Autonomous Pipeline Flow Prediction for Stable Multiphase Transport
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Solution Overview
Problem
Existing methods for predicting multiphase fluid flow in pipeline transport systems face challenges due to complex non-linear interactions, leading to irregular and unstable flow behaviors, which can cause pressure drops, deposit formations, and flow instabilities such as slug flow, bubbly flow, and annular flow.
Innovation Solution
An autonomous flow management system utilizing a computer-implemented method that simulates multiphase flow in pipelines, allowing for explicit numerical solution schemes that are stable independently of the Courant-Friedrichs-Lewy (CFL) condition, and preserves the positivity of mass.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional CFD simulation methods are used to predict multiphase fluid flow, then measurement precision of fluid behavior is improved, but computational time and processing power requirements increase significantly
Solution Approach 1:
The computational domain is divided into a finite number of control volumes, with each volume independently processed. This segmentation allows the simulation to be broken down into manageable discrete units that can be processed efficiently while maintaining overall prediction accuracy for multiphase flow behavior.
Solution Approach 2:
The patent replaces traditional mechanical CFD solving approaches with an autonomous agent-based system where virtual particles autonomously navigate and interact according to physics rules. This substitution fundamentally changes the computational paradigm from grid-based numerical solving to agent-based simulation, reducing computational burden while preserving accuracy.
2Productivity
If explicit numerical solution schemes are used to solve the transport equations, then computational speed is improved, but numerical stability deteriorates due to CFL condition constraints
Solution Approach 1:
The patent replaces traditional explicit/implicit numerical solution schemes with an autonomous agent-based simulation approach. Virtual particles naturally advance through the computational domain based on local flow conditions without requiring iterative solving or being constrained by CFL stability conditions, achieving both speed and stability simultaneously.
Solution Approach 2:
Each virtual particle autonomously determines its own trajectory and interactions based on local physics conditions without requiring global coordination or iterative convergence checks. This self-service approach eliminates the numerical stability constraints that plague traditional explicit schemes while maintaining computational efficiency.
3Measurement precision
If traditional CFD solvers are used to simulate multiphase flows, then measurement precision of flow characteristics is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex traditional CFD solver architecture with a simpler autonomous agent-based system. Instead of requiring pre-processors, complex numerical solvers, and post-processors, the system uses straightforward virtual particles that autonomously navigate the computational domain, significantly reducing overall system complexity while maintaining prediction accuracy.
Solution Approach 2:
The patent uses virtual particles that copy the essential physical behavior of actual fluid elements without requiring full computational complexity of traditional CFD models. Each virtual particle represents a simplified copy of fluid behavior, allowing accurate macroscopic flow prediction through aggregation of many simple microscopic agents.
4Measurement precision
If conventional simulation approaches are used for multiphase flow regulation, then measurement precision of flow instabilities is improved, but productivity of flow management decreases
Solution Approach 1:
The patent replaces conventional iterative CFD simulation approaches with autonomous agent-based simulation that provides immediate flow predictions without requiring multiple iterative solves. This substitution enables real-time or near-real-time flow instability detection and regulation, dramatically improving flow management productivity while maintaining detection accuracy through the autonomous particles' natural response to flow conditions.
Data Source
AI summary
This invention relates to an autonomous flow management system for regulating a multiphase flow in a pipeline-based transport system which utilises a novel computer-implemented method for predicting the multiphase fluid behaviour in the pipeline-based transport system. The computer-implemented method comprises applying a one-dimensional computational fluid dynamic applying a finite volume method in the solver and which estimates the mass flux out of the finite control volumes by i) applying a polynomial to spatially reconstruct the mass present in each finite control volume, ii) reconstructing the flow velocity as a function of the x-component of the flow velocity vector to determine a domain of dependence for each finite control volume representing the distance the fluid has travelled during a time step, and iii) sum the spatially reconstructed mass being present in the domain of dependence for each finite control volume and assume the summarised mass passes out of the respective finite control volume over the applied time step.