• 제목/요약/키워드: beam training

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Fuzzy Logic Modeling and Its Application to A Walking-Beam Reheating Furnace

  • Zhang, Bin;Wang, Jing-Cheng
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제7권3호
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    • pp.182-187
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    • 2007
  • A fuzzy modeling method is proposed to build the dynamic model of a walking-beam reheating furnace from the recorded data. In the proposed method, the number of membership function on each variable is increased individually and the modeling accuracy is evaluated iteratively. When the modeling accuracy is satisfied, the membership functions on each variable are fixed and the structure of fuzzy model is determined. Because the training data is limited, in this process, as the number of membership function increase, it is highly possible that some rules are missing, i.e., no data in the training set corresponds to the consequent part of a missing rule. To complete the rulebase, the output of the model constructed at the previous step is used to generate the consequent part of the missing rules. Finally, in the real time application, a rolling update scheme to rulebase is introduced to compensate the change of system dynamics and fine tune the rulebase. The proposed method is verified by the application to the modeling of a reheating furnace.

Characterization of a Neutron Beam Following Reconfiguration of the Neutron Radiography Reactor (NRAD) Core and Addition of New Fuel Elements

  • Craft, Aaron E.;Hilton, Bruce A.;Papaioannou, Glen C.
    • Nuclear Engineering and Technology
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    • 제48권1호
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    • pp.200-210
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    • 2016
  • The neutron radiography reactor (NRAD) is a 250 kW Mark-II Training, Research, Isotopes, General Atomics (TRIGA) reactor at Idaho National Laboratory, Idaho Falls, ID, USA. The East Radiography Station (ERS) is one of two neutron beams at the NRAD used for neutron radiography, which sits beneath a large hot cell and is primarily used for neutron radiography of highly radioactive objects. Additional fuel elements were added to the NRAD core in 2013 to increase the excess reactivity of the reactor, and may have changed some characteristics of the neutron beamline. This report discusses characterization of the neutron beamline following the addition of fuel to the NRAD. This work includes determination of the facility category according to the American Society for Testing and Materials (ASTM) standards, and also uses an array of gold foils to determine the neutron beam flux and evaluate the neutron beam profile. The NRAD ERS neutron beam is a Category I neutron radiography facility, the highest possible quality level according to the ASTM. Gold foil activation experiments show that the average neutron flux with length-to-diameter ratio (L/D) = 125 is $5.96{\times}10^6n/cm^2/s$ with a $2{\sigma}$ standard error of $2.90{\times}10^5n/cm^2/s$. The neutron beam profile can be considered flat for qualitative neutron radiographic evaluation purposes. However, the neutron beam profile should be taken into account for quantitative evaluation.

Numerical solution of beam equation using neural networks and evolutionary optimization tools

  • Babaei, Mehdi;Atasoy, Arman;Hajirasouliha, Iman;Mollaei, Somayeh;Jalilkhani, Maysam
    • Advances in Computational Design
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    • 제7권1호
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    • pp.1-17
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    • 2022
  • In this study, a new strategy is presented to transmit the fundamental elastic beam problem into the modern optimization platform and solve it by using artificial intelligence (AI) tools. As a practical example, deflection of Euler-Bernoulli beam is mathematically formulated by 2nd-order ordinary differential equations (ODEs) in accordance to the classical beam theory. This fundamental engineer problem is then transmitted from classic formulation to its artificial-intelligence presentation where the behavior of the beam is simulated by using neural networks (NNs). The supervised training strategy is employed in the developed NNs implemented in the heuristic optimization algorithms as the fitness function. Different evolutionary optimization tools such as genetic algorithm (GA) and particle swarm optimization (PSO) are used to solve this non-linear optimization problem. The step-by-step procedure of the proposed method is presented in the form of a practical flowchart. The results indicate that the proposed method of using AI toolsin solving beam ODEs can efficiently lead to accurate solutions with low computational costs, and should prove useful to solve more complex practical applications.

Flutter phenomenon in composite sandwich beams with flexible core under follower force

  • Saghavaz, Fahimeh Rashed;Payganeh, GHolamhassan;Fard, Keramat Malekzadeh
    • Steel and Composite Structures
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    • 제39권5호
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    • pp.615-630
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    • 2021
  • The main purpose of the present work was to study the dynamic instability of a three-layered, thick composite sandwich beam with the functionally graded (FG) flexible core subjected to an axial compressive follower force. Flutter instability of a sandwich cantilever beam was analyzed using the high-order theory of sandwich beams, for the first time. The governing equations in general for sandwich beams with an FG core were extracted and could be used for all types of sandwich beams with any types of face sheets and cores. A polynomial function is considered for the vertical distribution of the displacement field in the core layer along the thickness, based on the results of the first Frosting's higher order model. The governing partial differential equations and the equations of boundary conditions of the dynamic system are derived using Hamilton's principle. By applying the boundary conditions and numerical solution methods of squares quadrature, the beam flutter phenomenon is studied. In addition, the effects of different geometrical and material parameters on the flutter threshold were investigated. The results showed that the responses of the dynamic instability of the system were influenced by the follower force, the coefficients of FGs and the geometrical parameters like the core thickness. Comparison of the present results with the published results in the literature for the special case confirmed the accuracy of the proposed theory. The results showed that the follower force of the flutter phenomenon threshold for long beams tends to the corresponding results in the Timoshenko beam.

k-NN 분류 모델의 학습 데이터 구성에 따른 PIC 보의 하중 충실도 향상에 관한 연구 (Load Fidelity Improvement of Piecewise Integrated Composite Beam by Construction Training Data of k-NN Classification Model)

  • 함석우;전성식
    • Composites Research
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    • 제33권3호
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    • pp.108-114
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    • 2020
  • Piecewise Integrated Composite (PIC) 보는 하중 유형에 따라 구간을 나누어, 각 구간마다 하중 유형에 강한 복합재료의 적층 순서를 배열한 보이다. 본 연구는 PIC 보의 구간을 머신 러닝의 일종인 k-NN(k-Nearest Neighbor) 분류를 통해 나누어 기존에 제시되었던 PIC 보에 비해 우수한 굽힘 특성을 갖게 하는 것이 목적이다. 먼저, 알루미늄 보의 3점 굽힘 해석을 통하여 참조점에서의 3축 특성(Triaxiality) 값 데이터를 얻었고, 이를 통해 인장, 전단, 압축의 레이블을 가진 학습 데이터가 만들어진다. 학습 데이터를 통해 각 면마다 독립적인 k-NN 분류 모델을 구성하는 방법(Each plane)과 전체 면에 대한 k-NN 분류 모델을 구성하는 방법(one part)을 이용하여 k-NN 분류 모델을 생성하였고, 하이퍼파라미터의 튜닝을 통하여 다양한 하중 충실도를 도출하였다. 가장 높은 하중 충실도를 가진 k-NN 분류 모델을 기반으로 보를 매핑(mapping)하였고, PIC 보에 대하여 유한요소 해석을 진행한 결과, 기존에 제시되었던 PIC 보에 비해 최대하중과 흡수 에너지가 커지는 특성을 보였다. 하중 충실도를 수동으로 조절하여 100%로 만든 PIC 보와 비교하였을 때, 최대하중과 흡수에너지가 미소한 차이가 나타났으며 이는 타당한 하중 충실도로 보여진다.

실험적 뇌허혈로 인한 편마비 흰쥐에서 운동 적응 훈련이 기능 회복에 미치는 영향 (The Effect of Exercise Adaptive Training on Motor Function after Experimental brain ischemia in Rats)

  • 권영실;김진상
    • The Journal of Korean Physical Therapy
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    • 제13권3호
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    • pp.529-535
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    • 2001
  • The purpose of this study was to test that the exercise adaptive training enhance behavioral outcome significantly after focal brain ischemia in rats. After occlusion of middle cerebral artery in rats, they were housed in individual standard cages fur 24 hours. The control group was sacrificed 24 hours after ischemic event. The experimental group I was housed in standard cages for 7days. The experimental group ll was housed in enriched environment and had got exercise adaptive training fur 7days. The rats were examined five motor behavioral tests. In motor behavioral tests :postural reflex test, limb placement test, beam-walking test, rotarod test, horizontal wire test. The outcomes of control group and group I were significantly lower than the group II. The conclusion was that exercise adaptive training induced functional repair.

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Crack detection method for step-changed non-uniform beams using natural frequencies

  • Lee, Jong-Won
    • Smart Structures and Systems
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    • 제30권2호
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    • pp.173-181
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    • 2022
  • The current paper presents a technique to detect crack in non-uniform cantilever-type pipe beams, that have step changes in the properties of their cross sections, restrained by a translational and rotational spring with a tip mass at the free end. An equation for estimating the natural frequencies for the non-uniform beams is derived using the boundary and continuity conditions, and an equivalent bending stiffness for cracked beam is applied to calculate the natural frequencies of the cracked beam. An experimental study for a step-changed non-uniform cantilever-type pipe beam restrained by bolts with a tip mass is carried out to verify the proposed method. The translational and rotational spring constants are updated using the neural network technique to the results of the experiment for intact case in order to establish a baseline model for the subsequent crack detection. Then, several numerical simulations for the specimen are carried out using the derived equation for estimating the natural frequencies of the cracked beam to construct a set of training patterns of a neural network. The crack locations and sizes are identified using the trained neural network for the 5 damage cases. It is found that the crack locations and sizes are reasonably well estimated from a practical point of view. And it is considered that the usefulness of the proposed method for structural health monitoring of the step-changed non-uniform cantilever-type pipe beam-like structures elastically restrained in the ground and have a tip mass at the free end could be verified.

Thermal buckling of smart porous functionally graded nanobeam rested on Kerr foundation

  • Karami, Behrouz;Shahsavari, Davood;Nazemosadat, Seyed Mohammad Reza;Li, Li;Ebrahimi, Arash
    • Steel and Composite Structures
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    • 제29권3호
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    • pp.349-362
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    • 2018
  • Thermal buckling behavior of porous functionally graded nanobeam integrated with piezoelectric sensor and actuator based on the nonlocal higher-order shear deformation beam theory is investigated for the first time. Its material properties are assumed to be temperature-dependent and varying along the thickness direction according to the modified power-law rule. Note that the porosity with even type is considered herein. The equations of motion are obtained through Hamilton's principle. The influences of several parameters (such as type of temperature distribution, external electric voltage, material composition, porosity, small-scale effect, Ker foundation parameters, and beam thickness) on the thermal buckling of FG nanobeam are investigated in detail.

선택 빔형성을 적용한 다중경로 환경 VSB 수신 성능 개선 (Reception performance improvement of VSB in multipath channel using switched beamforming)

  • 배재휘;서재현;김주연;김승원
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 I
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    • pp.35-38
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    • 2003
  • We propose a switched beamforming to improve the reception performance of VSB system in severe Rayleigh fading channel. The VSB system has only about 3% of known training signal for the receiver in a data field and the reception performance of VSB receiver is degraded significantly when there are near-0 dB ghosts in receiving signal. The switched beamforming forms several beams in different directions and selects only one beam among them. For the selection of a beam with best channel condition for VSB equalizer, we extracted the channel profiles in time domain for all the beams by correlating the PN511 sequence in VSB field sync and selected optimal beam by comparing the channel profiles. The simulation results show that the proposed method improves the reception performance of VSB system in severe Rayleigh channel.

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확률신경망에 기초한 교량구조물의 손상평가 (Probabilistic Neural Network-Based Damage Assessment for Bridge Structures)

  • 조효남;강경구;이성칠;허춘근
    • 한국구조물진단유지관리공학회 논문집
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    • 제6권4호
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    • pp.169-179
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    • 2002
  • This paper presents an efficient algorithm for the estimation of damage location and severity in structure using Probabilistic Neural Network (PNN). Artificial neural network has been being used for damage assessment by many researchers, but there are still some barriers that must be overcome to improve its accuracy and efficiency. The major problems with the conventional neural network are the necessity of many training data for neural network learning and ambiguity in the relation of neural network architecture with convergence of solution. In this paper, PNN is used as a pattern classifier to overcome those problems in the conventional neural network. The basic idea of damage assessment algorithm proposed in this paper is that modal characteristics from a damaged structure are compared with the training patterns which represent the damage in specific element to determine how close it is to training patterns in terms of the probability from PNN. The training pattern that gives a maximum probability implies that the element used in producing the training pattern is considered as a damaged one. The proposed damage assessment algorithm using PNN is applied to a 2-span continuous beam model structure to verify the algorithm.