Neural Network Based Thickness Estimation from Multiple Radiographic Images

Back propagation (BP) type artificial neural networks (ANN) have been trained and used for thickness estimations from radiographic images. Test objects have been assembled from different materials and radiographic images of the test objects were obtained for thickness estimations. While some of the study has been based on the synthetic images formed through the radiographic simulation program XRSIM, the rest of the study has used actual radiographic images. The average estimation errors were 7% and 9% when two and three synthetic radiographic images obtained at different x-ray tube settings were used. With the actual images, the thickness of only one of the materials has been estimated and the material was identified. This has been due to the fact that scattering of x-rays by the test object results in a non uniform gray scale variation in the radiographic images even though the object thickness is uniform.     

Energy and exergy analysis of a latent heat storage system with phase change material for a solar collector

Analysis of energy and exergy has been performed for a latent heat storage system with phase change material (PCM) for a flat-plate solar collector. CaCl₂·6H₂O was used as PCM in thermal energy storage (TES) system. The designed collector combines in single unit solar energy collection and storage. PCMs are stored in a storage tank, which is located under the collector. A special heat transfer fluid was used to transfer heat from collector to PCM. Exergy analysis, which is based on the second law of thermodynamics, and energy analysis, which is based on the first law, were applied for evaluation of the system efficiency for charging period. The analyses were performed on 3 days in October. It was observed that the average net energy and exergy efficiencies are 45% and 2.2%, respectively.     

Modeling micro-end-milling operations. Part II: tool run-out

The effect of run-out is clearly noticed in micro-end-milling operations, while the same run-out creates negligible change at the cutting force profile of conventional end-milling operations. In this paper, the cutting force characteristics of micro-end-milling operations with tool run-out are investigated. An analytical cutting force model is developed for micro-end-milling operations with tool run-out. The proposed model has a compact set of expressions to be able to estimate the cutting force characteristics very quickly compared to the numerical approaches. The cutting forces of micro-end-milling operations simulated by the proposed model had good agreement with the experimental data.     

Modeling micro-end-milling operations. Part III: influence of tool wear

The characteristics of the cutting forces were studied at different usage levels and the analytical model of the micro-end-milling operations was modified to represent the tool wear. A new expression was derived from the model to estimate the remaining tool life from experimental data. The parameters of the model are estimated by using genetic algorithms. The difference between the simulated and experimental cutting force profiles for new and worn tools was less than 8%. The remaining tool life was estimated with typically 10% error from the experimental data. Maximum error was 20%. The introduced analytical model and genetic algorithm-based parameter estimation approach is very convenient for on-line tool wear monitoring without extensive experimental study.     

Parameter‐dependent Riccati equation–based output feedback adaptive control

A parameter‐dependent Riccati equation approach is proposed to design and analyze the stability properties of an output feedback adaptive control law design. The adaptive controller is intended to augment an existing fixed‐gain observer‐based output feedback control law. Although the formulation is in the setting of model reference adaptive control, the realization of the adaptive controller does not require implementing the reference model. In this regard, the increased complexity of implementing the adaptive controller, above that of a fixed‐gain control law, is less than that of other methods. The error signals are shown to be uniformly ultimately bounded, and an estimate for the ultimate bound is provided. The issue of sensor noise is addressed by introducing an error filter. The control design process and the theoretical results are illustrated using a model for wing rock dynamics.     

Hydrogen storage properties of magnesium nanotrees investigated by a quartz crystal microbalance system

We report enhanced low temperature hydrogen storage properties of magnesium “nanotrees” fabricated by glancing angle deposition (GLAD) method. The arrays of nanotrees and conventional thin films of elemental Mg have been deposited directly onto gold coated unpolished quartz crystal substrates. Mg nanotrees were about 15 μm in height, 10 μm by 1 μm in lateral size, and were composed of “nanoleaves” of about 20 nm in thickness, 2 μm length, and 1 μm width. Hydrogen absorption and desorption properties of Mg nanotrees and thin films were investigated using a quartz crystal microbalance (QCM) testing system that is capable of measuring weight changes with a nanogram sensitivity. QCM absorption tests were performed at temperatures 100, 200, and 300 °C under 30 bars of H₂ pressure. Measurements revealed that Mg nanotrees can absorb hydrogen at significantly higher weight percentage (wt%) and faster rates compared to conventional Mg films under similar conditions. Hydrogen storage of Mg thin film was observed to be at 0.02, 0.30 and 3.91 wt% (weight percentage), while it reached to 1.26, 3.75, and 5.86 wt% for nanotrees at temperatures 100, 200, and 300 °C, respectively, after 150 min. In addition, the results of desorption experiments show that Mg nanotrees can start to release hydrogen at temperatures as low as 100 °C at a rate of 0.11 wt% (vs. 0.01 wt% for thin film at the same temperature) with desorption rates reaching to 1.05 wt% at 200 °C (0.26 wt% for thin film) and 2.57 wt% at 300 °C (1.45 wt% for thin film), which are considerably lower desorption temperatures compared to previously reported values for bulk Mg (>300 °C). The enhancement in hydrogen absorption and desorption properties of Mg nanotrees is believed to originate from their thin and isolated nanoleaves that also have an improved oxidation resistance property.     

MOORA-based Taguchi optimisation for improving product or process quality

In this study a multi-objective optimisation on the basis of ratio analysis (MOORA)-based Taguchi application is used to solve multi-response optimisation problems. In this application, the MOORA method is integrated with the Taguchi method to convert the multi-response problem into a single-response problem. Four examples are considered in this paper for illustrative purposes. The MOORA-based Taguchi method is simple and robust compared to the other MADM methods, such as TOPSIS, VIKOR and GRA. The proposed model reduces the time associated with the amount of calculation steps significantly. We found that solution results of the MOORA-based Taguchi application and other hybrid models in the literature were not significantly different. The MOORA-based Taguchi application offers also a new tool in the optimisation of Taguchi’s multi response problem.     

Monodisperse Pd nanoparticles assembled on reduced graphene oxide-Fe3O4 nanocomposites as electrocatalysts for borohydride fuel cells

5 nm palladium nanoparticles (Pd NPs) are synthesized and assembled on reduced graphene oxide-iron oxide nanocomposite (rGO-Fe₃O₄) to be used in oxygen reduction reaction (ORR) and borohydride oxidation reaction (BOR) studies in alkaline media. The structure and morphology of the resulting Pd/rGO-Fe₃O₄ hybrid material are evaluated by X-ray diffraction (XRD), transmission electron microscopy (TEM), and energy dispersive X-ray spectroscopy (EDS) analyses. The electrochemical behavior of Pd/rGO-Fe₃O₄ hybrid material for the ORR and BOR is investigated by voltammetry with rotating disk and rotating ring disk electrode and electrochemical impedance spectroscopy, enabling evaluation of the number of exchanged electrons, Tafel slope, exchange current density and activation energy. The results reveal that ORR at Pd/rGO-Fe₃O₄ proceeds as a 2-electron process with Tafel slope of 0.133 V dec^?1, while BOR proceeds as a 5.6-electron process with Tafel slope of 0.350 V dec^?1 and exchange current density of 1.38 mA cm^?2. The BOR activation energy was found to be 12.4 kJ mol^?1. Overall, this study demonstrates the good efficiency of Pd/rGO-Fe₃O₄ hybrid material for BOR.     

Adding time dimension to relational model and extending relational algebra

A methodology for adding the time dimension to the relational model is proposed and relational algebra is extended for this purpose. We propose time-stamping attributes instead of adding time to tuples. Each attribute value is stored along with a time interval over which it is valid. Non-first normal form realations are used. A relation can have atomic, set-valued, triplet-valued, or set triplet-valued attributes. The last two types of attributes preserve the time (history). Furthermore, new algebraic operations are defined to extract information from historical relations. These operations convert one attribute type to another and do selection over the time dimension. Algebraic rules and identities for the new operations are also included.