The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.

Study of Oil-Bearing Drill Cuttings Cleaning and De-Oiling Treatment Method for Shale Gas Reservoirs

Due to its extensive use in shale gas exploration and development,oil-based drilling fluids generate large amounts of oil-bearing drill cuttings during the drilling process.The large amount of oil-bearing drill cuttings generated during the drilling process can lead to serious secondary contamination.In this study,a wetting agent FSC-6 with good hydrophobic and oleophobic properties was synthesized to construct an efficient oil removal system.For the first time,the mechanism of this system was analyzed by using the theory of adhesion function,interfacial tension and wettability.At the same time,a combined acoustic-chemical treatment process was applied to the wastewater and slag generated after the cleaning of the oil-bearing drill cuttings.The experimental results show that the application of this pollution-free technology can effectively solve the environmental pollution and resource recovery problems of oil-bearing drill cuttings.It meets the standard of drilling chips with oil content less than 2%in SY/T7422-2018“Oil-based drilling fluid drilling chips treatment system for oil and gas drilling equipment”.

Probability Distribution Characteristics of Strong Nonlinear Waves Under Typhoon Conditions in the Northern South China Sea

The generation and propagation mechanism of strong nonlinear waves in the South China Sea is an essential research area. In this study, the third-generation wave model WAVEWATCH Ⅲ is employed to simulate wave fields under extreme sea states. The model, integrating the ST6 source term, is validated against observed data, demonstrating its credibility. The spatial distribution of the occurrence probability of strong nonlinear waves during typhoons is shown, and the waves in the straits and the northeastern part of the South China Sea show strong nonlinear characteristics. The high-order spectral model HOS-ocean is employed to simulate the random wave surface series beneath five different platform areas. The waves during the typhoon exhibit strong nonlinear characteristics, and freak waves exist. The space-varying probability model is established to describe the short-term probability distribution of nonlinear wave series. The exceedance probability distributions of the wave surface beneath different platform areas are compared and analyzed. The results show that with an increase in the platform area, the probability of a strong nonlinear wave beneath the platform increases.

Probability Laws Derived from the Gamma Function

Several densities or probability laws of continuous random variables derive from the Euler Gamma function. These laws form the basis of sampling theory, namely hypothesis testing and estimation. Namely the gamma, beta, and Student law, through the chi-square law and the normal law are all distributions resulting from applications of Euleur functions.

On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.

High-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer based on probability density evolution method

This paper proposed an efficient research method for high-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer.Firstly,the dynamic model of projectile motion is established considering the flexible deformation of the barrel and the interaction between the projectile and the barrel.Subsequently,the accuracy of the dynamic model is verified based on the external ballistic projectile attitude test platform.Furthermore,the probability density evolution method(PDEM)is developed to high-dimensional uncertainty quantification of projectile motion.The engineering example highlights the results of the proposed method are consistent with the results obtained by the Monte Carlo Simulation(MCS).Finally,the influence of parameter uncertainty on the projectile disturbance at muzzle under different working conditions is analyzed.The results show that the disturbance of the pitch angular,pitch angular velocity and pitch angular of velocity decreases with the increase of launching angle,and the random parameter ranges of both the projectile and coupling model have similar influence on the disturbance of projectile angular motion at muzzle.

Integrating host biological and ecological variables to predict probability of haemosporidian infection in raptors

Variations in host traits that influence their exposure and susceptibility may impact probability of vector-transmitted diseases.Therefore,identifying the predictors of infection probability is necessary to understand the risk of disease outbreaks during expanding environmental perturbation.Here,we conducted a large survey based on microscopic examination and molecular analysis of haemosporidian parasite infection in raptors rescued at the Beijing Raptor Rescue Centre.Combining these data with biological and ecological variables of the raptors,we determined predictors that affect the probability of haemosporidian infection using generalized linear mixed models and multimodel inference.Our results showed that infection probability exhibited considerable variation across host species in raptors,and body mass,sex,and evolutionary history played relatively weaker roles in driving infection probability.Instead,activity pattern,age,geographic range size,migration distance,and nest type were important predictors of the probability of haemosporidian infection,and the role of each predictor differed in the three main haemosporidian genera(Plasmodium,Haemoproteus,and Leucocytozoon).This macro-ecological analysis will add to our understanding of host traits that influence the probability of avian haemosporidian infection and will help inform risk of emerging diseases.

Secrecy Outage Probability Minimization in Wireless-Powered Communications Using an Improved Biogeography-Based Optimization-Inspired Recurrent Neural Network

This paper focuses on wireless-powered communication systems,which are increasingly relevant in the Internet of Things(IoT)due to their ability to extend the operational lifetime of devices with limited energy.The main contribution of the paper is a novel approach to minimize the secrecy outage probability(SOP)in these systems.Minimizing SOP is crucial for maintaining the confidentiality and integrity of data,especially in situations where the transmission of sensitive data is critical.Our proposed method harnesses the power of an improved biogeography-based optimization(IBBO)to effectively train a recurrent neural network(RNN).The proposed IBBO introduces an innovative migration model.The core advantage of IBBO lies in its adeptness at maintaining equilibrium between exploration and exploitation.This is accomplished by integrating tactics such as advancing towards a random habitat,adopting the crossover operator from genetic algorithms(GA),and utilizing the global best(Gbest)operator from particle swarm optimization(PSO)into the IBBO framework.The IBBO demonstrates its efficacy by enabling the RNN to optimize the system parameters,resulting in significant outage probability reduction.Through comprehensive simulations,we showcase the superiority of the IBBO-RNN over existing approaches,highlighting its capability to achieve remarkable gains in SOP minimization.This paper compares nine methods for predicting outage probability in wireless-powered communications.The IBBO-RNN achieved the highest accuracy rate of 98.92%,showing a significant performance improvement.In contrast,the standard RNN recorded lower accuracy rates of 91.27%.The IBBO-RNN maintains lower SOP values across the entire signal-to-noise ratio(SNR)spectrum tested,suggesting that the method is highly effective at optimizing system parameters for improved secrecy even at lower SNRs.

A self-organization formation configuration based assignment probability and collision detection

The formation control of multiple unmanned aerial vehicles(multi-UAVs)has always been a research hotspot.Based on the straight line trajectory,a multi-UAVs target point assignment algorithm based on the assignment probability is proposed to achieve the shortest overall formation path of multi-UAVs with low complexity and reduce the energy consumption.In order to avoid the collision between UAVs in the formation process,the concept of safety ball is introduced,and the collision detection based on continuous motion of two time slots and the lane occupation detection after motion is proposed to avoid collision between UAVs.Based on the idea of game theory,a method of UAV motion form setting based on the maximization of interests is proposed,including the maximization of self-interest and the maximization of formation interest is proposed,so that multi-UAVs can complete the formation task quickly and reasonably with the linear trajectory assigned in advance.Finally,through simulation verification,the multi-UAVs target assignment algorithm based on the assignment probability proposed in this paper can effectively reduce the total path length,and the UAV motion selection method based on the maximization interests can effectively complete the task formation.

Prediction and Output Estimation of Pattern Moving in Non-Newtonian Mechanical Systems Based on Probability Density Evolution

A prediction framework based on the evolution of pattern motion probability density is proposed for the output prediction and estimation problem of non-Newtonian mechanical systems,assuming that the system satisfies the generalized Lipschitz condition.As a complex nonlinear system primarily governed by statistical laws rather than Newtonian mechanics,the output of non-Newtonian mechanics systems is difficult to describe through deterministic variables such as state variables,which poses difficulties in predicting and estimating the system’s output.In this article,the temporal variation of the system is described by constructing pattern category variables,which are non-deterministic variables.Since pattern category variables have statistical attributes but not operational attributes,operational attributes are assigned to them by posterior probability density,and a method for analyzing their motion laws using probability density evolution is proposed.Furthermore,a data-driven form of pattern motion probabilistic density evolution prediction method is designed by combining pseudo partial derivative(PPD),achieving prediction of the probability density satisfying the system’s output uncertainty.Based on this,the final prediction estimation of the system’s output value is realized by minimum variance unbiased estimation.Finally,a corresponding PPD estimation algorithm is designed using an extended state observer(ESO)to estimate the parameters to be estimated in the proposed prediction method.The effectiveness of the parameter estimation algorithm and prediction method is demonstrated through theoretical analysis,and the accuracy of the algorithm is verified by two numerical simulation examples.

Calculation of Two-Tailed Exact Probability in the Wald-Wolfowitz One-Sample Runs Test

The objectives of this paper are to demonstrate the algorithms employed by three statistical software programs (R, Real Statistics using Excel, and SPSS) for calculating the exact two-tailed probability of the Wald-Wolfowitz one-sample runs test for randomness, to present a novel approach for computing this probability, and to compare the four procedures by generating samples of 10 and 11 data points, varying the parameters n0 (number of zeros) and n1 (number of ones), as well as the number of runs. Fifty-nine samples are created to replicate the behavior of the distribution of the number of runs with 10 and 11 data points. The exact two-tailed probabilities for the four procedures were compared using Friedman’s test. Given the significant difference in central tendency, post-hoc comparisons were conducted using Conover’s test with Benjamini-Yekutielli correction. It is concluded that the procedures of Real Statistics using Excel and R exhibit some inadequacies in the calculation of the exact two-tailed probability, whereas the new proposal and the SPSS procedure are deemed more suitable. The proposed robust algorithm has a more transparent rationale than the SPSS one, albeit being somewhat more conservative. We recommend its implementation for this test and its application to others, such as the binomial and sign test.

Flashover Probability of Wind Turbine Blade and Impact of Strong Electromagnetic Pulse from Lightning Strikes on Wind Turbine Safety

This paper systematically studies the flashover probability of wind turbine blade lightning arrester and the impact of strong electromagnetic pulses on the local and surrounding wind turbines during lightning strikes.The research results indicate that the flashover probability of direct lightning strikes by the wind turbine blade lightning arrester is almost negligible,and the strong electromagnetic pulse of wind turbine blade during lightning strikes has a serious impact on the electronic equipment of the machine,while the impact on the surrounding wind turbine is relatively small.At the same time,the calculation formula for the reflection of lightning current on the carbon brush between the wind turbine hub and the engine compartment during the flashing of the wind turbine blades is provided,and the calculation method for calculating the spatial gradient distribution of electromagnetic field intensity using Biot-Savart Law theorem is applied.The limitations of using wind turbine blades for lightning protection are pointed out,and a technical route for achieving wind turbine lightning safety is proposed,which can be used as a reference for wind turbine lightning protection technicians.

Probability Distribution of Ratio of China Aviation Network Edge Vertices Degree and Its Evolutionary Trace Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of ratio of China aviation network edge vertices degree were studied based on the statistics data of China civil aviation network in 1988, 1994, 2001, 2008 and 2015. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network. Based on the statistical data, the ratio of edge vertices degree in China aviation network in 1988, 1994, 2001, 2008 and 2015 were calculated. Using the probability statistical analysis method and regression analysis approach, it was found that the ratio of edge vertices degree had linear probability distribution and the two parameters of the probability distribution had linear evolution trace.

Fracture prediction approach for oil-bearing reservoirs based on AVAZ attributes in an orthorhombic medium

Fracture systems in nature are complicated. Normally vertical fractures develop in an isotropic background. However, the presence of horizontal fine layering or horizontal fractures in reservoirs makes the vertical fractures develop in a VTI（a transversely isotropic media with a vertical symmetry axis） background. In this case, reservoirs can be described better by using an orthorhombic medium instead of a traditional HTI（a transversely isotropic media with a horizontal symmetry axis） medium. In this paper, we focus on the fracture prediction study within an orthorhombic medium for oil-bearing reservoirs. Firstly, we simplify the reflection coefficient approximation in an orthorhombic medium. Secondly, the impact of horizontal fracturing on the reflection coefficient approximation is analyzed theoretically. Then based on that approximation, we compare and analyze the relative impact of vertical fracturing, horizontal fracturing and fluid indicative factor on traditional ellipse fitting results and the scaled B attributes. We find that scaled B attributes are more sensitive to vertical fractures, so scaled B attributes are proposed to predict vertical fractures. Finally, a test is developed to predict the fracture development intensity of an oil-bearing reservoir. The fracture development observed in cores is used to validate the study method. The findings of both theoretical analyses and practical application reveal that compared with traditional methods, this new approach has improved the prediction of fracture development intensity in oil-bearing reservoirs.

Origin and Distribution of Hydrogen Sulfide in Oil-Bearing Basins,China

The concentration of hydrogen sulfide gas （H2S） varies greatly in the oil-bearing basins of China, from zero to 90%. At present, oil and gas reservoirs with high H2S concentration have been discovered in three basins, viz. the Bohai Bay Basin, Sichuan Basin and the Tarim Basin, whereas natural gas with low H2S concentration has been found in the Ordos Basin, the Songliao Basin and the Junggar Basin. Studies suggest that in China H2S origin types are very complex. In the carbonate reservoir of the Sichuan Basin, the Ordos Basin and the Tarim Basin, as well as the carbonatedominated reservoir in the Luojia area of the Jiyang depression in the Bohai Bay Basin, Wumaying areas of the Huanghua depression, and Zhaolanzhuang areas of the Jizhong depression, the H2S is of Thermochemical Sulfate Reduction （TSR） origin. The H2S is of Bacterial Sulphate Reduction （BSR） origin deduced from the waterflooding operation in the Changheng Oilfield （placanticline oil fields） in the Songliao Basin. H2S originates from thermal decomposition of sulfur-bearing crude oil in the heavy oil area in the Junggar Basin and in the Liaohe heavy oil steam pilot area in the western depression of the Bohai Bay Basin. The origin types are most complex, including TSR and thermal decomposition of sulfcompounds among other combinations of causes. Various methods have been tried to identify the origin mechanism and to predict the distribution of H2S. The origin identification methods for H2S mainly comprise sulfur and carbon isotopes, reservoir petrology, particular biomarkers, and petroleum geology integrated technologies; using a combination of these applications can allow the accurate identification of the origins of H2S. The prediction technologies for primary and secondary origin of H2S have been set up separately.

Sedimentary facies and depositional model of shallow water delta dominated by fluvial for Chang 8 oil-bearing group of Yanchang Formation in southwestern Ordos Basin,China

A systematic analysis of southwestern Ordos Basin's sedimentary characteristics,internal architectural element association styles and depositional model was illustrated through core statistics,well logging data and outcrop observations in Chang 8 oil-bearing group.This analysis indicates that shallow water delta sediments dominated by a fluvial system is the primary sedimentary system of the Chang 8 oil-bearing group of the Yanchang Formation in southwestern Ordos Basin.Four microfacies with fine grain sizes are identified: distributary channels,sheet sandstone,mouth bar and interdistributary fines.According to the sandbody's spatial distribution and internal architecture,two types of sandbody architectural element associations are identified: amalgamated distributary channels and thin-layer lobate sandstone.In this sedimentary system,net-like distributary channels at the delta with a narrow ribbon shape compose the skeleton of the sandbody that extends further into the delta front and shades into contiguous lobate distribution sheet sandstone in the distal delta front.The mouth bar is largely absent in this system.By analyzing the palaeogeomorphology,the palaeostructure background,sedimentary characteristics,sedimentary facies types and spatial distribution of sedimentary facies during the Chang 8 period,a distinctive depositional model of the Chang 8 shallow water fluvial-dominated delta was established,which primarily consists of straight multi-phase amalgamated distributary channels in the delta plain,net-like distributary channels frequently diverting and converging in the proximal delta front,sheet sandstones with dispersing contiguous lobate shapes in the distal delta front,and prodelta or shallow lake mudstones.

Palaeotemperatures and Diagenetic Phases of the Upper Triassic Oil-bearing Sandstones in the Eastern Part of the Ordos Basin

The maximum palaeotemperature of oil-bearing sandstones in the UpperTriassic in the eastern Ordos basin has been determined by using many methods including thevitrinite reflectance, fluid inclusion, apatite fission track, illite crystallinity, chlorite polytypeand diagenetic change of authigenic minerals. The thermal gradient in the Late Mesozoic wasabout 2.9-3.0℃/100m. The Upper Triassic was in a mature stage of organic matter andhydrocarbon began to be generated and migrated during this period. The palaeotemperatures ofoil-bearing sandstones were in the range of 88-110℃; those for the generation and migrationof oil ranged from 112 to 122℃. The thickness of the denuded strata overlying the UpperTriassic was 2465-2750m. The present burial depth of oil-bearing sandstones is generally from400 to 1200m. At a depth of ca. 1900m, the temperature may reach 140℃. Below this depth,organic matter was supermature and mainly generated gas.

A Newly Discovered Oil-bearing Mesoproterozoic Erathem within the Niu D1 Well, Liaoxi Depression, Yanliao Faulted Depression Zone, NE China

Objective The Yanshan Fold Belt is located within the northern margin of the North China platform and contains welldeveloped and widespread Neoproterozoic and Mesoproterozoic sedimentary units with a total thickness of up to 9000 m.Previous studies identified many oil seedlings as well as asphalt and ancient hydrocarbon reservoirs in Northern Hebei depression and western Liaoning depression.This research indicates that the Mesoproterozoic and Neoproterozoic sedimentary units are ideally suited for the formation of significant oil and gas resources.The Niu D1 well was drilled by the China Geological Survey(CGS)in the Niuyingzi area and intercepted oil immersions and oil-and gas-bearing units within a limestone reservoir in the middle Proterozoic Gaoyuzhuang Formation(Fig.1).This study presents new biomarker compound and carbon isotope data that indicate that the oil within this formation was derived from hydrocarbon source rocks of the Hongshuizhuang Formation,part of the Mesoproterozoic Jixian Series,and the reservoir type is overthrust fault fractured anticline hydrocarbon reservoir.The oil reservoir within the Gaoyuzhuang Formation limestone might represent the oldest oil reservoir discovered to date within the Yanliao faulted depression zone.

Probability Density Analysis of Nonlinear Random Ship Rolling

Ship rolling in random waves is a complicated nonlinear motion that contributes substantially to ship instability and capsizing.The finite element method(FEM)is employed in this paper to solve the Fokker Planck(FP)equations numerically for homoclinic and heteroclinic ship rolling under random waves described as periodic and Gaussian white noise excitations.The transient joint probability density functions(PDFs)and marginal PDFs of the rolling responses are also obtained.The effects of stimulation strength on ship rolling are further investigated from a probabilistic standpoint.The homoclinic ship rolling has two rolling states,the connection between the two peaks of the PDF is observed when the periodic excitation amplitude or the noise intensity is large,and the PDF is remarkably distributed in phase space.These phenomena increase the possibility of a random jump in ship motion states and the uncertainty of ship rolling,and the ship may lose stability due to unforeseeable facts or conditions.Meanwhile,only one rolling state is observed when the ship is in heteroclinic rolling.As the periodic excitation amplitude grows,the PDF concentration increases and drifts away from the beginning location,suggesting that the ship rolling substantially changes in a cycle and its stability is low.The PDF becomes increasingly uniform and covers a large region as the noise intensity increases,reducing the certainty of ship rolling and navigation safety.The current numerical solutions and analyses may be applied to evaluate the stability of a rolling ship in irregular waves and capsize mechanisms.

Error Probability Analysis for Ultra-Massive MIMO System and Near-Optimal Signal Detection

In this paper,average bit error probability(ABEP)bound of optimal maximum likelihood(ML)detector is first derived for ultra massive(UM)multiple-input-multiple-output(MIMO)system with generalized amplitude phase modulation(APM),which is confirmed by simulation results.Furthermore,a minimum residual criterion(MRC)based lowcomplexity near-optimal ML detector is proposed for UM-MIMO system.Specifically,we first obtain an initial estimated signal by a conventional detector,i.e.,matched filter(MF),or minimum mean square error(MMSE)and so on.Furthermore,MRC based error correction mechanism(ECM)is proposed to correct the erroneous symbol encountered in the initial result.Simulation results are shown that the performance of the proposed MRC-ECM based detector is capable of approaching theoretical ABEP of ML,despite only imposing a slightly higher complexity than that of the initial detector.