Development of the epoxy composite complex permittivity and its application in wind turbine blades

PhDOffshore wind farm structures may have the potential to affect marine navigation and communication systems by reflecting radar signals. With ever increasing size of wind turbines it is necessary to better understand the influence of radar signals on wind turbine blades in order to minimise the radar reflecting potential. One possible way of reducing radar reflection is to use radar absorbing materials. In this thesis, epoxy composite materials reinforced with five different types of nano-size additives: carbon nanotubes (CNTs), carbon blacks (CBs), silver, tungsten carbide and titanium oxide are manufactured and tested to investigated their potential as wind turbine blade material that absorb radar signals. Nanoadditives/epoxy composites with additives content ranging from 0.05-1 wt. % were fabricated by a simple cast moulding process. The nanoadditives were dispersed in the epoxy resin by sonication method. The degree of nanoadditives dispersion was observed by examining the surface of the composite materials using scanning electron microscope (SEM). Complex permittivity of the nanoadditives/epoxy composites was studied using a free wave transmittance only method at a frequency range of 6.5-10.5 GHz. The effect of the percolation threshold of the direct current conductivity on the composite permittivity was analysed and discussion. In order to get a better insight in the importance of the results they were compared to existing models (Maxwell- Garnett, Bruggeman, Bottcher, Lichtenecker and Lichtenecker-Rother). A new model based rule of mixtures is developed to predict the complex permittivity of the composite. A model of wind turbine rotor blade made of the nanoadditives/epoxy composite was developed using Comsol-multiphysics software. The data obtained from the experimental work was inputted in to the model to generate result of backscattered energy verses composite permittivity as a function of nanoadditives content. A decrease in backscattered energy was noticed with increasing nanoadditives content. The results demonstrate that radar reflecting signals will be significantly reduced by incorporating nanoadditives in the composite materials

Deep fusion of multi-channel neurophysiological signal for emotion recognition and monitoring

How to fuse multi-channel neurophysiological signals for emotion recognition is emerging as a hot research topic in community of Computational Psychophysiology. Nevertheless, prior feature engineering based approaches require extracting various domain knowledge related features at a high time cost. Moreover, traditional fusion method cannot fully utilise correlation information between different channels and frequency components. In this paper, we design a hybrid deep learning model, in which the 'Convolutional Neural Network (CNN)' is utilised for extracting task-related features, as well as mining inter-channel and inter-frequency correlation, besides, the 'Recurrent Neural Network (RNN)' is concatenated for integrating contextual information from the frame cube sequence. Experiments are carried out in a trial-level emotion recognition task, on the DEAP benchmarking dataset. Experimental results demonstrate that the proposed framework outperforms the classical methods, with regard to both of the emotional dimensions of Valence and Arousal

The Transportation Mode Distribution of Multimodal Transportation in Automotive Logistics

AbstractCurrently, road transportation is still the main part of China's automotive logistics. Railway and waterway traffic are increasing in recent years, but are still small in the proportion of China's automotive logistics. Therefore, the automotive logistics of multimodal transportation and the distribution of the mode of transport are paid more and more attention. This paper focuses on the transport allocation problem of the commodity car. When the route and demand are fixed, considering the transportation cost, transportation time and the mode of transportation capacity constraints, establish a model to solve the road, railway and waterway transportation allocation problem. And design a genetic algorithm to solve the mode of transportation allocation problem to minimize the logistics cost. Finally, a case study is given to verify it

Safety and Airworthiness Design of Ultra-Light and Very Light Amphibious Aircrafts

AbstractUltra-light and very light amphibious aircrafts are the special kinds of low-speed general aircrafts. They are low weighted and small sized but can takeoff and land either on land or water without changing the structure of any parts. These characteristics result in the distinctive configuration and structure design, and meanwhile bring about significant features of safety and airworthiness design. These problems are investigated by developing the ultra-light amphibious aircraft “Frigate bird” and analyzing the other aircrafts’ design. This paper mainly discusses the preliminary design about structure, aerodynamics, power effect, flying qualities, dynamics and statics on water. Some analysis methodologies and design parameters which are different from the conventional general aircrafts’ are also represented

The effects of cognitive style and emotional trade-off difficulty on information processing in decision-making

This study investigated the effects of cognitive style and emotional trade‐off difficulty (ETOD) on information processing in decision‐making. Eighty undergraduates (73.75% female, M = 21.90), grouped according to their cognitive style (field‐dependent or field‐independent), conducted an Information Display Board (IDB) task, through which search time, search depth and search pattern were measured. Participants' emotional states were assessed both before and after the IDB task. The results showed that participants experienced significantly more negative emotion under high ETOD compared to those under low ETOD. While both cognitive style and ETOD had significant effects on search time and search depth, only ETOD significantly influenced search pattern; individuals in both cognitive style groups tended to use attribute‐based processing under high ETOD and to use alternative‐based processing under low ETOD. There was also a significant interaction between cognitive style and ETOD for search time and search depth. We propose that these results are best accounted for by the coping behaviour framework under high ETOD, and by the negative emotion hypothesis under low ETOD