National Technical University of Athens

About: National Technical University of Athens is a education organization based out in Athens, Attiki, Greece. It is known for research contribution in the topics: Large Hadron Collider & Nonlinear system. The organization has 13445 authors who have published 31259 publications receiving 723504 citations. The organization is also known as: Athens Polytechnic & NTUA.

Enhancing the performance of parabolic trough collectors using nanofluids and turbulators

Abstract: Parabolic trough collector is one of the most usual solar collectors for applications up to 400 °C. The thermal enhancement of this collector concentrates a lot of interest and various techniques are tested in order for the thermal efficiency to be maximized with a reasonable penalty in the pressure drop. The use of nanofluids as working fluids, as well as the use of flow turbulators, mainly inserts and internal fins or tube dimples are the main techniques which are examined. The objective of this work is to give a complete literature review of the existing studies on this domain and to present a numerical comparative analysis between the most usual thermal enhancement techniques. More specifically, the use of oil-based nanofluids with 6% CuO is compared with the use of internal rectangular fins in the absorber, while the combination of these techniques is also examined. The analysis is conducted with a validated CFD model in SolidWorks Flow Simulation for various fluid temperature levels. According to the final results, the use of nanofluids leads to 0.76% thermal efficiency enhancement, the use of internal fins to 1.10% and the combination of these techniques to 1.54%. Moreover, emphasis is given in the pressure drop of the examined cases and in the evaluation criteria which are used in every case.

Nanotechnology and nanostructured materials: trends in carbon nanotubes

Abstract: Carbon nanotubes have attracted the attention of many researchers since their discovery last decade. These carbon molecules are tiny tubes with diameters down to 0.4 nm, while their lengths can grow up to a million times their diameter. Using their remarkable electrical properties, simple electronic logic circuits have been built. These structures are promising for the semiconductor industry which is leading the search for miniaturisation. They are not only very good conductors, but they also appear to be the yet found material with the biggest specific stiffness, having half the density of aluminium. This paper is written to give a consolidated view of the synthesis, the properties and applications of carbon nanotubes, with the aim of drawing attention to useful available information and to enhancing interest in this new highly advanced technological field for the researcher and the manufacturing engineer.

Rolling element bearing fault detection in industrial environments based on a K-means clustering approach

Abstract: A K-means clustering approach is proposed for the automated diagnosis of defective rolling element bearings. Since K-means clustering is an unsupervised learning procedure, the method can be directly implemented to measured vibration data. Thus, the need for training the method with data measured on the specific machine under defective bearing conditions is eliminated. This fact consists the major advantage of the method, especially in industrial environments. Critical to the success of the method is the feature set used, which consists of a set of appropriately selected frequency-domain parameters, extracted both from the raw signal, as well as from the signal envelope, as a result of the engineering expertise, gained from the understanding of the physical behavior of defective rolling element bearings. Other advantages of the method are its ease of programming, simplicity and robustness. In order to overcome the sensitivity of the method to the choice of the initial cluster centers, the initial centers are selected using features extracted from simulated signals, resulting from a well established model for the dynamic behavior of defective rolling element bearings. Then, the method is implemented as a two-stage procedure. At the first step, the method decides whether a bearing fault exists or not. At the second step, the type of the defect (e.g. inner or outer race) is identified. The effectiveness of the method is tested in one literature established laboratory test case and in three different industrial test cases. Each test case includes successive measurements from bearings under different types of defects. In all cases, the method presents a 100% classification success. Contrarily, a K-means clustering approach, which is based on typical statistical time domain based features, presents an unstable classification behavior.

Algorithm design for data communications in duty-cycled wireless sensor networks: A survey

Abstract: Although duty-cycling has long been a critical mechanism for energy conservation in wireless sensor networks, it is only recently that research efforts have been put to design data communication protocols that perform efficiently in duty-cycled wireless sensor networks (DC-WSNs). In this article, we survey these research problems, aiming at revealing insights into the following three key questions: what are the meaningful (algorithm design) problems for DC-WSNs, which problems have been studied and which have not, and what are the essential techniques behind the existing solutions? All these insights may serve as motivations and inspirations for further developments in this field.