• 제목/요약/키워드: random parameter

검색결과 604건 처리시간 0.025초

2-parameter criterion에 의한 탄소성 파괴확률 예측수법 (Method of Estimate of Fracture Probability for Elastic-Plasticity by 2-Parameter Criterion)

  • 김태식;윤한용;임명환;정의정
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2003년도 춘계학술대회
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    • pp.226-234
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    • 2003
  • Put Many researcher have made much progress in studying an estimate for fracture probability of brittle materials. However, studies of the fracture probability for the elastic-plasticity have not been made yet. An estimate method for fracture probability which is grafted onto 2-parameter criterion and statistical probability analysis is not only introduced in this study, but also applied to the simple 2dimensional model and carbon steel piping to evaluate the effect of random variable.

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Use of rotating disk for Darcy-Forchheimer flow of nanofluid; Similarity transformation through porous media

  • Hussain, Muzamal;Sharif, Humaira;Khadimallah, Mohamed Amine;Ayed, Hamdi;Banoqitah, Essam Mohammed;Loukil, Hassen;Ali, Imam;Mahmoud, S.R.;Tounsi, Abdelouahed
    • Computers and Concrete
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    • 제30권1호
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    • pp.1-8
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    • 2022
  • The basic purpose of the current study is to compute the numerical analysis of heat source/sink for Darcy-Forchheimer three dimensional nanofluid flow with gyrotactic microorganism by rotatable disk via porous media under the slip conditions. Due to nanoparticles, random and thermophoretic motion phenomenon occurs. The governing mathematical model is handled numerically by shooting method. Additionally, the characteristics of velocities, mass, heat, motile microorganisms and associated parameters are thoroughly analyzed via plots and tables. Different physical parameters like Forchheimer number, slip parameters like velocity, porosity parameter, Prandtl number, Brownian number, thermophoresis parameter, heat sink/source parameter, bioconvected Rayleigh number, buoyancy parameteron dimensionless velocities, temperature. Approximate values of Sherwood microorganism are analyzed.

Viscoplasticity model stochastic parameter identification: Multi-scale approach and Bayesian inference

  • Nguyen, Cong-Uy;Hoang, Truong-Vinh;Hadzalic, Emina;Dobrilla, Simona;Matthies, Hermann G.;Ibrahimbegovic, Adnan
    • Coupled systems mechanics
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    • 제11권5호
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    • pp.411-438
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    • 2022
  • In this paper, we present the parameter identification for inelastic and multi-scale problems. First, the theoretical background of several fundamental methods used in the upscaling process is reviewed. Several key definitions including random field, Bayesian theorem, Polynomial chaos expansion (PCE), and Gauss-Markov-Kalman filter are briefly summarized. An illustrative example is given to assimilate fracture energy in a simple inelastic problem with linear hardening and softening phases. Second, the parameter identification using the Gauss-Markov-Kalman filter is employed for a multi-scale problem to identify bulk and shear moduli and other material properties in a macro-scale with the data from a micro-scale as quantities of interest (QoI). The problem can also be viewed as upscaling homogenization.

Study on the Dynamic Model and Simulation of a Flexible Mechanical Arm Considering its Random Parameters

  • He Bai-Yan;Wang Shu-Xin
    • Journal of Mechanical Science and Technology
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    • 제19권spc1호
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    • pp.265-271
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    • 2005
  • Randomness exists in engineering. Tolerance, assemble-error, environment temperature and wear make the parameters of a mechanical system uncertain. So the behavior or response of the mechanical system is uncertain. In this paper, the uncertain parameters are treated as random variables. So if the probability distribution of a random parameter is known, the simulation of mechanical multibody dynamics can be made by Monte-Carlo method. Thus multibody dynamics simulation results can be obtained in statistics. A new concept called functional reliability is put forward in this paper, which can be defined as the probability of the dynamic parameters(such as position, orientation, velocity, acceleration etc.) of the key parts of a mechanical multibody system belong to their tolerance values. A flexible mechanical arm with random parameters is studied in this paper. The length, width, thickness and density of the flexible arm are treated as random variables and Gaussian distribution is used with given mean and variance. Computer code is developed based on the dynamic model and Monte-Carlo method to simulate the dynamic behavior of the flexible arm. At the same time the end effector's locating reliability is calculated with circular tolerance area. The theory and method presented in this paper are applicable on the dynamics modeling of general multibody systems.

다열 불투과성 수중방파제를 통과하는 다방향 불규칙파랑의 해석 (Analysis of Multi-directional Random Waves Propagating over Multi Arrayed Impermeable Submerged Breakwater)

  • 정재상;강규영;조용식
    • 한국해안해양공학회지
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    • 제19권1호
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    • pp.29-37
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    • 2007
  • 본 연구에서는 고유함수전개법을 사용하여 다열 불투과성 수중방파제를 통과하는 다방향 불규칙파랑의 통과와 반사를 계산하였다. 입사하는 다방향 불규칙파랑은 Bretschneider-Mitsuyasu 주파수 스펙트럼과 Mitsuyasu 타입의 방향스펙트럼을 사용하여 재현하였다. 첨두주파수의 Bragg 반사 조건에서 강한 반사가 발행하였다. 수중 방파제가 3열이고, 상대높이가 0.6일 때 입사하는 다방향 불규칙파 에너지의 25% 이상이 외해로 반사되었다. 그리고, 최대분산계수 $s_{max}$가 증가할 경우, 다방향 불규칙파랑의 반사율도 증가하였다.

전자결재 시스템에서 보안기법 설계 및 구현 (Design and Implementation of Security Technique in Electronic Signature System)

  • 유영모;강성수;김완규;송진국
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2001년도 추계종합학술대회
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    • pp.491-498
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    • 2001
  • 본 논문에서는 개방형 통신상에서 전송중인 데이터를 암호화시켜 정보의 노출을 방지하고 송신자가 인정한 수신자만이 이러한 정보를 받을 수 있도록 한 암호화 알고리즘을 제시한다. 암호화의 방법에는 크게 관용키 암호화 방법과 공개키 암호화 방법으로 나누는데 본 논문에서는 혼합형 암호화 방식의 개념을 이용했다. 이 알고리즘은 통신시간과 저장공간을 절약하기 위해 전송할 데이터를 압축한 다음 암호화시키게 되며, 암호화 key를 생성하기 위한 파라미터로서 키를 생성하게 하는 것이 특징이다. 파라미터는 키 값이 생성됨과 동시에 전송되고 매 26회마다 파라미터를 변경시켜 키를 재생성 시킨다. 암호화키의 구성요소인 random number 는 table 형태로 저장되는데 키가 40회마다 table을 재편성 key의 보안을 강화하였다. 이렇게 생성된 키와 원래 데이터는 연산과정을 거쳐 암호화가 이루어진다. 복호화는 전송된 파라미터를 조사해 복호화 키를 구한 다음 암호화 동작의 역순으로 수행한다. 본 논문에서 제시한 알고리즘을 구현 및 평가결과는 100KB 메시지 0.0152/sec 정도로 빠른 수행이 되었다.

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Predicting the CPT-based pile set-up parameters using HHO-RF and PSO-RF hybrid models

  • Yun Dawei;Zheng Bing;Gu Bingbing;Gao Xibo;Behnaz Razzaghzadeh
    • Structural Engineering and Mechanics
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    • 제86권5호
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    • pp.673-686
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    • 2023
  • Determining the properties of pile from cone penetration test (CPT) is costly, and need several in-situ tests. At the present study, two novel hybrid learning models, namely PSO-RF and HHO-RF, which are an amalgamation of random forest (RF) with particle swarm optimization (PSO) and Harris hawks optimization (HHO) were developed and applied to predict the pile set-up parameter "A" from CPT for the design aim of the projects. To forecast the "A," CPT data along were collected from different sites in Louisiana, where the selected variables as input were plasticity index (PI), undrained shear strength (Su), and over consolidation ratio (OCR). Results show that both PSO-RF and HHO-RF models have acceptable performance in predicting the set-up parameter "A," with R2 larger than 0.9094, representing the admissible correlation between observed and predicted values. HHO-RF has better proficiency than the PSO-RF model, with R2 and RMSE equal to 0.9328 and 0.0292 for the training phase and 0.9729 and 0.024 for testing data, respectively. Moreover, PI and OBJ indices are considered, in which the HHO-RF model has lower results which leads to outperforming this hybrid algorithm with respect to PSO-RF for predicting the pile set-up parameter "A," consequently being specified as the proposed model. Therefore, the results demonstrate the ability of the HHO algorithm in determining the optimal value of RF hyperparameters than PSO.

Utilizing the GOA-RF hybrid model, predicting the CPT-based pile set-up parameters

  • Zhao, Zhilong;Chen, Simin;Zhang, Dengke;Peng, Bin;Li, Xuyang;Zheng, Qian
    • Geomechanics and Engineering
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    • 제31권1호
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    • pp.113-127
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    • 2022
  • The undrained shear strength of soil is considered one of the engineering parameters of utmost significance in geotechnical design methods. In-situ experiments like cone penetration tests (CPT) have been used in the last several years to estimate the undrained shear strength depending on the characteristics of the soil. Nevertheless, the majority of these techniques rely on correlation presumptions, which may lead to uneven accuracy. This research's general aim is to extend a new united soft computing model, which is a combination of random forest (RF) with grasshopper optimization algorithm (GOA) to the pile set-up parameters' better approximation from CPT, based on two different types of data as inputs. Data type 1 contains pile parameters, and data type 2 consists of soil properties. The contribution of this article is that hybrid GOA - RF for the first time, was suggested to forecast the pile set-up parameter from CPT. In order to do this, CPT data and related bore log data were gathered from 70 various locations across Louisiana. With an R2 greater than 0.9098, which denotes the permissible relationship between measured and anticipated values, the results demonstrated that both models perform well in forecasting the set-up parameter. It is comprehensible that, in the training and testing step, the model with data type 2 has finer capability than the model using data type 1, with R2 and RMSE are 0.9272 and 0.0305 for the training step and 0.9182 and 0.0415 for the testing step. All in all, the models' results depict that the A parameter could be forecasted with adequate precision from the CPT data with the usage of hybrid GOA - RF models. However, the RF model with soil features as input parameters results in a finer commentary of pile set-up parameters.

피라미드 구조와 베이지안 접근법을 이용한 Markove Random Field의 효율적 모델링 (Efficient Methodology in Markov Random Field Modeling : Multiresolution Structure and Bayesian Approach in Parameter Estimation)

  • 정명희;홍의석
    • 대한원격탐사학회지
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    • 제15권2호
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    • pp.147-158
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    • 1999
  • 지표면에 대한 다양한 정보를 제공해 주는 원격탐사기법은 수 십년 동안 우리의 환경을 관찰하고 이해하는데 중요한 역할을 해왔다. 이러한 원격탐사 자료를 이용하는데 다양한 디지털 영상처리기법이 도입되어 자료에서 관찰되는 여러 가지 특성을 모형화하고 처리하는데 매우 유용하게 활용되어져 왔다. 화소들 간의 공간적 관계를 고려하는 Markov Random Field (MRF) 모형은 텍스처 모델링이나 영상분할 및 분류와 같은 여러 분야에서 많이 이용되는 모형으로 이것에 기초한 다양한 알고리즘이 발표되었다. 보통 원격탐사 자료는 그 크기가 매우 크고 시간적 간격을 두고 변화를 관측해 가는 경우에는 분석해야할 자료의 양이 매우 방대하다. 이러한 자료를 처리하는데 걸리는 시간은 처리해야할 자료의 양과는 비선형적 관계에 있다. 본 논문에서는 MRF를 이용하여 원격탐사 자료를 처리할 때 걸리는 시간을 단축하기 위한 방법론이 연구되었다. 이를 위해 논리적 구조로 영상을 피라미드형태로 감소하는 크기로 분석하는 multiresolution 구조가 고려되었는데 이는 연상의 거시적 특징과 미세한 특징을 효율적으로 분석할 수 있는 방법을 제공해 준다. 영상의 크기가 커질수록 파라미터 추정 또한 복잡하고 많은 시간을 요하게 된다. 본 논문에서는 이를 위해 Bayesian 방법을 이용하여 원격탐사 영상과 같은 크기가 큰 영상의 MRF 모형의 파라미터를 효율적으로 추정할 수 있는 방법에 제안되어 있다.

주기적 확률외란을 갖는 DC 전동기의 적응형 상태궤환 제어시스템 (Adaptive State Feedback Control System of DC Motors with Periodic Random Disturbance)

  • 정상철;김준수;조현철;이형기
    • 전기학회논문지
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    • 제57권6호
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    • pp.1036-1041
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    • 2008
  • Periodic disturbance is practically occurred in several engineering applications, especially in data storage systems. However, recently addressed controls for such problem were mostly dealt with its deterministic nature, which is rarely practical in real-time implementation. We present an adaptive control approach for DC motor systems with periodic stochastic disturbance whose frequency and magnitude are both random variables. We establish adaptive state feedback control which is linearly composed of nominal and corrective control parameter matrices. The former is derived from a nominal system model voiding disturbance and the latter is constructed from a disturbed system model by using Lyapunov stability theory. We carry out computer simulation to evaluate the proposed control methodology and compare to the recently addressed control method to demonstrate its superiority.