MDO Workflow Automates BOP Design Compliance
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Solution Overview
Problem
Conventional manual design workflows for blowout preventer (BOP) pipe rams are inefficient and time-consuming, requiring extensive testing to ensure compliance with standards like API Specification 16A and ASME Boiler and Pressure Vessel Code Section VIII, especially when designing for various drill pipe sizes.
Innovation Solution
A multi-disciplinary optimization (MDO) workflow that integrates computer-aided design (CAD), finite element analysis (FEA), digital manufacturing simulation (DMS), and optimization packages to automate the testing and optimization of pressure-controlling component designs, enabling simultaneous evaluation of multiple designs and materials for improved efficiency and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional manual design workflows are used for BOP pipe rams, then design compliance with standards can be ensured through extensive testing, but the design process becomes inefficient and time-consuming
Solution Approach 1:
The patent applies preliminary action by performing automated FEA simulations and compliance checks during the design phase itself, rather than relying on extensive physical testing later. The MDO workflow evaluates multiple design configurations virtually before manufacturing, ensuring standard compliance is built into the design rather than verified through time-consuming post-manufacturing testing.
Solution Approach 2:
The patent uses digital copying by creating virtual models of pipe rams and their operational conditions through FEA simulations. These digital twins allow comprehensive testing and validation of design compliance without requiring physical prototypes, dramatically reducing the time and resources needed for verification while maintaining reliability standards.
2Reliability
If extensive testing is performed to ensure design compliance, then reliability is improved, but development time and cost increase
Solution Approach 1:
The patent replaces mechanical testing systems with computational FEA simulation systems. Instead of physically testing each design configuration against API and ASME standards, the MDO workflow uses automated finite element analysis to evaluate compliance, reducing development time while maintaining the rigor of standard verification.
Solution Approach 2:
The patent applies parameter changes by systematically varying design parameters (such as wall thickness, material properties, geometric dimensions) within the FEA model to evaluate compliance under different conditions. This automated parameter exploration ensures comprehensive standard verification without requiring separate physical tests for each parameter combination.
3Adaptability or versatility
If multiple design configurations are evaluated manually, then design optimization is possible, but the complexity and time required increase significantly
Solution Approach 1:
The patent merges multiple separate evaluation processes (FEA analysis, compliance checking, optimization algorithms, and manufacturing cost assessment) into a single integrated MDO workflow. This unified system automatically evaluates multiple design configurations simultaneously, managing the complexity through systematic integration rather than separate manual processes.
Solution Approach 2:
The patent implements self-service by enabling the MDO workflow to automatically evaluate, compare, and optimize multiple design configurations without requiring manual intervention for each evaluation. The system autonomously performs FEA simulations, checks compliance with standards, and identifies optimal designs based on predefined criteria, reducing workflow complexity despite the comprehensive nature of the evaluation.
Data Source
AI summary
A multi-disciplinary optimization (MDO) framework and workflow facilitates analysis and optimization of set of designs of a pressure-controlling component. The MDO workflow generally enables design workflow integration and automation, which can improve engineering efficiency, and enables automated optimization within the workflow automation, which facilitates performance and reliability improvement for product development. The MDO workflow enables the integration of computer-aided design (CAD), finite element analysis (FEA), digital manufacturing simulation (DMS), and optimization packages to facilitate testing and optimization of a set of pressure-controlling component designs. As such, the MDO framework and workflow improve the efficiency of the design process by providing a scalable solution for automating aspects of the design process for a set of designs of a pressure-controlling component, which may represent a product family or a set of competing alternative designs.