Sensitivity Analysis of Multi-phase Seepage Parameters Affecting the Clayey Silt Hydrate Reservoir Productivity in the Shenhu Area,South China Sea

Natural gas hydrate(NGH)is an important future resource for the 21st century and a strategic resource with potential for commercial development in the third energy transition.It is of great significance to accurately predict the productivity of hydrate-bearing sediments(HBS).The multi-phase seepage parameters of HBS include permeability,porosity,which is closely related to permeability,and hydrate saturation,which has a direct impact on hydrate content.Existing research has shown that these multi-phase seepage parameters have a great impact on HBS productivity.Permeability directly affects the transmission of pressure-drop and discharge of methane gas,porosity and initial hydrate saturation affect the amount of hydrate decomposition and transmission process of pressure-drop,and also indirectly affect temperature variation of the reservoir.Considering the spatial heterogeneity of multi-phase seepage parameters,a depressurization production model with layered heterogeneity is established based on the clayey silt hydrate reservoir at W11 station in the Shenhu Sea area of the South China Sea.Tough+Hydrate software was used to calculate the production model;the process of gas production and seepage parameter evolution under different multi-phase seepage conditions were obtained.A sensitivity analysis of the parameters affecting the reservoir productivity was conducted so that:(a)a HBS model with layered heterogeneity can better describe the transmission process of pressure and thermal compensation mechanism of hydrate reservoir;(b)considering the multi-phase seepage parameter heterogeneity,the influence degrees of the parameters on HBS productivity were permeability,porosity and initial hydrate saturation,in order from large to small,and the influence of permeability was significantly greater than that of other parameters;(c)the production potential of the clayey silt reservoir should not only be determined by hydrate content or seepage capacity,but also by the comprehensive effect of the two;and(d)time scales need to be considered when studying the effects of changes in multi-phase seepage parameters on HBS productivity.

Rigorous back analysis of shear strength parameters of landslide slip

A rigorous back analysis of shear strength parameters of landslide slip was presented. Kinematical element method was adopted to determine factor of safety and critical failure surface, which overcomes the disadvantage of limit equilibrium method. The theoretical relationship between the combination of shear strength parameters and stability state was studied. The results show that the location of critical slip surface, F/tan f and F/c depend only on the value of c/tan f. The failure surface moves towards the inside of slope as c/tan f increases. According to the information involving factor of safety and critical failure surface in a specific cross-section, strength parameters can be back calculated based on the above findings. Three examples were given for demonstrating the validity of the present method. The shear strength parameters obtained by back analysis are almost consistent with their correct solutions or test results.

Composition Analysis and Identification of Ancient Glass Products Based on L1 Regularization Logistic Regression

In view of the composition analysis and identification of ancient glass products, L1 regularization, K-Means cluster analysis, elbow rule and other methods were comprehensively used to build logical regression, cluster analysis, hyper-parameter test and other models, and SPSS, Python and other tools were used to obtain the classification rules of glass products under different fluxes, sub classification under different chemical compositions, hyper-parameter K value test and rationality analysis. Research can provide theoretical support for the protection and restoration of ancient glass relics.

Diagnostic efficacy of virtual organ computer-assisted analysis in measuring the volume ratio of subchorionic hematoma with serum progesterone

BACKGROUND Subchorionic hematoma(SCH)is a common complication in early pregnancy characterized by the accumulation of blood between the uterine wall and the chorionic membrane.SCH can lead to adverse pregnancy outcomes such as miscarriage,preterm birth,and other complications.Early detection and accurate assessment of SCH are crucial for appropriate management and improved pregnancy outcomes.AIM To evaluate the diagnostic efficacy of virtual organ computer-assisted analysis(VOCAL)in measuring the volume ratio of SCH to gestational sac(GS)combined with serum progesterone on early pregnancy outcomes in patients with SCH.METHODS A total of 153 patients with SCH in their first-trimester pregnancies between 6 and 11 wk were enrolled.All patients were followed up until a gestational age of 20 wk.The parameters of transvaginal two-dimensional ultrasound,including the circumference of SCH(Cs),surface area of SCH(Ss),circumference of GS(Cg),and surface area of GS(Sg),and the parameters of VOCAL with transvaginal three-dimensional ultrasound,including the three-dimensional volume of SCH(3DVs)and GS(3DVg),were recorded.The size of the SCH and its ratio to the GS size(Cs/Cg,Ss/Sg,3DVs/3DVg)were recorded and compared.RESULTS Compared with those in the normal pregnancy group,the adverse pregnancy group had higher Cs/Cg,Ss/Sg,and 3DVs/3DVg ratios(P<0.05).When 3DVs/3DVg was 0.220,the highest predictive performance predicted adverse pregnancy outcomes,resulting in an AUC of 0.767,and the sensitivity,specificity were 70.2%,75%respectively.VOCAL measuring 3DVs/3DVg combined with serum progesterone gave a diagnostic AUC of 0.824 for early pregnancy outcome in SCH patients,with a high sensitivity of 82.1%and a specificity of 72.1%,which showed a significant difference between AUC.CONCLUSION VOCAL-measured 3DVs/3DVg effectively quantifies the severity of SCH,while combined serum progesterone better predicts adverse pregnancy outcomes.

Cookie Baking Process Optimization and Quality Analysis Based on Food 3D Printing

In order to obtain better quality cookies, food 3D printing technology was employed to prepare cookies. The texture, color, deformation, moisture content, and temperature of the cookie as evaluation indicators, the influences of baking process parameters, such as baking time, surface heating temperature and bottom heating temperature, on the quality of the cookie were studied to optimize the baking process parameters. The results showed that the baking process parameters had obvious effects on the texture, color, deformation, moisture content, and temperature of the cookie. All of the roasting surface heating temperature, bottom heating temperature and baking time had positive influences on the hardness, crunchiness, crispiness, and the total color difference(ΔE) of the cookie. When the heating temperatures of the surfac and bottom increased, the diameter and thickness deformation rate of the cookie increased. However,with the extension of baking time, the diameter and thickness deformation rate of the cookie first increased and then decreased. With the surface heating temperature of 180 ℃, the bottom heating temperature of 150 ℃, and baking time of 15 min, the cookie was crisp and moderate with moderate deformation and uniform color. There was no burnt phenomenon with the desired quality. Research results provided a theoretical basis for cookie manufactory based on food 3D printing technology.

Exploring the Relationship between Spatiotemporal Variations in Air Quality and Meteorological Parameters before and during the COVID-19 Pandemic in Xi’an

The COVID-19 pandemic has significantly changed the air pollution of the world. The present study investigated the temporal and spatial variability in air quality in Xi’an, China, and its relationship with meteorological parameters during and before the COVID-19 pandemic. The outcomes of this study indicated that air pollutants, PM2.5, NO2, PM10, CO, and SO2 are likely to decrease during winter (25%, 50%, 30%, 40%, and 35%) to spring (30%, 55%, 38%, 50%, and 40%) and summer (40%, 58%, 60%, 55%, and 47%), respectively. However, the concentration of O3-8h increased by 40%, 55%, and 65% during winter, spring, and summer, respectively. The values of the air quality index decreased during the COVID-19 period. Furthermore, significant positive trends were reported in PM2.5, NO2, PM10, O3, and SO2, and no notable trends in CO during the COVID-19 pandemic. Both during and before the COVID-19 period, PM10, NO2, PM2.5, CO, and SO2 showed a negative correlation with the temperature and a moderately positive significant correlation between O3-8h and temperature. The findings of this study would help understand the air pollution circumstances in Xi’an before and during the COVID-19 period and offer helpful information regarding the implications of different air pollution control strategies.

Parameter sensitivity analysis for a biochemically-based photosynthesis model

A challenge for the development of Land Surface Models(LSMs) is improving transpiration of water exchange and photosynthesis of carbon exchange between terrestrial plants and the atmosphere, both of which are governed by stoma in leaves. In the photosynthesis module of these LSMs, variations of parameters arising from diversity in plant functional types(PFTs) and climate remain unclear. Identifying sensitive parameters among all photosynthetic parameters before parameter estimation can not only reduce operation cost, but also improve the usability of photosynthesis models worldwide. Here, we analyzed 13 parameters of a biochemically-based photosynthesis model(FvCB), implemented in many LSMs, using two sensitivity analysis(SA) methods(i.e., the Sobol’ method and the Morris method) for setting up the parameter ensemble. Three different model performance metrics, i.e.,Root Mean Squared Error(RMSE), Nash Sutcliffe efficiency(NSE), and Standard Deviation(STDEV) were introduced for model assessment and sensitive parameters identification. The results showed that among all photosynthetic parameters only a small portion of parameters were sensitive, and the sensitive parameters were different across plant functional types: maximum rate of Rubisco activity(Vcmax25), maximum electron transport rate(Jmax25), triose phosphate use rate(TPU) and dark respiration in light(Rd) were sensitive in broad leafevergreen trees(BET), broad leaf-deciduous trees(BDT) and needle leaf-evergreen trees(NET), while only Vcmax25and TPU are sensitive in short vegetation(SV), dwarf trees and shrubs(DTS), and agriculture and grassland(AG). The two sensitivity analysis methods suggested a strong SA coherence;in contrast, different model performance metrics led to different SA results. This misfit suggests that more accurate values of sensitive parameters, specifically, species specific and seasonal variable parameters, are required to improve the performance of the FvCB model.

Analysis of Additional Damping Control Strategy and Parameter Optimization for Improving Small Signal Stability of VSC-HVDC System

The voltage source converter based high voltage direct current(VSC-HVDC)system is based on voltage source converter,and its control system is more complex.Also affected by the fast control of power electronics,oscillation phenomenon in wide frequency domain may occur.To address the problem of small signal stability of the VSCHVDC system,a converter control strategy is designed to improve its small signal stability,and the risk of system oscillation is reduced by attaching a damping controller and optimizing the control parameters.Based on the modeling of the VSC-HVDC system,the general architecture of the inner and outer loop control of the VSCHVDC converter is established;and the damping controllers for DC control and AC control are designed in the phase-locked loop and the inner and outer loop control parts respectively;the state-space statemodel of the control system is established to analyze its performance.And the electromagnetic transient simulation model is built on the PSCAD/EMTDC simulation platform to verify the accuracy of the small signal model.The influence of the parameters of each control part on the stability of the system is summarized.The main control parts affecting stability are optimized for the phenomenon of oscillation due to changes in operation mode occurring on the AC side due to faults and other reasons,which effectively eliminates system oscillation and improves system small signal stability,providing a certain reference for engineering design.

Singular analysis of bifurcation systems with two parameters

Bifurcation properties of dynamical systems with two parameters are investigated in this paper. The definition of transition set is proposed, and the approach developed is used to investigate the dynamic characteristic of the nonlin- ear forced Duffing system with nonlinear feedback controller. The whole parametric plane is divided into several persistent regions by the transition set, and then the bifurcation dia- grams in different persistent regions are obtained.

Fuzzy finite difference method for heat conduction analysis with uncertain parameters

A new numerical technique named as fuzzy finite difference method is proposed to solve the heat conduction problems with fuzzy uncertainties in both the phys- ical parameters and initial/boundary conditions. In virtue of the level-cut method, the difference discrete equations with fuzzy parameters are equivalently transformed into groups of interval equations. New stability analysis theory suited to fuzzy difference schemes is developed. Based on the parameter perturbation method, the interval ranges of the uncertain temperature field can be approximately predicted. Subsequently, fuzzy solutions to the original difference equations are obtained by the fuzzy resolution theorem. Two numerical examples are given to demonstrate the feasibility and efficiency of the presented method for solving both steady-state and transient heat conduction problems.

An Inverse Analysis of the Comprehensive Medium Parameters and a Simulation of the Crustal Deformation of the Qinghai-Tibet Plateau

Based on the theory of finite element analysis, an inverse analysis model for the comprehensive medium parameters of the Qinghai-Tibet Plateau is set up. With the help of GPS velocity field, the comprehensive crustal medium parameters of the plateau are inversely analyzed and the characteristics of the related movement macroscopically simulated. It is then concluded that the tectonic deformation of the plateau is mainly in the form of a N-S compression accompanied by an E-W stretching, and the present tectonic setting of the plateau should be the result of the collision between the Indian and the Eurasian continents during the Cenozoic.

Intelligent direct analysis of physical and mechanical parameters of tunnel surrounding rock based on adaptive immunity algorithm and BP neural network

Because of complexity and non-predictability of the tunnel surrounding rock, the problem with the determination of the physical and mechanical parameters of the surrounding rock has become a main obstacle to theoretical research and numerical analysis in tunnel engineering. During design, it is a frequent practice, therefore, to give recommended values by analog based on experience. It is a key point in current research to make use of the displacement back analytic method to comparatively accurately determine the parameters of the surrounding rock whereas artificial intelligence possesses an exceptionally strong capability of identifying, expressing and coping with such complex non-linear relationships. The parameters can be verified by searching the optimal network structure, using back analysis on measured data to search optimal parameters and performing direct computation of the obtained results. In the current paper, the direct analysis is performed with the biological emulation system and the software of Fast Lagrangian Analysis of Continua (FLAC3D. The high non-linearity, network reasoning and coupling ability of the neural network are employed. The output vector required of the training of the neural network is obtained with the numerical analysis software. And the overall space search is conducted by employing the Adaptive Immunity Algorithm. As a result, we are able to avoid the shortcoming that multiple parameters and optimized parameters are easy to fall into a local extremum. At the same time, the computing speed and efficiency are increased as well. Further, in the paper satisfactory conclusions are arrived at through the intelligent direct-back analysis on the monitored and measured data at the Erdaoya tunneling project. The results show that the physical and mechanical parameters obtained by the intelligent direct-back analysis proposed in the current paper have effectively improved the recommended values in the original prospecting data. This is of practical significance to the appraisal of stability and informationization design of the surrounding rock.

Estimation of forest parameters based on TM imagery and statistical analysis

One of the primary forestry research interests lies in estimating forest stand parameters by applying empirical or semi-empirical model to establish the relationship between the forest stand parameters and remote sensing data. Using remote sensing image and the inventory data from 2 compartments in northeast Florida, U.S.A., this paper explored the correlation between forest stand parameters and Landsat TM spectral digital number （DN） value. Results showed that less than 50% of the total variance could be explained by linear regression models with only either a single band or such vegetation indices as vegetation index （VI） or normalized difference vegetation index （NDVI） as predicators. In consequence, multi-linear regression models which synthesized more predicators were introduced to estimate forest parameters. Regression results were tested in terms of the other group of data, and verification showed a better capability of explaining over 75% variance except for forest density. The weakness and further improvement of prediction models were also discussed in the article. This paper is expected to provide a better understanding of the relationship between TM spectral and forest characteristics

Probabilistic model and analysis of coupled train-ballasted track-subgrade system with uncertain structural parameters

Random dynamic responses caused by the uncertainty of structural parameters of the coupled train-ballasted track-subgrade system under train loading can pose safety concerns to the train operation.This paper introduced a computational model for analyzing probabilistic dynamic responses of three-dimensional(3D)coupled train-ballasted track-subgrade system(TBTSS),where the coupling effects of uncertain rail irregularities,stiffness and damping properties of ballast and subgrade layers were simultaneously considered.The number theoretical method(NTM)was employed to design discrete points for the multi-dimensional stochastic parameters.The time-histories of stochastic dynamic vibrations of the TBSS with systematically uncertain structural parameters were calculated accurately and efficiently by employing the probability density evolution method(PDEM).The model-predicted results were consistent with those by the Monte Carlo simulation method.A sensitivity study was performed to assess the relative importance of those uncertain structural parameters,based on which a case study was presented to explore the stochastic probability evolution mechanism of such train-ballasted track-subgrade system.

Optimal analysis conditions for sperm motility parameters with a CASA system in a passerine bird, Passer montanus

Background:Sperm motility parameters,which can be measured objectively and repeatedly by a computer-assisted sperm analysis(CASA)system,are important indicators of sperm quality.However,the sperm motility parameters assessed by a CASA system can be affected by various factors,including instrument components and settings,sperm preparation or analysis procedures.To date,no standardized protocol is available that would permit to assess sperm kinetic characteristics in passerine birds and this lack precludes any comparison of sperm swimming ability and sperm quality across species.Methods:In this study,we chose the Tree Sparrow(Passer montanus)as the object to evaluate sperm motility parameters,including sperm motility,sperm velocity and sperm movement trajectory,at different analysis time,temperatures and pH using the WLJY-9000 CASA system.Results:Sperm motility parameters remained statistically unchanged at 1‒9 min.Progressive motility was similar at 38℃ and 40℃,but a greater percentage of slow progressive sperm was detected at 38℃ compared to 40℃ and 42℃.Additionally,progressive motility was lower and immotility was higher at 42℃than 38℃and/or 40℃(close to the body temperature of the Tree Sparrow).The percentages of rapid progressive sperm,progressive sperm and immotile sperm were statistically similar at pH 7.0,7.5 and 8.0 with the exception of lower percentage of progressive sperm at pH 7.0 compared to pH 7.5.In addition,slower sperm velocity and worse sperm movement trajectory were found at pH 6.0 and 9.0 than those at pH 8.0,7.5 or 7.0.Conclusions:Our study indicates that the ideal conditions for sperm motility parameters assessment in Tree Sparrow are obtained between 1 and 9 min after dilution,an environment at body temperature(40℃)and a pH around 7.5-8.0.The results of this study provide a reference for the evaluation of sperm characteristics and sperm quality using a CASA system in passerine birds.

Sensitivity analysis for parameters of a monitoring system for steep slopes of open-pit mines

Monitoring the stability of steep slopes of open-pit mines is a major issue relating to production safety in mines.In order to determine the technical parameters of a new type of supervising system applied in monitoring steep slopes of open-pit mines,the MSARMA method was used to establish analytical models for the monitoring system,given various parameter settings based on the description of mechanical monitoring principles.We used this sensitivity analysis to conclude that the setting of the most sensitive location of a mechanical monitoring system should be within a range of 1/5～1/2 of the lower part in a vertical direction of steep slopes,with a rational and feasible range of the dip angle setting between 0°～20°.Given the analytical results of our on-site experiments,we have shown that the parameters determined reflect the stability of steep slopes accurately and effectively.These conclusions provide a basis for the application of a new type of steep slope stability monitoring technology in open-pit mines.

Calibration and uniqueness analysis of microparameters for DEM cohesive granular material

The differential evolution(DE)algorithm was deployed to calibrate microparameters of the DEM cohesive granular material.4 macroparameters,namely,uniaxial compressive strength,direct tensile strength,Young’s modulus and Poisson’s ratio,can be calibrated to high accuracy.The best calibration accuracy could reach the sum of relative errors RE_(sum)<0.1%.Most calibrations can be achieved with RE_(sum)<5%within hours or RE_(sum)<1%within 2 days.Based on the calibrated results,microparameters uniqueness analysis was carried out to reveal the correlation between microparameters and the macroscopic mechanical behaviour of material:(1)microparameters effective modulus,tensile strength and normal-to-shear stiffness ratio control the elastic behaviour and stable crack growth,(2)microparameters cohesion and friction angles present a negative linear correlation that controls the axial strain and lateral strain prior to the peak stress,and(3)microparameters friction coefficient controls shear crack friction and slip mainly refers to the unstable crack behaviour.Consideration of more macroparameters to regulate the material mechanical behaviour that is dominated by shear crack and slip motion is highlighted for future study.The DE calibration method is expected to serve as an alternative method to calibrate the DEM cohesive granular material to its peak strength.

Observability Analysis in Parameters Estimation of an Uncooperative Space Target

To study the parameter estimating effects of a free-floating tumbling space target,the extended Kalman filter(EKF)scheme is utilized with different high-nonlinear translational and rotational coupled kinematic&dynamic models on the LIDAR measurements.Applying the aforementioned models and measurements results in the situation where one single state can be estimated differently with varying accuracies since the EKFs based on different models have different observabilities.In the proposed EKFs,the traditional quaternions based kinematics and dynamics and the dual vector quaternions(DVQ)based kinematics and dynamics are used for the modeling of the relative motions between a chaser satellite and an uncooperative target.In the non-contact estimating scenarios,only highly nonlinear relative attitude and range measurements:the grapple fixture on the target measured from the chaser satellite via vision-based sensors,can be used.By evaluating the results of the EKFs,the observability properties of each EKF are studied analytically and numerically with the the Observability Gramian matrices(OG)and the standard deviations for every estimated parameters.The analysis of observability perform intensive studies and reveal the intrinsic factors that affect the accuracy and stability of the parameters estimation of an uncooperative space target.Finally,the analytical and numerical results show the optimal composition of the kinematic&dynamic models and measurements.

Singularity analysis of Duffing-van der Pol system with two bifurcation parameters under multi-frequency excitations

Bifurcation properties of a Duffing-van der Pol system with two parameters under multi-frequency excitations are studied. Three cases are discussed： （1） λ 1 is considered as bifurcation parameter, （2） λ 2 is considered as bifurcation parameter, and （3） λ 1 and λ 2 are both considered as bifurcation parameters. According to the definition of transition sets, the whole parametric space is divided into several different persistent regions by the transition sets for different cases. The bifurcation diagrams in different persistent regions are obtained, which provides a theoretical basis for optimal design of the system.

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.