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Qian-Yong Chen

· Associate ProfessorVerified

University of Massachusetts Amherst · Mathematics and Statistics

Active 2001–2024

h-index13
Citations877
Papers4211 last 5y
Funding$117k
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About

Qian-Yong Chen is an Associate Professor in the Department of Mathematics and Statistics at the University of Massachusetts Amherst. He holds a Ph.D. from Brown University obtained in 2004, an M.S. from the Chinese Academy of Sciences in 1999, and a B.S. from the University of Science & Technology of China in 1996. His research interests encompass Numerical Analysis and Scientific Computing, focusing on the development and application of computational methods for complex mathematical problems. His work includes contributions to the understanding of turbulence through coarse-graining techniques, the dynamics of solitary waves and vortices in the Gross-Pitaevskii equation, and modeling of traffic flow and speed-density relationships. Dr. Chen has also engaged in the analysis of nonlinear Schrödinger equations under random nonlinearity management, uncertainty analysis in steady-state flows, and spectral methods for hyperbolic PDEs. He is involved in interdisciplinary research and contributes to advancing computational mathematics through his scholarly publications.

Research topics

  • Computer Science
  • Mathematics
  • Algorithm
  • Engineering
  • Mechanical engineering
  • Electronic engineering
  • Mathematical optimization
  • Structural engineering
  • Classical mechanics
  • Geometry
  • Computer graphics (images)
  • Statistics
  • Physics
  • Materials science
  • Electrical engineering
  • Composite material

Selected publications

  • A Multi-Scale Target Detection Method Using an Improved Faster Region Convolutional Neural Network Based on Enhanced Backbone and Optimized Mechanisms

    Journal of Imaging · 2024-08-13 · 6 citations

    articleOpen access1st author

    Currently, existing deep learning methods exhibit many limitations in multi-target detection, such as low accuracy and high rates of false detection and missed detections. This paper proposes an improved Faster R-CNN algorithm, aiming to enhance the algorithm's capability in detecting multi-scale targets. This algorithm has three improvements based on Faster R-CNN. Firstly, the new algorithm uses the ResNet101 network for feature extraction of the detection image, which achieves stronger feature extraction capabilities. Secondly, the new algorithm integrates Online Hard Example Mining (OHEM), Soft non-maximum suppression (Soft-NMS), and Distance Intersection Over Union (DIOU) modules, which improves the positive and negative sample imbalance and the problem of small targets being easily missed during model training. Finally, the Region Proposal Network (RPN) is simplified to achieve a faster detection speed and a lower miss rate. The multi-scale training (MST) strategy is also used to train the improved Faster R-CNN to achieve a balance between detection accuracy and efficiency. Compared to the other detection models, the improved Faster R-CNN demonstrates significant advantages in terms of mAP@0.5, F1-score, and Log average miss rate (LAMR). The model proposed in this paper provides valuable insights and inspiration for many fields, such as smart agriculture, medical diagnosis, and face recognition.

  • Deformation Evolution and Perceptual Prediction for Additive Manufacturing of Lightweight Composite Driven by Hybrid Digital Twins

    Chinese Journal of Mechanical Engineering · 2024-10-22 · 3 citations

    articleOpen access

    Abstract This paper proposes a deformation evolution and perceptual prediction methodology for additive manufacturing of lightweight composite driven by hybrid digital twins (HDT). In order to improve manufacturing quality of irregular lightweight composite through boosting conceptual design in aeronautic and aerospace engineering, the HDT meaning hybridization of physical and digital domains, including deformation and energy efficiency can be built, where the essential parameters can be perceptually predicted in advance, by virtue of the fusion of physical sensors and digital information. The long short term memory (LSTM) can be employed to void vanishing gradient problem and improve predicting precision via Recurrent Neural Networks, thereby laying a foundation for the HDT. The diverse manufacturing requirements of different regions are integrated into the parameters designing phase by attaching region weights confirmed via empiricism and in-service simulation. The effects of slicing strategy and external support structures on manufacturing quality are considered from the perspective of improving dimensional accuracy. The manufacturing efficiency and comprehensive costs are accounted as consideration factors, which are perceptually predicted via LSTM. The designed manufacturing parameters through HDT were virtually examined by evaluating the deformation and equivalent stress distributions of fabricated lightweight component with composite material through AM process simulation. The physical experiments were conducted to verify the HDT-based pre-designing and optimization method of manufacturing parameters via fused deposition modeling (FDM). The energy consumption of actual manufacturing process was measured via digital power meter and applied to evaluate accuracy of perceptual prediction outcomes. The dimensional accuracy and distortion distribution of the manufactured lightweight prototype made with composite material were measured through the coordinate measuring machine (CMM) and 3D optical scanner. The proposed method demonstrates effectiveness in improving manufacturing quality and accurately predicting energy consumption, which have been verified with a three-way solenoid valve element, in which the maximum deformation was reduced by 39.78% and the mean absolute percentage error for perceptual prediction was 3.76%.

  • Electrical endurance design of multi-operation isolators using semi-physical simulation via algebraic multigrid iteration

    Electrical Engineering · 2023-07-11

    article
  • [Exploration of relationship between postoperative serum caveolin-1 contents and delayed healing of tibial fracture patients].

    PubMed · 2022-06-25

    articleSenior author

    OBJECTIVE: To explore relationship between postoperative serum caveolin-1 contents after open reduction and internal fixation and delayed healing of tibial fracture patients. METHODS: From April 2018 to June 2020, 134 tibial fracture patients underwent open reduction and internal fixation were included, and divided into delayed healing group and normal healing group according to fracture healing condition. Contents of serum caveolin-1 protein before operation, 1, 4, 8, 12 weeks after operation between two groups were compared. Influencing factors of delayed healing was analyzed by Logistic regression model, and predictive value of serum caveolin-1 protein on delayed healing was analyzed by receiver operating characteristic(ROC) curve. RESULTS: <0.05). CONCLUSION: Decrease of serum caveolin-1 protein content at 4 and 8 weeks after open reduction and internal fixation for tibia fracture patients were related with delayed healing. Detection of serum caveolin-1 protein content at 4 and 8 weeks after operation has predictive value for delayed healing.

  • Cylindricity and flatness optimization for mechanical parts in additive manufacturing based on tolerance adaptive slicing

    The International Journal of Advanced Manufacturing Technology · 2021 · 21 citations

    1st authorCorresponding
    • Computer Science
    • Computer Science
    • Algorithm
  • Double Row Absorbable Anchor Bridge Suture Versus Hollow Nails for Treating Acute Posterior Cruciate Ligament Avulsion Fracture

    Research Square · 2021-09-28

    preprintOpen accessSenior author

    Abstract Objective To compare the outcomes of open reduction through double row absorbable anchor bridge suture with hollow nails for acute posterior cruciate ligament (PCL) avulsion fracture. Methods From May 2015 to May 2019, 35 patients with acute PCL avulsion fractures were treated by open reduction through double row absorbable anchor bridge suture or hollow nails. There were 15 cases in double row absorbable anchor group and 20 cases in hollow nails group. The operation time, incision length, postoperative ambulation time, hospitalization expenses, healing time of fracture and Lysholm score of patients at the last follow-up were compared between the two groups. Result All the patients in both group had operation perfromed smoothly without serious complication. The operation time in double row absorbable anchor group was (77.33±9.88) min which was longer compared to (59.75±7.86) min in the hollow nails group (p<0.05). The hospitalization expenses indouble row absorbable anchor group was (28132±2096)yuan which was higher compared to (15904±1113) yuan in the hollow nails group (p<0.05).The postoperative ambulation time in double row absorbable anchor group was (2.07±0.70) d which was shorter compared to (3.80±1.64) d in the hollow nails group (p<0.05). There were no significant difference between the two groups in incision length, healing time of fracture and Lysholm score of patients at the last follow-up (p>0.05). Conclusion Both open reduction through double row absorbable anchor bridge suture and hollow nails for acute PCL avulsion fracture have good clinical result. Double row absorbable anchor bridge suture had advantage of reliable fixation and shorter postoperative ambulation time incision length, however, hollow nails fixation had advantages of less operation time and lower hospitalization expenses.

  • Volumetric adaptive slicing of manifold mesh for rapid prototyping based on relative volume error

    Rapid Prototyping Journal · 2021 · 7 citations

    1st authorCorresponding
    • Computer Science
    • Computer Science
    • Materials science

    Purpose Compared with cusp height and area deviation ratio, volume error (VE) caused by the layer height could represent the stair-case effect more comprehensively. The proposed relative volume error (RVE)-based adaptive slicing method takes VE rather than cusp height as slicing criteria, which can improve part surface quality for functionalized additive manufacturing. Design/methodology/approach This paper proposes a volumetric adaptive slicing method of manifold mesh for rapid prototyping based on RVE. The pre-height sequences of manifold mesh are first preset to reduce the SE by dividing the whole layer sequence into several parts. A breadth-first search-based algorithm has been developed to generate a solid voxelization to get VE. A new parameter RVE is proposed to evaluate the VE caused by the sequence of the layer positions. The RVE slicing is conducted by iteratively adjusting the layer height sequences under different constraint conditions. Findings Three manifold models are used to verify the proposed method. Compared with uniform slicing with 0.2 mm layer height, cusp height-based method and area deviation-based method, the standard deviations of RVE of all three models are improved under the proposed method. The surface roughness measured by the confocal laser scanning microscope proves that the proposed RVE method can greatly improve part surface quality by minimizing RVE. Originality/value This paper proposes an RVE-based method to balance the surface quality and print time. RVE could be calculated by voxelized parts with required accuracy at a very fast speed by parallel.

  • Exergy efficiency design for multi-stream plate-fin heat exchangers based on entropy generation assessment

    International Journal of Exergy · 2021-01-01

    articleSenior author

    The fundamental concepts of energy, entropy and exergy are progressively introduced for deepening. Furthermore, the state corresponding to the designated exergy is creatively defined as the referential assessment benchmark so as to asymptotically reckon the optimal rigorous operation decisions. Inspired by bionics design, the different types of lateral perforated fins and wavy fins are designed for various application scenarios. The temperature, T-Q diagram, entropy generation, dimensionless entropy generation, exergy loss and exergy efficiency within either stream or system hierarchy are observed to evaluate the adjustable design portfolio, for trade-off between benefits and costs. The proposed entropy generation assessment (EGA) is verified by physical experiment under different Reynolds number. The results prove that, the net cost of multi-stream plate-fin heat exchangers (MPFHE) is reduced from 20,813 $/kW to 19,072 $/kW after using EGA by −8.36%, while maintaining exergy efficiency. Therefore, EGA herein has important perspicacity for energy availability utilisation and operating economical assessment among heat exchange fields.

  • Exergy efficiency design for multi-stream plate-fin heat exchangers based on entropy generation assessment

    International Journal of Exergy · 2021-01-01

    article

    The fundamental concepts of energy, entropy and exergy are progressively introduced for deepening. Furthermore, the state corresponding to the designated exergy is creatively defined as the referential assessment benchmark so as to asymptotically reckon the optimal rigorous operation decisions. Inspired by bionics design, the different types of lateral perforated fins and wavy fins are designed for various application scenarios. The temperature, T-Q diagram, entropy generation, dimensionless entropy generation, exergy loss and exergy efficiency within either stream or system hierarchy are observed to evaluate the adjustable design portfolio, for trade-off between benefits and costs. The proposed entropy generation assessment (EGA) is verified by physical experiment under different Reynolds number. The results prove that, the net cost of multi-stream plate-fin heat exchangers (MPFHE) is reduced from 20,813 $/kW to 19,072 $/kW after using EGA by −8.36%, while maintaining exergy efficiency. Therefore, EGA herein has important perspicacity for energy availability utilisation and operating economical assessment among heat exchange fields.

  • Electrical Performance Design for Circuit Breakers Based on Multi-domain Sequential Coupling

    Journal of The Institution of Engineers (India) Series B · 2020 · 1 citations

    • Computer Science
    • Computer Science
    • Mathematics

Recent grants

Frequent coauthors

  • Shuyou Zhang

    11 shared
  • Jinghua Xu

    Zhejiang University

    11 shared
  • Daiheng Ni

    11 shared
  • Haizhong Wang

    Sun Yat-sen University

    8 shared
  • Mingyu Gao

    Chinese Academy of Sciences

    6 shared
  • Boris A. Malomed

    6 shared
  • Jianrong Tan

    6 shared
  • P. G. Kevrekidis

    5 shared

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