scholarly journals Improvement of H2O2 Stabilization in Rainwater Samples

2013 ◽  
Vol 6 (2) ◽  
pp. 149-156
Keyword(s):  
Time Estimation ◽  
Sample Collection ◽  
Fluorometric Method ◽  
Sampling Protocol ◽  
Minimal Decomposition ◽  
Real Time Estimation ◽  
Remote Sites ◽  
Sodium Stannate ◽  
Few Data ◽  
Precipitation Events

Peroxides collected in rainwater readily decompose in the natural matrix, consequently it is hard to estimate their values present during precipitation events. For this reason, only few data concerning the concentration of aqueous H2O2 in dew, cloud and rainwater are available. Therefore, it is necessary to establish a sampling protocol under conditions that assure the real-time estimation of hydrogen peroxide in rainwater samples. Hydrogen Peroxide was determined by a fluorometric method in rainwater collected in fives sites in Mexico. Measured levels for all sampled sites were in agreement with values reported by other authors for marine and continental sites. To establish a sampling protocol, several methods reported for preservation of H2O2 in rainwater were assessed. Sampling protocol proposed in this research involves forming fluorescent dimmer on-site immediately after sample collection, and storing at dark and 4 ºC. This procedure gives a 10 days margin to perform sample analysis, guarantying a minimal decomposition of H2O2 in rainwater samples (approximately 10%) and allowing more time to perform sampling campaigns even in remote sites. The other methods evaluated (freezing, filtering, using acidified samplers, adding sodium stannate, and storing samples and their fluorescent dimmer at 0ºC) do not exert any preservation effect over H2O2 levels in rainwater samples.

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 A Fusion Algorithm for Estimating Time-Independent/-Dependent Parameters and States

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4068
Author(s):  
Zheshuo Zhang ◽  
Jie Zhang ◽  
Jiawen Dai ◽  
Bangji Zhang ◽  
Hengmin Qi
Keyword(s):  
Unscented Kalman Filter ◽  
Time Estimation ◽  
Estimation Algorithm ◽  
Estimation Methods ◽  
Fusion Algorithm ◽  
State Variable ◽  
Current Estimation ◽  
Real Time Estimation ◽  
And Control ◽  
Independent Parameters

Vehicle parameters are essential for dynamic analysis and control systems. One problem of the current estimation algorithm for vehicles’ parameters is that: real-time estimation methods only identify parts of vehicle parameters, whereas other parameters such as suspension damping coefficients and suspension and tire stiffnesses are assumed to be known in advance by means of an inertial parameter measurement device (IPMD). In this study, a fusion algorithm is proposed for identifying comprehensive vehicle parameters without the help of an IPMD, and vehicle parameters are divided into time-independent parameters (TIPs) and time-dependent parameters (TDPs) based on whether they change over time. TIPs are identified by a hybrid-mass state-variable (HMSV). A dual unscented Kalman filter (DUKF) is applied to update both TDPs and online states. The experiment is conducted on a real two-axle vehicle and the test data are used to estimate both TIPs and TDPs to validate the accuracy of the proposed algorithm. Numerical simulations are performed to further investigate the algorithm’s performance in terms of sprung mass variation, model error because of linearization and various road conditions. The results from both the experiment and simulation show that the proposed algorithm can estimate TIPs as well as update TDPs and online states with high accuracy and quick convergence, and no requirement of road information.

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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