A detailed rock density model of the Hong Kong territories

We used the geological map and published rock density measurements to compile the digital rock density model for the Hong Kong territories.We then estimated the average density for the whole territory.According to our result,the rock density values in Hong Kong vary from 2101 to 2681 kg·m^(-3).These density values are typically smaller than the average density of 2670 kg·m^(-3),often adopted to represent the average density of the upper continental crust in physical geodesy and gravimetric geophysics applications.This finding reflects that the geological configuration in Hong Kong is mainly formed by light volcanic formations and lava flows with overlying sedimentary deposits at many locations,while the percentage of heavier metamorphic rocks is very low(less than 1%).This product will improve the accuracy of a detailed geoid model and orthometric heights.

Speed limit effect during lane change in a two-lane lattice model under V2X environment

Speed limit measures are ubiquitous due to the complexity of the road environment,which can be supplied with the help of vehicle to everything(V2X)communication technology.Therefore,the influence of speed limit on traffic system will be investigated to construct a two-lane lattice model accounting for the speed limit effect during the lane change process under V2X environment.Accordingly,the stability condition and the mKdV equation are closely associated with the speed limit effect through theory analysis.Moreover,the evolution of density and hysteresis loop is simulated to demonstrate the positive role of the speed limit effect on traffic stability in the cases of strong reaction intensity and high limited speed.

Relationships between Terrain Features and Forecasting Errors of Surface Wind Speeds in a Mesoscale Numerical Weather Prediction Model

Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SMS-WARR(Shanghai Meteorological Service-WRF ADAS Rapid Refresh System),are analyzed to quantitatively reveal the relationships between the forecasted surface wind speed errors and terrain features,with the intent of providing clues to better apply the NWP model to complex terrain regions.The terrain features are described by three parameters:the standard deviation of the model grid-scale orography,terrain height error of the model,and slope angle.The results show that the forecast bias has a unimodal distribution with a change in the standard deviation of orography.The minimum ME(the mean value of bias)is 1.2 m s^(-1) when the standard deviation is between 60 and 70 m.A positive correlation exists between bias and terrain height error,with the ME increasing by 10%−30%for every 200 m increase in terrain height error.The ME decreases by 65.6%when slope angle increases from(0.5°−1.5°)to larger than 3.5°for uphill winds but increases by 35.4%when the absolute value of slope angle increases from(0.5°−1.5°)to(2.5°−3.5°)for downhill winds.Several sensitivity experiments are carried out with a model output statistical(MOS)calibration model for surface wind speeds and ME(RMSE)has been reduced by 90%(30%)by introducing terrain parameters,demonstrating the value of this study.

Numerical analysis of high‑speed railway slab tracks using calibrated and validated 3D time‑domain modelling

Concrete slabs are widely used in modern railways to increase the inherent resilient quality of the tracks,provide safe and smooth rides,and reduce the maintenance frequency.In this paper,the elastic performance of a novel slab trackform for high-speed railways is investigated using three-dimensional finite element modelling in Abaqus.It is then compared to the performance of a ballasted track.First,slab and ballasted track models are developed to replicate the full-scale testing of track sections.Once the models are calibrated with the experimental results,the novel slab model is developed and compared against the calibrated slab track results.The slab and ballasted track models are then extended to create linear dynamic models,considering the track geodynamics,and simulating train passages at various speeds,for which the Ledsgard documented case was used to validate the models.Trains travelling at low and high speeds are analysed to investigate the track deflections and the wave propagation in the soil,considering the issues associated with critical speeds.Various train loading methods are discussed,and the most practical approach is retained and described.Moreover,correlations are made between the geotechnical parameters of modern high-speed rail and conventional standards.It is found that considering the same ground condition,the slab track deflections are considerably smaller than those of the ballasted track at high speeds,while they show similar behaviour at low speeds.

Asymptotic normality of error density estimator in stationary and explosive autoregressive models

In this paper,we consider the limit distribution of the error density function estima-tor in the rst-order autoregressive models with negatively associated and positively associated random errors.Under mild regularity assumptions,some asymptotic normality results of the residual density estimator are obtained when the autoregressive models are stationary process and explosive process.In order to illustrate these results,some simulations such as con dence intervals and mean integrated square errors are provided in this paper.It shows that the residual density estimator can replace the density\estimator"which contains errors.

A novel refined dynamic model of high-speed maglev train-bridge coupled system for random vibration and running safety assessment

Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can be well characterized based on various stochastic excitations.A three-dimensional refined spatial random vibration analysis model of high-speed maglev train-bridge coupled system is established in this paper,in which multi-source uncertainty excitation can be considered simultaneously,and the probability density evolution method(PDEM)is adopted to reveal the system-specific uncertainty dynamic characteristic.The motion equation of the maglev vehicle model is composed of multi-rigid bodies with a total 210-degrees of freedom for each vehicle,and a refined electromagnetic force-air gap model is used to account for the interaction and coupling effect between the moving train and track beam bridges,which are directly established by using finite element method.The model is proven to be applicable by comparing with Monte Carlo simulation.By applying the proposed stochastic framework to the high maglev line,the random dynamic responses of maglev vehicles running on the bridges are studied for running safety and stability assessment.Moreover,the effects of track irregularity wavelength range under different amplitude and running speeds on the coupled system are investigated.The results show that the augmentation of train speed will move backward the sensitive wavelength interval,and track irregularity amplitude influences the response remarkably in the sensitive interval.

Modelling the response of larch growth to age,density,and elevation and the implications for multifunctional management in northwest China

Plantations of Rupprecht's larch(Larix principis-rupprechtii)have been widely established in the drylands of northwest and north China under traditional fastgrowing plantation management strategies.These strategies and the long-term logging ban have led to over-populated stands with lower structural and functional stability,less economic benefit and higher water consumption.To guide the sustainable management of larch plantations,field surveys and historical data compilation were undertaken in the Liupan Mountains of northwest China.The main influencing factors(stand structure and site condition)and their effects on mean tree height,mean DBH and timber volumes were determined based on up-boundary line analysis.Tree growth models coupling the effects of tree age,stand density,and elevation were established.Both height and DBH markedly increased initially and then slowly with tree age,decreased with stand density,and showed unimodal change with elevation.The coupled growth models accounted for72-78%of the variations in tree height,DBH and timber growth.Recommendations for future plantation management are:(1)prolong the rotation to at least 60 years to produce large-diameter,high-quality timber and maintain greater carbon stocks;(2)zone the target functions of stands by elevation;and,(3)reduce stand density for balanced supply of multiple ecosystem services.The growth models developed can predict growth response of larch plantations to density alteration under given ages and elevations,and assist the transformation from traditional management for maximum timber production to site-specific and multifunctional management with longer rotations and moderate tree density.

Spreading speed of a food-limited population model with delay

This paper is concerned with the spreading speed of a food-limited population model with delay.First,the existence of the solution of Cauchy problem is proved.Then,the spreading speed of solutions with compactly supported initial data is investigated by using the general Harnack inequality.Finally,we present some numerical simulations and investigate the dynamical behavior of the solution.

Wind Speed Prediction Using Chicken Swarm Optimization with Deep Learning Model

High precision and reliable wind speed forecasting have become a challenge for meteorologists.Convective events,namely,strong winds,thunderstorms,and tornadoes,along with large hail,are natural calamities that disturb daily life.For accurate prediction of wind speed and overcoming its uncertainty of change,several prediction approaches have been presented over the last few decades.As wind speed series have higher volatility and nonlinearity,it is urgent to present cutting-edge artificial intelligence(AI)technology.In this aspect,this paper presents an intelligent wind speed prediction using chicken swarm optimization with the hybrid deep learning(IWSP-CSODL)method.The presented IWSP-CSODL model estimates the wind speed using a hybrid deep learning and hyperparameter optimizer.In the presented IWSP-CSODL model,the prediction process is performed via a convolutional neural network(CNN)based long short-term memory with autoencoder(CBLSTMAE)model.To optimally modify the hyperparameters related to the CBLSTMAE model,the chicken swarm optimization(CSO)algorithm is utilized and thereby reduces the mean square error(MSE).The experimental validation of the IWSP-CSODL model is tested using wind series data under three distinct scenarios.The comparative study pointed out the better outcomes of the IWSP-CSODL model over other recent wind speed prediction models.

A Statistical Analysis of Wind Speed and Power Density Based on Weibull and Rayleigh Models of Jumla, Nepal

In the present study, wind speed data of Jumla, Nepal have been statistically analyzed. For this purpose, the daily averaged wind speed data for 10 year period (2004-2014: 2012 excluded) provided by Department of Hydrology and Meteorology (DHM) was analyzed to estimate wind power density. Wind speed as high as 18 m/s was recorded at height of 10 m. Annual mean wind speed was ascertained to be decreasing from 7.35 m/s in 2004 to 5.13 m/s in 2014 as a consequence of Global Climate Change. This is a subject of concern looking at government’s plan to harness wind energy. Monthly wind speed plot shows that the fastest wind speed is generally in month of June (Monsoon Season) and slowest in December/January (Winter Season). Results presented Weibull distribution to fit measured probability distribution better than the Rayleigh distribution for whole years in High altitude region of Nepal. Average value of wind power density based on mean and root mean cube seed approaches were 131.31 W/m2/year and 184.93 W/m2/year respectively indicating that Jumla stands in class III. Weibull distribution shows a good approximation for estimation of power density with maximum error of 3.68% when root mean cube speed is taken as reference.

Behaviour of non-ballast pre-stressed and precast track structures in high speed railway based on multiscale finite element model

In order to make further study on the mechanical property of CRTSIII type slab non-ballast track structures,which was self-designed in China,based on the method of the multiscale finite element model(FEM),the traditional FEM of slab non-ballast track structures was improved.The multiscale FEM of CRTSII type slab nonballast track structures was established based on the general finite element program ABAQUs.Then the comparative calculation was made between various FEMs,showing that the high solution precision,fast modelling speed and high solution efficiency could be obtained.Therefore,the multiscale FEM was suitable for the parametric study on mechanical behaviour of CRTSII type slab non-ballast track structures,and then the key influence factor and constructions could be optimized.

Synergistic effects of planting density and nitrogen fertilization on chlorophyll degradation and leaf senescence after silking in maize

Regulating planting density and nitrogen(N)fertilization could delay chlorophyll(Chl)degradation and leaf senescence in maize cultivars.This study measured changes in ear leaf green area(GLA_(ear)),Chl content,the activities of Chl a-degrading enzymes after silking,and the post-silking dry matter accumulation and grain yield under multiple planting densities and N fertilization rates.The dynamic change of GLA_(ear)after silking fitted to the logistic model,and the GLA_(ear) duration and the GLAearat 42 d after silking were affected mainly by the duration of the initial senescence period(T_(1))which was a key factor of the leaf senescence.The average chlorophyllase(CLH)activity was 8.3 times higher than pheophytinase activity and contributed most to the Chl content,indicating that CLH is a key enzyme for degrading Chl a in maize.Increasing density increased the CLH activity and decreased the Chl content,T1,GLAear,and GLA_(ear) duration.Under high density,appropriate N application reduced CLH activity,increased Chl content,prolonged T1,alleviated high-density-induced leaf senescence,and increased post-silking dry matter accumulation and grain yield.

Fine Sand and Clay Sediment Acoustic Properties of the Novel Sediment Sample from the Arabian Sea:Experimental Investigations and Biot−Stoll Model Validation

The present study explores the physical and acoustic characteristics of fine sand and clay in novel seabed marine sediments from of Pakistan coastline of the Arabian Sea.The measured physical parameters included mean grain size,mass density,bulk density,salinity,porosity,permeability,pore size and mineralogical composition.Acoustic properties,including sound speed and attenuation,in the high frequency range of 90-170 kHz were analyzed.A controlled laboratory setup with the acoustic transmission method and Fourier transform techniques was utilized to examine the sound propagation and absorption of novel seabed sediments.The standard deviation of mean sound speed in fresh water was 0.75 m/s,and attenuation was observed in the range of 0.43 to 0.61 dB/m.The mean sound velocity in sand and clay varied from 1706 to 1709 m/s and 1602 to 1608 m/s,respectively.Corresponding average attenuation was observed at 80 to 93 dB/m in sandy sediments and from 31.8 to 38.6 dB/m in clayey sediments.Sound velocity variation within sandy sediment is low,consistent with expected results,and smaller than the predicted uncertainty.However,clay sediment exhibited a positive linear correlation and low sound speed variation.Attenuation increased linearly with frequency for both sediments.Finally,the laboratory results were validated by using the Biot−Stoll model.The dispersion of sound speed in sandy and clayey sediments was consistent with the predictions of the Biot−Stoll model.Measured attenuation aligned more with Biot−Stoll model predictions due to improved permeability,tortuosity and pore size parameter fitting.

Factors affecting land dissection density in geomorphological regions of China

Land dissection density(LDD)provides morphological evidence regarding prior intense soil erosion and quantifies the distribution of land dissections.A comprehensive understanding of the potential factors influencing the spatial pattern and value of the LDD is vital in geological disasters,soil erosion,and other related domains.Land dissection phenomena in China affects large areas with different morphological,pedological,and climatic characteristics.Prior studies have focused on the potential factors influencing the LDD at a watershed scale.However,these results are insufficient to reflect the status quo of dissection development and its primary influencing factors on a national scale.LDD’s spatial patterns and the dominant factors at a regional scale in millions of square kilometers remain to be ascertained.This study used the geomorphon-based method and the geographical detector model to quantify the spatial pattern of LDD over China and identify the dominant factors affecting this pattern in China’s six first-order geomorphological regions(GR1~GR6).The results yield the following findings:(1)LDD in China ranges from 0~4.55 km/km^(2),which is larger in central and eastern regions than in other regions of China;(2)dominant factors and their dominant risk subcategories vary with each geomorphological region’s primary internal and external forces;(3)the influence of natural factors is more significant on the large regional scale in millions of square kilometers compared to anthropogenic factors;relief degree of land surface(RDLS)is dominant in GR1,GR2,and GR5;the slope is dominant in GR6,soil type is dominant in GR3 and GR4,and lithology plays a critical role in the dominant interactions of GR3,GR4,and GR6;(4)the interactions between factors on LDD’s spatial pattern have a more significant effect than individual factors.

Separation density prediction of geldart A^(-)dense medium in gas-solid fluidized bed coal beneficiators

Gas-solid Fluidized Bed Coal Beneficiator(GFBCB)process is a crucial dry coal beneficiation fluidization technology.The work employs the GFBCB process alongside a novel Geldart A^(-)dense medium,consisting of Geldart A magnetite particles and Geldart C ultrafine coal,to separate small-size separated objects in the GFBCB.The effects of various operational conditions,including the volume fraction of ultrafine coal,the gas velocity,the separated objects size,and the separation time,were investigated on the GFBCB's separation performance.The results indicated that the probable error for 6∼3 mm separated objects could be controlled within 0.10 g/cm^(3).Compared to the traditional Geldart B/D dense medium,the Geldart A/A^(-)dense medium exhibited better size-dependent separation performance with an overall probable error 0.04∼0.12 g/cm^(3).Moreover,it achieved a similar separation accuracy to the Geldart B/D dense medium fluidized bed with different external energy for the small-size object beneficiation.The work furthermore validated a separation density prediction model based on theoretical derivation,available for both Geldart B/D dense medium and Geldart A/A^(-)dense medium at different operational conditions.

Multiple model PHD filter for tracking sharply maneuvering targets using recursive RANSAC based adaptive birth estimation

An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as drones and agile missiles.The probability hypothesis density (PHD) filter, which propagates only the first-order statistical moment of the full target posterior, has been shown to be a computationally efficient solution to multitarget tracking problems. However, the standard PHD filter operates on the single dynamic model and requires prior information about target birth distribution, which leads to many limitations in terms of practical applications. In this paper,we introduce a nonzero mean, white noise turn rate dynamic model and generalize jump Markov systems to multitarget case to accommodate sharply maneuvering dynamics. Moreover, to adaptively estimate newborn targets’information, a measurement-driven method based on the recursive random sampling consensus (RANSAC) algorithm is proposed. Simulation results demonstrate that the proposed method achieves significant improvement in tracking multiple sharply maneuvering targets with adaptive birth estimation.

Wind Potential Modeling at Kanfarandé Site in the Republic of Guinea

The purpose of this work is to assess wind potential on the Kanfarandé site (Guinea). The data used for this research covers a period of 6 years (2018 to 2023) and consists of in situ data (Boké meteorological station) and satellite products via NASA Power Larc. The study is based on sorted hourly data (speed and direction). The treatments focus on the monthly, annual and seasonal average of speeds, by sector and their frequencies as well as the annual available powers. The obtained results made it possible, on the one hand, to assess wind potential and, on the other hand, to highlight the most favorable periods for wind energy exploitation. The analyzes show the months of July and August have the best average wind speeds with 5.01 m/s and 5.34 m/s respectively. Average wind speeds are higher during the day than at night with a peak observed at 6 p.m. The study also shows that the prevailing winds are oriented towards the South-West. The Weibull parameters determined for the site give an average of 4.5 m/s for the scale parameter and for the shape parameter 2.40 corresponding to an average power density of 65 w/m2 with an annual available power of 194.80 W/m2 and an annual available energy of 1706.45 kWh/m2.

Effect of the Density of Molten Metal on the Raining Phenomenon in Horizontal Centrifugal Casting

In this work the influence of the density of the molten metal on the emergence of the raining phenomenon in the horizontal centrifugal casting process is numerically studied. Transient 2D numerical simulations were carried out using Computational Fluid Dynamics software. Three molten metals with different density, namely aluminum, iron and lead, and three angular frequencies, namely 50, 66 and 77 rad/s were considered. It is found that the density of the molten metal significantly affects the emergence, transient or permanent, of the rain phenomenon. However, the magnitude and duration of the rain phenomenon depend on the angular frequency of the rotating mold. Likewise, since gravitational forces affect the metal according to its density, the value of the critical rotation speed of the mold is also affected.

Incompressible Limit of the Oldroyd-B Model with Density-Dependent Viscosity

This paper studies the existence and uniqueness of local strong solutions to an Oldroyd-B model with density-dependent viscosity in a bounded domain Ω ⊂ Rd, d = 2 or 3 via incompressible limit, in which the initial data is “well-prepared” and the velocity field enjoys the slip boundary conditions. The main idea is to derive the uniform energy estimates for nonlinear systems and corresponding incompressible limit.

Mathematical Wave Functions and 3D Finite Element Modelling of the Electron and Positron

The wave/particle duality of particles in Physics is well known. Particles have properties that uniquely characterize them from one another, such as mass, charge and spin. Charged particles have associated Electric and Magnetic fields. Also, every moving particle has a De Broglie wavelength determined by its mass and velocity. This paper shows that all of these properties of a particle can be derived from a single wave function equation for that particle. Wave functions for the Electron and the Positron are presented and principles are provided that can be used to calculate the wave functions of all the fundamental particles in Physics. Fundamental particles such as electrons and positrons are considered to be point particles in the Standard Model of Physics and are not considered to have a structure. This paper demonstrates that they do indeed have structure and that this structure extends into the space around the particle’s center (in fact, they have infinite extent), but with rapidly diminishing energy density with the distance from that center. The particles are formed from Electromagnetic standing waves, which are stable solutions to the Schrödinger and Classical wave equations. This stable structure therefore accounts for both the wave and particle nature of these particles. In fact, all of their properties such as mass, spin and electric charge, can be accounted for from this structure. These particle properties appear to originate from a single point at the center of the wave function structure, in the same sort of way that the Shell theorem of gravity causes the gravity of a body to appear to all originate from a central point. This paper represents the first two fully characterized fundamental particles, with a complete description of their structure and properties, built up from the underlying Electromagnetic waves that comprise these and all fundamental particles.