Current Issue : January - March Volume : 2019 Issue Number : 1 Articles : 5 Articles
Regarding the continuous development of high-speed trains and the increase of running speeds, the aerodynamic design of highspeed\ntrains has become significantly important, while reduction of drag and noise comprises a significant challenge in order to\noptimize aerodynamic design of high-speed trains. The design form factor of a high-speed train is highly influenced by\naerodynamic aspects including aerodynamic drag, lift force, and noise. With the high-speed train as the object, the paper aims\nto take bionic concept as the entry point, selecting the hummingbird as the bionic prototype and extracting bionic elements to\nestablish a bionic train model. Then, the finite volume method was used for numerical simulation and analysis of the\naerodynamic performance and aerodynamic noise of the bionic high-speed train. Computational results prove that drag and\nnoise of the bionic head type were lower than those of the original train; drag of the head train of the bionic model was reduced\nby 2.21% in comparison with the original model, while the whole-train drag was reduced by 3.53%, indicating that drag\nreduction effects are available and implying that the bionic head type could reduce drag and noise. Noise sources of the bionic\ntrain are mainly located at positions with easy airflow separation and violent turbulence motion. Large turbulence energy is in\nbogie areas and mainly exists at the leeward side of the bogie area. Obviously, the bogie area is the major noise source of the\ntrain. Aerodynamic noise of the bionic train in far-field comprises a wide-frequency range. Noises were concentrated within\n613 Hz~3150 Hz. When the bionic high-speed train ran at 350 km/h, through comparative analysis of total noise levels at\nobserved points of the high-speed train, it is found that this position with the maximum noise level was 25m away from the\nhead train nose tip, with the maximum value of 88.4 dB (A). When the bionic train ran at 600 km/h, the maximum sound\npressure level at the longitudinal point was 99.7 dB (A) and the average noise level was 96.6 dB (A). When the running speed\nincreased from 350 km/h to 600 km/h, the maximum noise level increased by 11.3 dB (A) and the average noise level increased\nby 11.6 dB (A). Computation results of aerodynamic noise at the point which is 7.5m away from the rail center show that the\nmaximum aerodynamic noise level existed at the first-end bogie of the head train, while the noise level was larger at the position\ncloser to the ground....
Carbon nanomaterials have gradually demonstrated their superiority for in-line process\nmonitoring of high-performance composites. To explore the advantages of structures, properties, as well\nas sensing mechanisms, three types of carbon nanomaterials-based fiber sensors, namely, carbon\nnanotube-coated fibers, reduced graphene oxide-coated fibers, and carbon fibers, were produced\nand used as key sensing elements embedded in fabrics for monitoring the manufacturing process of\nfiber-reinforced polymeric composites. Detailed microstructural characterizations were performed\nthrough SEM and Raman analyses. The resistance change of the smart fabric was monitored in\nthe real-time process of composite manufacturing. By systematically analyzing the piezoresistive\nperformance, a three-stage sensing behavior has been achieved for registering resin infiltration,\ngelation, cross-linking, and post-curing. In the first stage, the incorporation of resin expands\nthe packing structure of various sensing media and introduces different levels of increases in the\nresistance. In the second stage, the concomitant resin shrinkage dominates the resistance attenuation\nafter reaching the maximum level. In the last stage, the diminished shrinkage effect competes with the\ndisruption of the conducting network, resulting in continuous rising or depressing of the resistance....
Both cellulose nanofiber (CNF) and carbon nanotube (CNT) are nanoscale fibers that\nhave shown reinforcing effects in polymer composites. Itâ??s worth noting that CNF and CNT\ncould form a three-dimensional nano-network via mixing and vacuum filtration, which exhibit\nexcellent mechanical strength and electrical conductivity. In this study, the developed CNF/CNT\nfilm was applied as a nano-network template and immersed into polydimethylsiloxane (PDMS)\nsolutions. By controlling the immersed polydimethylsiloxane pre-polymer concentration,\nthe PDMS/CNF/CNT nanocomposite with various PDMS contents were fabricated after a curing\nprocess. Morphological images showed that the CNF/CNT nano-network was well-preserved inside\nthe PDMS, which resulted in significantly improved mechanical strength. While increasing the PDMS\ncontent (~71.3 wt %) gave rise to decreased tensile strength, the PDMS-30/CNF/CNT showed\na fracture strain of 7.5%, which was around seven fold higher than the rigid CNF/CNT and still\nkept a desirable strengthâ??Youngâ??s modulus and conductivity of 18.3 MPa, 805 MPa, and 0.8 S/cm,\nrespectively. Therefore, with the enhanced mechanical properties and the electrical conductivity,\nthe prepared PDMS/CNF/CNT composite films may offer promising and broad prospects in the\nfield of flexible devices....
We investigate the effect of various spherical nanoparticles in a polymer matrix on\ndispersion, chain dimensions and entanglements for ionic nanocomposites at dilute and high\nnanoparticle loading by means of molecular dynamics simulations. The nanoparticle dispersion can\nbe achieved in oligomer matrices due to the presence of electrostatic interactions. We show that the\noverall configuration of ionic oligomer chains, as characterized by their radii of gyration, can be\nperturbed at dilute nanoparticle loading by the presence of charged nanoparticles. In addition,\nthe nanoparticleâ??s diffusivity is reduced due to the electrostatic interactions, in comparison to\nconventional nanocomposites where the electrostatic interaction is absent. The charged nanoparticles\nare found to move by a hopping mechanism....
Recently, numerous musculoskeletal robots have been developed to realize the flexibility and dexterity analogous to human beings\nand animals. However, because the arrangement of many actuators is complex, the design of the control system for the robot is\ndifficult and challenging. We believe that control methods inspired by living things are important in the development of the\ncontrol systems for musculoskeletal robots. In this study, we propose a muscle coordination control method using attractor\nselection, a biologically inspired search method, for an antagonistic-driven musculoskeletal robot in which various muscles\n(monoarticular muscles and a polyarticular muscle) are arranged asymmetrically. First, muscle coordination control models for\nthe musculoskeletal robot are built using virtual antagonistic muscle structures with a virtually symmetric muscle arrangement.\nNext, the attractor selection is applied to the control model and subsequently applied to the previous control model without\nmuscle coordination to compare the control modelâ??s performance. Finally, position control experiments are conducted, and the\neffectiveness of the proposed muscle coordination control and the virtual antagonistic muscle structure is evaluated....
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