Improving Environmental Model Calibration and Prediction

2011 ◽  
Author(s):  
Jeffrey S. Baggett
1993 ◽  
Vol 68 (1-2) ◽  
pp. 1-19 ◽  
Author(s):  
Diederik T. Van der Molen ◽  
János Pintér

Author(s):  
Nikolay O. Nikitin ◽  
Pavel Vychuzhanin ◽  
Alexander Hvatov ◽  
Irina Deeva ◽  
Anna V. Kalyuzhnaya ◽  
...  

2010 ◽  
Vol 57 (1) ◽  
pp. 1-20
Author(s):  
Małgorzata Skorupa ◽  
Tomasz Machniewicz

Application of the Strip Yield Model to Crack Growth Predictions for Structural SteelA strip yield model implementation by the present authors is applied to predict fatigue crack growth observed in structural steel specimens under various constant and variable amplitude loading conditions. Attention is paid to the model calibration using the constraint factors in view of the dependence of both the crack closure mechanism and the material stress-strain response on the load history. Prediction capabilities of the model are considered in the context of the incompatibility between the crack growth resistance for constant and variable amplitude loading.


2003 ◽  
Vol 40 (6) ◽  
pp. 1212-1215 ◽  
Author(s):  
Heloise Beaugendre ◽  
Francois Morency ◽  
Wagdi G. Habashi ◽  
Pascal Benquet

1992 ◽  
Vol 26 (3-4) ◽  
pp. 753-762 ◽  
Author(s):  
A. F. Rozich

The purpose of this paper is to present the background and examples of methodology which enable environmental engineers and scientists to analyze activated sludge processes much more effectively than is otherwise possible with conventional approaches. Good process analyses are key for devising optimal design and operational strategies. The key features to the technique presented herein are the field-proven predictability of the model and the methodology for collecting data needed for calibrating the process model. Case histories prove the predictability of the model that is associated with the process analysis approach. The advantage of the approach advocated herein is the use of respirometric techniques to calibrate the model. These methods enable the process analyst to collect the requisite data for model calibration in twenty-four hours or less. This feature enables one to use this process analysis methodology for both design and operational applications. The paper will present the technical basis for the process model and how respirometric methods are utilized to compute biokinetic constants in a manner which is consistent with kinetic theory. Case histories will be discussed that demonstrate the predictability of the modeling approach and demonstrate the utility of this tool for process analysis.


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