19 research outputs found

    Screw Analysis, Modeling and Experiment on the Mechanics of Tibia Orthopedic with the Ilizarov External Fixator

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    The Ilizarov external fixator plays an important role in the correction of complex malformed limbs. Our purpose in this work was to reveal the transmission of adjustable forces between the external fixator and the broken bone, and express the stress distribution at the end of the broken bone during the orthopedic treatment. Firstly, the screw model of the fixator was established and the theoretical relationship between the adjustable force and the stress was obtained. A sheep tibia was taken as a representative research object and its ediTable 3D entity was obtained by CT scanning. Then the mechanical model of the fixator and tibia was built using the ABAQUS software. Correction experiments were performed on the sheep tibia to measure the adjustable/support forces and tensions of the tibia. The measured results were imported to the screw and mechanical model, and the theoretical and simulation values were calculated. The theoretical tensions calculated by the screw model had a similar shape and doubled the value compared with that of the measured results. The transfer efficiency between the two results was improved and kept at about 50% after the initial 2~3 periods. The maximum stress occurring at the surface of the broken bone end was near the Kirschner wire pinhole. The simulation results for the tensions from the mechanical model showed a similar change trend, and the value was slightly higher. A biomechanical model of the Ilizarov external fixator was derived and verified through calculations, simulations and experiments. The change law of the adjustable forces and the tensions existing in the broken sheep tibias is presented herein, and offers a helpful contribution to orthopedic treatment

    Adaptive Voltage Reference Based Controls of Converter Power Sharing and Pilot Voltage in HVDC System for Large-Scale Offshore Wind Integration

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    Active power sharing and voltage regulation are two of the major control challenges in the operation of the voltage source converter based multi-terminal high-voltage DC (VSC-MTDC) system when integrating large-scale offshore wind farms (OWFs). This paper proposes two novel adaptive voltage reference based droop control methods to regulate pilot DC voltage and share the power burden autonomously. The proposed Method I utilizes DC grid lossy model with the local voltage droop control strategy, while the proposed Method II adopts a modified pilot voltage droop control (MPVDC) to avoid the large errors caused by the DC grid lossless model. Dynamic simulations of a five-terminal MTDC grid are carried out using MATLAB/Simulink SimPowerSystems /Specialized Technology to verify the proposed autonomous control methods under various types of disturbance and contingency. In addition, comparative study is implemented to demonstrate the advantages of the proposed methods

    Multiple objective optimization based on particle swarm algorithm for MMC-MTDC system

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    Multi-terminal high voltage DC (MTDC) network is an effective technology to integrate large-scale offshore wind energy sources into conventional AC grids and improve the stability and flexibility of the power system. In this paper, firstly, an analytical model of a general applicable MTDC system integrated with several isolated AC grids is established. Then, an improved AC-DC power flow algorithm is used to eliminate the additional DC slack bus or droop bus iteration (SBI/DBI) step of the conventional AC-DC sequential power flow. A multi-objective optimal power flow (MOPF) algorithm is proposed to minimize two optimization targets, i.e., overall active power loss and generation costs of the system. To increase the degree of freedom, adaptive droop control is used in the proposed optimization algorithm in which the voltage references and droop coefficients of the modular multilevel converters (MMCs) are control variables. A multiple objective particle swarm optimization (MOPSO) method is applied to solve the MOPF problem and achieve the Pareto front. A technique for order of preference by similarity to ideal solution (TOPSIS) is incorporated in the decision analysis section and helps the decision maker to identify the best compromise solution.Published versionThis research is supported by the National Natural Science Foundation of China (51907026), Natural Science Foundation of Jiangsu Province, China (BK20190361), Key Research and Development Program of Jiangsu Province, China (BE2020081-2)
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