基于FAST和Sobol指数法的雷达系统效能敏感性分析

为了以较小的代价快速提升对空探测雷达系统的综合效能,首先搭建了对空探测雷达系统综合效能的评估指标体系,在此基础上完成了综合效能评估模型的建立。选择两种基于方差原理的全局敏感性分析方法,即傅里叶幅度敏感性测试(Fourier amplitudes sensitivity test,FAST)和Sobol指数法,分别从频域和时域对建立的评估模型进行敏感性分析。在基于FAST进行敏感性分析时,提出了21维输入指标所对应的特征频率集的选取方法;在基于Sobol指数法进行敏感性分析时,考虑了二阶及高阶敏感性指数的影响。对比FAST和Sobol指数法的分析结果,两种方法获得的敏感性分析结果具有较好的一致性。其中,功率和频率为对空探测雷达系统的主要影响指标,为雷达系统的研发和升级提供了可靠性依据。

CEEMD-FastICA-CWT联合瞬态响应阶次的电驱总成噪声源识别

以某增程式电驱动总成为研究对象,提出基于联合算法的噪声分离识别模型。首先,采用互补集合经验模态分解(complementary ensemble empirical mode decomposition,CEEMD)联合快速独立分量分析(fast independent component analysis,FastICA)方法提取纯电模式稳态工况下单一通道噪声信号特征,利用复Morlet小波变换及FFT对各分量信号时频特性进行识别。其次,采用阶次分析法和声能叠加法对稳态分量信号对应的各瞬态响应阶次能量进行对比分析,并结合皮尔逊积矩相关系数(Pearson product moment correlation coefficient,PPMCC)相似性识别确定不同噪声激励源贡献度。结果表明:减速齿副啮合噪声对该增程式电驱总成纯电模式运行噪声整体贡献度最大。

Shear wave splitting analysis of local earthquakes from dense arrays in Shimian,Sichuan

The Shimian area of Sichuan sits at the junction of the Bayan Har block.Sichuan-Yunnan rhombic block,and Yangtze block,where several faults intersect.This region features intense tectonic activity and frequent earthquakes.In this study,we used local seismic waveform data recorded using dense arrays deployed in the Shimian area to obtain the shear wave splitting parameters at 55 seismic stations and thereby determine the crustal anisotropic characteristics of the region.We then analyzed the crustal stress pattern and tectonic setting and explored their relationship in the study area.Although some stations returned a polarization direction of NNW-SSE.a dominant polarization direction of NW-SE was obtained for the fast shear wave at most seismic stations in the study area.The polarization directions of the fast shear wave were highly consistent throughout the study-area.This orientation was in accordance with the direction of the regional principal compressive stress and parallel to the trend of the Xianshuihe and Daliangshan faults.The distribution of crustal anisotropy in this area was affected by the regional tectonic stress field and the fault structures.The mean delay time between fast and slow shear waves was 3.83 ms/km.slightly greater than the values obtained in other regions of Sichuan.This indicates that the crustal media in our study area had a high anisotropic strength and also reveals the influence of tectonic complexity resulting from the intersection of multiple faults on the strength of seismic anisotropy.

Core and blanket thermal-hydraulic analysis of a molten salt fast reactor based on coupling of OpenMC and OpenFOAM

In the core of a molten salt fast reactor(MSFR),heavy metal fuel and fission products can be dissolved in a molten fluoride salt to form a eutectic mixture that acts as both fuel and coolant.Fission energy is released from the fuel salt and transferred to the second loop by fuel salt circulation.Therefore,the MSFR is characterized by strong interaction between the neutronics and the thermal hydraulics.Moreover,recirculation flow occurs,and nuclear heat is accumulated near the fertile blanket,which significantly affects both the flow and the temperature fields in the core.In this work,to further optimize the conceptual geometric design of the MSFR,three geometries of the core and fertile blanket are proposed,and the thermal-hydraulic characteristics,including the three-dimensional flow and temperature fields of the fuel and fertile salts,are simulated and analyzed using a coupling scheme between the open source codes OpenMC and OpenFOAM.The numerical results indicate that a flatter core temperature distribution can be obtained and the hot spot and flow stagnation zones that appear in the upper and lower parts of the core center near the reflector can be eliminated by curving both the top and bottom walls of the core.Moreover,eight cooling loops with a total flow rate of0.0555 m3 s-1 ensur an acceptable temperature distribusure an acceptable temperature distribution in the fertile blanket.

A novel stochastic modeling framework for coal production and logistics through options pricing analysis

We propose a novel stochastic modeling framework for coal production and logistics using option pricing theory.The problem of valuing the inherent real optionality a coal producer has when mining and processing thermal coal is modelled as pricing spread options of three assets under the stochastic volatility model.We derive a three-dimensional Fast Fourier Transform(“FFT”)lower bound approximation to value the inherent real optionality and for robustness check,we compare the semi-analytical pricing accuracy with the Monte Carlo simulation.Model parameters are estimated from the historical monthly data,and stochastic volatility parameters are obtained by matching the Kurtosis of the low-ash diff data to the Kurtosis of the stochastic volatility process which is assumed to follow Cox–Ingersoll–Ross(“CIR”)model.

Spectral Analysis and Validation of Parietal Signals for Different Arm Movements

Brain signal analysis plays a significant role in attaining data related to motor activities.The parietal region of the brain plays a vital role in muscular movements.This approach aims to demonstrate a unique technique to identify an ideal region of the human brain that generates signals responsible for muscular movements;perform statistical analysis to provide an absolute characterization of the signal and validate the obtained results using a prototype arm.This can enhance the practical implementation of these frequency extractions for future neuro-prosthetic applications and the characterization of neurological diseases like Parkinson’s disease(PD).To play out this handling method,electroencepha-logram(EEG)signals are gained while the subject is performing different wrist and elbow movements.Then,the frontal brain signals and just the parietal signals are separated from the obtained EEG signal by utilizing a band pass filter.Then,feature extraction is carried out using Fast Fourier Transform(FFT).Subse-quently,the extraction process is done by Daubechies(db4)and Haar wavelet(db1)in MATLAB and classified using the Levenberg-Marquardt Algorithm.The results of the frequency changes that occurred during various wrist move-ments in the parietal region are compared with the frequency changes that occurred in frontal EEG signals.This proposed algorithm also uses the deep learn-ing pattern analysis network to evaluate the matching sequence for each action that takes place.Maximum accuracy of 97.2%and maximum error range of 0.6684%are achieved during the analysis.Results of this research confirm that the Levenberg-Marquardt algorithm,along with the newly developed deep learn-ing hybrid PatternNet,provides a more accurate range of frequency changes than any other classifier used in previous works of literature.Based on the analysis,the peak-to-peak value is used to define the threshold for the prototype arm,which performs all the intended degrees of freedom(DOF),verifying the results.These results would aid the specialists in their decision-making by facilitating the ana-lysis and interpretation of brain signals in the field of neuroscience,specifically in tremor analysis in PD.

Genome-wide Association Analysis of Fast Chlorophyll Fluorescence Parameters in Maize

Fast chlorophyll fluorescence parameters are widely used to characterize the photosynthetic efficiency of plants. In this study, a genome-wide association analysis was used to detect key single-nueleotide polymorphisms （SNPs） associated with fast chlorophyll fluorescence parameters using more than 560 000 SNPs in a maize panel consisting of 404 inbred lines. In four fidd environments, 41 SNPs were detected to be associated with five fast chlorophyll fluorescence parameters, including ABS/CS0, ET0/CS0, TR0/ABS, ET0/TR0 and Pies. Among these identified SNPs, 8, 6, 18, 4 and 5 were significantly associated with ET0/TR0, ABS/ CS0, TR0/ABS, ET0/CS, and Plcs, respectively. These SNPs will help to discover genes for chlorophyll fluorescence parameters, better understand the genetic basis of photosynthesis, and assist in developing marker-assisted selection breeding programs in maize.

Fast analysis of derivatives of polycyclic aromatic hydrocarbons in soil by ultra-high performance supercritical fluid chromatography after supercritical fluid extraction enrichment

An efficient and environment-friendly method for simultaneous determination of 13 typical derivatives of polycyclic aromatic hydrocarbon(PAH)in petroleum-polluted soil with nitro-,oxy-and alkylfunctional group was developed using supercritical fluid extraction(SFE)followed by ultra-high performance supercritical fluid chromatography(UHPSFC).Parameters of UHPSFC,including type of stationary phase and mobile phase modifiers,gradient elution process,backpressure,column temperature,and the flow rate of mobile phase,were systematically optimized,achieving a fast separation within4.2 min.Limits of detection(LOD)were 0.005-0.1μg mL^(-1)or 0.1-2.0 ng g^(-1),respectively,with a good repeatability(RSD<5.0%).Before UHPSFC-PDA analysis,the PAH-derivatives in soil samples were effectively enriched in 15.0 min using SFE with an online carbon nanotubes(CNTs)collection trap.The soil samples were analyzed by the proposed method and the results were verified by GC-MS.Thus,SFE equipped with an online CNTs trap followed by UHPSFC-PDA analysis,which only consumed about2.0 mL organic solvent for a whole run,has been demonstrated to be an efficient way for screening and quantitative analysis of trace-level PAH-derivatives in soil samples.

Dual-single-atoms of Pt-Co boost sulfur redox kinetics for ultrafast Li-S batteries

Applications of lithium-sulfur(Li-S)batteries are still limited by the sluggish conversion kinetics from polysulfide to Li_(2)S.Although various single-atom catalysts are available for improving the conversion kinetics,the sulfur redox kinetics for Li-S batteries is still not ultrafast.Herein,in this work,a catalyst with dual-single-atom Pt-Co embedded in N-doped carbon nanotubes(Pt&Co@NCNT)was proposed by the atomic layer deposition method to suppress the shuttle effect and synergistically improve the interconversion kinetics from polysulfides to Li_(2)S.The X-ray absorption near edge curves indicated the reversible conversion of Li_(2)Sx on the S/Pt&Co@NCNT electrode.Meanwhile,density functional theory demonstrated that the Pt&Co@NCNT promoted the free energy of the phase transition of sulfur species and reduced the oxidative decomposition energy of Li_(2)S.As a result,the batteries assembled with S/Pt&Co@NCNT electrodes exhibited a high capacity retention of 80%at 100 cycles at a current density of 1.3 mA cm^(−2)(S loading:2.5 mg cm^(−2)).More importantly,an excellent rate performance was achieved with a high capacity of 822.1 mAh g^(−1) at a high current density of 12.7 mA cm^(−2).This work opens a new direction to boost the sulfur redox kinetics for ultrafast Li-S batteries.

Efficient Fast Independent Component Analysis Algorithm with Fifth-Order Convergence

Independent component analysis （ICA） is the primary statistical method for solving the problems of blind source separation. The fast ICA is a famous and excellent algorithm and its contrast function is optimized by the quadratic convergence of Newton iteration method. In order to improve the convergence speed and the separation precision of the fast ICA, an improved fast ICA algorithm is presented. The algorithm introduces an efficient Newton＇s iterative method with fifth-order convergence for optimizing the contrast function and gives the detail derivation process and the corresponding condition. The experimental results demonstrate that the convergence speed and the separation precision of the improved algorithm are better than that of the fast ICA.

Numerical analysis of temperature rise within 70MPa composite hydrogen vehicle cylinder during fast refueling

The numerical simulation model for predicting fast filling process of 70 MPa type Ⅲ(with metal liner) hydrogen vehicle cylinder was presented,which has considered turbulence,real gas effect and solid heat transfer issues.Through the numerical analysis method,the temperature distributions of the gas within the solid walls were revealed; adiabatic filling was studied to evaluate the heat dissipation during the filling; the influences of various filling conditions on temperature rise were analyzed in detail.Finally,cold filling was proposed to evaluate the effect on temperature rise and SoC(state of charge) within the cylinder.The hydrogen pre-cooling was proved to be an effective solution to reduce maximum temperature and acquire higher SoC during the filling process.

Analysis of OECD/NEA medium 1000 MWth sodium-cooled fast reactor using the Monte Carlo serpent code and ENDF/B-VIII.0 nuclear data library

This study presents a benchmark evaluation of the new ENDF/B-VIII.0 nuclear data library for the Organization for Economic Co-operation and Development/Nuclear Energy Agency Medium 1000 MWth sodium-cooled fast reactor(SFR).The study presented herein covers both SFR core types,i.e.,metallic fueled(MET-1000)and oxide fueled(MOX-1000),simulated using the continuous-energy Monte Carlo Serpent2 code.The neutronics performances of the ENDF/B-VIII.0-based simulations were compared mainly to two libraries:ENDF/B-VII.1 and JENDL-4.0.The comparison includes several neutronics parameters evaluated for the beginning and end of the cycle conditions.These parameters include the effective multiplication factor keff,total effective delayed neutron fraction beff,sodium void reactivity(DqNa),Doppler constant(DqDoppler),and control rod worth(DqCR).In addition,a sensitivity study was used to reveal the major isotope/reaction pairs contributing to the discrepancy observed in the performance of the three libraries using 33 and 44-energy-group structures.

Modified slow-fast analysis method for slow-fast dynamical systems with two scales in frequency domain

A modified slow-fast analysis method is presented for the periodically excited non-autonomous dynamical system with an order gap between the exciting frequency and the natural frequency.By regarding the exciting term as a slow-varying parameter,a generalized autonomous fast subsystem can be defined,the equilibrium branches as well as the bifurcations of which can be employed to account for the mechanism of the bursting oscillations by combining the transformed phase portrait introduced.As an example,a typical periodically excited Hartley model is used to demonstrate the validness of the method,in which the exciting frequency is far less than the natural frequency.The equilibrium branches and their bifurcations of the fast subsystem with the variation of the slow-varying parameter are presented.Bursting oscillations for two typical cases are considered,which reveals that,fold bifurcation may cause the the trajectory to jump between different equilibrium branches,while Hopf bifurcation may cause the trajectory to oscillate around the stable limit cycle.

Development and validation of a new oxide fuel rod performance analysis code for the liquid metal fast reactor

The integrity and reliability of fuel rods under both normal and accidental operating conditions are of great importance for nuclear reactors.In this study,considering various irradiation behaviors,a fuel rod performance analysis code,named KMC-Fueltra,was developed to evaluate the thermal–mechanical performance of oxide fuel rods under both normal and transient conditions in the LMFR.The accuracy and reliability of the KMC-Fueltra were validated by analytical solutions,as well as the results obtained from codes and experiments.The results indicated that KMC-Fueltra can predict the performance of oxide fuel rods under both normal and transient conditions in the LMFR.

The fast method and convergence analysis of the fractional magnetohydrodynamic coupled flow and heat transfer model for the generalized second-grade fluid

In this paper,we first establish a new fractional magnetohydrodynamic(MHD)coupled flow and heat transfer model for a generalized second-grade fluid.This coupled model consists of a fractional momentum equation and a heat conduction equation with a generalized form of Fourier law.The second-order fractional backward difference formula is applied to the temporal discretization and the Legendre spectral method is used for the spatial discretization.The fully discrete scheme is proved to be stable and convergent with an accuracy of O(τ^(2)+N-r),whereτis the time step-size and N is the polynomial degree.To reduce the memory requirements and computational cost,a fast method is developed,which is based on a globally uniform approximation of the trapezoidal rule for integrals on the real line.The strict convergence of the numerical scheme with this fast method is proved.We present the results of several numerical experiments to verify the effectiveness of the proposed method.Finally,we simulate the unsteady fractional MHD flow and heat transfer of the generalized second-grade fluid through a porous medium.The effects of the relevant parameters on the velocity and temperature are presented and analyzed in detail.

A Precise Algorithm for Non-Integer Harmonics Analysis Based on FFT and Neural Network

By means of an arificial neural network (ANN) model, higher measurement accuracy of integer harmonics can be obtained. Combining the windowed fast Fourier transform (FFT) algorithm with the improved ANN model, we present a new precise algorithm for non-integer harmonics analysis. According to the result obtained from the Hanning-windowed FFT algorithm, we choose the initial values of orders of harmonics for the neural network. Through such processing, the time of iterations is shortened and the convergence rate of neural network is raised thereby. The simulation results show that close non-integer harmonics can be separated from a signal with higher accuracy and better real-time by using the algorithm presented in the paper. Key words fast Fourier transform (FFT) - artificial neural network (ANN) - Hanning-window - harmonics analysis CLC number TM 935 Foundation item: Supported by the Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of China (2001-182) and the Science Foundation of Naval University of Engineering(HGDJJ03001).Biography: WANG Gong-bao (1962-), male, Professor, research direction: artificial neural network, wavelet analysis and their applications to signal processing in electric power systems.

Application of Wavelet Algorithm to Spectral Analysis of Oceanic Waves and Offshore Structure Responses

Fourier transform （FF） is a commonly used method in spectral analysis of ocean wave and offshore structure responses, but it is not suitable for records of short length. In this paper another method, wavelet transform （WT）, is applied to ＇analyze the data of short length. The Morlet wavelet is employed to calculate the spectra density functions for wave records and simulated Floating Production Storage and Offloading （FPSO） vessels＇ responses. Computed wave data include simulated wave data based on JONSWAP spectrum and the recorded data of Storm 149 from North Alwyn. Wavelet method is validated by comparing the statistical characteristics by WF method and those by fast Fourier transform （FFT） method with those of target spectra. The spectral density fnnctions＇ shapes calculated by WT are less malformed and have less error of statistical characteristics compared with those by FT especially when the record lengths decrease.

Efficacy and Safety of SGLT2 Inhibitors in Patients with Type 1 Diabetes:A Meta-analysis of Randomized Controlled Trials

Objective To assess the efficiency and safety of a novel sodium-glucose co-transporter 2(SGLT2) inhibitor—SGLT2 inhibitors,in combination with insulin for type 1 diabetes mellitus(T1DM). Methods We searched Medline,Embase,and the Cochrane Collaboration Library to identify the eligible studies published between January 2010 and July 2016 without restriction of language. The Food and Drug Administration(FDA) data and Clinical Trials(http://www.clinicaltrials.gov) were also searched. The included studies met the following criteria:randomized controlled trials; T1DM patients aged between 18 and 65 years old; patients were treated with insulin plus SGLT2 inhibitors for more than 2 weeks; patients' glycosylated hemoglobin(HbA1c) levels were between 7% and 12%. The SGLT2 inhibitors group was treated with SGLT2 inhibitors plus insulin,and the placebo group received placebo plus insulin treatment. The outcomes should include one of the following items:fasting blood glucose,HbA1c,glycosuria,or adverse effects. Data were analyzed by two physicians independently. The risk of bias was evaluated by using the Cochrane Collaboration's Risk of Bias tool and heterogeneity among studies was assessed using Chi-square test. Random effect model was used to analyze the treatment effects with Revman 5.3. Results Three trials including 178 patients were enrolled. As compared to the placebo group,SGLT2 inhibitor absolutely decreased fasting blood glucose [mean differences(MD)-2.47 mmol/L,95% confidence interval(CI)-3.65 to-1.28,P<0.001] and insulin dosage(standardized MD-0.75 U,95%CI-1.17 to-0.33,P<0.001). SGLT2 inhibitors could also increase the excretion of urine glucose(MD 131.09 g/24 h,95%CI 91.79 to 170.39,P<0.001). There were no significant differences in the incidences of hyperglycemia [odds ratio(OR) 1.82,95%CI 0.63 to 5.29,P=0.27],urinary tract infection(OR 0.95,95%CI 0.19 to 4.85,P=0.95),genital tract infection(OR 0.27,95%CI 0.01 to 7.19,P=0.43),and diabetic ketoacidosis(OR 6.03,95%CI 0.27 to 135.99,P=0.26) between the two groups. Conclusion SGLT2 inhibitors combined with insulin might be an efficient and safe treatment modality for T1DM patients.