• Title/Summary/Keyword: Stochastic Distribution

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Inverse Estimation Method for Spatial Randomness of Material Properties and Its Application to Topology Optimization on Shape of Geotechnical Structures (재료 물성치의 공간적 임의성에 대한 역추정 방법 및 지반구조 형상의 위상 최적화 적용)

  • Kim, Dae-Young;Song, Myung Kwan
    • Journal of the Korean Geosynthetics Society
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    • v.21 no.3
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    • pp.1-10
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    • 2022
  • In this paper, the spatial randomness and probability characteristics of material properties are inversely estimated by using a set of the stochastic fields for the material properties of geotechnical structures. By using the probability distribution and probability characteristics of these estimated material properties, topology optimization is performed on structure shape, and the results are compared with the existing deterministic topology optimization results. A set of stochastic fields for material properties is generated, and the spatial randomness of material properties in each field is simulated. The probability distribution and probability characteristics of actual material properties are estimated using the partial values of material properties in each stochastic field. The probability characteristics of the estimated actual material properties are compared with those of the stochastic field set. Also, response variability of the ground structure having a modulus of elasticity with randomness is compared with response variability of the ground structure having a modulus of elasticity without randomness. Therefore, the quantified stochastic topology optimization result can be obtained with considering the spatial randomness of actual material properties.

A Study on the Storage Life Estimation Method for Decrease of Muzzle Velocity using Gamma Process Model (감마과정 모델을 적용한 포구속도 저하량에 따른 저장수명 예측기법 연구)

  • Park, Sung-Ho;Kim, Jae-Hoon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.16 no.5
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    • pp.639-645
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    • 2013
  • The aim of the study is to investigate the method to estimate a storage life of propelling charge on the decrease of muzzle velocity by stochastic gamma process model. It is required to establish criterion for state failure to estimate the storage life and it is defined in this paper as a muzzle velocity difference between reference value and maximum allowable standard deviation multiplied by 6. The relationship between storage time and muzzle velocity is investigated by nonlinear regression analysis. The stochastic gamma process model is used to estimated the state distribution and the life distribution for storage time for 155mm propelling charge KM4A2 because the regression analysis is a deterministic method and it can't describe the distribution of life for storage time.

Freeway Design Capacity Estimation through the Analysis of Time Headway Distribution (차두시간분포 분석을 통한 고속도로 설계용량 산정모형의 개발)

  • Kim, Jum San;Park, Chang Ho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.2D
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    • pp.251-258
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    • 2006
  • This study is to develop an estimation method of freeway design capacity through the analysis of time headway distribution in continuum flow. Traffic flow-speed diagram and time headway distribution plotted from individual vehicle data shows: a) a road capacity is not deterministic but stochastic, b) time headway distribution for each vehicle speed group follows pearson type V distribution. The freeway design capacity estimation model is developed by determining a minimum time headway for capacity with stochastic method. The estimated capacity values for each design speed are lower when design speed ${\leq}80km/h$, and higher when design speed ${\geq}106km/h$ in comparison with HCM(2000)'s values. In addition, The distinguish difference is that this model leads flexible application in planning level by defining the capacity as stochastic distribution. In detail, this model could prevent a disutility to add a lane for only one excess demand in a road planning level.

A Study on Optimal Control of Slab Cooling Storage Considering Stochastic Properties of Internal Heat Generation (내부발열의 확률적 성상을 고려한 슬래브축냉의 최적제어)

  • Jung, Jae-Hoon
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.27 no.6
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    • pp.313-320
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    • 2015
  • In this paper, a method to obtain the probability distribution of room temperature and cooling load is presented, when the internal heat generation is applied to the system as a disturbance in the air conditioning system with slab cooling storage. The probability distribution of room temperature and the cooling load due to the disturbance were examined in one room of an office building. When considering only the electric power consumption as a probability component, it was found that the effect on room temperature and cooling load is small, because the probability component of the measured electric power consumption in the building is small. On the other hand, when considering the stochastic fluctuations of electric power consumption together with the heat generated by human bodies, the mean value of the cooling load was about 2,300 W and the ratio of the standard deviations was 19% (10 o'clock in second day). It was revealed that the stochastic effects of internal heat generation acting on the air conditioning system with slab cooling storage are not small.

Power Control with Nearest Neighbor Nodes Distribution for Coexisting Wireless Body Area Network Based on Stochastic Geometry

  • Liu, Ruixia;Wang, Yinglong;Shu, Minglei;Zhao, Huiqi;Chen, Changfang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.11
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    • pp.5218-5233
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    • 2018
  • The coexisting wireless body area networks (WBAN) is a very challenging issue because of strong inter-networks interference, which seriously affects energy consumption and spectrum utilization ratio. In this paper, we study a power control strategy with nearest neighbor nodes distribution for coexisting WBAN based on stochastic geometry. Using homogeneous Poisson point processes (PPP) model, the relationship between the transmission power and the networks distribution is analytically derived to reduce interference to other devices. The goal of this paper is to increase the transmission success probability and throughput through power control strategy. In addition, we evaluate the area spectral efficiency simultaneously active WBAN in the same channel. Finally, extensive simulations are conducted to evaluate the power control algorithm.

Sensitivity Analysis of Finite Fault Model in Stochastic Ground Motion Simulations (추계학적 지진동 모사에서 유한단층 모델의 민감도 분석)

  • Lee, Sang-Hyun;Rhie, Junkee
    • Journal of the Earthquake Engineering Society of Korea
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    • v.28 no.3
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    • pp.159-164
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    • 2024
  • Recent earthquakes in Korea, like Gyeongju and Pohang, have highlighted the need for accurate seismic hazard assessment. The lack of substantial ground motion data necessitates stochastic simulation methods, traditionally used with a simplistic point-source assumption. However, as earthquake magnitude increases, the influence of finite faults grows, demanding the adoption of finite faults in simulations for accurate ground motion estimates. We analyzed variations in simulated ground motions with and without the finite fault method for earthquakes with magnitude (Mw) ranging from 5.0 to 7.0, comparing pseudo-spectral acceleration. We also studied how slip distribution and hypocenter location affect simulations for a virtual earthquake that mimics the Gyeongju earthquake with Mw 5.4. Our findings reveal that finite fault effects become significant at magnitudes above Mw 5.8, particularly at high frequencies. Notably, near the hypocenter, the virtual earthquake's ground motion significantly changes using a finite fault model, especially with heterogeneous slip distribution. Therefore, applying finite fault models is crucial for simulating ground motions of large earthquakes (Mw ≥ 5.8 magnitude). Moreover, for accurate simulations of actual earthquakes with complex rupture processes having strong localized slips, incorporating finite faults is essential even for more minor earthquakes.

Simulation of non-Gaussian stochastic processes by amplitude modulation and phase reconstruction

  • Jiang, Yu;Tao, Junyong;Wang, Dezhi
    • Wind and Structures
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    • v.18 no.6
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    • pp.693-715
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    • 2014
  • Stochastic processes are used to represent phenomena in many diverse fields. Numerical simulation method is widely applied for the solution to stochastic problems of complex structures when alternative analytical methods are not applicable. In some practical applications the stochastic processes show non-Gaussian properties. When the stochastic processes deviate significantly from Gaussian, techniques for their accurate simulation must be available. The various existing simulation methods of non-Gaussian stochastic processes generally can only simulate super-Gaussian stochastic processes with the high-peak characteristics. And these methodologies are usually complicated and time consuming, not sufficiently intuitive. By revealing the inherent coupling effect of the phase and amplitude part of discrete Fourier representation of random time series on the non-Gaussian features (such as skewness and kurtosis) through theoretical analysis and simulation experiments, this paper presents a novel approach for the simulation of non-Gaussian stochastic processes with the prescribed amplitude probability density function (PDF) and power spectral density (PSD) by amplitude modulation and phase reconstruction. As compared to previous spectral representation method using phase modulation to obtain a non-Gaussian amplitude distribution, this non-Gaussian phase reconstruction strategy is more straightforward and efficient, capable of simulating both super-Gaussian and sub-Gaussian stochastic processes. Another attractive feature of the method is that the whole process can be implemented efficiently using the Fast Fourier Transform. Cases studies demonstrate the efficiency and accuracy of the proposed algorithm.

Application of Stochastic Optimization Method to (s, S) Inventory System ((s, S) 재고관리 시스템에 대한 확률최적화 기법의 응용)

  • Chimyung Kwon
    • Journal of the Korea Society for Simulation
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    • v.12 no.2
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    • pp.1-11
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    • 2003
  • In this paper, we focus an optimal policy focus optimal class of (s, S) inventory control systems. To this end, we use the perturbation analysis and apply a stochastic optimization algorithm to minimize the average cost over a period. We obtain the gradients of objective function with respect to ordering amount S and reorder point s via a combined perturbation method. This method uses the infinitesimal perturbation analysis and the smoothed perturbation analysis alternatively according to occurrences of ordering event changes. Our simulation results indicate that the optimal estimates of s and S obtained from a stochastic optimization algorithm are quite accurate. We consider that this may be due to the estimated gradients of little noise from the regenerative system simulation, and their effect on search procedure when we apply the stochastic optimization algorithm. The directions for future study stemming from this research pertain to extension to the more general inventory system with regard to demand distribution, backlogging policy, lead time, and review period. Another directions involves the efficiency of stochastic optimization algorithm related to searching procedure for an improving point of (s, S).

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Stochastic Project Scheduling Simulation System (SPSS III)

  • Lee Dong-Eun
    • Korean Journal of Construction Engineering and Management
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    • v.6 no.1 s.23
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    • pp.73-79
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    • 2005
  • This paper, introduces a Stochastic Project Scheduling Simulation system (SPSS III) developed by the author to predict a project completion probability in a certain time. The system integrates deterministic CPM, probabilistic PERT, and stochastic Discrete Event Simulation (DES) scheduling methods into one system. It implements automated statistical analysis methods for computing the minimum number of simulation runs, the significance of the difference between independent simulations, and the confidence interval for the mean project duration as well as sensitivity analysis method in What-if analyzer component. The SPSS 111 gives the several benefits to researchers in that it (1) complements PERT and Monte Carlo simulation by using stochastic activity durations via a web based JAVA simulation over the Internet, (2) provides a way to model a project network having different probability distribution functions, (3) implements statistical analyses method which enable to produce a reliable prediction of the probability of completing a project in a specified time, and (4) allows researchers to compare the outcome of CPM, PERT and DES under different variability or skewness in the activity duration data.

Stochastic Finite Element Analysis for Rock Caverns Considering the Effect of Discontinuities (불연속면의 영향을 고려한 암반동굴의 확률유한요소해석)

  • 최규섭;황신일;이경진
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1996.10a
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    • pp.95-102
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    • 1996
  • In this study, a stochastic finite element model is proposed with a view to consider the uncertainty of physical properties of discontinuous rock mass in the analysis of structural behavior on underground caverns. In so doing, the LHS(Latin Hypercube sampling) technique has been applied to make up weak points of the Crude Monte Carlo technique. Concerning the effect of discontinuities, a joint finite element model is used that is known to be superior in explaining faults, cleavage, things of that nature. To reflect the uncertainty of material properties, the variables such as the the elastic modulus, the poisson's ratio, the joint shear stiffness, and the joint normal stiffness have been used, all of which can be applicable through normal distribution, log-normal distribution, and rectangulary uniform distribution. The validity of the newly developed computer program has been confirmed in terms of verification examples. And, the applicability of the program has been tested in terms of the analysis of the circular cavern in discontinuous rock mass.

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