Uncertainty and Global Sensitivity Analysis of a Membrane Biogas Upgrading Process Using the COCO Simulator
[EN] Process designs based on deterministic simulations without considering parameter uncertainty or variability have a high probability of failing to meet specifications. In this work, uncertainty and global sensitivity analyses were applied to a biogas upgrading membrane process implemented in the...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/233342 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/233342 |
| Access Level: | acceso abierto |
| Palabra clave: | Uncertainty Global sensitivity Biogas upgrading Methane Carbon dioxide COCO simulator Morris Polynomial chaos expansion 07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos 09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación 13.- Tomar medidas urgentes para combatir el cambio climático y sus efectos |
| Sumario: | [EN] Process designs based on deterministic simulations without considering parameter uncertainty or variability have a high probability of failing to meet specifications. In this work, uncertainty and global sensitivity analyses were applied to a biogas upgrading membrane process implemented in the COCO simulator (CAPE-OPEN to CAPE-OPEN), considering both controlled and non-controlled scenarios. A user-defined model code was developed to simulate gas separation membrane stages, and a preliminary study of membrane parameter uncertainty was performed. In addition, a unit generating combinations of uncertainty factors was developed to interact with the simulator¿s parametric tool. Global sensitivity analyses were carried out using the Morris method and Sobol¿ indices obtained by Polynomial Chaos Expansion, allowing for the ranking and quantification of the influence of feed variability and membrane parameter uncertainty on product streams and process utilities. Results showed that when feed variability was ±10%, its effect exceeded the uncertainty of the membrane parameters. Uncertainty analysis using the Monte Carlo propagation method provided lower and upper tolerance limits for the main responses. Relative gaps between tolerance limits and mean product flows were 8¿9% at a feed variability of 5% and 14¿18% at a feed variability of 10%, while relative tolerance gaps resulting from composition were smaller (0.4¿1.2%). |
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