Optimization on Turbofan Engine Cycle Parameter Based on Improved Differential Evolution Algorithm

ZHANG Xiaobo 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10

In this paper, a two-spool mixed turbofan is considered. The turbofan is one of the research hotspots for military and civil aircraft power device, which shows outstanding performance advantages. Compared to the turbojet, turbofan is more efficient. For getting the performance of turbofan, the model for engine performance simulation is researched. The method for engine performance simulation and the cycle parameters for turbofan are discussed. For obtaining the optimal design of turbofan, suitable optimization method is required. Unfortunately, the optimization of the turbofan engine design is a non-linear non-differentiable problem, which makes it difficult to solve by conventional deterministic optimization method. In order to solve this problem, the differential evolution (DE) algorithm is considered. To overcome the original algorithm DE limitations, an improved DE algorithm with modifying mutation operator is proposed by this paper. The turbofan optimization problem is solved by employing the improved DE algorithm.

Modeling and Simulation of Gas Turbine Engine Based on Object-oriented Approach

ZHANG Xiaobo 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10

Considering the shortages of current modeling methods of gas turbine engine simulation systems, this paper analyzes in detail the process of modeling using object-oriented approach. The class structure suitable to the simulation system was designed. Properties and methods for each component class are increased, the basic class library of the simulation system is completed, and a set of model components are developed which can be re-used in simulation system. With a detailed analysis of the aerothermodynamics of engine components, this paper conducted a further subdivision, induction and abstraction of these components, and finally proposed such a method of class division that chooses the minimum process of aerothermodynamics calculation of gas turbine engine as the basic unit. The model based on the above mentioned method is of good expansibility and flexibility and can be applied to the gas turbine engine performance calculation with different types and complexity. By combining these components logically in the visual window frame, the user can easily complete the simulation model creation and then conduct the related calculations.

Test-Retest Reliability of “High-Order” Functional Connectivity in Young Healthy Adults

Zhang, Han,Chen, Xiaobo,Zhang, Yu,Shen, Dinggang Frontiers Media S.A. 2017 Frontiers in neuroscience Vol.11 No.-

<P>Functional connectivity (FC) has become a leading method for resting-state functional magnetic resonance imaging (rs-fMRI) analysis. However, the majority of the previous studies utilized pairwise, temporal synchronization-based FC. Recently, high-order FC (HOFC) methods were proposed with the idea of computing “correlation of correlations” to capture high-level, more complex associations among the brain regions. There are two types of HOFC. The first type is <I>topographical profile similarity-based HOFC</I> (<I>t</I>HOFC) and its variant, <I>associated HOFC</I> (<I>a</I>HOFC), for capturing different levels of HOFC. Instead of measuring the similarity of the original rs-fMRI signals with the traditional FC (low-order FC, or LOFC), tHOFC measures the similarity of LOFC profiles (i.e., a set of LOFC values between a region and all other regions) between each pair of brain regions. The second type is <I>dynamics-based HOFC</I> (<I>d</I>HOFC) which defines the quadruple relationship among every four brain regions by first calculating two pairwise dynamic LOFC “time series” and then measuring their temporal synchronization (i.e., temporal correlation of the LOFC fluctuations, not the BOLD fluctuations). Applications have shown the superiority of HOFC in both disease biomarker detection and individualized diagnosis than LOFC. However, no study has been carried out for the assessment of test-retest reliability of different HOFC metrics. In this paper, we systematically evaluate the reliability of the two types of HOFC methods using test-retest rs-fMRI data from 25 (12 females, age 24.48 ± 2.55 years) young healthy adults with seven repeated scans (with interval = 3–8 days). We found that all HOFC metrics have satisfactory reliability, specifically (1) fair-to-good for tHOFC and aHOFC, and (2) fair-to-moderate for dHOFC with relatively strong connectivity strength. We further give an in-depth analysis of the biological meanings of each HOFC metric and highlight their differences compared to the LOFC from the aspects of cross-level information exchanges, within-/between-network connectivity, and modulatory connectivity. In addition, how the dynamic analysis parameter (i.e., sliding window length) affects dHOFC reliability is also investigated. Our study reveals unique functional associations characterized by the HOFC metrics. Guidance and recommendations for future applications and clinical research using HOFC are provided. This study has made a further step toward unveiling more complex human brain connectome.</P>

Optically- and Thermally-Responsive Programmable Materials Based on Carbon Nanotube-Hydrogel Polymer Composites

Zhang, Xiaobo,Pint, Cary L.,Lee, Min Hyung,Schubert, Bryan Edward,Jamshidi, Arash,Takei, Kuniharu,Ko, Hyunhyub,Gillies, Andrew,Bardhan, Rizia,Urban, Jeffrey J.,Wu, Ming,Fearing, Ronald,Javey, Ali American Chemical Society 2011 NANO LETTERS Vol.11 No.8

<P>A simple approach is described to fabricate reversible, thermally- and optically responsive actuators utilizing composites of poly(<I>N</I>-isopropylacrylamide) (pNIPAM) loaded with single-walled carbon nanotubes. With nanotube loading at concentrations of 0.75 mg/mL, we demonstrate up to 5 times enhancement to the thermal response time of the nanotube-pNIPAM hydrogel actuators caused by the enhanced mass transport of water molecules. Additionally, we demonstrate the ability to obtain ultrafast near-infrared optical response in nanotube-pNIPAM hydrogels under laser excitation enabled by the strong absorption properties of nanotubes. The work opens the framework to design complex and programmable self-folding materials, such as cubes and flowers, with advanced built-in features, including tunable response time as determined by the nanotube loading.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/nalefd/2011/nalefd.2011.11.issue-8/nl201503e/production/images/medium/nl-2011-01503e_0002.gif'></P>

Learning-based structurally-guided construction of resting-state functional correlation tensors

Zhang, Lichi,Zhang, Han,Chen, Xiaobo,Wang, Qian,Yap, Pew-Thian,Shen, Dinggang Elsevier 2017 Magnetic resonance imaging Vol.43 No.-

<P><B>Abstract</B></P> <P>Functional magnetic resonance imaging (fMRI) measures changes in blood-oxygenation-level-dependent (BOLD) signals to detect brain activities. It has been recently reported that the spatial correlation patterns of resting-state BOLD signals in the white matter (WM) also give WM information often measured by diffusion tensor imaging (DTI). These correlation patterns can be captured using functional correlation tensor (FCT), which is analogous to the diffusion tensor (DT) obtained from DTI. In this paper, we propose a noise-robust FCT method aiming at further improving its quality, and making it eligible for further neuroscience study. The novel FCT estimation method consists of three major steps: <I>First</I>, we estimate the initial FCT using a patch-based approach for BOLD signal correlation to improve the noise robustness. <I>Second</I>, by utilizing the relationship between functional and diffusion data, we employ a regression forest model to learn the mapping between the initial FCTs and the corresponding DTs using the <I>training data</I>. The learned forest can then be applied to predict the DTI-like tensors given the initial FCTs from the testing fMRI data. <I>Third</I>, we re-estimate the enhanced FCT by utilizing the DTI-like tensors as a feedback guidance to further improve FCT computation. We have demonstrated the utility of our enhanced FCTs in Alzheimer's disease (AD) diagnosis by identifying mild cognitive impairment (MCI) patients from normal subjects.</P>

Cytosolic escape of mitochondrial DNA triggers cGAS-STING-NLRP3 axis-dependent nucleus pulposus cell pyroptosis

Zhang Weifeng,Li Gaocai,Luo Rongjin,Lei Jie,Song Yu,Wang Bingjin,Ma Liang,Liao Zhiwei,Ke Wencan,Liu Hui,Hua Wenbin,Zhao Kangcheng,Feng Xiaobo,Wu Xinghuo,Zhang Yukun,Wang Kun,Yang Cao 생화학분자생물학회 2022 Experimental and molecular medicine Vol.54 No.-

Low back pain (LBP) is a major musculoskeletal disorder and the socioeconomic problem with a high prevalence that mainly involves intervertebral disc (IVD) degeneration, characterized by progressive nucleus pulposus (NP) cell death and the development of an inflammatory microenvironment in NP tissue. Excessively accumulated cytosolic DNA acts as a damage-associated molecular pattern (DAMP) that is monitored by the cGAS-STING axis to trigger the immune response in many degenerative diseases. NLRP3 inflammasome-dependent pyroptosis is a type of inflammatory programmed death that promotes a chronic inflammatory response and tissue degeneration. However, the relationship between the cGAS-STING axis and NLRP3 inflammasome-induced pyroptosis in the pathogenesis of IVD degeneration remains unclear. Here, we used magnetic resonance imaging (MRI) and histopathology to demonstrate that cGAS, STING, and NLRP3 are associated with the degree of IVD degeneration. Oxidative stress induced cGAS-STING axis activation and NLRP3 inflammasome-mediated pyroptosis in a STING-dependent manner in human NP cells. Interestingly, the canonical morphological and functional characteristics of mitochondrial permeability transition pore (mPTP) opening with the cytosolic escape of mitochondrial DNA (mtDNA) were observed in human NP cells under oxidative stress. Furthermore, the administration of a specific pharmacological inhibitor of mPTP and self-mtDNA cytosolic leakage effectively reduced NLRP3 inflammasome-mediated pyroptotic NP cell death and microenvironmental inflammation in vitro and degenerative progression in a rat disc needle puncture model. Collectively, these data highlight the critical roles of the cGAS-STING-NLRP3 axis and pyroptosis in the progression of IVD degeneration and provide promising therapeutic approaches for discogenic LBP.

Effect of Front and Rear Rotor Stages on Aeroelasticity in Multi-Stage Environment

Xiaobo Zhang,Yanrong Wang,Xianghua Jiang,Zhizhong Fu 한국항공우주학회 2019 International Journal of Aeronautical and Space Sc Vol.20 No.1

An energy method based on the mixing-plane model and phase lagged boundary condition has been developed to estimate the flutter characteristics of rotor blades in multi-stage environment. The effects of front and rear rotor stages on the aerodynamic damping of the rotor blades have been investigated using this method. The results show that the mixing-plane model enables to consider the averaging effect of the other stages on the aeroelasticity of the checked rotor blades without having to perform the unsteady full annual multi-stage (FAMS) flow computations. Comparing with the isolated rotor blade, the upstream and downstream rotor stages have a significant influence on the aeroelasticity of the rotor blade with altering the intensity and location of the shock wave and separation flow region on suction surface. It is worth to point out that the neighbor rotor stages reduce the effect of the inter-blade phase angle (IBPA) on the aerodynamic damping. Moreover, the impact of the rear rotor stage on aerodynamic damping of the rotor blade is more remarkable than that of the front one. Compared to the measured data, the capability of this method used in the aeroelasticity assessment of a multi-stage turbomachine has been validated. Furthermore, the relationship between the aerodynamic damping and the motion of the shock wave has been revealed, which can assist the compressor design.

Mistuning Effects on Aero-elastic Stability of Contra-Rotating Turbine Blades

Xiaobo Zhang,Yanrong Wang 한국항공우주학회 2019 International Journal of Aeronautical and Space Sc Vol.20 No.1

The aero-elasticity of contra-rotating turbine blades has been evaluated by employing the energy method and the aero-elastic eigenvalue method, which is different from the normal turbine blades with HPT wake impinging on the LPT directly. The effects of two different intentional mistuning patterns and random mistuning with standard deviation from 0.1 to 1% on aeroelastic stability of the low-pressure turbine (LPT) blades have been investigated by use of the eigenvaluemethod. Studies show that the best stabilized effect can be obtained with a specific distribution of mistuning amount for alternate and sinusoidal patterns. The random mistuning can improve the stability of tuned system with the increase of the standard deviation. But when the standard deviation is greater than 0.6%, the improving effect is invariable. For the mistuned system, the random mistuning decreases the stability of the intentional mistuned system and the optimal mistuning pattern has been changed. Additionally, when the standard deviation of the random mistuning is fixed, the mistuning amount has a more significant effect on the alternate mistuning than the sinusoidal mistuning.

Influence of Control Parameters on Overall Performance of Geared Open Rotor Engine

Zhang Ziyu,Zhang Xiaobo,Wang Zhanxue 제어로봇시스템학회 2023 제어로봇시스템학회 국제학술대회 논문집 Vol.2023 No.10

Distributed Fuzzy Extended Kalman Filter for Multiagent Systems

Xiaobo Zhang,Haoshen Lin,Gang Liu,Bing He 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.5

In this study, a novel distributed Kalman filter based on a possibilistic framework was proposed to mitigate fuzzy noisein nonlinear multiagent systems. To describe fuzzy uncertainty, noises were modeled as fuzzy random variables with trapezoidal probability distributions instead of Gaussian distributions. A fuzzy information fusion (FIF) algorithm was proposed to fuse fuzzy state estimations from neighboring nodes. The nonlinear problem was solved by using local linearization. A distributed extended fuzzy information filter was designed by combining the FIF algorithm and local linearization in distributed sensor networks. The stability of this filter was analyzed. Finally, a target tracking simulation was performed to detail the effectiveness of the proposed filter algorithm.