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Experimental and Numerical Study on the Transient Flow Behavior in Gasoline Refueling System

Frontiers in Heat and Mass Transfer 2024年第1期22卷 107-127页

作者： Chenlin Zhu Yan Zhao Zhitao Jiang Jiafeng Xie Lifang Zeng Lijuan Qian Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province China Jiliang UniversityHangzhou310018China School of Aeronautics and Astronautics Zhejiang UniversityHangzhou310027China Ocean College Zhejiang UniversityZhoushan316021China

Efficient and secure refueling within the vehicle refueling systems exhibits a close correlation with the issues concerning fuel backflow and gasoline *** paper investigates the transient flow behavior in fuel hose refilling and simplified tank fuel replenishment using the volume of fluid *** numerical simulation is validated with the simplified hose refilling experiment and the evaporation simulation of Stefan *** effects of injection flow rate and injection directions have been discussed in the fuel hose refilling *** both the experiment and simulation,the pressure at the end of the refueling pipe in the lower located nozzle case is 30%higher than that in the upper located nozzle case at a high flow rate,and the backflow phenomenon occurs at the lower filling *** fluid will directly flush into the first pipe elbow,changing the flow pattern from bubble flow to slug flow,which results in low-frequency and high-amplitude flowpressure *** refueling system,consisting of a refueling pipe,fuel tank and a vapor return line,is analyzed,in which hexane evaporation is *** the early refueling period,a higher refueling rate will lead to more obvious splashing,which leads to a higher average mass of hexane vapor and pressure in the *** optimized fuel tank designs are *** lower fuel tank filling port exhibits significantly lower vapor hexane in the fuel tank compared to the other design,resulting in a reduction of 200 Pa in the peak pressure in the tank,which contributes to a substantial reduction of gasoline loss during tank filling.

关键词： Gas-liquid flow flow pattern gasoline evaporation optimized fuel tank

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Complementary Label Queries for Efficient Active Learning 23

Complementary Label Queries for Efficient Active Learning

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6th International Conference on Image and Graphics Processing, ICIGP 2023

作者： Liu, Shengyuan Hu, Tianlei Chen, Ke Mao, Yunqing Key Lab of Intelligent Computing Based Big Data of Zhejiang Province Zhejiang University China Co. Ltd. China

ISBN: (纸本)9781450398572

Many active learning methods are based on the assumption that a learner simply asks for the true labels of some training data from annotators. Unfortunately, it is expensive to exactly annotate instances in real-world classification tasks. To mitigate this problem, we propose a novel active learning setting, named active learning with complementary labels (ALCL). The ALCL learners only ask yes/no questions in some classes. After receiving answers from annotators, ALCL learners get a few supervised data and more training instances with complementary labels, which only specify one of the classes to which the pattern does not belong. There are two challenging issues in ALCL: the first is how to learn from these complementary labels, and another is how to sample instances to be queried. For the first issue, we propose a novel method that redistributes the weights of instances based on the balance of category contribution to learn from ordinary labels and complementary labels. For the second issue, we propose a weighting mechanism to improve existing uncertainty-based sampling strategies under this novel setup. Experiments on various datasets demonstrate the feasibility of ALCL and the superiority of our approaches. © 2023 ACM.

关键词： Image recognition

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Agent Planning with World Knowledge Model 38

Agent Planning with World Knowledge Model

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Qiao, Shuofei Fang, Runnan Zhang, Ningyu Zhu, Yuqi Chen, Xiang Deng, Shumin Jiang, Yong Xie, Pengjun Huang, Fei Chen, Huajun Zhejiang University China National University of Singapore NUS-NCS Joint Lab Singapore Alibaba Group China Zhejiang Key Laboratory of Big Data Intelligent Computing China

Recent endeavors towards directly using large language models (LLMs) as agent models to execute interactive planning tasks have shown commendable results. Despite their achievements, however, they still struggle with brainless trial-and-error in global planning and generating hallucinatory actions in local planning due to their poor understanding of the "real" physical world. Imitating humans' mental world knowledge model which provides global prior knowledge before the task and maintains local dynamic knowledge during the task, in this paper, we introduce parametric World Knowledge Model (WKM) to facilitate agent planning. Concretely, we steer the agent model to self-synthesize knowledge from both expert and sampled trajectories. Then we develop WKM, providing prior task knowledge to guide the global planning and dynamic state knowledge to assist the local planning. Experimental results on three complex real-world simulated datasets with three state-of-the-art open-source LLMs, Mistral-7B, Gemma-7B, and Llama-3-8B, demonstrate that our method can achieve superior performance compared to various strong baselines. Other interesting findings include: 1) our instance-level task knowledge can generalize better to unseen tasks, 2) weak WKM can guide strong agent model planning, and 3) unified WKM training has promising potential for further development. © 2024 Neural information processing systems foundation. All rights reserved.

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Predictive control for greenhouse temperature and humidity and energy optimization by improved NMPC objective function algorithm

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International Journal of Agricultural and Biological Engineering 2024年第5期17卷 128-136页

作者： Lina Wang Ying Zhang Mengjie Xu Qiuhui Liu Binrui Wang Institute of Mechanical and Electrical Engineering China Jiliang UniversityHangzhou 310018China Zhejiang Province Key Laboratory of On-line Testing Equipment Calibration Technology Research China Jiliang UniversityHangzhou 310018China Zhejiang Provincial Key Laboratory of Intelligent Manufacturing Quality Big Data Traceability and Application China Jiliang UniversityHangzhou 310018China

Persistent low temperatures in autumn and winter have a huge impact on crops,and greenhouses rely on solar radiation and heating equipment to meet the required indoor *** the energy cost of frequent operation of the actuators is exceptionally *** relationship between greenhouse environmental control accuracy and energy consumption is one of the key issues faced in greenhouse *** this study,a non-linear model predictive control method with an improved objective function was *** improved objective function used tolerance intervals and boundary constraints to optimize the objective *** nonlinear model predictive control(NMPC)controller design was based on the wavelet neural network(WNN)data-driven model and applied the interior point method to solve the optimal solution of the objective function control,thus balancing the contradiction between energy consumption and control *** simulation results showed that the improved NMPC method reduced energy consumption by 21.02%and 9.54%compared with the model predictive control and regular NMPC,which proved the method achieved good results in a low-temperature *** research can provide an important reference for the field as it offers a more efficient approach to managing greenhouse climates,potentially leading to substantial energy savings and enhanced sustainability in agricultural practices.

关键词： greenhouse environmental control greenhouse energy optimization nonlinear model predictive control objective function improvement

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A Digital Twin-based Framework of Motion Control and State Monitoring for Pneumatic Muscle

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Recent Patents on Mechanical Engineering 2023年第3期16卷 203-213页

作者： Xie, Shenglong Liu, Wenyuan Duan, Huiru Chen, Dijian Wan, Yanjian Key Laboratory of Intelligent Manufacturing Quality Big Data Tracking and Analysis of Zhejiang Province China Ji-liang University Zhejiang Hangzhou310018 China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Anhui University of Technology Anhui Ma'anshan243032 China

Introduction: The current digital twin systems usually have the drawback of high cost and complex technology, and it is necessary to develop a simple solution to reduce the cost and cycle for the development of digital twin systems, especially for small projects or systems with simple structures. Objective: A low-cost patent technology of digital twin system was proposed by taking the motion control and state monitoring system (MCSMS) of pneumatic muscle as an example. Methods: The MCSMS is developed based on the browser/server architecture. The software of 3ds Max and SolidWorks are used to make the virtual model, *** and JavaScript are applied to build the browser side. data of the physical world is collected and processed on the server side firstly, and then is sent to the browser side through HTTP communication protocol to realize data interchange between the browser and server. Results: In the roaming experiment and the experiment of motion control and state monitoring of pneumatic muscle, the MCSMS can work smoothly without obvious delay and has good real-time performance, which can realize the 3D visual monitoring of the pneumatic muscle very well. Conclusion: The experimental results indicate that the proposed method possesses the ability of good feasibility and effectiveness. © 2023 Bentham Science Publishers.

关键词： Muscle

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Comparison of 2-acetylfuran,2-ethylfuran,and 2-methylfuran spherically expanding flame intrinsic instabilities

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Science China(Technological Sciences) 2022年第10期65卷 2388-2398页

作者： XU CangSu WANG QianWen LI XiaoLu OPPONG Francis LIU WeiNan College of Energy Engineering State Key Laboratory of Clean Energy UtilizationZhejiang UniversityHangzhou 310027China College of Mechanical and Electrical Engineering Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang ProvinceChina Jiliang UniversityHangzhou 310018China

The intrinsic instability of three furan derivatives, namely, 2-acetylfuran(AF), 2-ethylfuran(EF), and 2-methylfuran(MF), is experimentally and theoretically investigated and compared. A deep-learning-based end-to-end system is used to segment the cells and measure the crack length on the cellular flame front of the spherically expanding flame to quantitively investigate the flame morphology. Moreover, the flame front radius profile is quantitively investigated to shed light on the correlation between disturbance amplitude and flame radius. With the use of the linear stability model, the theoretical critical flame radius and Peclet number are obtained and compared to their corresponding experimental results to characterize the outset of cellularization and evaluate the flame instability propensity. Our analysis shows that compared with AF and EF, MF is prone to cellularization at a smaller flame radius and has a faster cell proliferation rate and crack length growth rate before reaching the hydrodynamic saturation limit. Meanwhile, the average area of saturated cells tends to be similar for the three furan derivatives. Furthermore,AF premixed flame does not exhibit cellularization before the flame radius is less than 45 mm in low initial pressure.

关键词： furan derivatives spherical expanding flame flame intrinsic instability linear stability theory

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Research on Frequency of Radial Vibration of Elastic Thin Spherical Shell

Research on Frequency of Radial Vibration of Elastic Thin Sp...

引用

2023 International Congress on Ultrasonics, ICU Beijing 2023

作者： Haidao, Zhang Long, Xu Fengming, Li College of Science China Jiliang University Zhejiang Hangzhou310018 China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province China Jiliang University Hangzhou310018 China

The ultrasonic frequency radial vibration of an elastic thin spherical shell composed of isotropic materials is studied, the frequency equation of its vibration is deduced, and the equivalent circuit is obtained. The finite element software COMSOL is used to verify the obtained analytical theory, and the calculated results are basically consistent with the theoretical calculated values. The relevant conclusions provide references for the application of spherical shell structure in related fields. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Shells (structures)

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Deep Generative Modeling in Constraint Discovery and Anomaly Detection

SSRN

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SSRN 2024年

作者： Hu, Wentao Jiang, Dawei Wu, Sai Chen, Ke Chen, Gang Zhejiang Police College Hangzhou China The Key Laboratory of Big Data Intelligent Computing of Zhejiang Province Zhejiang University China

Experts in fraud detection and data security commonly encounter hurdles in the automatic extraction of constraints from relational databases, a vital step for the identification of anomalous data. The aim is to unearth intrinsic database constraints, so that any tuple infringements can be marked as anomalies. The crux of IceBerg is the KD-VAE, an innovative generative network. By integrating \underline{K}ernel \underline{D}ensity estimation with \underline{V}ariational \underline{A}uto\underline{E}ncoder, KD-VAE addresses the challenge of capturing complex data distributions, a critical aspect for effective anomaly detection. KD-VAE synergizes Kernel Density estimation with Variational Autoencoders, effectively addressing the intricacies of modeling complex data distributions, which is essential for proficient anomaly detection. The distinct combination of kernel density estimation with variational autoencoders in KD-VAE markedly improves the modeling of normal tuple distributions, thus facilitating enhanced anomaly detection. Anomalous data are pinpointed by evaluating the congruence of a tuple with the normal distributions, and anomalies are interpreted by contrasting detected aberrations against their normal analogs. Principal improvements encompass methodological refinements for generating interpretable rules, the addition of Jaccard and NMI to the evaluation metrics, and extensive empirical analyses over 13 real-world datasets. Furthermore, comparative analyses of temporal performance and visualizations for rule interpretation are introduced, yielding deeper insights into anomaly detection, and significantly surpassing our prior work's benchmarks. These progressions confirm IceBerg's exceptional capacity for modeling intricate, high-dimensional data distributions, establishing it as a formidable asset in the analysis of large-scale datasets. © 2024, The Authors. All rights reserved.

关键词： Anomaly detection

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GoPIM: GCN-Oriented Pipeline Optimization for PIM Accelerators 31

GoPIM: GCN-Oriented Pipeline Optimization for PIM Accelerato...

引用

31st IEEE International Symposium on High Performance Computer Architecture, HPCA 2025

作者： Yang, Siling He, Shuibing Wang, Wenjiong Yin, Yanlong Wu, Tong Chen, Weijian Zhang, Xuechen Sun, Xian-He Feng, Dan The State Key Laboratory of Blockchain and Data Security Zhejiang University China Zhejiang Lab China Institute of Blockchain and Data Security China Zhejiang Key Laboratory of Big Data Intelligent Computing China Washington State University Vancouver United States Illinois Institute of Technology United States Huazhong University of Science and Technology China Wuhan National Laboratory for Optoelectronics China

ISBN: (纸本)9798331506476

Graph convolutional networks (GCNs) are popular for a variety of graph learning tasks. ReRAM-based processing-in-memory (PIM) accelerators are promising to expedite GCN training owing to their in-situ computing capability. However, existing accelerators can be severely underutilized even with pipelines, due to the oversight of the skewed execution times of various GCN stages and the ignorance of skewed degrees of graph vertices. In this work, we propose GOPIM, a GCN-oriented pipeline optimization for PIM accelerators to expedite GCN training. First, GOPIM proposes an ML-based scheme that allocates crossbar resources to the most needed stages to streamline the overall pipeline. Second, GOPIM utilizes a selective vertex updating technique that evenly distributes vertices on crossbars by interleaved mapping. These techniques collectively reduce the overall execution time without losing much accuracy. We also provide a practical architecture design for GOPIM. Our experimental results show that, GoPIM achieves up to 191 × speedup and 16.1 × energy saving, compared to the state-of-the-art work. © 2025 IEEE.

关键词： Graph neural networks

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An ε-domination based two-archive 2 algorithm for many-objective optimization

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Journal of Systems Engineering and Electronics 2022年第1期33卷 156-169页

作者： WU Tianwei AN Siguang HAN Jianqiang SHENTU Nanying College of Mechanical and Electrical Engineering China Jiliang UniversityHangzhou 310018China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province China Jilang UniversityHangzhou 310018China

The two-archive 2 algorithm(Two_Arch2) is a manyobjective evolutionary algorithm for balancing the convergence,diversity,and complexity using diversity archive(DA) and convergence archive(CA).However,the individuals in DA are selected based on the traditional Pareto dominance which decreases the selection pressure in the high-dimensional *** traditional algorithm even cannot converge due to the weak selection ***,Two_Arch2 adopts DA as the output of the algorithm which is hard to maintain diversity and coverage of the final solutions synchronously and increase the complexity of the *** increase the evolutionary pressure of the algorithm and improve distribution and convergence of the final solutions,an ε-domination based Two_Arch2 algorithm(ε-Two_Arch2) for many-objective problems(MaOPs) is proposed in this *** ε-Two_Arch2,to decrease the computational complexity and speed up the convergence,a novel evolutionary framework with a fast update strategy is proposed;to increase the selection pressure,ε-domination is assigned to update the individuals in DA;to guarantee the uniform distribution of the solution,a boundary protection strategy based on I_(ε+) indicator is designated as two steps selection strategies to update individuals in *** evaluate the performance of the proposed algorithm,a series of benchmark functions with different numbers of objectives is *** results demonstrate that the proposed method is competitive with the state-of-the-art multi-objective evolutionary algorithms and the efficiency of the algorithm is significantly improved compared with Two_Arch2.

关键词： many-objective optimization ε-domination boundary protection strategy two-archive algorithm

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