
Contributed to the watertap-org/watertap repository by developing and refining advanced process modeling features for water treatment and desalination workflows. Delivered new unit models, such as a surrogate crystallizer and LSRRO flowsheet quick start, while improving property package consistency and flowsheet stability. Applied Python and Jupyter Notebooks to implement robust API integrations, error handling, and data visualization, emphasizing test-driven development and documentation. Addressed cross-platform CI reliability and optimized onboarding through tutorials and technical writing. The work focused on maintainable code, model correctness, and user experience, supporting both engineering accuracy and usability for process simulation and optimization in water treatment applications.
Summary for 2025-12: In watertap, delivered the LSRRO Flowsheet Quick Start Optimization to speed up model setup and improve usability, and resolved a circular import in the LSRRO module. Updated tests to exercise the new quick start functionality. These changes reduce setup time for LSRRO workflows, improve test reliability, and lay groundwork for further performance enhancements. Key commit included: c8da2e840533ba5866473f40198448d41ca089e3.
Summary for 2025-12: In watertap, delivered the LSRRO Flowsheet Quick Start Optimization to speed up model setup and improve usability, and resolved a circular import in the LSRRO module. Updated tests to exercise the new quick start functionality. These changes reduce setup time for LSRRO workflows, improve test reliability, and lay groundwork for further performance enhancements. Key commit included: c8da2e840533ba5866473f40198448d41ca089e3.
November 2025: Focused on stabilizing seawater property modeling in watertap to ensure consistent molality and osmotic pressure representations. Delivered a Seawater Property Model Consistency Fix, standardizing formatting and data representations across seawater models, reducing calculation errors and increasing reliability for downstream simulations and decision-making. The change, tracked under 9ac16739ffca014fc543eb559ee7e643a7aee44e (Update seawater property models for consistency (#1687)), demonstrates strong data modeling discipline, code hygiene, and cross-repo consistency. This work improves business value by boosting trust in model outputs used for design optimizations and regulatory reporting.
November 2025: Focused on stabilizing seawater property modeling in watertap to ensure consistent molality and osmotic pressure representations. Delivered a Seawater Property Model Consistency Fix, standardizing formatting and data representations across seawater models, reducing calculation errors and increasing reliability for downstream simulations and decision-making. The change, tracked under 9ac16739ffca014fc543eb559ee7e643a7aee44e (Update seawater property models for consistency (#1687)), demonstrates strong data modeling discipline, code hygiene, and cross-repo consistency. This work improves business value by boosting trust in model outputs used for design optimizations and regulatory reporting.
September 2025 highlights focused on stabilizing CI for Windows and delivering user-facing WaterTAP enhancements. The work reduced test flakiness in Windows builds and improved onboarding for WaterTAP flows via a new LSRRO tutorial and notebook improvements.
September 2025 highlights focused on stabilizing CI for Windows and delivering user-facing WaterTAP enhancements. The work reduced test flakiness in Windows builds and improved onboarding for WaterTAP flows via a new LSRRO tutorial and notebook improvements.
July 2025 monthly summary for watertap: Delivered key features and stability improvements with a strong focus on robustness and maintainability.
July 2025 monthly summary for watertap: Delivered key features and stability improvements with a strong focus on robustness and maintainability.
May 2025: Reinforced documentation quality and user onboarding for watertap by delivering a focused tutorial docs fix and preserving codebase stability. The primary accomplishment was correcting a broken link in the tutorial index to ensure reliable access to the parmest_demo tutorial, improving user navigation and reducing potential support tickets.
May 2025: Reinforced documentation quality and user onboarding for watertap by delivering a focused tutorial docs fix and preserving codebase stability. The primary accomplishment was correcting a broken link in the tutorial index to ensure reliable access to the parmest_demo tutorial, improving user navigation and reducing potential support tickets.
In December 2024, delivered and stabilized the OLI API client integration for watertap, focusing on reliability, error handling, and maintainability. Core issues affecting API requests, file operations, and session database cleanup were addressed, with test flakiness managed to stabilize the integration flow. The work reduces downtime, improves data ingestion reliability, and accelerates downstream analytics.
In December 2024, delivered and stabilized the OLI API client integration for watertap, focusing on reliability, error handling, and maintainability. Core issues affecting API requests, file operations, and session database cleanup were addressed, with test flakiness managed to stabilize the integration flow. The work reduces downtime, improves data ingestion reliability, and accelerates downstream analytics.
2024-10 monthly summary for watertap-org/watertap: Delivered a generic surrogate crystallizer model in the MCAS property package, including new property calculations for specific enthalpy and saturation pressure and a new unit model. The update includes accompanying documentation and testing to validate the feature and maintain QA coverage. Overall impact: higher-fidelity crystallization modeling, enabling more accurate process design and faster scenario analysis. Technologies/skills demonstrated: Python modeling, unit model integration, property calculation logic, test-driven development, and documentation.
2024-10 monthly summary for watertap-org/watertap: Delivered a generic surrogate crystallizer model in the MCAS property package, including new property calculations for specific enthalpy and saturation pressure and a new unit model. The update includes accompanying documentation and testing to validate the feature and maintain QA coverage. Overall impact: higher-fidelity crystallization modeling, enabling more accurate process design and faster scenario analysis. Technologies/skills demonstrated: Python modeling, unit model integration, property calculation logic, test-driven development, and documentation.

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