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| 1 | Distributed Collaborative Response Surface Method for Mechanical Dynamic Assembly Reliability Design显示文摘Because of the randomness of many impact factors influencing the dynamic assembly relationship of complex machinery,the reliability analysis of dynamic assembly relationship needs to be accomplished considering the randomness from a probabilistic perspective.To improve the accuracy and efficiency of dynamic assembly relationship reliability analysis,the mechanical dynamic assembly reliability(MDAR)theory and a distributed collaborative response surface method(DCRSM)are proposed.The mathematic model of DCRSM is established based on the quadratic response surface function,and verified by the assembly relationship reliability analysis of aeroengine high pressure turbine(HPT)blade-tip radial running clearance(BTRRC).Through the comparison of the DCRSM,traditional response surface method(RSM)and Monte Carlo Method(MCM),the results show that the DCRSM is not able to accomplish the computational task which is impossible for the other methods when the number of simulation is more than 100 000times,but also the computational precision for the DCRSM is basically consistent with the MCM and improved by 0.40~4.63%to the RSM,furthermore,the computational efficiency of DCRSM is up to about 188 times of the MCM and 55 times of the RSM under10000 times simulations.The DCRSM is demonstrated to be a feasible and effective approach for markedly improving the computational efficiency and accuracy of MDAR analysis.Thus,the proposed research provides the promising theory and method for the MDAR design and optimization,and opens a novel research direction of probabilistic analysis for developing the high-performance and high-reliability of aeroengine. | BAI Guangchen FEI Chengwei | 2013 | Chinese Journal of Mechanical Engineering2013，26，6： | 23 |
| 2 | Function of Ca^(2+)-/calmodulin-dependent protein kinase Ⅳ in Ca^(2+)-stimulated neuronal signaling and behavior显示文摘The activity of Ca2+/calmodulin-dependent protein kinase IV(Ca MKIV) is sensitive to activity-dependent changes in the level of intracellular Ca2+.Following neuronal stimulation,the activation of Ca MKIV may trigger synaptic modifications and transcriptional responses,both of which are involved in regulating cognitive and emotional behavior.Here,we used Ca MKIV knockout(KO) neurons and mice to examine the function of Ca MKIV in Ca2+-stimulated intracellular signaling and animal behavior,respectively.Following NMDA receptor activation or membrane depolarization,the up-regulation of CREB(c AMP responsive element binding protein) and its target gene Bdnf(brain-derived neurotrophic factor) was intact in cortical neurons obtained from Ca MKIV KO mice.Ca MKIV KO mice displayed severe impairment in contextual fear memory but normal locomotor activity and anxiety level in the contextual training chamber.Although Ca MKIV KO mice showed normal memory in the standard passive avoidance task,they were defective in learning the temporal dissociative passive avoidance task.As indicated by the light/dark test and marble-burying test data,Ca MKIV KO mice showed less anxiety and normal perseveration.In the voluntary wheel-running test,Ca MKIV KO mice showed normal running time and distance but higher maximal running speed.Our results demonstrate the function of Ca MKIV in regulating different forms of fear memory,anxiety,and certain aspect of motor function. | SONG ZiXiang CHEN Qi DING Qi ZHENG Fei LI ChengWei XU LePing WANG HongBing | 2015 | Science China(Life Sciences)2015，58，1： | 6 |
| 3 | Advanced multiple response surface method of sensitivity analysis for turbine blisk reliability with multi-physics coupling显示文摘To reasonably implement the reliability analysis and describe the significance of influencing parameters for the multi-failure modes of turbine blisk, advanced multiple response surface method(AMRSM) was proposed for multi-failure mode sensitivity analysis for reliability. The mathematical model of AMRSM was established and the basic principle of multi-failure mode sensitivity analysis for reliability with AMRSM was given. The important parameters of turbine blisk failures are obtained by the multi-failure mode sensitivity analysis of turbine blisk. Through the reliability sensitivity analyses of multiple failure modes(deformation, stress and strain) with the proposed method considering fluid–thermal–solid interaction, it is shown that the comprehensive reliability of turbine blisk is 0.9931 when the allowable deformation, stress and strain are3.7*10^(-3)m, 1.0023*10~9 Pa and 1.05*10^(-2)m/m, respectively; the main impact factors of turbine blisk failure are gas velocity, gas temperature and rotational speed. As demonstrated in the comparison of methods(Monte Carlo(MC) method, traditional response surface method(RSM), multiple response surface method(MRSM) and AMRSM), the proposed AMRSM improves computational efficiency with acceptable computational accuracy. The efforts of this study provide the AMRSM with high precision and efficiency for multi-failure mode reliability analysis, and offer a useful insight for the reliability optimization design of multi-failure mode structure. | Zhang Chunyi Song Lukai Fei Chengwei Lu Cheng Xie Yongmei | 2016 | Chinese Journal of Aeronautics2016，29，4： | 4 |
| 4 | Whole-process design and experimental validation of landing gear lower drag stay with global/local linked driven optimization strategy显示文摘Landing gear lower drag stay is a key component which connects fuselage and landing gear and directly effects the safety and performance of aircraft takeoff and landing. To effectively design the lower drag stay and reduce the weight of landing gear, Global/local Linked Driven Optimization Strategy(GLDOS) was developed to conduct the overall process design of lower drag stay in respect of optimization thought. The whole-process optimization involves two stages of structural conceptual design and detailed design. In the structural conceptual design, the landing gear lower drag stay was globally topologically optimized by adopting multiple starting points algorithm. In the detailed design, the local size and shape of landing gear lower drag stay were globally optimized by the gradient optimization strategy. The GLDOS method adopts different optimization strategies for different optimization stages to acquire the optimum design effect. Through the experimental validation, the weight of the optimized lower dray stay with the developed GLDOS is reduced by 16.79% while keeping enough strength and stiffness, which satisfies the requirements of engineering design under the typical loading conditions. The proposed GLDOS is validated to be accurate and efficient in optimization scheme and design cycles. The efforts of this paper provide a whole-process optimization approach regarding different optimization technologies in different design phases, which is significant in reducing structural weight and enhance design tp wid 1 precision for complex structures in aircrafts. | Chengwei FEI Haotian LIU Zhengzheng ZHU Liqiang AN Shaolin LI Cheng LU | 2021 | Chinese Journal of Aeronautics2021，34，2： | 2 |
| 5 | Novel Kriging-Based Decomposed-Coordinated Approach for Estimating the Clearance Reliability of Assembled Structures显示文摘Turbine blisks are assembled using blades,disks and casings.They can endure complex loads at a high temperature,high pressure and high speed.The safe operation of assembled structures depends on the reliability of each component.Monte Carlo(MC)simulation is commonly used to analyze structural reliability,but this method needs to run thousands of computations.In order to assess the clearance reliability of assembled structures in an efficient and precise manner,the novel Kriging-based decomposed-coordinated(DC)(DCNK)approach is proposed by integrating the DC strategy,the Kriging model and the importance sampling-based Markov chain(MCIS)technique.In this method,the DC strategy is used to decompose a multi-objective problem into many single-objective problems.The relationships between these many single-objectives and the overall objective are then coordinated.The Kriging model is applied to establish the limit state functions of the single-objectives and multi-objective problems,while the MCIS method is used to assess the structural assembled clearance reliability.Moreover,a highly nonlinear complex compound function is first utilized to verify the DCNK model from a mathematical perspective.Then,the reliability of an aeroengine high-pressure turbine(HPT)blade-tip radial running clearance(BTRRC)is analyzed to validate the DCNK approach by considering thermo-structural interaction.The analytical results show that the reliability is 0.9976 when the allowance value of the BTTRC is 1.7650×10^(−3)m.Compared with different methodologies(including direct simulation,the classical Kriging model,and the weighted response surface method(WRSM)),the proposed method holds obvious advantages in computing time and precision,as well as simulation efficiency and precision.The efforts of this paper provide a useful approach to analyzing assembled clearance reliability and contribute to the development of structural reliability theory. | Da Teng Yunwen Feng Cheng Lu Chengwei Fei Jiaqi Liu Xiaofeng Xue | 2021 | Computer Modeling in Engineering & Sciences2021，，11： | 2 |
| 6 | Dynamic parametric modeling-based model updating strategy of aeroengine casings显示文摘For accurate Finite Element(FE)modeling for the structural dynamics of aeroengine casings,Parametric Modeling-based Model Updating Strategy(PM-MUS)is proposed based on efficient FE parametric modeling and model updating techniques regarding uncorrelated/correlated mode shapes.Casings structure is parametrically modeled by simplifying initial structural FE model and equivalently simulating mechanical characteristics.Uncorrelated modes between FE model and experiment are reasonably handled by adopting an objective function to recognize correct correlated modes pairs.The parametrized FE model is updated to effectively describe structural dynamic characteristics in respect of testing data.The model updating technology is firstly validated by the detailed FE model updating of one fixed–fixed beam structure in light of correlated/uncorrelated mode shapes and measured mode data.The PM-MUS is applied to the FE parametrized model updating of an aeroengine stator system(casings)which is constructed by the proposed parametric modeling approach.As revealed in this study,(A)the updated models by the proposed updating strategy and dynamic test data is accurate,and(B)the uncorrelated modes like close modes can be effectively handled and precisely identify the FE model mode associated the corresponding experimental mode,and(C)parametric modeling can enhance the dynamic modeling updating of complex structure in the accuracy of mode matching.The efforts of this study provide an efficient dynamic model updating strategy(PM-MUS)for aeroengine casings by parametric modeling and experimental test data regarding uncorrelated modes. | Chengwei FEI Haotian LIU Shaolin LI Huan LI Liqiang AN Cheng LU | 2021 | Chinese Journal of Aeronautics2021，34，12： | 2 |
| 7 | Hierarchical model updating strategy of complex assembled structures with uncorrelated dynamic modes显示文摘In structural simulation and design,an accurate computational model directly determines the effectiveness of performance evaluation.To establish a high-fidelity dynamic model of a complex assembled structure,a Hierarchical Model Updating Strategy(HMUS)is developed for Finite Element(FE)model updating with regard to uncorrelated modes.The principle of HMUS is first elaborated by integrating hierarchical modeling concept,model updating technology with proper uncorrelated mode treatment,and parametric modeling.In the developed strategy,the correct correlated mode pairs amongst the uncorrelated modes are identified by an error minimization procedure.The proposed updating technique is validated by the dynamic FE model updating of a simple fixed–fixed beam.The proposed HMUS is then applied to the FE model updating of an aeroengine stator system(casings)to demonstrate its effectiveness.Our studies reveal that(A)parametric modeling technique is able to build an efficient equivalent model by simplifying complex structure in geometry while ensuring the consistency of mechanical characteristics;(B)the developed model updating technique efficiently processes the uncorrelated modes and precisely identifies correct Correlated Mode Pairs(CMPs)between FE model and experiment;(C)the proposed HMUS is accurate and efficient in the FE model updating of complex assembled structures such as aeroengine casings with large-scale model,complex geometry,high-nonlinearity and numerous parameters;(D)it is appropriate to update a complex structural FE model parameterized.The efforts of this study provide an efficient updating strategy for the dynamic model updating of complex assembled structures with experimental test data,which is promising to promote the precision and feasibility of simulation-based design optimization and performance evaluation of complex structures. | Chengwei FEI Haotian LIU Rhea PATRICIA LIEM Yatsze CHOY Lei HAN | 2022 | Chinese Journal of Aeronautics2022，35，3： | 1 |
| 8 | Development of a rapid and sensitive quantum dot-based immunochromatographic strip by double labeling PCR products for detection of Staphylococcus aureus in food显示文摘 | Xingxing Chen Min Gan Hong Xu Fei Chen Xing Ming Hengyi Xu Hua Wei Feng Xu Chengwei Liu | 2014 | Food Control2014，，： | 1 |
| 9 | Fusion Fault Diagnosis Approach to Rolling Bearing with Vibrational and Acoustic Emission Signals显示文摘As the key component in aeroengine rotor systems,the health status of rolling bearings directly influences the reliability and safety of aeroengine rotor systems.In order to monitor rolling bearing conditions,a fusion fault diagnosis method,namely empirical mode decomposition(EMD)-Mahalanobis distance(E2MD)and improved wavelet threshold(IWT)(E2MD-IWT)for vibrational signals and acoustic emission(AE)signals is developed to improve the diagnostic accuracy of rolling bearings.The IWT method is proposed with a hard wavelet threshold and a soft wavelet threshold.Moreover,it is shown to be effective through numerical simulation.EMD is utilized to process the original AE signals for rolling bearings so as to generate a set of components called intrinsic modes functions(IMFs).The Mahalanobis distance(MD)approach is introduced in order to determine the smallest MD between the original AE signal and IMF components.Then,the IWT approach is employed to select the IMF components with the largest MD.It is demonstrated that the proposed E2MD-IWT method for vibrational and AE signals can improve rolling bearing fault diagnosis,beyond its ability to effectively eliminate noise signals.This study offers a promising approach to fault diagnosis for rolling bearings in aeroengines with regard to vibration signals and AE signals. | Junyu Chen Yunwen Feng Cheng Lu Chengwei Fei | 2021 | Computer Modeling in Engineering & Sciences2021，，11： | 0 |
| 10 | An Insight into Machine Learning Algorithms to Map the Occurrence of the Soil Mattic Horizon in the Northeastern Qinghai-Tibetan Plateau显示文摘Soil diagnostic horizons, which each have a set of quantified properties, play a key role in soil classification. However, they are difficult to predict, and few attempts have been made to map their spatial occurrence. We evaluated and compared four machine learning algorithms, namely, the classification and regression tree(CART), random forest(RF), boosted regression trees(BRT), and support vector machine(SVM), to map the occurrence of the soil mattic horizon in the northeastern Qinghai-Tibetan Plateau using readily available ancillary data. The mechanisms of resampling and ensemble techniques significantly improved prediction accuracies(measured based on area under the receiver operator characteristic curve score(AUC)) and produced more stable results for the BRT(AUC of 0.921 ± 0.012, mean ± standard deviation) and RF(0.908 ± 0.013) algorithms compared to the CART algorithm(0.784 ± 0.012), which is the most commonly used machine learning method. Although the SVM algorithm yielded a comparable AUC value(0.906 ± 0.006) to the RF and BRT algorithms, it is sensitive to parameter settings, which are extremely time-consuming.Therefore, we consider it inadequate for occurrence-distribution modeling. Considering the obvious advantages of high prediction accuracy, robustness to parameter settings, the ability to estimate uncertainty in prediction, and easy interpretation of predictor variables, BRT seems to be the most desirable method. These results provide an insight into the use of machine learning algorithms to map the mattic horizon and potentially other soil diagnostic horizons. | ZHI Junjun ZHANG Ganlin YANG Renmin YANG Fei JIN Chengwei LIU Feng SONG Xiaodong ZHAO Yuguo LI Decheng | 2018 | Pedosphere2018，28，5： | 0 |
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