scholarly journals Fitting regression model and experimental validation for high pressure PEM electrolyzer

2009 ◽  
Vol 1 (07) ◽  
pp. 417-425
Author(s):  
M. Santarelli ◽  
P. Medina ◽  
M. Calì
Keyword(s):  
High Pressure ◽  
Regression Model ◽  
Experimental Validation ◽  
Pem Electrolyzer

scholarly journals Faraday’s Efficiency Modeling of a Proton Exchange Membrane Electrolyzer Based on Experimental Data

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4792 ◽  
Author(s):  
Burin Yodwong ◽  
Damien Guilbert ◽  
Matheepot Phattanasak ◽  
Wattana Kaewmanee ◽  
Melika Hinaje ◽  
...  
Keyword(s):  
High Pressure ◽  
Hydrogen Pressure ◽  
Proton Exchange Membrane ◽  
Proton Exchange ◽  
Gas Pressure ◽  
Operating Conditions ◽  
Mechanical Resistance ◽  
Pem Electrolyzer ◽  
Hydrogen Crossover ◽  
Exchange Membrane

In electrolyzers, Faraday’s efficiency is a relevant parameter to assess the amount of hydrogen generated according to the input energy and energy efficiency. Faraday’s efficiency expresses the faradaic losses due to the gas crossover current. The thickness of the membrane and operating conditions (i.e., temperature, gas pressure) may affect the Faraday’s efficiency. The developed models in the literature are mainly focused on alkaline electrolyzers and based on the current and temperature change. However, the modeling of the effect of gas pressure on Faraday’s efficiency remains a major concern. In proton exchange membrane (PEM) electrolyzers, the thickness of the used membranes is very thin, enabling decreasing ohmic losses and the membrane to operate at high pressure because of its high mechanical resistance. Nowadays, high-pressure hydrogen production is mandatory to make its storage easier and to avoid the use of an external compressor. However, when increasing the hydrogen pressure, the hydrogen crossover currents rise, particularly at low current densities. Therefore, faradaic losses due to the hydrogen crossover increase. In this article, experiments are performed on a commercial PEM electrolyzer to investigate Faraday’s efficiency based on the current and hydrogen pressure change. The obtained results have allowed modeling the effects of Faraday’s efficiency by a simple empirical model valid for the studied PEM electrolyzer stack. The comparison between the experiments and the model shows very good accuracy in replicating Faraday’s efficiency.

700 bar type IV high pressure hydrogen storage vessel burst – Simulation and experimental validation

2015 ◽  
Vol 40 (38) ◽  
pp. 13183-13192 ◽  
Author(s):  
Juan Pedro Berro Ramirez ◽  
Damien Halm ◽  
Jean-Claude Grandidier ◽  
Stéphane Villalonga ◽  
Fabien Nony
Keyword(s):  
High Pressure ◽  
Hydrogen Storage ◽  
Experimental Validation ◽  
Storage Vessel ◽  
Type Iv ◽  
Hydrogen Storage Vessel ◽  
Pressure Hydrogen

Comparison of gas excess adsorption models and high pressure experimental validation

2012 ◽  
Vol 90 (11) ◽  
pp. 2002-2012 ◽  
Author(s):  
Ch. Chilev ◽  
F. Darkrim Lamari ◽  
E. Kirilova ◽  
I. Pentchev
Keyword(s):  
High Pressure ◽  
Experimental Validation ◽  
Excess Adsorption ◽  
Adsorption Models

Validation of Adaptive Gaussian Process Regression Model Used for SIF Prediction

2018 ◽  
Author(s):  
Arvind Keprate ◽  
R. M. Chandima Ratnayake ◽  
Shankar Sankararaman
Keyword(s):  
Regression Model ◽  
Gaussian Process ◽  
Prediction Accuracy ◽  
Experimental Validation ◽  
Gaussian Process Regression ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Data Sets ◽  
Maximum Absolute Error ◽  
Data Points

The main aim of this paper is to perform the validation of the adaptive Gaussian process regression model (AGPRM) developed by the authors for the Stress Intensity Factor (SIF) prediction of a crack propagating in topside piping. For validation purposes, the values of SIF obtained from experiments available in the literature are used. Sixty-six data points (consisting of L, a, c and SIF values obtained by experiments) are used to train the AGPRM, while four independent data sets are used for validation purposes. The experimental validation of the AGPRM also consists of the comparison of the prediction accuracy of AGPRM and Finite Element Method (FEM) relative to the experimentally derived SIF values. Four metrics, namely, Root Mean Square Error (RMSE), Average Absolute Error (AAE), Maximum Absolute Error (MAE), and Coefficient of Determination (R2), are used to compare the accuracy. A case study illustrating the development and experimental validation of the AGPRM is presented. Results indicate that the prediction accuracy of the AGPRM is comparable with and even higher than that of the FEM, provided the training points of the AGPRM are aptly chosen.

How do situational variables, related to shooting, in elite Gaelic football impact shot success?

2021 ◽  
pp. 174795412110554
Author(s):  
Kevin McGuigan ◽  
Kieran Collins ◽  
Kevin McDaid
Keyword(s):  
High Pressure ◽  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Average Distance ◽  
Initial Model ◽  
Type Method ◽  
Situational Variables ◽  
Shot Type ◽  
The Impact

Analysis of 3926 shots from the 2019 Senior inter-county football championship aims to establish the impact of distance, angle, shot type, method and pressure on shot success. Findings demonstrate that shots from free kicks contribute 20.5% of the total attempts in Gaelic football, with a success rate of 75%, in contrast to 50% success of shots from open play. Moreover, the range from which free kick success is >57.6% accuracy extends to 40 m, while from open play this is passed at a range of 28 m. There were almost twice as many right foot shots (64.4%) compared with the left foot (32.4%), with right foot attempts marginally more accurate. Shots under low pressure were most successful, while those under medium pressure were less successful than those under high pressure, albeit taken from an average distance of 7.5 m closer to the target. A logistic regression model to explore the impact of all variables on shot outcome demonstrates the significance of shot distance, angle and pressure on the kicker, as well as whether shots are taken with the hand or foot. This research provides an important step in understanding the scale of the impact of a range of variables on shot success in Gaelic football while simultaneously providing an initial model to predict the shot outcome based on these variables.

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