5. Capabilities

Version 3.0.0 of WE-UQ app was released July 2023. The following lists the functionality available in this current version. (Note: New features and fixes in this release are marked blue in the following list of features.)

5.1. Structural Information Model

Applications used to specify/select the structural model to be used in the analysis.

  1. MDOF: creating idealized multi-degree-of-freedom models

  2. MDOF-LU: auto-generated multi-degree-of-freedom model

  3. OpenSees: user-defined OpenSees models

  4. CustomPy: user-defined OpenSees models

5.2. Wind Loading Event

Applications used to specify/select wind loading for the structure.

  1. Stochastic Wind: simulating stochastic wind speed using spectral method

  2. CFD-Digital Wind Tunnel: CFD simulation of boundary layer wind tunnel

  3. CFD-Wind Load on Isolated Buildings: CFD-based wind load simulation for isolated buildings

  4. DEDM_HRP: database-enabled design framework based on wind-tunnel data for high-rise buildings

  5. LowRiseTPU: extracting aerodynamics loads based on TPU database for low-rise buildings

  6. Wind Tunnel Experiment: uses pressure tap measurements from building in wind tunnel experiment

  7. Existing: User-supplied time-varying floor loads

5.3. Engineering Demand Parameter Generator

Applications to identify the output parameters of interest given the wind loading and the structural model.

  1. Standard Wind: (serviceability) inter-story drift ratio, peak floor acceleration

  2. User Defined: user-specified EDP

5.4. Finite Element Application

Applications used to determine the response output parameters given the ground motion and structural model.

  1. OpenSees: Open System for Earthquake Engineering Simulation

  2. CustomPy: Any user-supplied Python application can be incorporated

5.5. Uncertainty Quantification

Applications to perform the uncertainty quantification for the response parameters given the inputs and the random variables present.

  1. Forward Uncertainty Propagation

    1. Dakota Options

      1. Monte Carlo Sampling (MCS)

      2. Latin Hypercube Sampling (LHS)

      3. Gaussian Process Regression

      4. Polynomial Chaos Expansion

    2. SimCenterUQ Options

      1. Monte Carlo Sampling (MCS) a. Resample from an existing correlated dataset of samples

  2. Global Sensitivity Analysis

    1. Dakota Sensitivity Options

      1. MCS

      2. LHS

    2. SimCenterUQ Options

      1. Probability Model-based Global Sensitivity Analysis (PM-GSA)

        1. Import input/output samples from data files

  3. Surrogate Modeling

    1. SimCenterUQ Engine Surrogate Options:

      1. Surrogate modeling using Probabilistic Learning on Manifolds (PLoM)