Based on the important applications of structural damping composites in aerospace and automobile areas, novel structural-damping composites reinforced by nitrile rubber coated 3-D braided carbon fibers (RCF 3D / epoxy) were successfully prepared through the vacuum assisted resin transfer molding process in this work. The damping property of the composites was experimentally investigated using cantilever beam vibration test and dynamic mechanical analysis. The results exhibit that the damping loss factor of the composites obtained from cantilever beam vibration test increases by 120%, reaching 0.068 after nitrile rubber coating modification. At the frequency of 1 Hz at room temperature, the loss factor of RCF 3D /epoxy is about five times as high as that of the original composites. Furthermore, the impact strength and transverse shear strength increase by 11 and 6.8%, respectively, although the flexural strength and modulus and the longitudinal shear strength decrease slightly. The product of elastic modulus and loss factor E*η as the maximum merit index reaches 2.17 GPa. The results mentioned above indicate that rubber coating modification proposed in this work is an effective way to optimize the damping property with a negligible influence on mechanical properties of the RCF 3D /epoxy, which will be a promising strategy for obtaining structural-damping composites. POLYM. COM-POS., 40:E599-E608, 2019. A novel structural-damping composites reinforced by nitrilerubber coated 3-D braided carbon fibers (RCF 3D /epoxy) were successfully prepared through RTM process. 2. Nitrile rubber coating on the fibers to absorb the vibrational energy is an effective method to improve the damping performance of the 3D braided composites. 3. The RCF 3D /EP composites showed the excellent compatibility of stiffness and damping of materials simultaneously.
Sit to stand is one of the essential physical tasks of normal daily function,it requires coordinated constructions of the muscle of the lower extremities and truck.Specifically,subjects with movement disorder have reported to experience difficulties in rising from a seated position.Based on the captured signals,the angle and angular velocity of the STS, this paper simulate the STS on SimMechanics and get a similar result with the force plate.
In the real-time decision-making and local planning process of autonomous vehicles in dynamic environments, the autonomous driving system may fail to find a reasonable policy or even gets trapped in some situation due to the complexity of global tasks and the incompatibility between upper level maneuver decisions with the lower level trajectory planning. To solve this problem, this paper presents a synchronous maneuver searching and trajectory planning (SMSTP) algorithm based on the topological concept of homotopy. Firstly, a set of alternative maneuvers with boundary limits are enumerated on a multilane road. Instead of sampling numerous paths in the whole spatio-temporal space, we, for the first time, propose using Trajectory Profiles (TPs) to quickly construct the topological maneuvers represented by different routes, and put forward a corridor generation algorithm based on graph-search. The bounded corridor further constrains the maneuver's space in the spatial space. A step-wise heuristic optimization algorithm is then proposed to synchronously generate a feasible trajectory for each maneuver. To achieve real-time performance, we initialize the states to be optimized with the boundary constraints of maneuvers, and we set some heuristic states as terminal targets in the quadratic cost function. The solution of a feasible trajectory is always guaranteed only if a specific maneuver is given. The simulation and realistic driving-test experiments verified that the proposed SMSTP algorithm has a short computation time which is less than 37ms, and the experimental results showed the validity and effectiveness of the SMSTP algorithm.
Dynamic adaptive video streaming over HTTP (DASH) is widely studied and has been adopted in modern video players to ensure user quality of experience (QoE). In DASH, adaptive bitrate control is a key part whose ultimate goal is to maximize video bitrate while minimizing rebuffering. Throughput prediction plays an important role in helping select the proper video bitrate dynamically. In this paper, we studied the influence of throughput prediction on adaptive video streaming. Because the real-world network is dynamic, different methods need to be tested with large-scale deployments and analyzed statistically. However, this is difficult in academic research. Therefore, we established a reproducible trace-based emulation environment, which enables us to compare different methods quantitatively under the artificially same condition, with limited experiments. The throughput prediction methods are implemented into DASH to evaluate the effect on QoE for video streaming. The results indicate that the prediction method using long short-term memory (LSTM) performs better than the other methods. However, throughput prediction alone is not enough to ensure high QoE. To further improve the QoE, we proposed the decision map method (DMM), where the buffer occupancy is also incorporated to make a selection. By using this decision map, the choice of bitrate can be smarter than that when only prediction information is used. The total QoE is further improved by 32.1% in the ferry trace, which shows the effectiveness of DMM in further improving the performance of throughput prediction in adaptive bitrate control.
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