Conceptual models become alive with Vivid OPM: How can animated visualization render abstract ideas concrete?

2018 ◽  
pp. 324-351
Keyword(s):  
Conceptual Models ◽  
Abstract Ideas

Improving Performance Prediction in Deep-Water Reservoirs: Learning from Outcrop Analogues, Conceptual Models and Flow Simulation

2008 ◽  
Author(s):  
Jonathan Stewart ◽  
Paul Alexander Dunn ◽  
Colin Lyttle ◽  
Kirt Campion ◽  
Adedayo Oyerinde ◽  
...  
Keyword(s):  
Deep Water ◽  
Performance Prediction ◽  
Conceptual Models ◽  
Flow Simulation ◽  
Water Reservoirs

Teaching Family Theories: Building Conceptual Models Using Deductive Theorizing

2015 ◽  
Vol 20 (3) ◽  
Author(s):  
Cheryl Buehler ◽  
Shakiera Causey ◽  
Sara Etz Mendonça ◽  
Alia Henderson ◽  
Pamela Linton Norcross ◽  
...  
Keyword(s):  
Conceptual Models

Les tempêtes de fin d'hiver 2020

2020 ◽  
pp. 089
Author(s):  
Michael Kreitz
Keyword(s):  
Conceptual Models ◽  
Deep Convection

La fin de l'hiver 2019-2020 est marquée par la succession de tempêtes. Les zones de vents forts répondent à des schémas conceptuels très différent : jet de basses couches, jet en air froid, sting jet, forte instabilité et tempête de pente aval. The end of winter 2019-2020 is characterised by successive windstorms. The areas of severe winds correspond to various conceptual models: warm jet, cold jet, sting jet, deep convection and downslope windstorm.

Reliability Concepts in Reservoir Design

1989 ◽  
Vol 20 (4-5) ◽  
pp. 231-248 ◽  
Author(s):  
Erich J. Plate
Keyword(s):  
Water Resources ◽  
Reliability Analysis ◽  
Conceptual Models ◽  
Dam Failure ◽  
Figures Of Merit ◽  
Irrigation Reservoir ◽  
Modes Of Failure ◽  
Reservoir Design ◽  
General Reliability ◽  
Operational Failure

The case of a dam for an irrigation reservoir is used as an example to illustrate the different modes of failure of a water resources system. The types of failure to which a dam can be subjected are described in the first section of the paper, in terms of a framework of general reliability analysis. Two applications are considered: the case of operational failure, illustrated by means of an irrigation reservoir for arid countries, and the case of dam failure due to overtopping. Conceptual models are given which permit the inclusion of reliability and other figures of merit into both operation and safety analysis.

Multiple data parameter identification for nonlinear conceptual models

1997 ◽  
Vol 36 (5) ◽  
pp. 61-68 ◽  
Author(s):  
Hermann Eberl ◽  
Amar Khelil ◽  
Peter Wilderer
Keyword(s):  
Optimization Problem ◽  
Conceptual Models ◽  
Reference Data ◽  
Transport Model ◽  
Calibration Method ◽  
Data Sets ◽  
Multiple Data ◽  
Marquardt Algorithm ◽  
Multicriteria Optimization Problem ◽  
Higher Order Differential Equations

A numerical method for the identification of parameters of nonlinear higher order differential equations is presented, which is based on the Levenberg-Marquardt algorithm. The estimation of the parameters can be performed by using several reference data sets simultaneously. This leads to a multicriteria optimization problem, which will be treated by using the Pareto optimality concept. In this paper, the emphasis is put on the presentation of the calibration method. As an example identification of the parameters of a nonlinear hydrological transport model for urban runoff is included, but the method can be applied to other problems as well.

Sign in / Sign up

Export Citation Format

Share Document