Supplementary material for the article "Utilizing Machine Learning for Phenomena-based Synthesis of Intensified Process Flowsheets", submitted to The 36th European Symposium on Computer Aided Process Engineering (ESCAPE 36). The document includes information about the heurstic and samplic logic rules used in generating the initial dataset, and the grid search results for hyperparamter optimization.

Supplemental information for the article "Multi-Scale Design for Clean Energy Systems: Industrial Electrification and Flexible Operation of Ammonia Synthesis", which has been submitted to 36th European Symposium on Computer Aided Process Engineering. The document includes parametric data and model information.

This deterministic model formulation describes one root-to-leaf path in a scenario tree that describes the evolution of uncertainty for power grid capacity expansion planning problems. The main manuscript then extends this deterministic formulation to multi-stage and two-stage stochastic programs.

Digital supplementary material for the ESCAPE 36 submission "Modeling and Simulation of Nitrogen Generation by Pressure Swing Adsorption for Power-to-Ammonia". Contains relevant model parameters from the literature.

This document contains the supplementary material for the paper titled “Assessing the Impact of Solvent Recycling in Cooling Crystallization using Computer-Aided Molecular and Process Design”, submitted to the ESCAPE36 conference for consideration.

This document contains digital supplementary material (detailed model description, parameters for different case studies and additional figures) related to the article "Optimization of Site-wide Heat-Integrated Utility Systems with Heat Pumps using MILP" which is submitted to the peer reviewed conference proceeding of the 36th European Symposium on Computer Aided Process Engineering (ESCAPE 36).

This document contains the supplementary material for the paper titled “A Comparative Analysis of Sequential Active Learning Approaches: Statistical Design of Experiments versus Bayesian Optimisation”, submitted to the ESCAPE36 conference for consideration.

This study presents a mixed-integer bilinear optimization model for the cost-optimal design of a Northern European hydrogen supply chain with integrated CCS, focusing on exports from Norway to Germany and CO2 sequestration in Norway. The model is formulated as a superstructure problem and implemented in Pyomo, considering multiple locations for infrastructure nodes and transport options for hydrogen, wood chips, and CO2.

This is supplementary material for the paper "Generative AI in Process Design Instruction: A Survey of Students and Faculty" in Systems and Control Transactions. The supplementary material contains reference information for the paper. Specifically, it contains the survey questions used in the study, the raw data results of that survey, and a ChatGPT transcript of a session in which ChatGPT was used to synthesize a flowsheet of an ammonia synthesis process and perform an analysis of the conceptual design.

This study presents a mixed-integer bilinear optimization model for the cost-optimal design of a Northern European hydrogen supply chain with integrated CCS, focusing on exports from Norway to Germany and CO2 sequestration in Norway. The model is formulated as a superstructure problem and implemented in Pyomo, considering multiple locations for infrastructure nodes and transport options for hydrogen, wood chips, and CO2.

This study investigates the potential of producing hydrogen based on currently unused biomass potentials in Norway and exporting the hydrogen to the European Union. Export of hydrogen via compressed hydrogen is compared with the export of wood chips via bulk shipping and the production of hydrogen from wood chips in the respective import country. A mixed-integer linear optimization model was developed to minimize total supply chain costs of the two parallel supply chain options. Results show that shipping wood chips and producing hydrogen in the importing country is more cost-effective than producing and shipping compressed hydrogen from Norway, with levelized supply chain costs of 33.4 NOK/kgH2 versus 47.6 NOK/kgH2, respectively . This arises mainly because of significantly higher investment costs for compressed hydrogen ships and lower payload. However, hydrogen production in Norway and export via compressed hydrogen shipping result in lower overall emissions due to Norway's highe... [more]

This supplementary material contains tables and figures with the data necessary to replicate the results described in the manuscript.

The source code contains a run_experiments.sh script, which can be used to replicate the results described in the manuscript.

Aspen Plus Equation-Oriented model for Single and Double Stage Absorption Heat Transformer