Probabilistic Calculation Research Articles

Determination of Energy and Electric Capacity of On-Board Supercapaci-tor Regenerative Energy Storage

Purpose. Development of a method for determining the main functional parameters of on-board supercapacitor recuperative energy storage based on the asymptotic theory of extreme statistics by Gumbel, taking into account stochastic nature of changes in recuperated voltage and current. Methodology. To achieve this purpose, methods, devices and computer systems for temporary registration of recuperated voltages and currents on operating electric locomotives, methods of the theory of random processes and methods of probabilistic and statistical processing of registrograms of voltages and currents were used. Findings. A computational and experimental method for estimating recuperative energy has been proposed and practically applied. A probabilistic method has been developed for determining the energy and electric capacity of on-board supercapacitor recuperative energy storage units. Numerical probabilistic and statistical calculations of the energy and electric capacity of on-board storage for the VL8 and VL11M6 electric locomotives during their operation in the sections of Prydniprovska railway have been carried out. It was found that the energy and electric capacity of on-board storage devices are distributed according to an exponential law with a clear prevalence of their minimum values and in compliance with direct proportionality between them. Originality. For the first time, an autonomous phase of recuperative braking mode of an electric rolling stock has been developed, which makes it possible to significantly reduce the mass and dimension of a supercapacitor storage. The asymptotic theory of extreme statistics by Gumbel was adapted to the method for calculating energy and electric capacity of an on-board storage device, which made it possible to take into account the influence of stochastic nature of changes in the recuperated voltage and current. The probabilistic influence regularities of the change nature in the recuperation energy on the capacity of on-board storage in the phase of recuperative braking have been established. Further development was obtained by a computational-experimental method for assessing the recuperative energy, based on monitoring and using the time dependences of voltage and current obtained in real modes of recuperative braking. For the first time in electric traction systems, it was proposed to carry out the transition from the recuperative braking mode to the recuperative regeneration mode. Practical value. The developed method and technique based on it make it possible to evaluate functional parameters of on-board storage device of all types of electric rolling stock, considering stochastic nature of recuperated voltages and currents. Numerical-graphic dependences of the energy intensity and capacity of the on-board storage are recommended for predicting and evaluating these parameters for various modes of recuperative braking. Since the task of designing an on-board storage unit (in terms of mass and dimensions) is ambiguous, therefore, in each specific case of the type of electric locomotive and recuperation modes, it must be solved individually, taking into account the probability of the corresponding capacitance values.

Traumatisme et résilience associés à la pandémie de la COVID-19 dans les villes de Bafoussam et de Dschang au Cameroun

IntroductionThe emergence of the Covid-19 pandemic in Cameroon, as in Africa and around the world, was marked by a suddenness and unpredictability that fascinated the imagination. The considerable psychic and social repercussions of the pandemic mobilized a significant anguish of death. The sudden onset of the pandemic was followed by spectacular, high-profile deaths that fascinated the imagination, listing it in the order of traumatic events, provoking reactions of astonishment, flight and avoidance. GoalThe objective of this study is to determine the symptomatology of post-traumatic stress disorder, as well as the resilience, associated with the Covid-19 pandemic in the Western Region of Cameroon. MethodologyThe research was carried out following the model of general population mental health surveys. The availability of area frames (sampling) made it possible to opt for probabilistic calculations. First and second year master's students in clinical psychology from Dschang University were involved in data collection. They benefited from a two-day seminar on data collection techniques in the general population. The calculated sample size is 384 households. The anticipated response rate, set at 90%, made it possible to increase robustness and to anticipate a total sample of 424 households, spread over 3 districts of Bafoussam and Dschang, according to the choice previously made. The study followed the ethical provisions of the Helsinki Protocol. The data collection tools used are: the Impact of Event Scale-Revised and the Connor-Davidson Resilience Scale. Results409 subjects were recruited, representing a completion rate of 106.5%. 70.7% of subjects exhibited symptoms of PTSD. These symptoms are more often mild (40.9%) or moderate (25.6%). Women are more affected (73.7%) by PTSD than men (67.9%). In addition to sex and age, area of residence and marital status, appear to be significantly associated with symptoms of PTSD: subjects under 35 years of age have a significantly higher prevalence rate than those over 35; the rate of PTSD is significantly higher in subjects living in urban areas than in those living in rural areas; single subjects are more affected by PTSD (40.1%) than married subjects (26.7%). The average score recorded on the CD-RISC is 64.3, the standard deviation is 15.3 and the coefficient of variation is 24%. This average falls into the second quartile of the distribution, indicating average resilience. CD-RISC scores are not affected by gender, age, marital status, level of education, or occupational status. These characteristics are therefore not factors of resilience. ConclusionThe Covid-19 pandemic has had a psychological impact in Cameroon which has made it a major psychosocial stressor. More than 6 in 10 people have symptoms of PTSD. But this symptomatology is often weak or moderate, testifying to an effective resilience, to balance the traumatic effects of the pandemic.

Potential impact of prioritisation methods on the outcome of cumulative exposure assessments of pesticides

This report describes the potential impact of a prioritisation method on the outcome of cumulative exposure assessments of pesticides. The method aims to reduce the laborious task of the establishment of cumulative assessment groups (CRAs). The prioritisation method consisted of two steps: 1) identification of low-priority substances and 2) identification of priority organs. The first step aimed to identify low-priority substances based on hazard quotient (HQ) thresholds for single substances relevant for acute effects on the nervous system or chronic effects on the thyroid. For this, probabilistic calculations of chronic and acute HQs were performed for 210 substancesand 10 surveys. Priority pesticides were retained according to four different thresholds, namely an HQ larger than0.1 at the 99th percentile of exposure, or an HQ larger than 0.01, 0.1 or 0.2 at the 99.9th percentile of exposure. In the second step, AGs for the nervous system and the thyroid were compiled and risk metrics obtained for those organs was compared with the risk of higher tier AGs at the specific effect. It was concluded that risk assessment of AGs at the target organ level using critical effects (i.e. using the health-based guidance value of substances) is feasible. The prioritisation thresholds were applied for AGs at the target organ level and for AGs at the specific effect level. The prioritisation threshold of having an HQ larger than 0.1 at 99.9th percentile to retain substances could be used for those AGs. It reduced the number of substances in the AG nervous system to 50% and the number of substances in the AG thyroid to 70% without having a substantialimpact on the total margin of exposure. In conclusion, the prioritisation method could be used to simplify CRA and may contribute to a cost-effective approach whilst still providing a high level of protection.

Probabilistic power flow calculation based on importance-Hammersley sampling with Eigen-decomposition

This paper presents a novel probabilistic power flow calculation method for power systems with integrated wind farms, based on importance sampling and Hammersley sequence with eigen-decomposition. The method proposed in this paper adopts importance sampling to build probability density functions in a desired range to compress the sampling space and hence reduce the calculation burden. The Hammersley sequence, a kind of low discrepancy sequence, is used to obtain uniform samples for improving the sampling efficiency. In addition, since the traditional Cholesky method is unable to decompose the non-positive definite correlation matrix, this paper applies the eigen-decomposition to solve this problem for multiple correlated wind sources. Case studies are conducted on modified IEEE test systems, where the advantages of the proposed method are verified. According to the simulation results, the proposed method shows greater accuracy and efficiency, compared to the traditional methods.

Static Stability Analysis Based on Probabilistic Power Flow Calculation considering P2G Technology

At present, integrated energy systems have received extensive attention, but there is no basic framework for stability analysis of coupled systems. The injection of a large amount of renewable energy also has a great impact on the stability of the system. This paper focuses on how to analyze the static stability of the coupling system with uncertainty, which mainly considers the uncertainty of wind power generation and photovoltaic power generation and also considers the influence of P2G technology on the whole system. Firstly, this paper analyzes the principles of wind power generation and photovoltaic power generation and constructs the probability model of renewable energy power generation power. Then, the three-point estimation method is used to process the data, and the probability distribution of the unknown quantity is obtained by probabilistic power flow analysis. Finally, the probability distribution of each eigenvalue is obtained by analyzing the sensitivity of the characteristic roots to the voltage. Thus, the static stability of the system is judged. The applicability of proposed methodology is demonstrated by analyzing an integrated IEEE 14-bus power system and a Belgian 20-node gas system in this paper.

Revised Comparison of Tunnel Collapse Frequencies and Tunnel Failure Probabilities

Comparison of calculated failure probabilities of technical systems with observed failure frequencies is an important part of the assessment of probabilistic calculations and can point to significant factors that are neglected in the calculations. Recent comparisons of failure probabilities and failure frequencies of nuclear power plants, bridges, and dams have shown that the calculated and observed values correspond surprisingly well. In addition, although various factors could be identified which have both positive and negative influences on the observed values, they almost cancel each other out. This study focuses on the comparison as it relates to tunnels. Extensive statistics indicate that most tunnel collapses occur during construction. Although this is also seen to a certain extent in bridges, it is not to the extent seen in tunnels. Events such as earthquakes and floods, which are the major causes of collapse of other structures, account for only about 10% to 20% of all tunnel collapses. Increasingly, tunnels are also being proven probabilistically. Based on these calculations, the available failure statistics can be compared with representative probabilistic tunnel proofs. The comparison shows large deviations between individual computations as well as between the mean value of all computations and the observed collapse frequencies.

Using Quantitative Passive Thermography and Modified Paris-Law for Probabilistic Calculation of the Fatigue Damage Development in a CFRP-Aluminum Hybrid Joint.

Although metal to Carbon-fiber-reinforced-polymer (CFRP) hybrid-joints possess a high lightweight construction potential, their extensive application has to deal with interfacial stress concentrations promoting fatigue damage. Furthermore, the underlying damage processes and their influencing factors are still not completely understood. Besides interfacial property-gradients, generic shapes counteract a precise determination of local stresses or strains, respectively. Hence, new methods are required that combine non-destructive testing and fracture mechanics to account for the fatigue damage. In this work, data of mechanical fatigue testing of an aluminum-CFRP hybrid-structure is presented by means of the dynamic stiffness and the mechanical hysteresis. Additionally, in situ passive thermography allows for capturing the heat development due to delamination growth. Correlating the obtained data implies that faster delamination growth coincides with higher amplitude values of lock-in thermography and higher mechanical hysteresis. Supported by this observation, a model is formulated to calculate the local dissipation per loading cycle. Further integration into a Paris-law like formulation results in a calculation model to account for the mode-I fatigue delamination growth. Additional validation of the model parameters shows good agreement with the experimental data.

Study on prediction of three-dimensional surface roughness of nano-ZrO2 ceramics under two-dimensional ultrasonic-assisted grinding

Ultrasonic-assisted grinding technology can significantly improve the processing quality of hard and brittle materials, with the continuous improvement of machining accuracy, and the three-dimensional roughness characterization of ultra-precision machined surfaces has gradually become a research hotspot. However, it is necessary to develop a reliable three-dimensional roughness prediction model because the experimental measurement of three-dimensional roughness is time-consuming and laborious. In this study, the probabilistic analysis of the two-dimensional ultrasonic-assisted grinding (TUAG) process of nano-ZrO2 ceramics was carried out, and the influence of the random distribution, random prominence height, and unique motion trajectory of abrasive particles on the material removal mechanism of workpiece surface was explored. On that basis, a probabilistic calculation method for the height of residual material on the surface of nano-ZrO2 ceramics under TUAG was further proposed to obtain the more accurate height value which accords with the characteristics of three-dimensional roughness sampling. According to the obtained height value, the three-dimensional roughness prediction model of nano-ZrO2 ceramic under TUAG was developed. The accuracy and reliability of the theoretical model have been verified by the simulation analysis and the TUAG experiment of nano-ZrO2 ceramics, and this study can provide a new theoretical reference to evaluate and predict the quality of the ultra-precision machined surface of hard and brittle materials.

Probabilistic Dynamic Optimal Energy Flow Calculation for the gas-electric coupling system

Due to pollution and energy shortage, the multi-energy interconnected system formed by natural gas and electricity coupling has attracted a lot of attention because of its cleanness and high efficiency. The operation of natural gas system and electrical power system belong to different time scales. At the same time, more and more new energy sources such as wind and photovoltaic power generation in the electrical power system increase the uncertainty of power supply. The operation of gas-electric coupling system must consider the impact of these factors. In response to these problems, this paper considers the impact of timing on the operating state of gas-electric coupling system based on the multi-period optimization model, and proposes a probabilistic energy flow calculation method, namely the Latin Hypercube sampling Markov Chain simulation (LHMCS). This method can quickly obtain the influence of random factors on the operating state of gas-electric coupling system. Finally, a simulation example verifies the rationality and effectiveness of the method proposed.

Оценка обеспеченности результатов расчетов несущей способности по нормальному сечению внецентренно сжатых железобетонных элементов с использованием нелинейной деформационной модели при действии циклов замораживания и оттаивания

As a result of numerical modeling using the probabilistic method, there has been estimated the security of the results of calculating the load-bearing capacity of eccentrically compressed reinforced concrete elements with symmetrical reinforcement along the normal cross-section, taking into account the effects of freezing and thawing cycles (FTC). The distributions of the strength and deformation concrete characteristics used in the probabilistic calculation are formed on the basis of the results of experimental studies. It is shown that the security of the results of calculations of the load-bearing capacity under eccentrical compression according to the nonlinear deformation model in accordance with the current norms depends on the eccentricity of the longitudinal force and the reinforcement center. The author has substantiated that the decrease in the load-bearing capacity for the normal cross-section regarding the studied elements under the action of the FTC is maximal at small eccentricities and not significant at large eccentricities of the longitudinal force, and it depends on the percentage of longitudinal reinforcement.

Probabilistic Load Flow Calculation of Power System Integrated with Wind Farm Based on Kriging Model

Because of the randomness and uncertainty, integration of large-scale wind farms in a power system will exert significant influences on the distribution of power flow. This paper uses polynomial normal transformation method to deal with non-normal random variable correlation, and solves probabilistic load flow based on Kriging method. This method is a kind of smallest unbiased variance estimation method which estimates unknown information via employing a point within the confidence scope of weighted linear combination. Compared with traditional approaches which need a greater number of calculation times, long simulation time, and large memory space, Kriging method can rapidly estimate node state variables and branch current power distribution situation. As one of the generator nodes in the western Yunnan power grid, a certain wind farm is chosen for empirical analysis. Results are used to compare with those by Monte Carlo-based accurate solution, which proves the validity and veracity of the model in wind farm power modeling as output of the actual turbine through PSD-BPA.

Investigation of the dynamic characteristics of the “building - pile foundation” system with the random parameters of foundation soils

This article presents the results of a study on the random variability influence of soil deformation parameters - elastic modulus, Poisson’s ratio - on the dynamic characteristics of a building. The spatial finite element system “building - pile foundation” is considered, taking into account the reduction in the acceleration of ground vibrations with depth. The probabilistic calculation of the system is carried out by the Monte Carlo method, the random parameters of the subgrade are taken to be distributed according to the normal law. Statistical characteristics of free frequencies of system vibrations were obtained, it was found that within the same soil type, it is possible to realize system vibrations with a predominance of both the 1st and 2nd forms.

Simulation of two-dimensional distribution laws of random correlated quantities of natural-climatic factors in context of probabilistic assessment of reliability of hydraulic structures of cascades of hydroschemes

When performing calculations to assess reliability of hydraulic structures of cascades of hydroschemes on the basis of probabilistic methods, the necessity to simulate random natural-climatic phenomena producing loads and effects on hydraulic structures arises. In particular, statistical series of random quantities of such important natural-climatic phenomena are considered: annual lowest average monthly temperatures, annual maximal amplitudes of average monthly temperatures. Each of the enumerated natural-climatic phenomena is characterized by presence of close correlation connections between random quantities when passing from one hydroscheme of the cascade to another. The necessity to consider correlation connections requires construction (simulation) of joint distribution law of random quantities system. The purpose of the work is simulation of joint distribution law of system of random variables that do not satisfy the normal distributions, taking into account correlation connections between random variables when passing from one hydroscheme of the cascade to another. Methods of the theory of correlation and methods of mathematical statistics with the use of software package MathCad were used in the course of the investigation. Simulation of joint law of distribution of system of random variables that do not satisfy normal distributions, taking into account correlation connections between random variables when passing from one hydroscheme of the cascade to another, and also assessment of accuracy of results, that were performed, have shown advantages of this approach from the viewpoint of accuracy of results obtained by different procedures. The results can be used in probabilistic calculations of reliability of hydraulic structures and cascades of hydroschemes.

Determination of Petrophysical Parameters of Reservoir Rock with a Special Look to Shale Effect (Case Study: One of the Gas Fields in Southern Iran)

Determination of petrophysical parameters is necessary for modeling hydrocarbon reservoir rock. The petrophysical properties of rocks influenced mainly by the presence of clay in sedimentary environments. Accurate determination of reservoir quality and other petrophysical parameters such as porosity, type, and distribution of reservoir fluid, and lithology are based on evaluation and determination of shale volume. If the effect of shale volume in the formation not calculated and considered, it will have an apparent impact on the results of calculating the porosity and saturation of the reservoir water. This study performed due to the importance of shale in petrophysical calculations of this gas reservoir. The shale volume and its effect on determining the petrophysical properties and ignoring it studied in gas well P19. This evaluation was performed in Formations A and B at depths of 3363.77 to 3738.98 m with a thickness of 375 m using a probabilistic calculation method. The results of evaluations of this well without considering shale showed that the total porosity was 0.1 percent, the complete water saturation was 31 percent, and the active water saturation was 29 percent, which led to a 1 percent increase in effective porosity. The difference between water saturation values in Archie and Indonesia methods and 3.3 percent shale volume in the zones show that despite the low shale volume in Formations A and B, its effect on petrophysical parameters has been significant. The results showed that if the shale effect not seen in the evaluation of this gas reservoir, it can lead to significant errors in calculations and correct determination of petrophysical parameters.

The reliability of steel-concrete beams in the process of reconstruction

Introduction. The author solves a number of problems, including the substantiation of the required reliability level for steel-concrete beams in a reconstructed building, design parameters applicable to steel-concrete beams, use of probabilistic methods in the reliability assessment of steel-concrete beams, and reliability assessment of steel-concrete beams. Materials and methods. The engineering data, used in the reliability analysis, included steel beam examination and testing results, obtained by the Koucherenko Central Research and Development Institute of Steel Structures in 2017. The analysis was performed for the cases that took account of or failed to take account of the behaviour of a cast-in-plaсe reinforced concrete floor slab. A method of statistic simulation has proven that the probability values of snow loads set for Moscow by Construction regulations 20.13330.2016 are far below the true ones. This discrepancy reduces the reliability of the contour beams of the construction facility analyzed in this article. Results. B-12, B-45, B-49 and B-61 types of beams were used to compare the testing results with probabilistic calculations. Selected calculation results are provided in the article. An 8 mm deflection, caused by the temporary design load of 2.4 kN/m2 ensures the normal operation of a structure with a probability of 0.9973. Conclusions. A comparison between experimentally and analytically obtained deflection values has proven that the design model must have steel-concrete beams, rather than steel ones. Whenever a building structure is designed, its reliability level must be identified. The reliability of structures, having any criticality rating, depends on the values of the resistance probability in terms of their construction materials and the loads applied to them. Contour steel-concrete beams comply with the technology requirements and reliability values pre-set in the project documentation. Calculation results are validated by their convergence with the experimental data. Probabilistic methods should become a must in structural design. This measure can reduce the risk of failure or cut project costs.

Influence of the foundation bed stiffness on the dynamic properties of the building as of a multi-mass cantilever bar

Relevance. The study of the interaction of buildings and structures with the base during an earthquake is one of the most important tasks of the theory of earthquake resistance. The response of the structure to seismic impact depends to a large extent on the ratio of the stiffness characteristics of the soil, foundation, and foundation structure. Moreover, taking into account a rather high degree of statistical variability of the characteristics of the soil foundation, it is possible to ensure the required level of safety of a structure only through the use of probabilistic models and a quantitative assessment of the reliability of the construction-base system as a whole. At present, for the calculation of the construction - base system for seismic loads, deterministic discrete models of the finite element method are mainly used. But these models are poorly adapted for probabilistic calculations and require extensive statistical data, which are currently insufficient. Therefore, in problems of reliability assessment, it is advisable to use simplified analytical models, which make it possible to derive the value of the statistical variability of its reaction with relatively small initial information about the system. The aim of the work - based on the well-known solution for the single-mass model to present an analytical solution in the matrix form of the problem of free horizontal vibrations of a multi-mass cantilever rod on the foundation specified by the elastic half-space model. Methods. A study was made of the effect of the compliance of the soil foundation on the frequencies and forms of horizontal vibrations of the structure. A comparison of the results with the calculation performed by the finite element method is given. Results. The obtained solution is intended to conduct a probabilistic calculation of the construction-base system under seismic loads and evaluate its reliability.

Problems of ship repairing and maintenance activities in shipyards and mathematical methods to solve that

Mathematical statistics are applied in the field of engineering sciences where there are conditions of risk and uncertainty and where it is necessary to make some rigorously argued decisions. This paper purpouse is to illustrate, the opportunity to use probability theory in solving complex problems from the maritime vessels shipyard maintance and repairing activity, conditioned by uncertainty, risk and variability. The authors intended to demonstrate the fact that usinng the theory of probabilistic calculations could provide an efficient solution for the maintenance work of the drydocked ships in respect with requirement of the classification societies.

Probabilistic analysis of settlements under a pile foundation of a road bridge pylon

The paper addresses the reliability change of a road bridge pile foundation due to the unpredictable increase of settlements in time. The analysis is based on the Rędziński Bridge in Wrocław, Poland, its design assumptions, and monitoring results. The bridge foundation rests on a multi-layered subsoil assumed random. The Finite Element model of the subgrade is generated in ZSoil® software. To simplify the probabilistic approach, substitute soil strata stiffness parameters are adopted. Tracing their time decrement allows for a comprehensive definition of the entire foundation over-settlement produced by numerous factors. Preliminary sensitivity analysis of settlements to the stiffness variation properly simplifies the random model. The Serviceability Limit State helps to assess the foundation reliability index, further compared with the condition in the EN 1990:2002/A1:2005 standard. In addition, real-life settlements are also measured in the first year of bridge operation, they are used to calibrate the reliability index assessment. An innovative approach is proposed, where appropriate time-wise fluctuation functions represent the expected settlement increase and the related reliability reduction. These fluctuation functions help to plan the future remedial actions to maintain the initial bridge safety and to indicate the action frequency and scope. Future reliability levels may be extrapolated too. The real-life survey database of settlements makes it possible to validate the results of probabilistic calculations. A dedicated flowchart is devised to support further analysis of a wide structural domain.

Probabilistic impact of wind energy integration on distribution transformers

In traditional power grid, the direction of power flow of transformers is usually fixed in one direction. However, with the integration of the renewable energy sources, such as wind farms, the power flow in the grid becomes fluctuating and uncertain, which may cause the reverse power flow passing the transformer. For example, excessive reverse power flow may lead to the increase of transformer power loss and challenge the thermal stability of the transformer. This paper investigates the impact of wind energy integration on the existing power system infrastructure, such as distribution transformers. Probabilistic power flow (PPF) method is used for the analysis. Firstly, a sampling method based on Halton sequence is applied for PPF calculation. Then, to ensure the accuracy of probabilistic power flow calculation, the correlation between wind speeds of different wind farms is considered. A 30-Bus system is used for the probabilistic analysis of the transformer reverse power flow with different level of wind penetration. The results show that the reverse power flow of transformer may occur before 100% wind penetration is achieved. The higher the total wind power capacity in the grid causes the greater probability of transformer reverse power flow. Also, the location of wind farms will also affect the probability of transformer reverse power flow.

Probabilistic Load Flow Calculation Considering Correlation Based on Bayesian Network

This study proposes a Bayesian network model for nonlinear dependence of wind speed, solar irradiation, and load. The probabilistic load flow calculation based on a Bayesian network model can effectively obtain the probability characteristics of probabilistic load flow solutions (such as the probability density function of the bus voltage and branch flow) considering the correlation of random variables. First, the wind speed, solar irradiation, and load time series are converted to random variables by the kernel density estimation method, and the probability values of random variables are obtained. Applying the probability value of a random variable as the input data of the Bayesian network, the correlation model is established through structure learning based on the Monte Carlo Markov chain method and parameter learning based on the maximum-likelihood estimation method. Sampling from the Bayesian network, discrete probability values are obtained, and they are transformed to continuous probability values by interpolation. Then, the correlation samples of random variables are obtained by cumulative probability distribution inverse transformation of continuous probability values. Compared to the C-vine copula method and Latin hypercube sampling with modified alternating projections, the proposed Bayesian network model can better present the nonlinear dependence among wind speed, solar irradiation, and load. Finally, the proposed method is verified by probabilistic load flow calculation of the IEEE 69-bus distribution system.