COMPUTATIONAL SCIENCE AND ENGINEERING
Bring detailed physics into design exploration, uncertainty analysis and adaptive digital twins.
CONCEPTUAL WORKFLOW
Projection-based reduced-order models (pROMs) represent a system in a smaller space while retaining a connection to its governing equations.
Resolve the governing equations with a full-order model (FOM).
Learn a reduced basis and solve the projected equations in fewer coordinates.
Select nonlinear evaluations to reduce remaining full-order work.
Assess approximation error, stability and total computational cost.
Apply qualified models to design studies, optimization and adaptive digital twins.
PALLC CAPABILITY
PALLC brings computational physics, model reduction and systems engineering into a connected workflow—from preparing the reference model to integrating a reduced model where it supports a decision.
OFFLINE / PREPARATION
We define the operating conditions and outputs that matter, then use full-order solutions to construct a compact model representation. Projection reduces the state dimension; hyper-reduction focuses expensive physics evaluations on selected parts of the model.
ONLINE / INTEGRATION
We integrate reduced models with numerical solvers and the tools that consume their outputs. Defined inputs, units and interfaces support repeated evaluations in analysis workflows and connected simulation environments.
ACCURACY / INTENDED USE
We establish the outputs, operating range and acceptance criteria for each application. Numerical checks assess approximation error, stability, conservation and computational cost. Physical validation connects predictions to relevant observations and their measurement uncertainty.
ANALYSIS / INTEGRATION
Compare alternatives and explore tradeoffs with reduced models tailored to the engineering outputs that guide the design.
Examine how changing inputs and modeling assumptions affect predicted behavior, helping teams understand sensitivity and make informed decisions.
Connect reduced physics models with observations and system context. Assess model updates as operating conditions change.