Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.

Dynamic Analysis of A Deep-Water Compliant Vertical Access Riser with A Variable Length During Installation

Compliant vertical access risers(CVAR)have broad application prospects in deep-water oil and gas transportation.However,the mechanical behaviors of the CVAR with a variable length during installation remains unclear.To address this issue,based on the flexible segment method,a model of CVAR with a variable length during installation is established in this study,which is verified by the comparison with commercial software.Then,the mechanical behaviors of CVAR during installation are investigated.The results reveal that the CVAR configuration is significantly affected by the buoyancy blocks.The streamwise displacement of CVAR increases with the increase of current velocity.When the BOP weight is insuffcient,obvious upbending is observed in the lower region and transition region,leading to local compression.When the platform moves in the opposite direction to the current,the maximum stress is larger than that of the scenario when the platform moves in the same direction as the current.

Numerical Analysis of Flow-Induced Vibration and Noise Generation in a Variable Cross-Section Channel

Flow channels with a variable cross-section are important components of piping system and are widely used in variousfields of engineering.Using afinite element method and modal analysis theory,flow-induced noise,mode shapes,and structure-borne noise in such systems are investigated in this study.The results demonstrate that the maximum displacement and equivalent stress are located in the part with variable cross-sectional area.The aver-age excitation force on theflow channel wall increases with theflow velocity.The maximum excitation force occurs in the range of 0–20 Hz,and then it decreases gradually in the range of 20–1000 Hz.Additionally,as theflow velocity rises from 1 to 3 m/s,the overall sound pressure level associated with theflow-induced noise grows from 49.37 to 66.37 dB.Similarly,the overall sound pressure level associated with the structure-borne noise rises from 40.27 to 72.20 dB.When theflow velocity is increased,the increment of the structure-borne noise is higher than that of theflow-induced noise.

Instantaneous rotation speed measurement and error analysis for variable speed hydraulic system

In order to monitor the working state of piston motor and measure its instantaneous rotation speed accurately, the measuring principle and method of instantaneous rotation speed based on industrial personal computer and data acquisition card are introduced, and the major error source, influence mechanism and processing method of data quantization error are dis- cussed. By means of hybrid programming approach of LabVIEW and MATLAB, the instantaneous rotation speed measurement system for the piston motor in variable speed hydraulic system is designed. The simulation and experimental results show that the designed instantaneous speed measurement system is feasible. Furthermore, the sampling frequency has an important influ- ence on the instantaneous rotation speed measurement of piston motor and higher sampling frequency can lower quantization er- ror and improve measurement accuracy.

Inverse reliability analysis and design for tunnel face stability considering soil spatial variability

The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.

A comprehensive review of heart rate variability as an indicator in the regulation of the autonomic nervous system by acupuncture:a bibliometric analysis

This study sought to conduct a bibliometric analysis of acupuncture studies focusing on heart rate variability(HRV)and to investigate the correlation between various acupoints and their effects on HRV by utilizing association rule mining and network analysis.A total of 536 publications on the topic of acupuncture studies based on HRV.The disease keyword analysis revealed that HRV-related acupuncture studies were mainly related to pain,inflammation,emotional disorders,gastrointestinal function,and hypertension.A separate analysis was conducted on acupuncture prescriptions,and Neiguan(PC6)and Zusanli(ST36)were the most frequently used acupoints.The core acupoints for HRV regulation were identified as PC6,ST36,Shenmen(HT7),Hegu(LI4),Sanyinjiao(SP6),Jianshi(PC5),Taichong(LR3),Quchi(LI11),Guanyuan(CV4),Baihui(GV20),and Taixi(KI3).Additionally,the research encompassed 46 reports on acupuncture animal experiments conducted on HRV,with ST36 being the most frequently utilized acupoint.The research presented in this study offers valuable insights into the global research trend and hotspots in acupuncture-based HRV studies,as well as identifying frequently used combinations of acupoints.The findings may be helpful for further research in this field and provide valuable information about the potential use of acupuncture for improving HRV in both humans and animals.

DISPLACEMENT CONTROL AND KINETIC ANALYSIS OF A NOVEL VARIABLE DISPLACEMENT COMPRESSOR FOR AUTOMOTIVE AIR CONDITIONER

A novel variable displacement compressor (VDC) for automotive air conditioner (AAC) is introduced, which inherits the advantages of common wobble plate type VDC. It has fewer parts and makes less noise, and instead of pneumatic valve the displacement is controlled by electronic control valve. In order to know the control mechanism well and get a good control effect, a mathematical model for the variable displacement mechanism is developed according to the geometrical and kinematical information of the compressor. Using the model, the effect of relevant parameters on variable displace control is estimated. It is helpful to make the optimum decision in the flow control of AAC. As the novel displacement control device, the structure and control rule of electronic control valve is introduced. It can get better effect than the conventional pneumatic valves. And by using this new electronic control device, the optimum systemic control of AAC is available.

Modeling and analysis of piezoelectric beam with periodically variable cross-sections for vibration energy harvesting

A bimorph piezoelectric beam with periodically variable cross-sections is used for the vibration energy harvesting. The effects of two geometrical parameters on the first band gap of this periodic beam are investigated by the generalized differential quadrature rule （GDQR） method. The GDQR method is also used to calculate the forced vibration response of the beam and voltage of each piezoelectric layer when the beam is subject to a sinusoidal base excitation. Results obtained from the analytical method are compared with those obtained from the finite element simulation with ANSYS, and good agreement is found. The voltage output of this periodic beam over its first band gap is calculated and compared with the voltage output of the uniform piezoelectric beam. It is concluded that this periodic beam has three advantages over the uniform piezoelectric beam, i.e., generating more voltage outputs over a wide frequency range, absorbing vibration, and being less weight.

Advanced reliability analysis of slopes in spatially variable soils using multivariate adaptive regression splines

This study aims to extend the multivariate adaptive regression splines(MARS)-Monte Carlo simulation(MCS) method for reliability analysis of slopes in spatially variable soils. This approach is used to explore the influences of the multiscale spatial variability of soil properties on the probability of failure(P_f) of the slopes. In the proposed approach, the relationship between the factor of safety and the soil strength parameters characterized with spatial variability is approximated by the MARS, with the aid of Karhunen-Loeve expansion. MCS is subsequently performed on the established MARS model to evaluate Pf.Finally, a nominally homogeneous cohesive-frictional slope and a heterogeneous cohesive slope, which are both characterized with different spatial variabilities, are utilized to illustrate the proposed approach.Results showed that the proposed approach can estimate the P_f of the slopes efficiently in spatially variable soils with sufficient accuracy. Moreover, the approach is relatively robust to the influence of different statistics of soil properties, thereby making it an effective and practical tool for addressing slope reliability problems concerning time-consuming deterministic stability models with low levels of P_f.Furthermore, disregarding the multiscale spatial variability of soil properties can overestimate or underestimate the P_f. Although the difference is small in general, the multiscale spatial variability of the soil properties must still be considered in the reliability analysis of heterogeneous slopes, especially for those highly related to cost effective and accurate designs.

POWER FLOW ANALYSIS AND APPLICATION SIMULATION OF ELECTROMAGNETIC CONTINUOUSLY VARIABLE TRANSMISSION

With the structure of two air gaps and two rotors, the electromagnetic continuously variable transmission（EMCVT） is a novel power-split continuously variable transmission（CVT）. There are two kinds of power flowing through the EMCVT, one is mechanical power and the other is electric power. In the mean time, there are three power ports in the EMCVT, one is the outer rotor named mechanical power port and the other two are the inner rotor and the stator named electric power ports. The mechanical power port is connected to the driving wheels through the final gear and the electric ports are connected to the batteries through the transducers. The two kinds of power are coupled on the outer rotor of the EMCVT. The EMCVT can be equipped on the conventional vehicle being regarded as the CVT and it also can be equipped on the hybrid electric vehicle（HEV） as the multi-energy sources assembly. The power flows of these two kinds of applications are analysed. The back electromotive force（EMF） equations are illatively studied and so the dynamic mathematic model is theorized. In order to certify the feasibility of the above theories, three simulations are carried out in allusion to the above two kinds of mentioned applications of the EMCVT and a five speed automatic transmission（AT） vehicle. The simulation results illustrate that the efficiency of the EMCVT vehicles is higher than that of the AT vehicle owed to the optimized operation area of the engine. Hence the fuel consumption of the EMCVT vehicles is knock-down.

Reliability analysis for aeroengine turbine disc fatigue life with multiple random variables based on distributed collaborative response surface method

The fatigue life of aeroengine turbine disc presents great dispersion due to the randomness of the basic variables,such as applied load,working temperature,geometrical dimensions and material properties.In order to ameliorate reliability analysis efficiency without loss of reliability,the distributed collaborative response surface method(DCRSM) was proposed,and its basic theories were established in this work.Considering the failure dependency among the failure modes,the distributed response surface was constructed to establish the relationship between the failure mode and the relevant random variables.Then,the failure modes were considered as the random variables of system response to obtain the distributed collaborative response surface model based on structure failure criterion.Finally,the given turbine disc structure was employed to illustrate the feasibility and validity of the presented method.Through the comparison of DCRSM,Monte Carlo method(MCM) and the traditional response surface method(RSM),the results show that the computational precision for DCRSM is more consistent with MCM than RSM,while DCRSM needs far less computing time than MCM and RSM under the same simulation conditions.Thus,DCRSM is demonstrated to be a feasible and valid approach for improving the computational efficiency of reliability analysis for aeroengine turbine disc fatigue life with multiple random variables,and has great potential value for the complicated mechanical structure with multi-component and multi-failure mode.

Finite element analysis of rolling process for variable cross-section blade

Due to the variation of the blade cross-section, the deformation stress and strain of the workpiece keep changing during the rolling process and the conventional rolling theory is no longer valid. The complexity and diversity of the blade cross-section determine it impossible to establish an universal theoretical model for the rolling process. Finite element analysis(FEA) provides a perspective solution to the prediction. The FEA software DEFORM was applied to discovering the deformation, stress, strain and velocity field of the variable cross-section workpiece, and the effects of friction coefficient and rolling speed during the rolling process. which indicates that the average rolling force at friction coefficient of 0.4 is 6.5% higher than that at 0.12, and the rolling velocity has less effect on the equivalent stress and strain distribution, which would confer instructive significance on the theoretical study as well as the engineering practice.

Integrating dual-role variables in data envelopment analysis

Traditional data envelopment analysis（DEA） theory assumes that decision variables are regarded as inputs or outputs,and no variable can play the roles of both an input and an output at the same time.In fact,there exist some variables that work as inputs and outputs simultaneously and are called dual-role variables.Traditional DEA models cannot be used to appraise the performance of decision making units containing dual-role variables.The paper analyzes the structure and properties of the production systems comprising dual-role variables,and proposes a DEA model integrating dual-role variables.Finally the proposed model is illustrated to evaluate the efficiency of university departments.

A Recursive Method of Time-Frequency Analysis for the Signal Processing of Flutter Test with Progression Variable Speed

Focused on the non-statlonarity and real-time analysis of signal in flutter test with progression variable speed （FTPVS）, a new method of recursive time-frequency analysis is presented. The time-varying system is tracked on-line by building a time-varying parameter model, and then the relevant parameter spectrum can be obtained. The feasibility and advantages of the method are examined by digital simulation. The results of FTPVS at low-speed wind-tunnel promise the engineering application perspective of the method.

Numerical and Experimental Analysis of A Vertical-Axis Eccentric-disc Variable-Pitch Turbine(VEVT)

A combined experimental and numerical investigation is carried out to study the performance of a vertical-axis eccentric-disc variable-pitch turbine(VEVT).A scheme of eccentric disc pitch control mechanism based on doubleblock mechanism is proposed.The eccentric control mechanism and the deflection angle control mechanism in the pitch control structure are designed and optimized according to the functional requirements of the turbine,and the three-dimensional model of the turbine is established.Kinematics analysis of the eccentric disc pitch control mechanism is carried out.Kinematics parameters and kinematics equations which can characterize its motion characteristics are derived.Kinematics analysis and simulation are carried out,and the motion law of the corresponding mechanical system is obtained.By analyzing the force and motion of blade of VEVT,the expressions of the important parameters such as deflection angle,attack angle and energy utilization coefficient are obtained.The lateral induced velocity coefficient is acquired by momentum theorem,the hydrodynamic parameters such as energy utilization coefficient are derived,and the hydrodynamic characteristics of VEVT are also obtained.The experimental results show that the turbine has good energy capture capability at different inflow velocities of different sizes and directions,which verifies that VEVT has good self-startup performance and high energy capture efficiency.

An XBi-CFAO Method for the Optimization of Multi-Layered Variable Stiffness Composites Using Isogeometric Analysis

This paper presents an effective fiber angle optimization method for two and multi-layered variable stiffness composites.A gradient-based fiber angle optimization method is developed based on isogeometric analysis(IGA).Firstly,the element densities and fiber angles for two and multi-layered composites are synchronously optimized using an extended Bi-layered continuous fiber angle optimization method(XBi-CFAO).The densities and fiber angles in the base layer are attached to the control points.The structure response and sensitivity analysis are accomplished using the non-uniform rational B-spline(NURBS)based IGA.By the benefit of the B-spline space,this method is free from checkerboards,and no additional filtering is needed to smooth the sensitivity numbers.Then the curved fiber paths are generated using the streamline method and the discontinuous fiber paths are smoothed using a partitioned selection process.The proposed method in the paper can alleviate the phenomenon of fiber discontinuity,enhance information retention for the optimized fiber angles of the singular points and save calculating resources effectively.

New approaches to cognitive work analysis through latent variable modeling in mining operations

This paper discusses the utilization of latent variable modeling related to occupational health and safety in the mining industry.Latent variable modeling,which is a statistical model that relates observable and latent variables,could be used to facilitate researchers’understandings of the underlying constructs or hypothetical factors and their magnitude of effect that constitute a complex system.This enhanced understanding,in turn,can help emphasize the important factors to improve mine safety.The most commonly used techniques include the exploratory factor analysis(EFA),the confirmatory factor analysis(CFA)and the structural equation model with latent variables(SEM).A critical comparison of the three techniques regarding mine safety is provided.Possible applications of latent variable modeling in mining engineering are explored.In this scope,relevant research papers were reviewed.They suggest that the application of such methods could prove useful in mine accident and safety research.Application of latent variables analysis in cognitive work analysis was proposed to improve the understanding of human-work relationships in mining operations.

Decision variables analysis for structured modeling

Structured modeling is the most commonly used modeling method, but it is not quite addaptive to significant changes in environmental conditions. Therefore, Decision Variables Analysis(DVA), a new modelling method is proposed to deal with linear programming modeling and changing environments. In variant linear programming , the most complicated relationships are those among decision variables. DVA classifies the decision variables into different levels using different index sets, and divides a model into different elements so that any change can only have its effect on part of the whole model. DVA takes into consideration the complicated relationships among decision variables at different levels, and can therefore sucessfully solve any modeling problem in dramatically changing environments.

Spatial distribution analysis on climatic variables in northeast China

Information ecology is a new research area of modern ecology. Here describes the spatial distribution analysis methods of four sorts of climatic variables, i.e. temperature, precipitation, relative humidity and sunshine fraction in Northeast China. First, digital terrain models was built with large scale maps and vector data. Then trend surface analysis and interpolation method were used to analyze the spatial distribution of these four kinds of climatic variables at three temporal scale: (1) monthly data; (2) mean monthly data of thirty years, and (3) mean annual data of thirty years. Ecological information system were used for graphics analysis on the spatial distribution of these climatic variables.

Security analysis of continuous-variable quantum key distribution scheme

In this paper security of the quantum key distribution scheme using correlations of continuous variable Einstein- Podolsky-Rosen （EPR） pairs is investigated. A new approach for calculating the secret information rate △I is proposed by using the Shannon information theory. Employing an available parameter F which is associated with the entanglement of the EPR pairs, one can detect easily the eavesdropping. Results show that the proposed scheme is secure against individual bearn splitter attack strategy with a proper squeeze parameter.