diff --git a/doc/source/index.rst b/doc/source/index.rst index 9352de3c6..3092bb16b 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -24,19 +24,13 @@ Utilized in both academia and industry, it supports cutting-edge natural hazards about/acknowledgments.rst release_notes/index.rst -.. toctree:: - :caption: The Pelicun Framework - :maxdepth: 1 - :numbered: 4 - - pelicun_framework/pelicun_framework.rst - .. toctree:: :caption: User Guide :maxdepth: 1 :numbered: 4 user_guide/install.rst + user_guide/pelicun_framework.rst user_guide/feature_overview.rst user_guide/damage_and_loss_library.rst user_guide/bug_reports_and_feature_requests.rst diff --git a/doc/source/pelicun_framework/figures/MainWorkflowComps.png b/doc/source/user_guide/figures/MainWorkflowComps.png similarity index 100% rename from doc/source/pelicun_framework/figures/MainWorkflowComps.png rename to doc/source/user_guide/figures/MainWorkflowComps.png diff --git a/doc/source/pelicun_framework/figures/ModelTypes.png b/doc/source/user_guide/figures/ModelTypes.png similarity index 100% rename from doc/source/pelicun_framework/figures/ModelTypes.png rename to doc/source/user_guide/figures/ModelTypes.png diff --git a/doc/source/pelicun_framework/figures/PerfAssWorkflows.png b/doc/source/user_guide/figures/PerfAssWorkflows.png similarity index 100% rename from doc/source/pelicun_framework/figures/PerfAssWorkflows.png rename to doc/source/user_guide/figures/PerfAssWorkflows.png diff --git a/doc/source/user_guide/install.rst b/doc/source/user_guide/install.rst index 7474a9d04..8484fe38e 100644 --- a/doc/source/user_guide/install.rst +++ b/doc/source/user_guide/install.rst @@ -8,6 +8,7 @@ Join our growing community of users and developers dedicated to advancing risk e Getting started --------------- +=============== `Pelicun `_ is available on the Python Package Index (PyPI) and should work out-of-the-box in all major platforms. .. tip:: diff --git a/doc/source/pelicun_framework/pelicun_framework.rst b/doc/source/user_guide/pelicun_framework.rst similarity index 79% rename from doc/source/pelicun_framework/pelicun_framework.rst rename to doc/source/user_guide/pelicun_framework.rst index d1412c706..f539e0c93 100644 --- a/doc/source/pelicun_framework/pelicun_framework.rst +++ b/doc/source/user_guide/pelicun_framework.rst @@ -1,21 +1,11 @@ .. _pelicun_framework: -.. admonition:: Coming soon. - - This section is still under construction. - - Section objectives: - - - Introduce the pelicun framework. - - Define terminology. - - Describe the components of pelicun and how they interact with each other. - - Provide a set of reference documents on loss estimation frameworks. - -.. - TODO(AZ): The following content comes from the prior documentation pages and may be useful when writing this section. The content is assumed to be replaced or updated. +===================== +The Pelicun Framework +===================== Abbreviations -............. +------------- :BIM: Building Information Model @@ -45,60 +35,47 @@ Abbreviations :LS: Limit State +.. + TODO(JVM): Go over the glossary and remove unused terms. -Glossary -........ - -The following terms may be found throughout this document: - -.. glossary:: - - Workflow - The automation of a business process, in whole or part, during which documents, information or tasks are passed from one participant to another for action, according to a set of procedural rules.” [Workflow Management Coalition]. - - Application - A software application performs operations on data residing in a computer for a user or another program; it can be self-contained, typically termed a program or part of a group of programs. - - Scientific Workflow - A sequence of steps that propagate input data through a series of applications to produce output files. It is a loosely coupled application performing workflows in which each of the coordinated tasks is performed using an individual application. Each of the individual applications takes some data inputs and produces data outputs, which are then consumed by subsequent tasks according to the workflow definition. They are termed scientific because they are typically used by scientists to process, manage, and visualize ever-increasing amounts of data applied to "scientific" problems. - - Scientific Workflow System - An application or application to aid a user in setting up, scheduling, running and monitoring a user-defined scientific workflow. +.. + TODO(JVM): Ensure acronyms are spelled out on the first instance. - Software Framework - A software framework defines a set of component interfaces. It provides a set of implementations in the code of these interfaces, which allows developers to build applications for the domain for which the framework has been designed. For example, a C++ framework will provide a set of abstract classes that define interfaces and a set of concrete classes that implement the interfaces, which will allow developers to quickly build and release applications using the concrete classes. Frameworks allow developers to extend the functionality of the applications by introducing their components that meet the component interface. +Introduction to Pelicun +----------------------- -Introduction to pelicun -....................... +Pelicun is an open-source Python package released under a **3-Clause BSD** license (see :ref:`license`). +It can be used to conduct natural hazard risk analyses. +That is, to quantify damage and losses from a natural hazard scenario. +Applications can range from a simple and straightforward use of a vulnerability function to model the performance of an entire asset to detailed high-resolution evaluations involving the individual components it is comprised of. +Spatial scales can span form a single asset to portfolio-level evaluations involving thousands of assets. -pelicun is an open-source library released under a **3-Clause BSD** license (see :ref:`license`). -The pelicun library can be used to quantify damages and losses from a natural hazard scenario in the form of decision variables (DVs). -This functionality is typically utilized for performance-based engineering and regional natural hazard risk assessment. -This library can help in several steps of performance assessment: +Pelicun implements state of the art approaches to natural hazards risk estimation, and as such, is rooted in probabilistic methods. +Common steps of an assessment using Pelicun include the following: -* **Describe the joint distribution of asset response.** +* **Describe the joint distribution of demands or asset response.** The response of a structure or other type of asset to natural hazard event is typically described by so-called engineering demand parameters (EDPs). Pelicun provides various options to characterize the distribution of EDPs. It can calibrate a multivariate distribution that describes the joint distribution of EDPs if raw EDP data is available. - Users can control the type of each marginal distribution, apply truncation limits to consider collapses, and censor part of the data to consider detection limits in their analysis. - Alternatively, pelicun can use raw EDP data as-is without resampling from a fitted distribution. + Users can control the type of each marginal distribution, apply truncation limits to the marginal distributions, and censor part of the data to consider detection limits in their analysis. + Alternatively, Pelicun can use empirical EDP data directly, without resampling from a fitted distribution. -* **Define the performance model of an asset.** - The fragility and consequence functions from the first two editions of FEMA P-58 and the HAZUS earthquake and hurricane wind and storm surge models for buildings are provided with pelicun. +* **Define a performance model.** + The fragility and consequence functions from the first two editions of FEMA P-58 and the HAZUS earthquake and hurricane wind and storm surge models for buildings are provided with Pelicun. This facilitates the creation of performance models without having to collect and provide component descriptions and corresponding fragility and consequence functions. An auto-population interface encourages researchers to develop and share rulesets that automate the performance-model definition based on the available building information. Example scripts for such auto-population are also provided with the tool. * **Simulate asset damage.** - Given the EDP samples, and the performance model, pelicun efficiently simulates the damages in each component of the asset and identifies the proportion of realizations that resulted in collapse. + Given the EDP samples, and the performance model, Pelicun efficiently simulates the damages in each component of the asset and identifies the proportion of realizations that resulted in collapse. * **Estimate the consequences of damage.** - Using information about collapse and component damages, the following consequences can be estimated with pelicun: repair cost and time, unsafe placarding (red tag), injuries of various severity and fatalities. + Using information about collapse and component damages, the following consequences can be estimated with Pelicun: repair cost and time, unsafe placarding (red tag), injuries of various severity and fatalities. Overview -........ +-------- -The conceptual design of the pelicun framework is modeled after the FEMA P-58 methodology, which is generalized to provide a flexible system that can accommodate a large variety of damage and loss assessment methods. In the following discussion, we first describe the types of performance assessment workflows this framework aims to support; then, we explain the four interdependent models that comprise the framework. +The conceptual design of the Pelicun framework is modeled after the FEMA P-58 methodology, which is generalized to provide a flexible system that can accommodate a large variety of damage and loss assessment methods. In the following discussion, we first describe the types of performance assessment workflows this framework aims to support; then, we explain the four interdependent models that comprise the framework. Loss assessment in its most basic form requires the characterization of the seismic hazard as input and aims to provide an estimate of the consequences, or losses, as output. Using the terminology of FEMA P-58, the severity of the seismic hazard is quantified with the help of intensity measures (IMs). These are characteristic attributes of the ground motions, such as spectral acceleration, peak ground acceleration, or peak ground velocity. Consequences are measured by decision variables (DVs). The most popular DVs are repair cost, repair time, and the number of injuries and fatalities. :numref:`figPerfAssWorkflows` shows three different paths, or performance assessment workflows, from IM to DV: @@ -118,14 +95,14 @@ III. The third path introduces one more intermediate step: response estimation. The functions introduced above are typically idealized relationships that provide a probabilistic description of a scalar output (e.g., repair cost as a random variable) as a function of a scalar input. The cumulative distribution function and the survival function of Normal and Lognormal distributions are commonly used in fragility and vulnerability functions. Consequence functions are often constant or linear functions of the quantity of damaged components. Response estimation is the only notable exception to this type of approximation, because it is regularly performed using complex nonlinear models of structural behavior and detailed time histories of seismic excitation. -Uncertainty quantification is an important part of loss assessment. The uncertainty in decision variables is almost always characterized using forward propagation techniques, Monte Carlo simulation being the most widely used among them. The distribution of random decision variables rarely belongs to a standard family, hence, a large number of samples are needed to describe details of these distributions besides central tendencies. The simulations that generate such large number of samples at a regional scale can demand substantial computational resources. Since the idealized functions in paths I and II can be evaluated with minimal computational effort, these are applicable to large-scale studies. In path III, however, the computational effort needed for complex response simulation is often several orders of magnitude higher than that for other steps. The current state of the art approach to response estimation mitigates the computational burden by simulating at most a few dozen EDP samples and re-sampling them either by fitting a probability distribution or by bootstrapping. This re-sampling technique generates a sufficiently large number of samples for the second part of path III. Although response history analyses are out of the scope of the pelicun framework, it is designed to be able to accommodate the more efficient, approximate methods, such as capacity spectra and surrogate models. Surrogate models of structural response (e.g., [11]) promise to promptly estimate numerical response simulation results with high accuracy. +Uncertainty quantification is an important part of loss assessment. The uncertainty in decision variables is almost always characterized using forward propagation techniques, Monte Carlo simulation being the most widely used among them. The distribution of random decision variables rarely belongs to a standard family, hence, a large number of samples are needed to describe details of these distributions besides central tendencies. The simulations that generate such large number of samples at a regional scale can demand substantial computational resources. Since the idealized functions in paths I and II can be evaluated with minimal computational effort, these are applicable to large-scale studies. In path III, however, the computational effort needed for complex response simulation is often several orders of magnitude higher than that for other steps. The current state of the art approach to response estimation mitigates the computational burden by simulating at most a few dozen EDP samples and re-sampling them either by fitting a probability distribution or by bootstrapping. This re-sampling technique generates a sufficiently large number of samples for the second part of path III. Although response history analyses are out of the scope of the Pelicun framework, it is designed to be able to accommodate the more efficient, approximate methods, such as capacity spectra and surrogate models. Surrogate models of structural response (e.g., [11]) promise to promptly estimate numerical response simulation results with high accuracy. -Currently, the scope of the framework is limited to the simulation of direct losses and the calculations are performed independently for every building. Despite the independent calculations, the pelicun framework can produce regional loss estimates that preserve the spatial patterns that are characteristic to the hazard, and the built environment. Those patterns stem from (i) the spatial correlation in ground motion intensities; (ii) the spatial clusters of buildings that are similar from a structural or architectural point of view; (iii) the layout of lifeline networks that connect buildings and heavily influence the indirect consequences of the disaster; and (iv) the spatial correlations in socioeconomic characteristics of the region. The first two effects can be considered by careful preparation of inputs, while the other two are important only after the direct losses have been estimated. Handling buildings independently enables embarrassingly parallel job configurations on High Performance Computing (HPC) clusters. Such jobs scale very well and require minimal additional work to set up and run on a supercomputer. +Currently, the scope of the framework is limited to the simulation of direct losses and the calculations are performed independently for every building. Despite the independent calculations, the Pelicun framework can produce regional loss estimates that preserve the spatial patterns that are characteristic to the hazard, and the built environment. Those patterns stem from (i) the spatial correlation in ground motion intensities; (ii) the spatial clusters of buildings that are similar from a structural or architectural point of view; (iii) the layout of lifeline networks that connect buildings and heavily influence the indirect consequences of the disaster; and (iv) the spatial correlations in socioeconomic characteristics of the region. The first two effects can be considered by careful preparation of inputs, while the other two are important only after the direct losses have been estimated. Handling buildings independently enables embarrassingly parallel job configurations on High Performance Computing (HPC) clusters. Such jobs scale very well and require minimal additional work to set up and run on a supercomputer. Performance Assessment Workflow -............................... +------------------------------- -:numref:`figMainWorkflowComps` introduces the main parts and the generic workflow of the pelicun framework and shows how its implementation connects to other modules in the SimCenter Application Framework. Each of the four highlighted models and their logical relationship are described in more detail in :numref:`figModelTypes`. +:numref:`figMainWorkflowComps` introduces the main parts and the generic workflow of the Pelicun framework and shows how its implementation connects to other modules in the SimCenter Application Framework. Each of the four highlighted models and their logical relationship are described in more detail in :numref:`figModelTypes`. .. _figMainWorkflowComps: @@ -133,7 +110,7 @@ Performance Assessment Workflow :align: center :figclass: align-center - The main components and the workflow of the pelicun framework. + The main components and the workflow of the Pelicun framework. .. _figModelTypes: @@ -141,25 +118,25 @@ Performance Assessment Workflow :align: center :figclass: align-center - The four types of models and their logical relationships in the pelicun framework. + The four types of models and their logical relationships in the Pelicun framework. -The calculation starts with two files: the Asset Information Model (AIM) and the EVENT file. Currently, both files are expected to follow a standard JSON file format defined by the SimCenter. Support of other file formats and data structures only require a custom parser method. The open source implementation of the framework can be extended by such a method and the following part of the calculation does not require any further adjustment. AIM is a generalized version of the widely used BIM (Building Information Model) idea and it holds structural, architectural, and performance-related information about an asset. The word asset is used to emphasize that the scope of pelicun is not limited to building structures. The EVENT file describes the characteristic seismic events. It typically holds information about the frequency and intensity of the event, such as its occurrence rate or return period, and corresponding ground motion acceleration time histories or a collection of intensity measures. +The calculation starts with two files: the Asset Information Model (AIM) and the EVENT file. Currently, both files are expected to follow a standard JSON file format defined by the SimCenter. Support of other file formats and data structures only require a custom parser method. The open source implementation of the framework can be extended by such a method and the following part of the calculation does not require any further adjustment. AIM is a generalized version of the widely used Building Information Model (BIM) idea and it holds structural, architectural, and performance-related information about an asset. The word asset is used to emphasize that the scope of Pelicun is not limited to building structures. The EVENT file describes the characteristic seismic events. It typically holds information about the frequency and intensity of the event, such as its occurrence rate or return period, and corresponding ground motion acceleration time histories or a collection of intensity measures. -Two threads run in parallel and lead to the simulation of damage and losses: (a) response estimation, creating the response model, and simulation of EDPs; and (b) assembling the performance, damage, and loss models. In thread (a), the AIM and EVENT files are used to estimate the response of the asset to the seismic event and characterize it using EDPs. Peak interstory drift (PID), residual interstory drift (RID), and peak floor acceleration (PFA) are typically used as EDPs for building structures. Response simulation is out of the scope of pelicun; it is either performed by the response estimation module in the Application Framework (Fig. 1) or it can be performed by any other application if pelicun is used outside of the scope of SimCenter. The pelicun framework can take advantage of response estimation methods that use idealized models for the seismic demand and the structural capacity, such as the capacity curve-based method in HAZUS or the regression-based closed-form approximation in the second edition of FEMA P-58 vol. 5 [12]. If the performance assessment follows path I or II from :numref:`figPerfAssWorkflows`, the estimated response is not needed, and the relevant IM values are used as EDPs. +Two threads run in parallel and lead to the simulation of damage and losses: (a) response estimation, creating the response model, and simulation of EDPs; and (b) assembling the performance, damage, and loss models. In thread (a), the AIM and EVENT files are used to estimate the response of the asset to the seismic event and characterize it using EDPs. Peak interstory drift (PID), residual interstory drift (RID), and peak floor acceleration (PFA) are typically used as EDPs for building structures. Response simulation is out of the scope of Pelicun; it is either performed by the response estimation module in the Application Framework (Fig. 1) or it can be performed by any other application if Pelicun is used outside of the scope of SimCenter. The Pelicun framework can take advantage of response estimation methods that use idealized models for the seismic demand and the structural capacity, such as the capacity curve-based method in HAZUS or the regression-based closed-form approximation in the second edition of FEMA P-58 vol. 5 [12]. If the performance assessment follows path I or II from :numref:`figPerfAssWorkflows`, the estimated response is not needed, and the relevant IM values are used as EDPs. Response Model -.............. +-------------- The response model is based on the samples in the raw EDP file and provides a probabilistic description of the structural response. The samples can include an arbitrary number of EDP types (EDPt in Fig. 4) that describe the structural response at pre-defined locations and directions (EDPt,l,d). In buildings, locations typically correspond to floors or stories, and two directions are assigned to the primary and secondary horizontal axes. However, one might use more than two directions to collect several responses at each floor of an irregular building and locations can refer to other parts of structures, such as the piers of a bridge or segments of a pipeline. EDPs can be resampled either after fitting a probability distribution function to the raw data or by bootstrapping the raw EDPs. Besides the widely used multivariate lognormal distribution, its truncated version is also available. This allows the consideration, for example, that PID values above a pre-defined truncation limit are not reliable. Another option, using the raw EDPs as-is, is useful in regional simulations to preserve the order of samples and maintain the spatial dependencies introduced in random characteristics of the building inventory or the seismic hazard. Performance Model -................. +----------------- Thread (b) in Fig. 3 starts with parsing the AIM file and constructing a performance model. If the definition in the file is incomplete, the auto-populate method tries to fill the gaps using information about normative component quantities and pre-defined rulesets. Rulesets can link structural information, such as the year of construction, to performance model details, such as the type of structural details and corresponding components. -The performance model in pelicun is based on that of the FEMA P-58 method. It disaggregates the asset into a hierarchical description of its structural and non-structural components and contents (Fig. 4): +The performance model in Pelicun is based on that of the FEMA P-58 method. It disaggregates the asset into a hierarchical description of its structural and non-structural components and contents (Fig. 4): - Fragility Groups (FGs) are at the highest level of this hierarchy. Each FG is a collection of components that have similar fragility controlled by a specific type of EDP and their damage leads to similar consequences. @@ -169,35 +146,24 @@ The performance model in pelicun is based on that of the FEMA P-58 method. It di In performance models built according to the FEMA P-58 method, buildings typically have FGs sensitive to either PID or PFA. Within each FG, components are grouped into PGs by stories and the drift-sensitive ones are also grouped by direction. The damage of acceleration-sensitive components is based on the maximum of PFAs in the two horizontal directions. The Applied Technology Council (ATC) provides a recommendation for the correlation between component damages within a PG. If the damages are correlated, all components in a PG are collected in a single CG. Otherwise, the performance model can identify an arbitrary number of CGs and their damages are evaluated independently. -The pelicun framework handles the probabilistic sampling for the entire performance model with a single high-dimensional random variable. This allows for custom dependencies in the model at any level of the hierarchy. For example, one can assign a 0.8 correlation coefficient between the fragility of all components in an FG that are on the same floor, but in different directions and hence, in different PGs. In another example, one can assign a 0.7 correlation coefficient between component quantities in the same direction along all or a subset of floors. These correlations can capture more realistic exposure and damage and consider the influence of extreme cases. Such cases are overlooked when independent variables are used because the deviations from the mean are cancelling each other. +The Pelicun framework handles the probabilistic sampling for the entire performance model with a single high-dimensional random variable. This allows for custom dependencies in the model at any level of the hierarchy. For example, one can assign a 0.8 correlation coefficient between the fragility of all components in an FG that are on the same floor, but in different directions and hence, in different PGs. In another example, one can assign a 0.7 correlation coefficient between component quantities in the same direction along all or a subset of floors. These correlations can capture more realistic exposure and damage and consider the influence of extreme cases. Such cases are overlooked when independent variables are used because the deviations from the mean are cancelling each other. This performance model in Fig. 4 can also be applied to more holistic description of buildings. For example, to describe earthquake damage to buildings following HAZUS, three FGs can handle structural, acceleration-sensitive non-structural, and drift-sensitive non-structural components. Each FG has a single PG because HAZUS uses building-level EDPs—only one location and direction is used in this case. Since components describe the damage to the entire building, using one CG per PG with “1 ea” as the assigned, deterministic component quantity is appropriate. -The performance model in pelicun can facilitate filling the gap between the holistic and atomic approaches of performance assessment by using components at an intermediate resolution, such as story-based descriptions, for example. These models are promising because they require less detailed inputs than FEMA P-58, but they can provide more information than the building-level approaches in HAZUS. +The performance model in Pelicun can facilitate filling the gap between the holistic and atomic approaches of performance assessment by using components at an intermediate resolution, such as story-based descriptions, for example. These models are promising because they require less detailed inputs than FEMA P-58, but they can provide more information than the building-level approaches in HAZUS. Damage Model -............ +------------ -Each Fragility Group in the performance model shall have a corresponding fragility model in the Damage & Loss Database. In the fragility model, Damage State Groups (DSGs) collect Damage States (DSs) that are triggered by similar magnitudes of the controlling EDP. In pelicun, Lognormal damage state exceedance curves are converted into random EDP limits that trigger DSGs. When multiple DSGs are used, assuming perfect correlation between their EDP limits reproduces the conventional model that uses exceedance curves. The approach used in this framework, however, allows researchers to experiment with partially correlated or independent EDP limits. Experimental results suggest that these might be more realistic representations of component fragility. A DSG often has only a single DS. When multiple DSs are present, they can be triggered either simultaneously or they can be mutually exclusive following the corresponding definitions in FEMA P-58. +Each Fragility Group in the performance model shall have a corresponding fragility model in the Damage & Loss Database. In the fragility model, Damage State Groups (DSGs) collect Damage States (DSs) that are triggered by similar magnitudes of the controlling EDP. In Pelicun, Lognormal damage state exceedance curves are converted into random EDP limits that trigger DSGs. When multiple DSGs are used, assuming perfect correlation between their EDP limits reproduces the conventional model that uses exceedance curves. The approach used in this framework, however, allows researchers to experiment with partially correlated or independent EDP limits. Experimental results suggest that these might be more realistic representations of component fragility. A DSG often has only a single DS. When multiple DSs are present, they can be triggered either simultaneously or they can be mutually exclusive following the corresponding definitions in FEMA P-58. Loss Model -.......... +---------- -Each Damage State has a corresponding set of consequence descriptions in the Damage & Loss Database. These are used to define a consequence model that identifies a set of decision variables (DVs) and corresponding consequence functions that link the amount of damaged components to the value of the DV. The constant and quantity-dependent stepwise consequence functions from FEMA P-58 are available in pelicun. +Each Damage State has a corresponding set of consequence descriptions in the Damage & Loss Database. These are used to define a consequence model that identifies a set of decision variables (DVs) and corresponding consequence functions that link the amount of damaged components to the value of the DV. The constant and quantity-dependent stepwise consequence functions from FEMA P-58 are available in Pelicun. Collapses and their consequences are also handled by the damage and the loss models. The collapse model describes collapse events using the concept of collapse modes introduced in FEMA P-58. Collapse is either triggered by EDP values exceeding a collapse limit or it can be randomly triggered based on a collapse probability prescribed in the AIM file. The latter approach allows for external collapse fragility models. Each collapse mode has a corresponding collapse consequence model that describes the corresponding injuries and losses. Similarly to the performance model, the randomness in damage and losses is handled with a few high-dimensional random variables. This allows researchers to experiment with various correlation structures between damages of components, and consequences of those damages. Among the consequences, the repair costs and times and the number of injuries of various severities are also linked; allowing, for example, to consider that repairs that cost more than expected will also take longer time to finish. -Once the damage and loss models are assembled, the previously sampled EDPs are used to evaluate the Damage Measures (Fig. 3). These DMs identify the Damage State of each Component Group in the structure. This information is used by the loss simulation to generate the Decision Variables. The final step of the calculation in pelicun is to aggregate results into a Damage and Loss (DL) file that provides a concise overview of the damage and losses. All intermediate data generated during the calculation (i.e., EDPs, DMs, DVs) are also saved in CSV files. - -Assessment -.......... - -.. admonition:: Coming soon. - - This section is still under construction. - - Section objectives: - - - Discuss assessment objects. +Once the damage and loss models are assembled, the previously sampled EDPs are used to evaluate the Damage Measures (Fig. 3). These DMs identify the Damage State of each Component Group in the structure. This information is used by the loss simulation to generate the Decision Variables. The final step of the calculation in Pelicun is to aggregate results into a Damage and Loss (DL) file that provides a concise overview of the damage and losses. All intermediate data generated during the calculation (i.e., EDPs, DMs, DVs) are also saved in CSV files.