scholarly journals Computational-Time Reduction of Fourier-Based Analytical Models

2018 ◽  
Vol 33 (1) ◽  
pp. 281-289 ◽  
Author(s):  
Bert Hannon ◽  
Peter Sergeant ◽  
Luc Dupre
Keyword(s):  
Analytical Models ◽  
Computational Time ◽  
Time Reduction

scholarly journals Optimization of Well Sidetrack under Uncertainty using Response Surface and Decision Support. I. Primary Recovery Mechanism

2019 ◽  
Vol 8 (4) ◽  
pp. 3294-3302
Keyword(s):  
Net Present Value ◽  
Analytical Models ◽  
Computational Time ◽  
Reservoir Properties ◽  
Multi Objective ◽  
Recovery Mechanism ◽  
Cumulative Production ◽  
Early Production ◽  
Proxy Models ◽  
Predicted Values

The Optimal sidetrack time (tR-OPT) has been estimated for uncertainty of the probability of success (POS) of the sidetrack operation, reservoir properties and economics for a reservoir under primary recovery mechanism. The case studies worked on in literature considered in this study are for those for primary recovery in which production profiles were represented by empirical and analytical models. However, not all recovery can be adequately replicated by these analytical models. Hence, the need to apply proxy models not just to predict cumulative production but net-present-value (NPV). In this study the analysis of a decision tree with several branches is carried out to maximize NPV that is evaluated under the influence of production stoppage due to the sidetrack into another non-communicating upper zone with uncertainty of reservoir properties. The optimal sidetrack time adds a severe non-linearity in the response of the resulting proxy model and expected monetary value (EMV), the objective function. Multi -objective functions of proxy models over time-intervals for highly time impacted terminal branches, known as split design was applied to evaluate when to conduct a well sidetrack operation under risk and uncertainty in order to resolve severe non-linearity of the NPV solved by a standard optimization algorithm in a spreadsheet. The Predicted values of optimal sidetrack time by the developed workflow was relatively reasonable and highly satisfactory in comparison with simulation results and that of empirical and analytical models. Though, further performance improvement is possible, the constraint on computational time for multi-objective optimization must be weighed against the desired result. Monte Carlo implementation on EMV based on uncertainty of reservoir properties and varying POS acknowledges the fact that for favourable POS, that is values approaching 1.0, tR-OPT clustered at early production life with a spike and the later for unfavourable values.

A Study on Computational Time Reduction of Road Obstacle Detection by Parallel Image Processor

2014 ◽  
Vol 18 (5) ◽  
pp. 849-855 ◽  
Author(s):  
Yutaro Okamoto ◽  
◽  
Chinthaka Premachandra ◽  
Kiyotaka Kato
Keyword(s):  
Detection Algorithm ◽  
Obstacle Detection ◽  
Transport Systems ◽  
Computational Time ◽  
Intelligent Transport Systems ◽  
Image Processor ◽  
Intelligent Transport ◽  
The Road ◽  
Parallel Image ◽  
Time Reduction

Automatic road obstacle detection is one of the significant problem in Intelligent Transport Systems (ITS). Many studies have been conducted for this interesting problem by using on-vehicle cameras. However, those methods still needs a dozens ofmillisecondsfor image processing. To develop the quick obstacle avoidance devices for vehicles, further computational time reduction is expected. Furthermore, regarding the applications, compact hardware is also expected for implementation. Thus, we study on computational time reduction of the road obstacle detection by using a small-type parallel image processor. Here, computational time is reduced by developing an obstacle detection algorithm which is appropriated to parallel processing concept of that hardware. According to the experimental evaluation of the new proposal, we could limit computational time for eleven milliseconds with a good obstacle detection performance.

423 Finite Element Modeling for Computational Time Reduction in Brain Shift Analysis

2009 ◽  
Vol 2009 (0) ◽  
pp. _423-1_-_423-5_
Author(s):  
Youhei AZUMA ◽  
Kazuhiko ADACHI ◽  
Yu HASEGAWA ◽  
Atsushi FUJITA ◽  
Eiji KOHMURA
Keyword(s):  
Finite Element ◽  
Finite Element Modeling ◽  
Computational Time ◽  
Brain Shift ◽  
Element Modeling ◽  
Shift Analysis ◽  
Time Reduction

scholarly journals A semi-analytical coupled simulation approach for induction heating

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Maialen Areitioaurtena ◽  
Unai Segurajauregi ◽  
Ville Akujärvi ◽  
Martin Fisk ◽  
Iker Urresti ◽  
...  
Keyword(s):  
Finite Element ◽  
Induction Heating ◽  
Skin Depth ◽  
Analytical Models ◽  
Computational Time ◽  
Average Error ◽  
Heating Process ◽  
Thermal Problem ◽  
Double Row ◽  
Modeling Strategy

AbstractThe numerical simulation of the induction heating process can be computationally expensive, especially if ferromagnetic materials are studied. There are several analytical models that describe the electromagnetic phenomena. However, these are very limited by the geometry of the coil and the workpiece. Thus, the usual method for computing more complex systems is to use the finite element method to solve the set of equations in the multiphysical system, but this easily becomes very time consuming. This paper deals with the problem of solving a coupled electromagnetic - thermal problem with higher computational efficiency. For this purpose, a semi-analytical modeling strategy is proposed, that is based on an initial finite element computation, followed by the use of analytical electromagnetic equations to solve the coupled electromagnetic-thermal problem. The usage of the simplified model is restricted to simple geometrical features such as flat or curved surfaces with great curvature to skin depth ratio. Numerical and experimental validation of the model show an average error between 0.9% and 4.1% in the prediction of the temperature evolution, reaching a greater accuracy than other analyzed commercial softwares. A 3D case of a double-row large size ball bearing is also presented, fully validating the proposed approach in terms of computational time and accuracy for complex industrial cases.

Flow in Linear Composite Reservoirs

2015 ◽  
Vol 18 (04) ◽  
pp. 577-589 ◽  
Author(s):  
Etim H. Idorenyin ◽  
Ezeddin E. Shirif
Keyword(s):  
Composite System ◽  
Constant Pressure ◽  
Computational Effort ◽  
Analytical Models ◽  
Computational Time ◽  
Linear Composite ◽  
Linear Assembly ◽  
Time Required ◽  
Flow Boundaries ◽  
Homogeneous Regions

Summary This study presents a fast and accurate closed-form, fully analytical solution for modeling fluid flow in linear composite reservoirs. A linear composite system, as mentioned here, refers to a porous medium that can be represented as a linear assembly of distinct homogeneous regions. It is assumed that adjacent regions are connected along an interface of pressure and flux continuity. The solution presented here differs from known analytical models in literature because it does not contain an infinite series that often takes a toll on computational time, especially when accuracy is of prime importance. Thus, this solution finds great use in inverse problems encountered in both rate and pressure transient analyses primarily because of its accuracy and the relatively short computational time required. Depending on the values of the interface coefficients (key parameters in our solution), infinite boundaries, no-flow boundaries, constant-pressure boundaries, and transition interfaces (that is, partially sealing boundaries) can be represented in our model without much computational effort.

Sign in / Sign up

Export Citation Format

Share Document