Model scope and methods - WITNESS: Difference between revisions
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It is a global Integrated Assessment Model (IAM) framework, covering the world globally (regionalization and sectorization are in progress to be fully completed by end'24). The framework covers MacroEconomics, Energy, Materials, Natural resources, Environment, Population and Public Policies - mostly endogenous and fully coupled (i.e. taking into account all the feedback loops representing mutual interactions between models). | It is a global Integrated Assessment Model (IAM) framework, covering the world globally (regionalization and sectorization are in progress to be fully completed by end'24). The framework covers MacroEconomics, Energy, Materials, Natural resources, Environment, Population and Public Policies - mostly endogenous and fully coupled (i.e. taking into account all the feedback loops representing mutual interactions between models). | ||
The methodological approach to implementing WITNESS is to apply complex [ | The methodological approach to implementing WITNESS is to apply complex [http://en.wikipedia.org/wiki/System of systems/ system of systems] simulation techniques to IAM modelling ([http:///hal.science/hal-04227335/document more details on system of systems simulation]), with the high level system view presented below: | ||
[[File:WITNESS Overview.png|alt=WITNESS high level system view|none|thumb|500x500px|WITNESS high level system view]] | [[File:WITNESS Overview.png|alt=WITNESS high level system view|none|thumb|500x500px|WITNESS high level system view]] | ||
Most of the models are based on equations rather than data analysis and extrapolation, and the feedback loops generated by models interdependencies are efficiently and largely automatically tackled by the underlying simulation platform specifically developed to support it. | Most of the models are based on equations rather than data analysis and extrapolation, and the feedback loops generated by models interdependencies are efficiently and largely automatically tackled by the underlying simulation platform specifically developed to support it. | ||
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= WITNESS framework = | = WITNESS framework = | ||
At the top level, the system of systems approach define high level systems and their interactions (which you can roughly see in the picture above). From an implementation point of view, they will define [ | At the top level, the system of systems approach define high level systems and their interactions (which you can roughly see in the picture above). From an implementation point of view, they will define [http:///en.wikipedia.org/wiki/Namespace namespaces] within which sub-system models will interact and exchange. An [http:///en.wikipedia.org/wiki/Ontology (information science) ontology] is also defined to formalize all modules and parameter's names. In the main namespace, all interfaces exposed by each of the main systems are automatically coupled using the ontology [http:///en.wikipedia.org/wiki/Semantic Web semantic] and [http:///en.wikipedia.org/wiki/Multidisciplinary design optimization multidisciplinary analysis and optimization (MDAO)] computational methods. | ||
Going down recursively refining each system is similar, you will define sub-namespaces for each sub-system you identify to further refine it if needed, and you will define your current systems interfaces to let them be automatically be coupled through the ontology in your current namespace. | Going down recursively refining each system is similar, you will define sub-namespaces for each sub-system you identify to further refine it if needed, and you will define your current systems interfaces to let them be automatically be coupled through the ontology in your current namespace. | ||
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This methodology allow for easy refinement of models as the models interconnexions are prescriptive (expose interfaces in specific namespaces) but not descriptive (connections handling is automated an holistic within namespace). You can also decide to replace in some area the driver running multidisciplinary analysis (MDA), by a controller running multi-disciplinary optimization (MDO) of you want to orient the result vs an objective or want to respect specific constraints. | This methodology allow for easy refinement of models as the models interconnexions are prescriptive (expose interfaces in specific namespaces) but not descriptive (connections handling is automated an holistic within namespace). You can also decide to replace in some area the driver running multidisciplinary analysis (MDA), by a controller running multi-disciplinary optimization (MDO) of you want to orient the result vs an objective or want to respect specific constraints. | ||
For example in the basic WITNESS framework, an MDO controller is optimizing ventilation of available investment from Macro-economy to various Energy production techniques in Energy system, in order to maximize energy production while minimizing emissions under resources and materials contraints (more details [ | For example in the basic WITNESS framework, an MDO controller is optimizing ventilation of available investment from Macro-economy to various Energy production techniques in Energy system, in order to maximize energy production while minimizing emissions under resources and materials contraints (more details [http:///www.witness4climate.org/optimizing-investments-in-energy-production-technology/ here]). | ||
= SoSTrades simulation platform = | = SoSTrades simulation platform = | ||
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The model themselves are written in Python language and wrapped in an SoSTrades discipline that integrate model code, documentation, interfaces... Models not written in Python or requesting specific setup (libraries, licenses, computing infrastructure...) can be integrated through a REST API (or any available python mechanism). | The model themselves are written in Python language and wrapped in an SoSTrades discipline that integrate model code, documentation, interfaces... Models not written in Python or requesting specific setup (libraries, licenses, computing infrastructure...) can be integrated through a REST API (or any available python mechanism). | ||
Coupling of the models is performed using an extended / improved version of [ | Coupling of the models is performed using an extended / improved version of [http:///gemseo.readthedocs.io/en/stable/index.html GEMSEO] library, that is providing various applied mathematics standard solvers implementation. The platform facilitated usage of full [http:///en.wikipedia.org/wiki/Adjoint state method adjoint] based optimization by consistently managing gradients, that makes optimization cost almost independent of the number of parameters used. Those gradient also enable sensitivity analyses. | ||
The platform itself can be used through a REST API to setup / run / analyse a scenario, and generate a synthesis HTML widget that can be embedded in some external dashboard. | The platform itself can be used through a REST API to setup / run / analyse a scenario, and generate a synthesis HTML widget that can be embedded in some external dashboard. | ||
= Development team = | = Development team = | ||
WITNESS and SoSTrades are part of [ | WITNESS and SoSTrades are part of [http:///os-climate.org/transition-analysis/ Transition analysis] project of the [http:///os-climate.org/ Open Source for Climate], part of the [http:///www.finos.org/os-climate FINOS] initiative from the [http:///www.linuxfoundation.org/ Linux Foundation]. | ||
Their development is strongly supported by [ | Their development is strongly supported by [http:///www.capgemini.com/ Capgemini], which is also providing industrial grade deployment and support option, as well as several extensions to derive from WITNESS generated transition scenario various enterprise strategy models. | ||
More details can be found on [ | More details can be found on [http:///www.witness4climate.org/world-environmental-impact-and-economics-scenarios/ witness4climate.org] website.{{ModelDocumentationTemplate | ||
|IsDocumentationOf=WITNESS | |IsDocumentationOf=WITNESS | ||
|DocumentationCategory=Model scope and methods | |DocumentationCategory=Model scope and methods | ||
}} | }} | ||
Revision as of 15:47, 21 August 2024
Model scope
WITNESS stands for "World environmental ImpacT aNd Economics ScenarioS".
It is a global Integrated Assessment Model (IAM) framework, covering the world globally (regionalization and sectorization are in progress to be fully completed by end'24). The framework covers MacroEconomics, Energy, Materials, Natural resources, Environment, Population and Public Policies - mostly endogenous and fully coupled (i.e. taking into account all the feedback loops representing mutual interactions between models).
The methodological approach to implementing WITNESS is to apply complex system of systems simulation techniques to IAM modelling (more details on system of systems simulation), with the high level system view presented below:
Most of the models are based on equations rather than data analysis and extrapolation, and the feedback loops generated by models interdependencies are efficiently and largely automatically tackled by the underlying simulation platform specifically developed to support it.
This simulation platform called SoSTrades (which stands for "System of Systems Trades"), and can by the way be used independently as a generic and powerful MDAO simulation platform and is an extension of the specialized GEMSEO library.
WITNESS framework
At the top level, the system of systems approach define high level systems and their interactions (which you can roughly see in the picture above). From an implementation point of view, they will define namespaces within which sub-system models will interact and exchange. An ontology is also defined to formalize all modules and parameter's names. In the main namespace, all interfaces exposed by each of the main systems are automatically coupled using the ontology semantic and multidisciplinary analysis and optimization (MDAO) computational methods.
Going down recursively refining each system is similar, you will define sub-namespaces for each sub-system you identify to further refine it if needed, and you will define your current systems interfaces to let them be automatically be coupled through the ontology in your current namespace.
This methodology allow for easy refinement of models as the models interconnexions are prescriptive (expose interfaces in specific namespaces) but not descriptive (connections handling is automated an holistic within namespace). You can also decide to replace in some area the driver running multidisciplinary analysis (MDA), by a controller running multi-disciplinary optimization (MDO) of you want to orient the result vs an objective or want to respect specific constraints.
For example in the basic WITNESS framework, an MDO controller is optimizing ventilation of available investment from Macro-economy to various Energy production techniques in Energy system, in order to maximize energy production while minimizing emissions under resources and materials contraints (more details here).
SoSTrades simulation platform
The SoSTrades simulation platform is a cooperative platform with a multi-user web front-end and cloud backend (Docker/Kubernetes).
The model themselves are written in Python language and wrapped in an SoSTrades discipline that integrate model code, documentation, interfaces... Models not written in Python or requesting specific setup (libraries, licenses, computing infrastructure...) can be integrated through a REST API (or any available python mechanism).
Coupling of the models is performed using an extended / improved version of GEMSEO library, that is providing various applied mathematics standard solvers implementation. The platform facilitated usage of full adjoint based optimization by consistently managing gradients, that makes optimization cost almost independent of the number of parameters used. Those gradient also enable sensitivity analyses.
The platform itself can be used through a REST API to setup / run / analyse a scenario, and generate a synthesis HTML widget that can be embedded in some external dashboard.
Development team
WITNESS and SoSTrades are part of Transition analysis project of the Open Source for Climate, part of the FINOS initiative from the Linux Foundation.
Their development is strongly supported by Capgemini, which is also providing industrial grade deployment and support option, as well as several extensions to derive from WITNESS generated transition scenario various enterprise strategy models.
More details can be found on witness4climate.org website.
Note: The documentation of WITNESS is 'in preparation' and is not yet 'published'!| Corresponding documentation | |
|---|---|
| Previous versions | |
| No previous version available | |
| Model information | |
| Model link | |
| Institution | Open-Source for Climate (OS-C), N/A, https://os-climate.org/transition-analysis/., Linux Foundation (LF), N/A, https://www.linuxfoundation.org/. |
| Solution concept | Systems dynamics based approach |
| Solution method | OptimizationSimulation-based optimization |
| Anticipation | |