Demos msa

README.md

@@ -38,29 +38,30 @@
 
 # ✨ Key Features
 
-The OQ-VMTK is a powerful toolkit developed by scientists at the Global Earthquake Model (GEM) Foundation. Designed for earthquake engineers and catastrophe modellers, it provides a comprehensive OpenSees-based platform for running representative (idealised) models, developing fragility and vulnerability assessments, and offering extensive flexibility in defining seismic demand, structural capacity, damage criteria, and damage-to-loss conversion.
+The OQ-VMTK is a powerful toolkit developed by scientists at the Global Earthquake Model (GEM) Foundation. Designed for earthquake engineers and catastrophe modellers, it provides a comprehensive platform powered by OpenSees for running representative (idealised) models, developing fragility and vulnerability assessments, and offering extensive flexibility in defining seismic demand, structural capacity, damage criteria, and damage-to-loss conversion.
 
-## 🏗️ Single/Multi-Degree-of-Freedom System Modeling
-- Effortlessly create single- and multi-degree-of-freedom models using intuitive low-level parameters.
+## 🏗️ Single- and Multi-Degree-of-Freedom Systems Calibration and Modeling
 - Define structures with key attributes like storey count, first-mode transformation factors, and force-deformation relationships.
+- Effortlessly create and visualize single- (SDOF) and multi-degree-of-freedom (MDOF) stick-and-mass models using intuitive low-level parameters.
+- Calibrate multi-degree-of-freedom stick-and-mass models based on SDOF parameters.
 
 ## 🔍 Comprehensive Analysis Suite
 ### 📊 Linear & Nonlinear Analysis
 - **Modal Analysis:** Extract vibration periods and mode shapes with precision.
 - **Gravity Analysis:** Perform gravity analysis and ensure system stability before running advanced simulations.
-- **Nonlinear Static Analysis:** Perform static and cyclic pushover tests to assess the system's lateral load resisting capacity, dissipated energy and other metrics.
-- **Dynamic Time-History Analysis:** Simulate dynamic response of structures using selected ground-motion records.
+- **Nonlinear Static Analyses:** Perform static and cyclic pushover tests to assess the system's lateral load resisting capacity, dissipated energy and other metrics.
+- **Nonlinear Time-History Analyses:** Simulate dynamic response of structures using ground-motion records and extract peak response quantities such as peak storey drifts, peak displacements and peak floor accelerations.
 
 ### 🌍 Seismic Fragility & Vulnerability Assessment
-- **Fragility Analysis:** Characterize EDP|IM relationships using Cloud Analysis and determine damage exceedance probabilities (accounting for record-to-record variability & modeling uncertainty).
-- **Storey Loss Function Generation:** Generate storey loss functions based on user-specific inventory of structural and nonstructural components and building contents.
-- **Vulnerability Analysis:** Derive vulnerability functions to estimate economic and human-based decision variables, incorporating damage-to-loss ratios and/or storey loss functions.
+- **Fragility Analysis:** Conduct probabilistic seismic demand modeling to establish relationships between engineering demand parameters (EDPs) and intensity measures (IMs) using nonlinear time-history analyses (e.g., cloud analysis, multiple stripe analyses). Estimate damage exceedance probabilities while accounting for record-to-record variability and modeling uncertainty. Multiple approaches are supported, including conventional methods (e.g., lognormal cumulative distribution functions) and advanced techniques (e.g., generalized linear models and ordinal models).
+- **Storey Loss Function Generation:** Develop storey-level loss functions based on a user-defined inventory of structural components, nonstructural components, and building contents.
+- **Vulnerability Analysis:** Derive vulnerability functions to evaluate both economic and human-centered decision variables. These functions integrate damage-to-loss ratios and/or storey loss functions, with explicit treatment of uncertainties associated with loss conditional on ground-shaking intensity.
 
 ### 📈 Powerful Visualization & Plotting Tools
 - Generate insightful plots for:
   - **Model Overview:** Nodes and elements in your OpenSees model.
-  - **Cloud Analysis Results:** Fitted IM|EDP relationships.
-  - **Seismic Demand Profiles:** Peak storey drifts and floor accelerations.
+  - **Cloud Analysis Results:** Visualize probabilistic seismic demand models (i.e., IM-EDP data and fitted relationships).
+  - **Seismic Demand Profiles:** Visualize peak storey drifts and peak floor accelerations distributions along the height of idealised systems.
   - **Fragility Functions:** Visualize probability-based structural performance.
   - **Storey Loss Functions:** Visualize storey loss function simulations and models.
   - **Vulnerability Functions:** Understand risk and loss estimates.

demos/README.md

@@ -17,16 +17,17 @@ This example provides an application of nonlinear dynamic procedures such as non
 The MDOF stick model is compiled and analysed in OpenSees using the `modeller` module and the seismic demands (i.e., drifts and accelerations) are visualised using the `plotter` module. Useful note on post-processing analysis quantities is also demonstrated to provide users with a consistent output readable across all OQ-VMTK modules and functions.
 
 ## FragilityAnalysis: Example of Supported Fragility Analyses Methods
-This example provides an application of nonlinear dynamic procedures such as nonlinear time-history on a multi-degree-of-freedom (MDOF) stick model where global and local response parameters such as storey displacements, interstorey drifts and floor accelerations are quantified.
-The MDOF stick model is compiled and analysed in OpenSees using the `modeller` module and the seismic demands (i.e., drifts and accelerations) are visualised using the `plotter` module. Useful note on post-processing analysis quantities is also demonstrated to provide users with a consistent output readable across all OQ-VMTK modules and functions.
+This example demonstrates the application of the `postprocessor` module to derive fragility functions through both conventional and state-of-the-art methodologies. It applies multiple approaches to estimate probabilities of exceedance for arbitrary demand-based damage states following nonlinear time-history analyses. The methods include lognormal cumulative distribution functions, generalized linear models, and ordinal models. The treatment of fragility function rotation and additional epistemic uncertainty in fragility functions is also addressed.
 
 ## StoreyLossFunctionGeneration: Example of Storey Loss Function Generation
 This example demonstrates an application for reading inventory files that list damageable structural components, nonstructural components, and building contents, along with their associated metrics—such as quantities, fragility function parameters based on demand, and corresponding costs. The core of this application is the use of the `SLFGenerator` module, which creates storey loss functions. These functions link expected decision variables, whether financial loss, societal impact, or downtime, to seismic demand, represented by engineering demand parameters (e.g., peak storey drift or peak floor acceleration).
 
-## CloudAnalysis: End-to-End Vulnerability Analysis of an MDOF System using Cloud Analysis
-This example performs nonlinear time-history analysis on a multi-degree-of-freedom (MDOF) structural system calibrated using SDOF global capacity and using cloud analysis to assess seismic performance. The example additionally demonstrates postprocessing of cloud analysis results, including fragility curve estimation and vulnerability assessment visualization.
+## StoreyLossFunctionApplication: Example of Storey Loss Function Application
+This example demonstrates an application of storey loss functions where vulnerability functions associated with nonstructural components are derived. The loss model is derived after interpolating the storey loss associated with engineering demand parameters (i.e., peak storey drift or peak floor acceleration) quantified following nonlinear time-history analyses.
+
+## CloudAnalysis: Example of End-to-End Vulnerability Analysis of an MDOF System using Cloud Analysis
+This example performs nonlinear time-history analysis on a multi-degree-of-freedom structural system calibrated using SDOF global capacity and using cloud analysis to assess seismic performance. The example additionally demonstrates postprocessing of cloud analysis results, including fragility curve estimation and vulnerability assessment visualization. It incorporates multiple modules including the `calibration`, `modeller`, `postprocessor`, `plotter` and `utilities` modules
 
-## Example 3: Generating and Visualizing Storey Loss Functions
-This example focuses on computing and visualizing storey loss functions, providing insights into seismic damage assessment and economic loss estimation.
+---
 
 Each example includes relevant scripts, input data, and instructions to guide users through the analysis. Feel free to explore and modify them to suit your specific needs!