scholarly journals REAL-TIME ESTIMATION OF GROUND SNOW LOAD USING SNOW LAYER MODEL

2021 ◽  
Vol 86 (781) ◽  
pp. 371-380
Author(s):  
Dai KOMIYAMA ◽  
Ashidmaa BATSUURI ◽  
Toru TAKAHASHI
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Layer Model ◽  
Snow Layer ◽  
Snow Load ◽  
Ground Snow Load ◽  
Real Time Estimation

scholarly journals ESTIMATION OF GROUND SNOW LOAD USING SNOW LAYER MODEL

2001 ◽  
Vol 66 (545) ◽  
pp. 35-41 ◽  
Author(s):  
Toru TAKAHASHI ◽  
Taiki KAWAMURA ◽  
Koji KURAMOTO
Keyword(s):  
Layer Model ◽  
Snow Layer ◽  
Snow Load ◽  
Ground Snow Load

A machine for real-time estimation of the tribological characteristics of materials

2020 ◽  
Vol 86 (4) ◽  
pp. 61-65
Author(s):  
M. V. Abramchuk ◽  
R. V. Pechenko ◽  
K. A. Nuzhdin ◽  
V. M. Musalimov
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Tribological Characteristics ◽  
Continuous Processing ◽  
Friction Machine ◽  
Dynamic Friction Coefficient ◽  
Displacement Sensors ◽  
Frictional Interaction ◽  
Real Time Estimation ◽  
Automated Quality Control

A reciprocating friction machine Tribal-T intended for automated quality control of the rubbing surfaces of tribopairs is described. The distinctive feature of the machine consists in implementation of the forced relative motion due to the frictional interaction of the rubbing surfaces fixed on the drive and conjugate platforms. Continuous processing of the signals from displacement sensors is carried out under conditions of continuous recording of mutual displacements of loaded tribopairs using classical approaches of the theory of automatic control to identify the tribological characteristics. The machine provides consistent visual real time monitoring of the parameters. The MATLAB based computer technologies are actively used in data processing. The calculated tribological characteristics of materials, i.e., the dynamic friction coefficient, damping coefficient and measure of the surface roughness, are presented. The tests revealed that a Tribal-T reciprocating friction machine is effective for real-time study of the aforementioned tribological characteristics of materials and can be used for monitoring of the condition of tribo-nodes of machines and mechanisms.

Onboard Real-time Estimation of Mean Orbital Elements with Atmospheric Drag

2013 ◽  
Vol 39 (10) ◽  
pp. 1722
Author(s):  
Zhao-Wei SUN ◽  
Wei-Chao ZHONG ◽  
Shi-Jie ZHANG ◽  
Jian ZHANG
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Atmospheric Drag ◽  
Orbital Elements ◽  
Real Time Estimation

Soft sensor for real-time estimation of tablet potency in continuous direct compression manufacturing operation

2021 ◽  
Vol 602 ◽  
pp. 120624
Author(s):  
Reza Kamyar ◽  
David Lauri Pla ◽  
Anas Husain ◽  
Giuseppe Cogoni ◽  
Zilong Wang
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Soft Sensor ◽  
Direct Compression ◽  
Real Time Estimation

scholarly journals Real-Time Estimation of Microgrid Inertia and Damping Constant

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Ujjwol Tamrakar ◽  
David A. Copp ◽  
Tu Nguyen ◽  
Timothy M. Hansen ◽  
Reinaldo Tonkoski
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Real Time Estimation

scholarly journals Joint structure for the real-time estimation and control of automotive dry clutch engagement

2018 ◽  
Vol 51 (15) ◽  
pp. 1062-1067 ◽  
Author(s):  
Mojtaba Sharifzadeh ◽  
Mario Pisaturo ◽  
Arash Farnam ◽  
Adolfo Senatore
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
The Real ◽  
Joint Structure ◽  
Clutch Engagement ◽  
Real Time Estimation ◽  
Dry Clutch ◽  
Estimation And Control ◽  
And Control

scholarly journals An Approach for Real-time Estimation of Railway Passenger Flow

2010 ◽  
Vol 51 (2) ◽  
pp. 82-88 ◽  
Author(s):  
Yoichi SUGIYAMA ◽  
Hiroshi MATSUBARA ◽  
Shuichi MYOJO ◽  
Kazuki TAMURA ◽  
Naoya OZAKI
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Passenger Flow ◽  
Real Time Estimation ◽  
Railway Passenger
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