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Yu Zhou

Bio: Yu Zhou is an academic researcher from Beihang University. The author has contributed to research in topics: Two-stroke engine & Engineering. The author has an hindex of 9, co-authored 22 publications receiving 211 citations. Previous affiliations of Yu Zhou include China Academy of Launch Vehicle Technology.

Papers
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Journal ArticleDOI
TL;DR: This paper breaks traditional procedures and presents a DT-based optimization strategy on the consideration of both machining efficiency and aerodynamic performance, as well as builds a reified 5-dimensional DT model.

51 citations

Journal ArticleDOI
TL;DR: In this paper, a temperature-constrained topology optimization for thermo-mechanical coupled problems under a design-dependent temperature field considering the thermal expansion effect remains an open problem.
Abstract: Temperature-constrained topology optimization for thermo-mechanical coupled problems under a design-dependent temperature field considering the thermal expansion effect remains an open problem. A t...

44 citations

Journal ArticleDOI
TL;DR: In this paper, the authors formulated a systematic design methodology to seek optimal parameters and geometric model of the Tesla turbine which is applied to a coolant waste heat recovery system of an automobile engine.

44 citations

Journal ArticleDOI
TL;DR: In this paper, experiments and numerical simulations are conducted to investigate the thermohydrodynamic (THD) performance of a turbocharger rotor-bearing system, and the results suggest that solid parts play a significant role in THD analysis, because the temperature fields of solid parts affect the oil film clearances by thermal expansion.

34 citations

Journal ArticleDOI
Fenzhu Ji1, Zhang Xiangbo1, Farong Du1, Shuiting Ding1, Yunhai Zhao1, Zheng Xu1, Yan Wang1, Yu Zhou1 
TL;DR: In this paper, a simulation model of a range-extended electric vehicle (REEV) based on vehicle dynamic is constructed to evaluate the contribution of MGTRE to REEV performance, especially for driving range based on the New European Driving Cycle.

32 citations


Cited by
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Journal ArticleDOI
TL;DR: This paper provides a comprehensive review of different types of EV range extending technologies, including internal combustion engines, free-piston linear generators, fuel cells, micro gas turbines, and zinc-air batteries, outlining their definitions, working mechanisms, and some recent developments of each range extending technology.
Abstract: Emissions from the transportation sector are significant contributors to climate change and health problems because of the common use of gasoline vehicles Countries in the world are attempting to transition away from gasoline vehicles and to electric vehicles (EVs), in order to reduce emissions However, there are several practical limitations with EVs, one of which is the “range anxiety” issue, due to the lack of charging infrastructure, the high cost of long-ranged EVs, and the limited range of affordable EVs One potential solution to the range anxiety problem is the use of range extenders, to extend the driving range of EVs while optimizing the costs and performance of the vehicles This paper provides a comprehensive review of different types of EV range extending technologies, including internal combustion engines, free-piston linear generators, fuel cells, micro gas turbines, and zinc-air batteries, outlining their definitions, working mechanisms, and some recent developments of each range extending technology A comparison between the different technologies, highlighting the advantages and disadvantages of each, is also presented to help address future research needs Since EVs will be a significant part of the automotive industry future, range extenders will be an important concept to be explored to provide a cost-effective, reliable, efficient, and dynamic solution to combat the range anxiety issue that consumers currently have

91 citations

Journal ArticleDOI
TL;DR: The hybridization of Reynolds-averaged Navier-Stokes (RANS) and large eddy simulation (LES) methods is seen to be the most promising way to efficiently deal with separated turbulent flow simulations relevant to aerospace and wind energy applications.

71 citations

Journal ArticleDOI
TL;DR: Key developments of BTT probes, signal preprocessing and vibration monitoring are reviewed comprehensively, and detailed prospects are discussed on future directions including but not limited to uncertainty calibration, deep compressed sensing, deep learning, fusion of B TT and blade tip clearance.

59 citations

Journal ArticleDOI
23 Sep 2021-Sensors
TL;DR: In this paper, a survey comprehensively reviews over 300 manuscripts on AI-driven DT technologies of Industry 4.0 used over the past five years and summarizes their general developments and the current state of AI-integration in the fields of smart manufacturing and advanced robotics.
Abstract: Digital twin (DT) and artificial intelligence (AI) technologies have grown rapidly in recent years and are considered by both academia and industry to be key enablers for Industry 4.0. As a digital replica of a physical entity, the basis of DT is the infrastructure and data, the core is the algorithm and model, and the application is the software and service. The grounding of DT and AI in industrial sectors is even more dependent on the systematic and in-depth integration of domain-specific expertise. This survey comprehensively reviews over 300 manuscripts on AI-driven DT technologies of Industry 4.0 used over the past five years and summarizes their general developments and the current state of AI-integration in the fields of smart manufacturing and advanced robotics. These cover conventional sophisticated metal machining and industrial automation as well as emerging techniques, such as 3D printing and human–robot interaction/cooperation. Furthermore, advantages of AI-driven DTs in the context of sustainable development are elaborated. Practical challenges and development prospects of AI-driven DTs are discussed with a respective focus on different levels. A route for AI-integration in multiscale/fidelity DTs with multiscale/fidelity data sources in Industry 4.0 is outlined.

54 citations

Journal ArticleDOI
TL;DR: This paper breaks traditional procedures and presents a DT-based optimization strategy on the consideration of both machining efficiency and aerodynamic performance, as well as builds a reified 5-dimensional DT model.

51 citations