PCP [Ni8(OH)4(OH2)2(PBP)6] (NiPBP, H2PBP = 4,4\u2019-bis(1H-pyrazol-4-yl)biphenyl), whose 3-D architecture is built upon octametallic hydroxo clusters reciprocally connected by the organic spaces, is a very promising candidate for gas adsorption applications, owing to its remarkable thermal stability (up to 400 \ub0C in air) and its high void volume (70%). As such, NiPBP was selected as a proof-of-concept material to demonstrate how an optimized set of solid state techniques can concur to create a comprehensive and coherent picture, relating (average and local) structural features to adsorptive properties. To this aim, the response of NiPBP toward different gases, retrieved by gas adsorption measurements (N2 at 77 K, in the low pressure region; H2 at 77 K, in the high pressure region), was explained in terms of local-level details, as emerged by coupling electronic, X-ray (absorption and emission), and variable temperature IR spectroscopy

Prediction of welding responses using AI approach : adaptive neuro-fuzzy inference system and genetic programming

Laser welding of thin sheets has widespread application in various fields such as battery manufacturing, automobiles, aviation, electronics circuits and medical sciences. Hence, it is very essential to develop a predictive model using artificial intelligence in order to achieve high-quality weldments in an economical manner. In the present study, two advanced artificial intelligence techniques, namely adaptive neuro-fuzzy inference system (ANFIS) and multi-gene genetic programming (MGGP), were implemented to predict the welding responses such as heat-affected zone, surface roughness and welding strength during joining of thin sheets using Nd:YAG laser. The study attempts to develop an appropriate predictive model for the welding process. In the proposed methodology, 70% of the experimental data constitutes the training set whereas remaining 30% data is used as testing set. The results of this study indicated that the root-mean-square error (RMSE) of tested data set ranges between 7 and 16% for MGGP model, while RMSE for testing data set lies 18–35% for ANFIS model. The study indicates that the MGGP predicts the welding responses in a superior manner in laser welding process and can be applied for accurate prediction of performance measures

Comprehensive survey on nanobiomaterials for bone tissue engineering applications

One of the most important ideas ever produced by the application of materials science to the medical field is the notion of biomaterials. The nanostructured biomaterials play a crucial role in the development of new treatment strategies including not only the replacement of tissues and organs, but also repair and regeneration. They are designed to interact with damaged or injured tissues to induce regeneration, or as a forest for the production of laboratory tissues, so they must be micro-environmentally sensitive. The existing materials have many limitations, including impaired cell attachment, proliferation, and toxicity. Nanotechnology may open new avenues to bone tissue engineering by forming new assemblies similar in size and shape to the existing hierarchical bone structure. Organic and inorganic nanobiomaterials are increasingly used for bone tissue engineering applications because they may allow to overcome some of the current restrictions entailed by bone regeneration methods. This review covers the applications of different organic and inorganic nanobiomaterials in the field of hard tissue engineering

Towards better performances for a novel rooftop solar PV system

Solar photovoltaic (PV) systems are used worldwide for clean production of electricity. Photovoltaic simulation tool serve to predict the amount of energy generated by the PV solar array structure. This paper presents the photovoltaic system installed on the rooftop of the G.D. Naidu Block at Vellore Institute of Technology (Vellore, India). A novel PV plant design is developed here in order to improve the energetic efficiency of an existing PV system. The effectiveness of proposed design is evaluated over an entire year using the PVsyst v6.70 software, which works on accurate plant specifications. For this purpose, Metronome 7.1 weather data sets of ambient temperature and radiation from PVsyst database are used for the investigation. The cost of the proposed PV system and the required payback period are analyzed as well. Simulation results demonstrate the superiority of the proposed PV system design over the existing one in terms of the amount of electric energy injected in the grid, energy conversion efficiency, and reductions in CO2/SO2/NO emissions. Performance ratio of proposed design (Design 2) is 0.791 whereas the existing design (Design 1) is only 0.704. Design 2 provides 40 MWh more energy to grid than Design 1 due to reducing shading losses. The daily system energy generated for Design 2 is maximum (in particular, 26-29% higher than for Design 1) between March and May, when the sun is brightest and directly above our head. Shading analysis carried out for both designs revealed that the existing Design 1 has more shading loss while the proposed Design 2 may reduce this loss by about 11-13%, which results in a better efficiency of energy production. The article also documents significant emission reduction and cost analysis calculation for the proposed Design 2

An Optical System to Monitor the Displacement Field of Glass-fibre Posts Subjected to Thermal Loading

Endocanalar posts are necessary to build up and retain coronal restorations but they do not reinforce dental roots. It was observed that the dislodgement of post-retained restorations commonly occurs after several years of function and long-term retention may be influenced by various factors such as temperature changes. Temperature changes, in fact, produce micrometric deformations of post and surrounding tissues/materials that may generate high stress concentrations at the interface thus leading to failure. In this study we present an optical system based on the projection moiré technique that has been utilized to monitor the displacement field of endocanalar glass-fibre posts subjected to temperature changes. Measurements were performed on forty samples and the average displacement values registered at the apical and middle region were determined for six different temperature levels. A total of 480 displacement measurements was hence performed. The values of the standard deviation computed for each of the tested temperatures over the forty samples appear reasonably small which proves the robustness and the reliability of the proposed optical technique. The possible implications for the use of the system in the applicative context were discussed

Graphene-Based Membrane Technology: Reaching Out to the Oil and Gas Industry

This paper presents a critical review and the state of the art of graphene porous membranes, a brand-new technology and backdrop to discuss its potential application for efficient water desalination in low salinity water injection (LSWI). LSWI technology consists in injecting designed, adequately modified, filtered water to maximize oil production. To this end, desalination technologies already available can be further optimized, for example, via graphene membranes, to achieve greater efficiency in water-oil displacement. Theoretical and experimental applications of graphene porous membranes in water desalination have shown promising results over the last 5-6 years. Needless to say, improvements are still needed before graphene porous membranes become readily available. However, the present work simply sets out to demonstrate, at least in principle, the practical potential graphene membranes would have in hydrocarbon recovery processes