孔辰 - 哈尔滨工业大学 - 能源科学与工程学院

个人简介

孔辰，男，中共党员，工学博士，1995年5月1日生（劳动节），山东省曲阜市人（马上成为黑龙江省哈尔滨市人）。教育工作经历 2023.08-至今哈尔滨工业大学能源学院讲师 2017.09-2023.06 哈尔滨工业大学动力工程及工程热物理工学博士 2013.09-2017.07 哈尔滨工程大学动力工程及工程热物理工学学士荣誉奖项 2023年，第十六届吴仲华优秀研究生奖 2023年，哈尔滨工业大学优秀博士学位论文 2023年，哈尔滨工业大学优秀博士毕业生 2022年，哈尔滨工业大学优秀学生奖 2021年，第四届中国空天推进技术论坛优秀论文一等奖 2020年，先进动力所“最有魅力师兄奖” 2019年，先进动力所“最佳组织奖”

研究领域

高超声速推进流场感知

近期论文

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Research on mixing characteristics of scramjet combustor equipped with strut injector Development and evolution mechanism of streamwise vortex in an inward-turning inlet A deep learning approach for velocity field prediction in a scramjet isolator from Schlieren images Hysteresis behavior of shock train driven by continuous incoming Mach number variation in an isolator with background waves Experimental investigation of micro-ramp control for shock train under various incoming flow conditions A Bayesian data assimilation method to enhance the time sequence prediction ability of data-driven models Mechanism of shock-train/boundary-layer interaction in spanwise concave isolator channels Research on flame prediction in a scramjet combustor using data-driven model Prediction model of temperature field in dual-mode combustors based on wall pressure Research on time sequence prediction of the flow field structure of supersonic cascade channels in wide range based on artificial neural network Efficient Prediction of Supersonic Flowfield in an Isolator Based on Pressure Sequence Recent progress of machine learning in flow modeling and active flow control Micro-Ramp Control for Shock Train Structure and Oscillation Data-driven super-resolution reconstruction of supersonic flow field by convolutional neural networks An efficient deep learning framework to reconstruct the flow field sequences of the supersonic cascade channel Prediction model of flow field in an isolator over various operating conditions A deep learning approach for the velocity field prediction in a scramjet isolator Investigation of shock wave control by suction in a supersonic cascade Deep learning methods for super-resolution reconstruction of temperature fields in a supersonic combustor Experimental study on the forced oscillation of shock train in an isolator with background waves Experimental study and analysis of shock train self-excited oscillation in an isolator with background waves带有背景波系的隔离段内激波串自激振荡的实验研究与分析 Flowfield Reconstruction and Shock Train Leading Edge Detection in Scramjet Isolators Flow field reconstruction and prediction of the supersonic cascade channel based on a symmetry neural network under complex and variable conditions Flame oscillation characteristics in a kerosene fueled dual mode combustor equipped with thin strut flameholder