Probability Density Function Distribution Research Articles

Assessing wind energy exploitation potential in several regions of Viet Nam using Kernel density estimation model

This article analyzes and assesses the potential for wind energy exploitation in six regions of Vietnam. The wind speed data are used to construct wind speed probability distributions (WSPDs) based on kernel density estimation (KDE). The KDE distribution, with six bandwidth selection methods, is implemented to generate probability density functions (PDFs) for each region's data to describe wind speed characteristics. The statistical tests Cramér-Von Mises (CvM), Anderson-Darling (A-D), and Kolmogorov-Smirnov (K-S) are applied to evaluate the PDFs' goodness-of-fit performance. The analysis results present the KDE distribution using the least-squares cross-validation (LSCV), and the Scott bandwidth selection method has outstanding fitting performance. Based on these PDF distributions, the wind turbine (WT) power curve is used to estimate and predict the amount of electricity that can be produced. This study also proposes a reliable method for wind power output planning based on wind speed that can be universally applied.

Research on bridge safety early warning method based on strain energy theory and health monitoring data

Bridges are technology-intensive and heavily invested permanent infrastructure. After completion and opening to traffic, bridge structures are easy to be affected by factors such as traffic load and atmospheric environment. Therefore, it is necessary to do safety warning and evaluation of bridges, especially the abnormal behavior in the early stages of bridge operation. In this research paper, a large-span continuous rigid frame bridge installed with the health monitoring system (HMS), of which a large amount of health monitoring data are collected by the HMS, is used as an example, and then a bridge safety early warning method is proposed when the bridge is during early operating period. First of all, the research finding that the internal stress of the prototype bridge obeys normal distribution through statistical analysis is used; next, we deduce that the strain energy inside the prototype bridge is subject to the Non-central Chi-square distribution combined with the strain energy and statistical theories; in the end, the key probability density distribution function of strain energy and its parameters are derived by using the key stress distribution function of the high performance concrete C50 strength grade used in the prototype bridge. The method recommended in this paper is conducive to the formulation of bridge preventive maintenance strategies.

Difference of Soil Thickness Depending on Climate Zones and Geological Classification: Based on a Survey of Mountain Slopes in Japan

There is little information which examines and compares climate zones or geology/topography in their relation to soil thickness along mountain slopes, where soil thickness is a possible contributing factor for the increase of sediment wash-off. In this study, the data obtained from handy penetration tests conducted throughout Japan are collected and attached to information on climate zones and geography/topography with the aim of clarifying the difference in soil thickness according to the climate zone and geological classification. The probability distribution of soil thickness was found to fit roughly with the probability density function of a log-normal distribution, regardless of the climate zone or geological age / lithology. A comparison of μ showed that the soil thickness at target sites in the Pacific climate zone, which have high rainfall, was large, at approximately 2.1 m. Meanwhile, the soil thickness was low, at approximately 1.5 m, at target sites in the Setouchi climate zone, which has low rainfall. A comparison of the geology showed that soil thicknesses of sites where the geology consisted of Tertiary and Quaternary sedimentary rocks were high, at approximately 2.1 m and 2.3 m, respectively. This suggests that, in high-precipitation regions, the weathering of rocks is promoted so that the soil layers tend to increase in thickness.

Annual Variations of PM10, PM2.5 and PM1.0 Fraction at an Urban Site in Ansan, Korea

This study examines particulate matter (PM) concentrations, specifically PM10, PM2.5, and PM1.0, at an urban site in Ansan, South Korea. Three BAM-1020 continuous monitors measured PM10, PM2.5, and PM1.0 hourly from January to December 2021, with data acquisition rates of 97.1%, 97.3%, and 93.4%, respectively. Average annual concentrations were 45.7±48.4 µg/m³ (PM10), 26.4±22.7 µg/m³ (PM2.5), and 18.5±14.5 µg/m³ (PM1.0). PM10 was 91% of the annual air quality standard, while PM2.5 exceeded this standard by 176%, indicating severe pollution. Statistical analyses using probability density function (PDF) and cumulative distribution function (CDF) showed 98.5% of data converged at 150 µg/m³ (PM10), 75 µg/m³ (PM2.5), and 50 µg/m³ (PM1.0), with the remaining 1.5% corresponding to approximately 131 hours, annually. In 2021, all six observed yellow dust events occurred in spring (March to May). PM10, PM2.5, and PM1.0 concentrations increased from January to March, peaked in March, decreased until September, and rose again. The coarse fraction ratio increased stepwise from February to May, likely due to yellow dust and episodes of high PM concentration in the spring. The PM1.0 concentration was higher in summer and fall compared with that in spring and winter. The PM1.0/PM2.5 ratio was highest in summer and fall even though the annual PM1.0concentration was lowest, suggesting a higher secondary formation rate of fine particles during these periods. This underscores the need for further scientific investigation on PM1.0. The study provides insights into the simultaneous observation and distribution characteristics of PM10, PM2.5, and PM1.0, highlighting the mass concentration, distribution, and ratio of PM1.0. These findings are crucial for understanding PM distribution in Ansan, an industrial complex, and can serve as essential data for chemical composition comparisons, data validation, public health strategies, and cost-benefit analyses for regional PM improvement.

Inefficient star formation in high Mach number environments

Context. The star formation rate (SFR), the number of stars formed per unit of time, is a fundamental quantity in the evolution of the Universe. Aims. While turbulence is believed to play a crucial role in setting the SFR, the exact mechanism remains unclear. Turbulence promotes star formation by compressing the gas, but also slows it down by stabilizing the gas against gravity. Most widely used analytical models rely on questionable assumptions, including: i) integrating over the density PDF, a one-point statistical description that ignores spatial correlation, ii) selecting self-gravitating gas based on a density threshold that often ignores turbulent dispersion, iii) assuming the freefall time as the timescale for estimating SFR without considering the need to rejuvenate the density PDF, iv) assuming the density probability distribution function (PDF) to be log-normal. This leads to the reliance on fudge factors for rough agreement with simulations. Even more seriously, when a more accurate density PDF is being used, the classical theory predicts a SFR that is essentially 0. Methods. Improving upon the only existing model that incorporates the spatial correlation of the density field, we present a new analytical model that, in a companion paper, is rigorously compared against a large series of numerical simulations. We calculate the time needed to rejuvenate density fluctuations of a given density and spatial scale, revealing that it is generally much longer than the freefall time, rendering the latter inappropriate for use. Results. We make specific predictions regarding the role of the Mach number, ℳ, and the driving scale of turbulence divided by the mean Jeans length. At low to moderate Mach numbers, turbulence does not reduce and may even slightly promote star formation by broadening the PDF. However, at higher Mach numbers, most density fluctuations are stabilized by turbulent dispersion, leading to a steep drop in the SFR as the Mach number increases. A fundamental parameter is the exponent of the power spectrum of the natural logarithm of the density, ln ρ, characterizing the spatial distribution of the density field. In the high Mach regime, the SFR strongly depends on it, as lower values imply a paucity of massive, gravitationally unstable clumps. Conclusions. We provide a revised analytical model to calculate the SFR of a system, considering not only the mean density and Mach number but also the spatial distribution of the gas through the power spectrum of ln ρ, as well as the injection scale of turbulence. At low Mach numbers, the model predicts a relatively high SFR nearly independent of ℳ, whereas for high Mach, the SFR is a steeply decreasing function of ℳ.

Stabilization of nonhomogenous semi-Markov jump linear systems with synchronous switching delays via aperiodically intermittent control

A type of nonhomogenous semi-Markov jump linear systems with synchronous switching delays is considered in the present paper. Owing to the existence of time-varying delays and nonhomogenous semi-Markov switching process, the selection of Lyapunov functional and the transformation of some time-varying parameters become more complicated in comparison with many existing works. To overcome these difficulties, a sort of Lyapunov–Krasovskii functional related to switching delays is introduced. Simultaneously, the technique of convex combination is applied to tackle a variety of time-varying terms including transition probabilities (TPs), probability distribution function and probability density function (PDF). Then, a time-invariant stability criterion superior to many relevant works in conservativeness is obtained to ensure mean-square exponential stability (MES). Based on this result, time-invariant conditions for mean square exponential stability of the controlled system are also attained by the continuous feedback control. Subsequently, to stand on the point of cost reduction, an aperiodically intermittent control (AIC) is adopted in such a system and a stability criterion is attained as well under more relaxed restrictions on relative parameters. Finally, a numerical example is provided to verify the effectiveness and correctness of the results.

Seismic fragility analysis of long-span rigid-frame bridge on mountainous soft clay site

In order to assess the damage condition of bridge components for a large-span rigid bridge in a soft clay site in a mountainous area in China southwest, a finite element model of a large-span rigid bridge is established based on the OpenSees software, and the joint probability density distribution function of the ground motion strength and seismic demand and the marginal distribution function of the ground motion are introduced into the kernel density function. As a basis to get the method of calculating the fragility of the bridge members, and the method is verified for its feasibility, on this basis, the damage condition of the bridge components are analyzed, and finally the damage condition of the bridge system are analyzed by the first-order bounds method and the improved PCM method (IPCM). The results showed that: (1) Kernel density method (KDE) can effectively calculate the damage probability of each component, for example, under ground motions with PGA equal to 0.2 g, the probability of slight damage of the 1# pier is 29%, that of the intermediate consolidation pier (2# pier ~ 4# pier) is about 90%; the probability of slight damage of the 1# bearing is 48%, and that of the 2# bearing is 87%. (2) Reasonable value of the expansion joints can effectively reduce the probability of main beam collision. In this investigation, the value is taken as 0.18 m ~ 0.24 m. (3) The bridge system is more likely to be damaged than a single component in the system, and the damage probability of a single component cannot be used as a criterion for the bridge system in the actual working condition. Comparing the first-order boundary law with the IPCM method, the IPCM method has higher accuracy.

Capacity Optimization for RSMA-Based Multi-User System over Underwater Turbulence Channel

The underwater environment used for communication is harsh and complex, necessitating heightened standards for spectral efficiency and reliability in underwater wireless optical communication (UWOC) systems. The focus of this work is on the performance of multi-user UWOC systems operating in oblique channels of ocean turbulence downlink, where users are randomly distributed at a certain depth. A joint optimization scheme is proposed, which joints rate-splitting multiple access (RSMA) and power allocation so that the system’s ergodic sum capacity is optimized to improve the transmission bandwidth. Furthermore, the probability density function (PDF) and cumulative distribution function (CDF) models for the received signal-to-noise ratio (SNR) of a multi-user multiple-input multiple-output (MIMO) system operating in the turbulent underwater oblique channels are established, accounting for the avalanche photodiode (APD) shot noise and solar radiation noise. Theoretical derivations are presented to quantify the ergodic capacity and outage probability of the multi-user system utilizing the RSMA technology. Subsequently, a numerical analysis is conducted to investigate the influence of the power allocation coefficient, RSMA, and the joint optimization algorithm on the performance of a two-user MIMO system leveraging RSMA. The simulation results show that our optimization scheme effectively reduces the outage probability, thereby achieving the maximum system sum rate and validating the practical feasibility and efficacy of the proposed scheme.

On Epidemiological and Actuarial Analyses of Health Insurance Models for Communicable Diseases

This article examines an SIDRS disease model design for insurance contracts, in which the insured population is exposed to the risks of communicable diseases. For the epidemiological models, the population is structured into four demographic groups, namely: susceptibles (S), infected PHs undergoing treatment (I), infected PHs who are diseased (D), and infected PHs who recovered (R) from the disease, with part of the latter thereafter re-entering the group of susceptibles (S) and continuing with the insurer by paying premiums until he or she is infected again. The infective class is a union of the class of those undergoing treatment, deceased policy holders (PHs), and those who have recovered. The number of deceased PHs is counted as part of the insured population because the number PHs who die of the disease must be accounted for and are entitled to claims. The insurance policies are designed for the members of the susceptible group: the latter constantly face the risk of infection and death due to the disease. The probability of PHs remaining susceptible for the SIDRS disease model is formulated. The probability density function (PDF) and cumulative distribution function (CDFs) for the SIDRS disease model for an insurance policy are obtained. For the actuarial part, we used actuarial techniques and principles to determine the financial obligations of the parties and the insurance amounts for the insurer and PHs. The cumulative insurance reserve for an annuity and a lump sum plan are also considered. To ascertain the risk of insolvency, premium adjustment for the PHs is considered. Some numerical computations of the results arising from our model analyses are also considered in this article. This article has practical applications in health insurance schemes. It is also applicable in the determination of insurance premiums payable by PHs who did not have the disease and insurance claims receivable by those who are hospitalized or die of the disease. Our model can also be practically applicable in the determination of health insurance reserves for communicable diseases.

Modeling insurance loss data using novel approach of moment exponential model: Inference, actuarial measures and application

Asymmetrical probability models are helpful for analyzing skewed data sets since they allow you to describe the form of the distribution and anticipate the chance of extreme events. This article defines a novel approach to continuous moment exponential distribution called the exponentiated generalized moment exponential model. The extension has two additional parameters accounting for the distribution’s shape. We extend this distribution probability density, cumulative distribution, hazard rate, and survival functions and establish different key statistical properties. Parameter estimation is obtained using different procedures, notably maximum likelihood estimation, least square, and Bayesian methods. A Monte Carlo simulation experiment is conducted to assess parameter performance and indicator risk measures. This article examines two distinct actual data sets in order to highlight the significance of the proposed model as well as its application in a variety of settings. The new model is compared to a large number of well-known extensions that were developed by other businesses.

Physical layer security in SWIPT-based cooperative vehicular relaying networks

The future of autonomous transportation systems depends on energy sustainability and secure information exchange from low-power vehicular sensors, hence the increased interest in vehicular sensor charging using simultaneous wireless information and power transfer (SWIPT). This study investigates the physical layer security of a SWIPT-based radio frequency energy harvesting cooperative vehicular relaying network subjected to cascade Nakagami-m and double Nakagami-m (DN) fading channels. In the considered system model, a stationary source communicates with a mobile destination through a power-splitting-based decode-and-forward relay in the presence of a mobile passive eavesdropper. Based on the Gamma-distributed first term of the Laguerre series, new statistical probability density function (PDF) and cumulative distribution function (CDF) expressions for the DN are derived to accurately model the complex cascaded fading scenario. The secrecy performance metrics analyzed are the secrecy outage probability (SOP), the probability of non-zero secrecy capacity (PNZSC), and the intercept probability (IP). In addition, the asymptotic SOP (ASOP) is investigated in the high signal-to-noise ratio (SNR) to enhance the comprehension of the secrecy performance. Based on the derived ASOP, the secrecy diversity order (SDO) of the proposed system is determined and examined. Particularly, we present analytical closed-form expressions for the secrecy performance metrics and provide a detailed understanding of the impact of the system parameters under the cascade fading scenario. Then, a power splitting (PS) optimization problem is formulated to minimize the SOP. The results demonstrate a reduction in the SOP with the proposed PS scheme compared to the equal PS scheme. The obtained analytical findings are validated using Monte Carlo simulations.

Testing for Markovian character of transfer of fluctuations in solar wind turbulence on kinetic scales.

We apply statistical analysis to search for processes responsible for turbulence in physical systems. In our previous studies, we have shown that solar wind turbulence in the inertial range of large magnetohydrodynamic scales exhibits Markov properties. We have recently extended this approach on much smaller kinetic scales. Here we are testing for the Markovian character of stochastic processes in a kinetic regime based on magnetic field and velocity fluctuations in the solar wind, measured onboard the Magnetospheric Multiscale (MMS) mission: behind the bow shock, inside the magnetosheath, and near the magnetopause. We have verified that the Chapman-Kolmogorov necessary conditions for Markov processes is satisfied for local transfer of energy between the magnetic and velocity fields also on kinetic scales. We have confirmed that for magnetic fluctuations, the first Kramers-Moyal coefficient is linear, while the second term is quadratic, corresponding to drift and diffusion processes in the resulting Fokker-Planck equation. It means that magnetic self-similar turbulence is described by generalized Ornstein-Uhlenbeck processes. We show that for the magnetic case, the Fokker-Planck equationleads to the probability density functions of the kappa distributions, which exhibit global universal scale invariance with a linear scaling and lack of intermittency. On the contrary, for velocity fluctuations, higher order Kramers-Moyal coefficients should be taken into account and hence scale invariance is not observed. However, the nonextensity parameter in Tsallis entropy provides a robust measure of the departure of the system from equilibrium. The obtained results are important for a better understanding of the physical mechanism governing turbulent systems in space and laboratory.

Molecular cloud matching in CO and dust in M33

This study is aimed to contribute to a more comprehensive understanding of the molecular hydrogen distribution in the galaxy M33 by introducing novel methods for generating high angular resolution (18.2″, equivalent to 75 pc for a distance of 847 kpc) column density maps of molecular hydrogen (NH2). M33 is a local group galaxy that has been observed with Herschel in the far-infrared (FIR) wavelength range from 70 to 500 μm. Previous studies have presented total hydrogen column density maps (NH), using these FIR data (partly combined with mid-IR maps), employing various methods. We first performed a spectral energy distribution (SED) fit to the 160, 250, 350, and 500 μm continuum data obtain NH, using a technique similar to one previously reported in the literature. We also use a second method which involves translating only the 250 μm map into a NH map at the same angular resolution of 18.2″. An NH2 map via each method is then obtained by subtracting the H I component. Distinguishing our study from previous ones, we adopt a more versatile approach by considering a variable emissivity index, β, and dust absorption coefficient, κ0. This choice enables us to construct a κ0 map, thereby enhancing the depth and accuracy of our investigation of the hydrogen column density. We address the inherent biases and challenges within both methods (which give similar results) and compare them with existing maps available in the literature. Moreover, we calculate a map of the carbon monoxide CO(1 − 0)-to-molecular hydrogen (H2) conversion factor (XCO factor), which shows a strong dispersion around an average value of 1.8 × 1020 cm−2/(K km s−1) throughout the disk. We obtain column density probability distribution functions (N-PDFs) from the NH, NH2, and NH I maps and discuss their shape, consisting of several log-normal and power-law tail components.

Defining a clinically meaningful within-patient change threshold for the Cohen-Mansfield Agitation Inventory in Alzheimer's dementia.

The Cohen-Mansfield Agitation Inventory (CMAI) quantifies the frequency of agitation behaviors in elderly persons. This post hoc analysis of data from the brexpiprazole clinical program aimed to determine a meaningful within-patient change (MWPC) threshold for CMAI Total score among patients with agitation associated with dementia due to Alzheimer's disease. Data were included from three 12-week, multicenter, randomized, double-blind, placebo-controlled, parallel-arm trials of brexpiprazole for the treatment of agitation associated with dementia due to Alzheimer's disease (ClinicalTrials.gov identifiers: NCT01862640, NCT01922258, NCT03548584). Change in CMAI Total score (range 29-203; higher scores indicate higher frequency of agitation behaviors) from baseline to Week 12 was the primary endpoint in each trial. MWPC thresholds were estimated from anchor-based mean change analyses and receiver operating characteristic (ROC) curves. The Clinical Global Impression-Severity of illness (CGI-S) and Clinical Global Impression-Improvement (CGI-I) scales, both as related to agitation, were used as anchors. Empirical cumulative distribution functions (eCDFs) and probability density functions (PDFs) were plotted as supportive evidence. Distribution-based methods were also employed. Data from 898 patients were analyzed (mean age, 73.7 years; mean baseline CMAI Total score, 73.8). The mean CMAI Total score change corresponding to a difference of small improvement vs. stable (CGI-S one-point decrease vs. no change), or minimally improved vs. no change (CGI-I rating of 3 vs. 4), ranged from -10.6 to -13.5 points. The mean CMAI Total score change corresponding to a difference of moderate improvement vs. stable (CGI-S two-point decrease vs. no change), or much improved vs. no change (CGI-I rating of 2 vs. 4), ranged from -20.2 to -25.7 points. ROC curve analyses generally produced smaller estimates of meaningful change. eCDFs and PDFs showed good distribution and separation of CMAI Total score change between CGI-S/CGI-I categories. In distribution-based analyses, the minimal detectable change for CMAI Total score (10.5-11.8 points) was generally lower than anchor-suggested thresholds. Triangulation of evidence from anchor- and distribution-based analyses supports an MWPC threshold for CMAI Total score of -20 points, with a threshold range of -15 to -25 points, in patients with agitation associated with dementia due to Alzheimer's disease.

Research on Spatial Developable Mechanism Considering Revolute Clearance Joints with Irregular Rough Surfaces

Due to assembling, manufacturing errors, and wear, irregular rough surfaces inevitably exist in joints, which will increase the contact stiffness nonlinearity at the joint of the spatial developable mechanism, and the traditional contact force model is difficult to accurately predict the contact force change of irregular rough surface clearance. Aiming at the difficulty of accurately predicting the dynamic behavior of the spatial developable mechanism caused by rough joint clearance, an improved clearance contact force modeling method based on an uncoordinated contact model is proposed in this paper. The influence of rough peak distribution on the contact area is analyzed. The stiffness of the traditional Hertz model is modified based on the probability distribution density function of the rough peak, and an improved contact force model based on dynamic contact stiffness is established. Based on the Lagrange multiplier method, the dynamics model of spatial developable mechanism is constructed. Based on the model, the dynamic analysis of the spatial expansion mechanism is carried out, and the influence of the roughness of the contact surface and the size of the clearance on the dynamic characteristics of the system are explored; as well, the influence of different clearance parameters on the dynamic characteristics of the development mechanism is revealed. Through the analysis, this paper provides a theoretical basis for predicting the effect of a spatial revolute clearance joint on the dynamic characteristics of the mechanism and lays a good foundation for the manufacture and application of the mechanism.

Mechanisms of investors’ bounded rationality and market herding effect by the stochastic Ising financial model

The widespread herding effect prevalent in China’s stock market is caused by investors’ bounded rationality behavior. However, the underlying mechanisms are not fully understood. This article aims to use the stochastic Ising financial model, which explains this problem from the perspective of Econophysics. The probability density function and power-law distribution of return data simulated by the stochastic Ising financial model show sharp peaks and fat tails, similar to the stylized facts of real Chinese stock market data. Further, we use this financial model to simulate herding behavior in the market. The results show that when the degree of investor irrationality (represented by β) increases, the Herd Effect Index (HERDI) also rises. When β exceeds a critical point, the HERDI index fluctuates more violently. Through empirical analysis, we find that there is an interactive relationship between investors’ bounded rational behavior and market herding effects, and this model can effectively explain these two phenomena.

A study on N-policy BMAP/G/1 queueing system

This study presents a simple approach for analyzing the BMAP/G/1 queueing system under N policy. In this policy, the server goes idle at the end of a busy period and the queue length is checked at every arrival moment. The idle server starts serving customers when the queue length reaches or above a predetermined number, namely N, and keeps doing so until the system is completely empty. We first use a simple sequential substitution approach to derive the system length distribution at departure epoch. A comparative study is also conducted to highlight the benefits and strength of our straightforward approach to that of the RG-factorization technique and the roots finding method. We extract the distribution of system length at a random time point by utilizing the remaining service time of a customer who is currently being served as the supplementary variable. The probability density function of the sojourn time distribution for an arbitrary customer of an incoming batch is also computed. We propose an expected linear cost function to estimate the optimal value of N at minimum cost. The validity of our analytic technique has been shown through a variety of numerical examples involving different service time distributions.

Wind resource assessment for turbine class identification in Bayanzhaganxiang, China

Abstract The wind resource assessment has been used effectively to identify the classification of wind turbines at a particular wind farm site. The current study used WAsP software and various statistical methods such as graphical, energy pattern factor, standard deviation, and Rayleigh distribution methods to find the Weibull parameters by evaluating the raw data collected from August 2005 until July 2006 at four (4) different heights of the meteorological mast station in Bayanzhaganxiang, China. The Weibull parameters were utilized to find the annual mean wind speed, probability density, and cumulative distribution functions of wind conditions at the reference heights of 70 m, 50 m, 30 m, and 10 m. The wind shear coefficient was 0.130 with an overall roughness factor of 0.0385 m, suggesting the site vicinity is an open country with no significant structures and vegetation. The results also showed that the post-processed output from WAsP and standard deviation method at the sensor’s height of 70 m have a correlation coefficient and confidence level of 0.99977 and above 95%, respectively. Based on the turbine classification from GL Wind 2003 and IEC 61400-1 Ed.2, it was found that the turbine class ideal for the site is class III wind turbines with an annual mean wind speed of 7.439 m/s at a hub height of 99 m. The measured wind power density at hub height was calculated according to IEC 61400-12-1, which yields 464.36 W/m2. The characteristic wind turbulence at 70 m high is IEC subclass B. Among the selected wind turbines, the net annual energy production with efficiency is 8,059.57 MWh/year using Avantis AV1010, with the highest capacity factor of 40.05%. It has been found that the lowest energy generation cost is US$ 0.0292/kWh for a period of 20 years.

Influence of Foundation Stiffness on the Fragility Curves of a Concrete Gravity Dam Subjected to Near-Field Ground Motions Using Finite Element Method

A concrete gravity dam is being investigated to determine the fragility curves during near-field ground motions under various foundation stiffness conditions. This is accomplished using the finite element method for modeling the Latyan dam and its dam-reservoir-bed complex interaction system. The nonlinear constitutive model of concrete, plastic damage, is used to simulate the cyclic behavior of tensile and compressive failures in concrete. An acoustic element is used to model the propagation of compressive waves in the reservoir to account for the hydrodynamic effects of the lake reservoir. A total of 100 real and scaled accelerograms are used to simulate near-filed seismic loading in eight different concrete-to-foundation stiffness ratios. Based on the peak ground acceleration (PGA) of the earthquake, numerical models are applied to obtain the probability density function (PDF) and cumulative distribution function (CDF) for lognormal distributions and to determine and analyze the fragility curves of the dam. According to the findings, the seismic performance of the dam is improved for stiffness ratios of 0.75, 1, and 1.5, and the best seismic performance is determined for stiffness ratios of 1. Concrete dams with stiffness ratios of 0.75, however, perform better when the peak ground acceleration is greater than 0.74g compared to those with stiffness ratios of 1. DOI: https://doi.org/10.52783/pst.502

Dynamics and probability density function of a stochastic COVID-19 epidemic model with nonlinear incidence

In this paper, a stochastic SEIQ model with nonlinear incidence rate is proposed. The existence and uniqueness of global positive solution of the stochastic model are proved. Then, by constructing some Lyapunov functions, we derive a sufficient condition for the ergodic stationary distribution when [Formula: see text] is greater than one. By solving a four-dimensional Fokker–Planck equation, we get the exact expression of log-normal probability density function of stationary distribution for the stochastic model. Sufficient condition for the extinction of the exposed and infected population is also provided. Finally, numerical simulations are presented to verify the above theoretical results.