• Analysis and selection of optimal solvent-based technologies for biogas upgrading 

      Carranza Abaid, Andres; Ramos Wanderley, Ricardo; Knuutila, Hanna K; Jakobsen, Jana Poplsteinova (Journal article; Peer reviewed, 2021)
      Biogas upgrading is an important industrial process for producing biomethane, a sustainable energy source with low carbon footprint. There are three main solvent-based alternatives for biogas upgrading: water scrubbing, ...
    • A Computationally Efficient Formulation of the Governing Equations for Unit Operation Design 

      Carranza Abaid, Andres; Jakobsen, Jana Poplsteinova (Peer reviewed; Journal article, 2021)
      A computationally-efficient numerical method that uses a Pseudo-Eulerian formulation (PEF) for the design calculation of unit operations is presented and validated. This method is applicable to any unit operation that can ...
    • A Non-Autonomous Relativistic Frame of Reference for Unit Operation Design 

      Carranza Abaid, Andres; Jakobsen, Jana Poplsteinova (Peer reviewed; Journal article, 2020)
      This contribution presents an efficient systematic algorithm for unit operation design that uses a newly developed non-autonomous relativistic frame of reference (NARF). The NARF is aimed towards the conceptual design of ...
    • A Petlyuk distillation column dynamic analysis: Hysteresis and bifurcations 

      Carranza Abaid, Andres; Gonzalez-Garcia, Raul (Peer reviewed; Journal article, 2020)
      Thermally coupled distillation columns (TCDC) have proven to be a superior and feasible alternative compared to conventional distillation. However, their inherent system complexity presents optimization and operational ...
    • Surrogate modelling of VLE: Integrating machine learning with thermodynamic constraints 

      Carranza Abaid, Andres; Svendsen, Hallvard Fjøsne; Jakobsen, Jana Poplsteinova (Peer reviewed; Journal article, 2020)
      An easy-to-implement methodology to develop accurate, fast and thermodynamically consistent surrogate machine learning (ML) models for multicomponent phase equilibria is proposed. The methodology is successfully applied ...