scholarly journals Optimal Experimental Design for Parameter Estimation of an IL-6 Signaling Model

Processes ◽  
2017 ◽  
Vol 5 (4) ◽  
pp. 49 ◽  
Author(s):  
Andrew Sinkoe ◽  
Juergen Hahn
Keyword(s):  
Parameter Estimation ◽  
Experimental Design ◽  
Optimal Experimental Design ◽  
Signaling Model

scholarly journals Optimal Experimental Design for Parameter Estimation of a Cell Signaling Model

2009 ◽  
Vol 5 (11) ◽  
pp. e1000558 ◽  
Author(s):  
Samuel Bandara ◽  
Johannes P. Schlöder ◽  
Roland Eils ◽  
Hans Georg Bock ◽  
Tobias Meyer
Keyword(s):  
Parameter Estimation ◽  
Experimental Design ◽  
Cell Signaling ◽  
Optimal Experimental Design ◽  
Signaling Model ◽  
A Cell

Optimal experimental design for the parameter estimation of conduction heated foods

2001 ◽  
Vol 48 (2) ◽  
pp. 109-119 ◽  
Author(s):  
H.B. Nahor ◽  
N. Scheerlinck ◽  
R. Verniest ◽  
J. De Baerdemaeker ◽  
B.M. Nicolaı̈
Keyword(s):  
Parameter Estimation ◽  
Experimental Design ◽  
Optimal Experimental Design

Predicting Optimal Borehole Locations for Parameter Estimation in Geothermal Reservoirs Using Optimal Experimental Design

2021 ◽  
Author(s):  
Johanna Fink ◽  
Ralf Seidler
Keyword(s):  
Parameter Estimation ◽  
Experimental Design ◽  
Mathematical Optimization ◽  
Simulation Software ◽  
Geothermal Reservoir ◽  
Temperature Measurements ◽  
Optimal Experimental Design ◽  
Reservoir Engineering ◽  
Hydraulic Permeability ◽  
Geothermal Reservoirs

<p>Drilling boreholes during exploration and development of geothermal reservoirs not only involves high cost, but also bears significant risks of failure. In geothermal reservoir engineering, techniques of optimal experimental design (OED) have the potential to improve the decision making process. Previous publications explained the formulation and implementation of this mathematical optimization problem and demonstrated its feasibility for finding borehole locations in two- and three-dimensional reservoir models that minimize the uncertainty of estimating hydraulic permeability of a model unit from temperature measurements. Subsequently, minimizing the uncertainty of the parameter estimation results in a more reliable parametrization of the reservoir simulation, improving the overall process in geothermal reservoir engineering.</p><p>Various OED techniques are implemented in the Environment for Combining Optimization and Simulation Software (EFCOSS). To address problems arising from geothermal modeling, this software framework links mathematical optimization software with SHEMAT-Suite, a geothermal simulation code for fluid flow and heat transport through porous media. This contribution shows how to determine experimental conditions such that the uncertainty when estimating different parameters of model units from temperature measurements in the borehole is minimized. Numerical simulations of synthetic geothermal reservoir scenarios are presented to demonstrate the OED workflow and its applicability to geothermal reservoir modeling</p>

Optimal experimental design for parameter estimation in unstructured growth models

1994 ◽  
Vol 10 (5) ◽  
pp. 480-488 ◽  
Author(s):  
M. Baltes ◽  
R. Schneider ◽  
C. Sturm ◽  
M. Reuss
Keyword(s):  
Parameter Estimation ◽  
Experimental Design ◽  
Growth Models ◽  
Optimal Experimental Design

scholarly journals Optimal experimental design for parameter estimation in column outflow experiments

2002 ◽  
Vol 38 (10) ◽  
pp. 4-1-4-11 ◽  
Author(s):  
Angelika E. Altmann-Dieses ◽  
Johannes P. Schlöder ◽  
Hans Georg Bock ◽  
Otto Richter
Keyword(s):  
Parameter Estimation ◽  
Experimental Design ◽  
Optimal Experimental Design
Sign in / Sign up

Export Citation Format

Share Document