Automated Author ProfileBell, Ian H.
Bell, Ian H.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.0 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
We focus on deterministic global optimization (DGO) for nonconvex parameter estimation problems. Realistic and accurate solutions often require a fitting against very large measurement data sets, resulting in intractable size for DGO. Thus, we aim at accelerating the branch-and-bound algorithm by using reduced data sets for constructing valid bounds. We focus on fitting the equation of state for propane, which is of high interest for the chemical industry. The resulting estimation problem is a challenging nonconvex mixed-integer nonlinear optimization problem. We investigate the validity of using reduced data sets by comparing how the lower and upper bounds change when replacing the full data set with different reduced data sets. We account for regions with high and low quality fits by considering the results for the whole feasible region and 100 different subregions. Our results indicate that both regions containing solution candidates and regions containing only low quality fits can be identified based on reduced data sets. Moreover, we observe that the average CPU time per branch-and-bound iteration typically decreases if reduced data sets are used.
Authors
- Saß, Susanne ;
- Tsoukalas, Angelos ;
- Bell, Ian H. ;
- Bongartz, Dominik ;
- Najman, Jaromil ;
- Mitsos, Alexander
This work presents an equation of state that contains the residual Helmholtz free energy as a ratio of polynomials in density with temperature-dependent coefficients and demonstrates that it is a viable alternative for describing thermodynamic properties accurately. The specific form of the equation in this work has six density terms in the numerator, three density terms in the denominator, and five temperature parameters for each temperature-dependent coefficient. Nitrogen, argon, and methane serve as prototype fluids to demonstrate the capability of the form to describe p–ρ–T behaviour, vapour pressures, speeds of sound, and isochoric heat capacities up to 1000 MPa. Characteristic curves for several properties of nitrogen generated using the equation exhibit proper behaviour at high temperatures and pressures. Because the equation contains no exponential terms or non-integer exponents, the computational time associated with the new equation is more than a factor of 10 less than that required for similar equations with comparable accuracy.
Authors
- Gomez-Osorio, Martin A. ;
- Browne, Robert A. ;
- Cristancho, Diego E. ;
- Holste, James C. ;
- Hall, Kenneth R. ;
- Bell, Ian H.
This work presents an equation of state that contains the residual Helmholtz free energy as a ratio of polynomials in density with temperature-dependent coefficients and demonstrates that it is a viable alternative for describing thermodynamic properties accurately. The specific form of the equation in this work has six density terms in the numerator, three density terms in the denominator, and five temperature parameters for each temperature-dependent coefficient. Nitrogen, argon, and methane serve as prototype fluids to demonstrate the capability of the form to describe p–ρ–T behaviour, vapour pressures, speeds of sound, and isochoric heat capacities up to 1000 MPa. Characteristic curves for several properties of nitrogen generated using the equation exhibit proper behaviour at high temperatures and pressures. Because the equation contains no exponential terms or non-integer exponents, the computational time associated with the new equation is more than a factor of 10 less than that required for similar equations with comparable accuracy.
Authors
- Gomez-Osorio, Martin A. ;
- Browne, Robert A. ;
- Cristancho, Diego E. ;
- Holste, James C. ;
- Hall, Kenneth R. ;
- Bell, Ian H.