scholarly journals Fuzzy state space model for a pressurizer in a nuclear power plant

2015 ◽  
Vol 11 (2) ◽  
Author(s):  
A. Ashaari ◽  
T. Ahmad ◽  
Mustaffa Shamsuddin ◽  
S. Zenian
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
State Space ◽  
Nuclear Power ◽  
State Space Model ◽  
Published Data ◽  
State Space Approach ◽  
Space Model ◽  
Fuzzy State ◽  
Space Approach

In this paper, Fuzzy State Space Model (FSSM) for a nuclear power plant is proposed. Pressurizer is used to control pressure and temperature in a nuclear power plant. In order to maintain the pressure and the temperature of the system, the effectiveness of the system needs to be monitored frequently. Hence, fuzzy state space approach is used to model the pressurizer. The influence of input to output of the pressurizer is established and presented in this paper. The result from the model is then verified against published data.

scholarly journals A latent low-dimensional common input drives a pool of motor neurons: a probabilistic latent state-space model

2017 ◽  
Vol 118 (4) ◽  
pp. 2238-2250 ◽  
Author(s):  
Daniel F. Feeney ◽  
François G. Meyer ◽  
Nicholas Noone ◽  
Roger M. Enoka
Keyword(s):  
State Space ◽  
Motor Neurons ◽  
Input Signal ◽  
State Space Model ◽  
Motor Units ◽  
Common Input ◽  
State Space Approach ◽  
Space Model ◽  
Discharge Activity ◽  
The Common

Motor neurons appear to be activated with a common input signal that modulates the discharge activity of all neurons in the motor nucleus. It has proven difficult for neurophysiologists to quantify the variability in a common input signal, but characterization of such a signal may improve our understanding of how the activation signal varies across motor tasks. Contemporary methods of quantifying the common input to motor neurons rely on compiling discrete action potentials into continuous time series, assuming the motor pool acts as a linear filter, and requiring signals to be of sufficient duration for frequency analysis. We introduce a space-state model in which the discharge activity of motor neurons is modeled as inhomogeneous Poisson processes and propose a method to quantify an abstract latent trajectory that represents the common input received by motor neurons. The approach also approximates the variation in synaptic noise in the common input signal. The model is validated with four data sets: a simulation of 120 motor units, a pair of integrate-and-fire neurons with a Renshaw cell providing inhibitory feedback, the discharge activity of 10 integrate-and-fire neurons, and the discharge times of concurrently active motor units during an isometric voluntary contraction. The simulations revealed that a latent state-space model is able to quantify the trajectory and variability of the common input signal across all four conditions. When compared with the cumulative spike train method of characterizing common input, the state-space approach was more sensitive to the details of the common input current and was less influenced by the duration of the signal. The state-space approach appears to be capable of detecting rather modest changes in common input signals across conditions. NEW & NOTEWORTHY We propose a state-space model that explicitly delineates a common input signal sent to motor neurons and the physiological noise inherent in synaptic signal transmission. This is the first application of a deterministic state-space model to represent the discharge characteristics of motor units during voluntary contractions.

scholarly journals On morphological variability of some species of pennate (Bacillariophyta) from the reservoirs of the Chernobyl nuclear power plant exclusion zone (Ukraine)

Algologia ◽  
2021 ◽  
Vol 31 (3) ◽  
pp. 205-214
Author(s):  
S.I. Genkal ◽  
◽  
V.I. Shcherbak ◽  
N.Ye. Semenyuk ◽  
◽  
...  
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Morphological Variability ◽  
Central Area ◽  
Microscopy Study ◽  
Electron Microscopy Study ◽  
Chernobyl Nuclear Power Plant ◽  
Published Data ◽  
Exclusion Zone

This scanning electron microscopy study of the morphology of pennate diatoms (Achnanthidium eutrophilum (Lange-Bertalot) Lange-Bertalot, Aneumastis stroesei Mann et Stickle, Gomphonema italicum Kützing, G. pala Reichardt, G. vibrio Ehrenberg, Punctastriata ovalis Williams et Round) from phytoperiphytic communities in the cooling pond of the Chernobyl nuclear power plant and natural lakes of the Exclusion Zone (Glyboke and Daleke lakes) has revealed a higher variability in quantitative characteristics (valve length and width, number of striae in 10 µm). At the same time, no variability of qualitative features (shape of valve, axial and central area, raphe and striae arrangement) has been observed in these species. In A. eutrophilum, the number of striae in 10 µm differ from the published data, in A. stroesei – the valve length, in G. pala, G. vibrio and P. ovalis – the valve length and width. The range of variation in the number of striae in 10 µm in G. pala and the valve length and the number of striae in 10 µm in A. stroesei and G. italicum disagree with the literature data. The first electron micrographs of the inner surface of the valve and the corresponding data on its morphology are obtained for A. eutrophilum, A. stroesei, G. italicum, G. pala and G. vibrio.

scholarly journals Fuzzy State Space Model of Multivariable Control Systems

2009 ◽  
Vol 2 (2) ◽  
Author(s):  
R. Ismail ◽  
K. Jusoff ◽  
T. Ahmad ◽  
S. Ahmad ◽  
R.S. Ahmad
Keyword(s):  
State Space ◽  
Control Systems ◽  
State Space Model ◽  
Multivariable Control ◽  
Space Model ◽  
Multivariable Control Systems ◽  
Fuzzy State

Probabilistic Fracture Assessment of Wall Thinning Pipe

2005 ◽  
Author(s):  
Hideo Machida ◽  
Kotoji Ando
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Probability Density Function ◽  
Wear Rate ◽  
Probability Density ◽  
Density Function ◽  
Failure Probability ◽  
Nuclear Power ◽  
Published Data ◽  
Wall Thinning

This paper describes failure probability assessment of thinning pipe of a nuclear-power plant. The rupture of the feed water piping in the turbine building due to wall thinning happened in Kansai Electric Power Company (KEPCO) Mihama nuclear power plant Unit-3 on August 9, 2004. The variation between the prediction and measured wear rate was evaluated using the published data from KEPCO, and the probability density function was created. Using this probability density function, the failure probability of wall thinning pipe was evaluated using Monte Carlo simulation. The parameters of this evaluation are thinning patterns, wear rate, an applied stress and an inspection interval. The requirements to the inspection were clarified from the probability of failure.

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