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Poon, Sarah

Publications and source records attributed to Poon, Sarah.

Model Diagnostics for Equation Oriented Models: Roadblocks and the Path Forward

This poster was presented at the Foundations of Computer Aided Process Design (FOCAPD) 2024 conference with a paper describing efforts to develop a unified workflow and toolbox for diagnosing issues in equation-oriented models as part of the IDAES modeling framework. The poster presents the work currently underway within the IDAES project to develop and integrate cutting edge model analysis techniques into a common toolbox and workflow for model developers to use.

Lee, Andrew↗

Model Diagnostics for Equation Oriented Models: Roadblocks and the Path Forward

Conference paper for FOCAPD24 describing efforts to develop a unified workflow and toolbox for diagnosing issues in equation-oriented models as part of the IDAES modeling framework. The paper presents the work currently underway within the IDAES project to develop and integrate cutting edge model analysis techniques into a common toolbox and workflow for model developers to use.

Lee, Andrew↗

PARETO UI 24.01.24 (0.9.0) Release

This is a standalone release of PARETO UI using the previously released PARETO version 0.9.0 for the backend.. New features in this version of PARETO UI are: - Added functionality to upload GIS map network visualizations and auto generate input templates - Added map visualizations based on GIS data

PARETO,PARETO-UI,PSE,Process Systems Engineering,P↗

PARETO 0.9.0 Release

PARETO 0.9.0 Release. Highlights: New Features - Initial beneficial reuse implementation - Post-optimization timing for infrastructure buildout Bug Fixes - Address Pyomo solver bug for UI Gurobi solve - Update Toy Case Study to feasible data for hydraulics post_process - Update Jupyter notebook for fall release UI Updates - Added functionality to optimize with hydraulics options - Added new plots to KPI dashboard for water quality and hydraulics timelines

PARETO,PARETO-UI,PSE,Process Systems Engineering,P↗

PARETO 0.8.0 Release

PARETO 0.8.0 Release. Highlights: Model Updates - Applied unified sets for pipeline and trucking arcs in strategic model - Apply unified sets for pipeline and trucking arcs in operational model - Added new config argument for removal efficiency calculation method - Standardized bidirectional capacity constraint - Added dependencies removed in IDAES 2.1 - Created bounding functions & utilities - Added Hydraulics module to the strategic model - Add additional arc types to strategic model Documentation and Tutorial Updates - Improved PARETO treatment document - Introduced general tutorial and treatment module Jupyter notebooks for Strategic Model - Update docs with correct support email list address - Consolidate and deduplicate Getting Started and resources for developers - Enable Black formatting for Jupyter notebooks - Add Binder configuration files and README Bug Fixes - Fix strategic model documentation typos - Removed duplicated units from output file header UI Updates - Added view for comparing different scenarios - Added functionality for manually overriding PARETO decisions

PARETO,PARETO-UI,PSE,Process Systems Engineering,P↗

PARETO 0.7.0 Release

PARETO 0.7.0 Release. Highlights: - Update years for copyright - Correct Core-dev installation instructions - Improve delivery constraint indexing - Incorporate component removal efficiency at treatment sites - Allow model Parameters to be mutable - Address CodeCov failures - Ensure compatibility with IDAES v2

PARETO,PARETO-UI,PSE,Process Systems Engineering,P↗

PARETO 0.5.0 Release

PARETO 0.5.0 Release. Highlights: Treatment Center Modeling - New case study with desalination, clean brine, and evaporation treatment technologies - New option to reduce disposal capacity due to Seismic Response Areas (SRA) - New option to consider water sharing outside of system General Updates - New features for Sankey Diagram visualization (multiple regions, filtered time periods) - Introduce badges to README.md - Convert documentation to ASCII LaTeX - Code cleaning and maintenance - Correct strategic model documentation typo - Update and format treatment demo input spreadsheet Bug Fixes - Fix water quality operational model results printing bug - Piping and trucking variables are now built only over defined arcs instead of all possible connections - Revise pipeline expansion cost constraints, ensure that all pipelines built incur cost

PARETO,PARETO-UI,PSE,Process Systems Engineering,P↗

Science Capsule: Towards Sharing and Reproducibility of Scientific Workflows

Workflows are increasingly processing large volumes of data from scientific instruments, experiments and sensors. These workflows often consist of complex data processing and analysis steps that might include a diverse ecosystem of tools and also often involve human-in-the-loop steps. Sharing and reproducing these workflows with collaborators and the larger community is critical but hard to do without the entire context of the workflow including user notes and execution environment. In this paper, we describe Science Capsule, which is a framework to capture, share, and reproduce scientific workflows. Science Capsule captures, manages and represents both computational and human elements of a workflow. It automatically captures and processes events associated with the execution and data life cycle of workflows, and lets users add other types and forms of scientific artifacts. Science Capsule also allows users to create `workflow snapshots' that keep track of the different versions of a workflow and their lineage, allowing scientists to incrementally share and extend workflows between users. Our results show that Science Capsule is capable of processing and organizing events in near real-time for high-throughput experimental and data analysis workflows without incurring any significant performance overheads.

Ghoshal, Devarshi↗

Investigating User Experiences with Data Abstractions on High Performance Computing Systems

Scientific exploration generates expanding volumes of data that commonly require High Performance Computing (HPC) systems to facilitate research. HPC systems are complex ecosystems of hardware and software that frequently are not user friendly. The Usable Data Abstractions (UDA) project set out to build usable software for scientific workflows in HPC environments by undertaking multiple rounds of qualitative user research. Qualitative research investigates how individuals accomplish their work and our interview-based study surfaced a variety of insights about the experiences of working in and with HPC ecosystems. This report examines multiple facets to the experiences of scientists and developers using and supporting HPC systems. We discuss how stakeholders grasp the design and configuration of these systems, the impacts of abstraction layers on their ability to successfully do work, and the varied perceptions of time that shape this work. Examining the adoption of the Cori HPC at NERSC we explore the anticipations and lived experiences of users interacting with this system’s novel storage feature, the Burst Buffer. We present lessons learned from across these insights to illustrate just some of the challenges HPC facilities and their stakeholders need to account for when procuring and supporting these essential scientific resources to ensure their usability and utility to a variety of scientific practices.

97 MATHEMATICS AND COMPUTING↗