Investigation on milling force of thin-walled workpiece considering dynamic characteristics of workpiece

Yichao Dun,Lida Zhu,Shuhao Wang 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.9

The idea of integral calculus is used in traditional milling force prediction methods. In the traditional method, the milling cutter is divided into many micro-elements, the force of each micro-element is calculated, and then the integral summation process is applied to all the micro-elements. In traditional milling force prediction methods, both the workpiece and the tool are assumed to be rigid bodies. In this paper, the method is improved; the Fourier series expansion is used to approximate the periodic milling force and the workpiece is considered as a single degree of freedom spring-damping-vibration system. Through the forced vibration model of periodic force, the vibration displacement of the workpiece is obtained. Then, the radial cutting depth is corrected by the vibration displacement of the workpiece. Finally, the original milling force is corrected with the corrected radial cutting depth. The milling force prediction model based on thin-walled workpiece is obtained through the above process. The model is named as variable-radial-cutting-depth-algorithm (VRCDA). Finally, the accuracy of this model was verified through modal test and milling force acquisition experiments.

Yet another Hybrid Strategy for Auto-tuning SpMV on GPUs

Zhaohui Wang,Xiaojie Qiu,Aimin Zhang,Yichao Cheng,Yi Peng,Sun Sun 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.5

Sparse matrix-vector multiplication (SpMV) is a key linear algebra algorithm and is widely used in many application domains. Besides multi-core architecture, there is also extensive research focusing on accelerating SpMV on many-core Graphics Processing Units (GPUs). SpMV computations have many indirect and irregular memory accesses, and load imbalance could occur while mapping computations onto single-instruction, multiple-data (SIMD) GPUs. SpMV is highly memory bandwidth-bound, though GPUs have massive computational resources, the performance of SpMV on GPUs is still unsatisfying. In this paper, we present a new hybrid strategy for auto-tuning SpMV on GPUs. Our strategy combines the advantages of row-major storage and column-major storage. Like many other strategies, we reordered a given sparse matrix according to row lengths in decreasing order. In order to be more adaptive and efficient, we proposed a new hybrid Blocked CSR and JDS (BCJ) format based on original CSR and JDS. BCJ splits a sparse matrix into a denser part and a sparser part after reordering and uses different kernels to process the corresponding part. And we proposed corresponding auto-tuning framework to help transforming matrix and launching kernels according to the sparsity characteristics of the matrix. A CUDA implementation of BCJ outperforms the original formats significantly on a broad range of unstructured sparse matrices.

Adaptive Extraction Method for Phase Foreground Region in Laser Interferometry of Gear

Xian Wang,Yichao Zhao,Chaoyang Ju,Chaoyong Zhang 한국광학회 2023 Current Optics and Photonics Vol.7 No.4

Tooth surface shape error is an important parameter in gear accuracy evaluation. When tooth surface shape error is measured by laser interferometry, the gear interferogram is highly distorted and the gray level distribution is not uniform. Therefore, it is important for gear interferometry to extract the foreground region from the gear interference fringe image directly and accurately. This paper presents an approach for foreground extraction in gear interference images by leveraging the sinusoidal variation characteristics shown by the interference fringes. A gray level mask with an adaptive threshold is established to capture the relevant features, while a local variance evaluation function is employed to analyze the fluctuation state of the interference image and derive a repair mask. By combining these masks, the foreground region is directly extracted. Comparative evaluations using qualitative and quantitative assessment methods are performed to compare the proposed algorithm with both reference results and traditional approaches. The experimental findings reveal a remarkable degree of matching between the algorithm and the reference results. As a result, this method shows great potential for widespread application in the foreground extraction of gear interference images.

Prediction of flow boiling heat transfer coefficient in horizontal channels varying from conventional to small-diameter scales by genetic neural network

Jing Zhang,Yichao Ma,Mingjun Wang,Dalin Zhang,Suizheng Qiu,Wenxi Tian,Guanghui Su 한국원자력학회 2019 Nuclear Engineering and Technology Vol.51 No.8

Three-layer back propagation network (BPN) and genetic neural network (GNN) were developed in this study to predict the flow boiling heat transfer coefficient (HTC) in conventional and small-diameter channels. The GNN has higher precision than BPN (with root mean square errors of 17.16% and 20.50%, respectively) and other correlations. The inputs include vapor quality x, mass flux G, heat flux q, diameter D and physical parameter φ, and the predicted flow boiling HTC is set as the outputs. Influences of input parameters on the flow boiling HTC are discussed based on the trained GNN: nucleate boiling promoted by a larger saturated pressure, a larger heat flux and a smaller diameter is dominant in small channels; convective boiling improved by a larger mass flux and a larger vapor quality is more significant in conventional channels. The HTC increases with pressure both in conventional and small channels. The HTC in conventional channels rises when mass flux increases but remains almost unaffected in small channels. A larger heat flux leads to the HTC growth in small channels and an increase of HTC was observed in conventional channels at a higher vapor quality. HTC increases inversely with diameter before dry out.

Cointegration based modeling and anomaly detection approaches using monitoring data of a suspension bridge

Ziyuan Fan,Qiao Huang,Yuan Ren,Qiaowei Ye,Weijie Chang,Yichao Wang 국제구조공학회 2023 Smart Structures and Systems, An International Jou Vol.31 No.2

For long-span bridges with a structural health monitoring (SHM) system, environmental temperature-driven responses are proved to be a main component in measurements. However, anomalous structural behavior may be hidden incomplicated recorded data. In order to receive reliable assessment of structural performance, it is important to study therelationship between temperature and monitoring data. This paper presents an application of the cointegration based methodology to detect anomalies that may be masked by temperature effects and then forecast the temperature-induced deflection (TID) of long-span suspension bridges. Firstly, temperature effects on girder deflection are analyzed with fieldmeasured data of a suspension bridge. Subsequently, the cointegration testing procedure is conducted. A threshold-based anomaly detection framework that eliminates the influence of environmental temperature is also proposed. The cointegrated residual series is extracted as the index to monitor anomaly events in bridges. Then, wavelet separation method is used to obtain TIDs from recorded data. Combining cointegration theory with autoregressive moving average (ARMA) model, TIDs for longspan bridges are modeled and forecasted. Finally, in-situ measurements of Xihoumen Bridge are adopted as an example to demonstrate the effectiveness of the cointegration based approach. In conclusion, the proposed method is practical for actual structures which ensures the efficient management and maintenance based on monitoring data.

Spatiotemporal Expression Patterns and Antibody Reactivity of Taeniidae Endophilin B1

Ahn, Chun-Seob,Bae, Young-An,Kim, Seon-Hee,Kim, Jeong-Geun,Yu, Jae-Ran,Yang, Hyun-Jong,Eom, Keeseon S.,Wang, Hu,Kang, Insug,Yang, Yichao,Kong, Yoon American Society for Microbiology 2016 Journal of clinical microbiology Vol.54 No.10

<P>Larval Taeniidae, such as metacestodes of Taenia solium, Echinococcus granulosus, and Echinococcus multilocularis, produce chronic and fatal helminthic diseases. Proper identification of these zoonotic cestodiases is often challenging and is hampered in some clinical settings. Endophilin B1 plays critical roles in the maintenance of membrane contours and endocytosis. We isolated proteins homologous to endophilin B1 from T. solium, Taenia saginata, and Taenia asiatica. The three Taeniidae endophilin B1 proteins shared 92.9 to 96.6% sequence identity. They harbored a Bin1/amphiphysin/Rvs (BAR) domain and residues for a dimeric interface but lacked a SRC homology 3 (SH3) domain. Endophilin B1 showed a unique immunological profile and was abundantly expressed in the tegumental syncytium of Taeniidae metacestodes and adults. Bacterially expressed recombinant T. solium endophilin B1 (rTsMEndoB1) demonstrated a sensitivity of 79.7% (345/433 cases) for serodiagnosis of larval Taeniidae infections. The protein showed strong immune recognition patterns against sera from patients with chronic neurocysticercosis, cystic echinococcosis, or advanced-stage alveolar echinococcosis. Adult Taeniidae infections exhibited moderate degrees of positive antibody responses (65.7% [23/35 samples]). rTsMEndoB1 showed some cross-reactivity with sera from patients infected with Diphyllobothriidae (23.6% [25/106 samples]) but not with sera from patients with other parasitic diseases or normal controls. The specificity was 91.7% (256/301 samples). The positive and negative predictive values were 93.6% and 73.4%, respectively. Our results demonstrate that Taeniidae endophilin B1 may be involved in the control of membrane dynamics, thus contributing to shaping and maintaining the tegumental curvature. rTsMEndoB1 may be useful for large-scale screening, as well as for individual diagnosis and follow-up surveillance of Taeniidae infections.</P>