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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

Optimizing Chromatographic Separations

Optimizing Chromatographic Separations

Optimizing chromatographic separations is crucial for obtaining clean separations in a minimum amount of time. Optimization is required for several factors, including kinetic effects related to band broadening, plate height, capacity factor, and separation factor.
Band broadening refers to spreading solute bands as they travel through the column. This broadening can impact resolution. Plate height (H) represents the length required for one theoretical plate. A lower plate height corresponds to...

Modeling and Similitude

Modeling and Similitude

Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...

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相关实验视频

Updated: May 10, 2025

Measurement of the Rheology of Crude Oil in Equilibrium with CO2 at Reservoir Conditions

Measurement of the Rheology of Crude Oil in Equilibrium with CO2 at Reservoir Conditions

Published on: June 6, 2017

使用基于分类的约束建模优化高度受约束的石油回收过程.

Zahir Aghayev^1,2, Dimitrios Voulanas^3,4, Eduardo Gildin³

¹Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, Connecticut 06269, United States.

Industrial & engineering chemistry research

|April 21, 2025

概括

此摘要是机器生成的。

这项研究优化了复杂的洪水处理操作,使用替代模型和分类来处理众多约束,大大降低了计算成本,以获得最大的经济收益.

更多相关视频

Pore-scale Imaging and Characterization of Hydrocarbon Reservoir Rock Wettability at Subsurface Conditions Using X-ray Microtomography

Pore-scale Imaging and Characterization of Hydrocarbon Reservoir Rock Wettability at Subsurface Conditions Using X-ray Microtomography

Published on: October 21, 2018

Enhanced Oil Recovery using a Combination of Biosurfactants

Enhanced Oil Recovery using a Combination of Biosurfactants

Published on: June 3, 2022

相关实验视频

Last Updated: May 10, 2025

Measurement of the Rheology of Crude Oil in Equilibrium with CO2 at Reservoir Conditions

Measurement of the Rheology of Crude Oil in Equilibrium with CO2 at Reservoir Conditions

Published on: June 6, 2017

Pore-scale Imaging and Characterization of Hydrocarbon Reservoir Rock Wettability at Subsurface Conditions Using X-ray Microtomography

Pore-scale Imaging and Characterization of Hydrocarbon Reservoir Rock Wettability at Subsurface Conditions Using X-ray Microtomography

Published on: October 21, 2018

Enhanced Oil Recovery using a Combination of Biosurfactants

Enhanced Oil Recovery using a Combination of Biosurfactants

Published on: June 3, 2022

科学领域:

石油工程是石油工程中的一个.
计算科学计算科学
优化理论优化理论

背景情况:

实际操作,特别是石油工程,经常遇到复杂的,高维度的问题与众多的约束.
优化这些流程,如水泛滥,由于大量的操作限制,在计算上是昂贵和具有挑战性的.

研究的目的:

开发一个高效和可行的优化方法,用于高度限制的水库模拟.
为了减少与优化复杂的洪水流程相关的计算负担.

主要方法:

使用Feedforward神经网络 (FFNN) 作为客观量化 (净当前价值 - NPV) 的替代模型.
实施了基于分类的约束处理技术,将众多约束转化为二进制可行/不可行的问题.
在线训练模型使用水库模拟数据 (Egg和UNISIM模型) 并在线阶段使用基于模型和基于搜索的优化器.

主要成果:

通过20,000个底孔压力 (BHP) 设置和NPV输出,实现了替代模型 (R2>0.98) 的高预测精度.
基于分类的约束处理有效地区分了可行和不可行的储设置.
综合方法显著降低了计算负载,同时确保了优化和可行的解决方案.

结论:

拟议的方法提供了一个计算效率高和有效的解决方案,以优化高度受限制的洪水运行.
将准确的代用模型与基于分类的约束处理集成,与确定性方法相比,可以获得更好的结果,最大限度地提高经济收益.