The application of simple modeling techniques to corrosion induced deterioration of reinforced concrete

2011 ◽  
pp. 527-534
Author(s):  
J Broomfield
Keyword(s):  
Reinforced Concrete ◽  
Modeling Techniques ◽  
Simple Modeling

Observation of Subsurface Structure of Pt/C Catalyst Using Pair Distribution Function and Simple Modeling Techniques

2020 ◽  
Vol 93 (1) ◽  
pp. 37-42
Author(s):  
Masakuni Takahashi ◽  
Koji Ohara ◽  
Kentaro Yamamoto ◽  
Tomoki Uchiyama ◽  
Hajime Tanida ◽  
...  
Keyword(s):  
Distribution Function ◽  
Pair Distribution Function ◽  
Subsurface Structure ◽  
Modeling Techniques ◽  
Simple Modeling

scholarly journals Modeling error in experimental assays using the bootstrap principle: Understanding discrepancies between assays using different dispensing technologies

2015 ◽  
Author(s):  
Sonya M Hanson ◽  
Sean Ekins ◽  
John D Chodera
Keyword(s):  
Modeling Error ◽  
Dilution Series ◽  
Sources Of Error ◽  
Simple Set ◽  
Modeling Techniques ◽  
Primary Origin ◽  
The Creation ◽  
Simple Modeling

All experimental assay data contains error, but the magnitude, type, and primary origin of this error is often not obvious. Here, we describe a simple set of assay modeling techniques based on the bootstrap principle that allow sources of error and bias to be simulated and propagated into assay results. We demonstrate how deceptively simple operations---such as the creation of a dilution series with a robotic liquid handler---can significantly amplify imprecision and even contribute substantially to bias. To illustrate these techniques, we review an example of how the choice of dispensing technology can impact assay measurements, and show how large contributions to discrepancies between assays can be easily understood and potentially corrected for. These simple modeling techniques---illustrated with an accompanying IPython notebook---can allow modelers to understand the expected error and bias in experimental datasets, and even help experimentalists design assays to more effectively reach accuracy and imprecision goals.

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