Establishment of 40,000 A Rogowski coil calibration system and its uncertainty analysis

Previous work has established the Fiducial Calibration System (FCS), a technique, which, for the first time provides a method that allows for the accuracy of a CMM to be transferred to the shop floor. This paper addresses the range of applicability of the FCS, and provides a method to answer two fundamental questions. First, given a set of machines and fiducials, how much improvement in precision of the finished part can be expected? And second, given a desired precision of the finished part, what machines and fiducials are required? The achievable improvement in precision using the FCS depends on a number of factors including, but not limited to: the type of fiducial, the probing system on the machine and CMM, the time required to make a measurement, and the frequency of measurement. In this paper, the sensitivity of the method to such items is evaluated through an uncertainty analysis, and examples are given indicating how this analysis can be used in a variety of cases.

Download Full-text

Measurement Uncertainty Analysis of a Transfer Standard Force Calibration System

Journal of Testing and Evaluation ◽

10.1520/jte12635j ◽

1994 ◽

Vol 22 (1) ◽

pp. 70

Author(s):

DR Petersen ◽

FM Tovey

Keyword(s):

Uncertainty Analysis ◽

Measurement Uncertainty ◽

Calibration System ◽

Transfer Standard ◽

Force Calibration

Download Full-text

Advancing model calibration and uncertainty analysis of SWAT models using cloud computing infrastructure: LCC-SWAT

Journal of Hydroinformatics ◽

10.2166/hydro.2020.066 ◽

2020 ◽

Author(s):

Masood Zamani ◽

Narayan Kumar Shrestha ◽

Taimoor Akhtar ◽

Trevor Boston ◽

Prasad Daggupati

Keyword(s):

Uncertainty Analysis ◽

Model Calibration ◽

Assessment Tool ◽

Optimization Techniques ◽

Calibration System ◽

Single Node ◽

Computationally Intensive ◽

Analysis System ◽

Smart Computing ◽

Water Assessment

Abstract Calibration and uncertainty analysis of a complex, over-parameterized environmental model such as the Soil and Water Assessment Tool (SWAT) requires thousands of simulation runs and multiple calibration iterations. A parallel calibration system is thus desired that can be deployed on cloud-based architectures for reducing calibration runtime. This paper presents a cloud-based calibration and uncertainty analysis system called LCC-SWAT that is designed for SWAT models. Two optimization techniques, sequential uncertainty fitting (SUFI-2) and dynamically dimensioned search (DDS), have been implemented in LCC-SWAT. Moreover, the cloud-based system has been deployed on the Southern Ontario Smart Computing Innovation Platform's (SOSCIP) Cloud Analytics platform for diagnostic assessment of parallel calibration runtime on both single-node and multi-node CPU architectures. Unlike other calibrations/uncertainty analysis systems developed on the cloud, this system is capable of generating a comprehensive set of statistical information automatically, which facilitates broader analyses of the performance of the SWAT models. Experimental results on SWAT models of different complexities showed that LCC-SWAT can reduce runtime significantly. The runtime reduction is more pronounced for more complex and computationally intensive models. However, the reported runtime efficiency is significantly higher for single node systems. Comparative experiments with DDS and SUFI-2 show that parallel DDS outperforms parallel SUFI-2 in terms of both parameter identifiability and reducing uncertainty in model simulations. LCC-SWAT is a flexible calibration system and other optimization algorithms and asynchronous parallelization strategies can be added to it in future.

Download Full-text