Data & Software

Engineering concept

Parametric Design Study Explorer

An analysis-interface concept for browsing simulation runs, assumptions, rejected cases, and design tradeoffs.

PythonpandasPlotlyStreamlit

Project brief

This concept would develop an interactive viewer for a parameter study in which many CAD or simulation variants must be compared. A run schema would capture geometry parameters, boundary assumptions, solver status, and output metrics while retaining failed or incomplete cases. The interface would connect a selected case to its assumptions and supporting files, allowing comparisons without losing context. Demonstration data would be explicitly illustrative, with any numerical charts labelled accordingly. Proposed deliverables include a run-table format, case filters, comparison views, and exportable selections for follow-up analysis. The tool would support engineering judgment rather than declare an optimum from arbitrary weights, and it would make validity limits and missing data visible alongside attractive candidate designs.

Design concept developed for this portfolio. The diagrams describe the proposed system; implementation and testing are part of the validation plan.

The engineering challenge

Compare many design alternatives without hiding failed runs or separating metrics from their assumptions.

Engineering approach

  1. Define run metadata and validity fields.
  2. Expose filters for geometry, conditions, and solver state.
  3. Connect every metric to a source case.
  4. Use labelled illustrative runs to exercise comparisons.

Validation plan

  • Verify failed and missing cases remain discoverable.
  • Check selected metrics against the underlying run table.
  • Test comparisons with differing boundary conditions to prevent accidental mixing.

Concept scope

  • Assumption-aware filtering
  • Failed-run visibility
  • Case comparison view
  • Supporting-file references
  • Selection export

Software & engineering tools

Python, pandas, Plotly, Streamlit, JSON