Ecolego

Ecolego
Developer(s)	AFRY
Initial release	December 2003
Stable release	Ecolego 7 / Dec 6, 2019
Written in	Java
Operating system	Windows, MacOSX, Linux and Unix
Type	Simulation software
License	Proprietary
Website	www.ecolego.se

Last updated March 02, 2024

Ecolego is a simulation software tool that is used for creating dynamic models and performing deterministic and probabilistic simulations. It is also used for conducting risk assessments of complex dynamic systems evolving over time.

Ecolego can be applied in a variety of areas, but is mainly used for risk assessment in radioecology,^[1] environmental physics and PBPK modeling.^[2] To facilitate the use of Ecolego in the field of radiology, specialized databases and other add-ons have been developed. For example, all radionuclides and their decay products have been integrated in the software.

History

Ecolego was co-founded by Swedish Radiation Safety Authority (SSM)^[3]^[4]^[5] , the authority in Sweden responsible for the regulation of radioactive waste management and disposal, and NRPA^[6] , the Norwegian Radiation Protection Authority.

The software was initially developed as a complementary user interface to create compartmental models in Simulink. Simulink had very powerful and fast solvers for ordinary differential equations, but lacked support for running probabilistic simulations and handling of parameter values. Also, Simulink is very detailed – every equation is modeled by graphically operator blocks– making modeling time consuming and prone to mistakes. By relying on Simulink for simulations, full attention could be given to the development of an advanced user interface.

As more and more features where added to Ecolego, the need for an integrated simulation engine grew. With the release of Ecolego 4 in 2008, a set of state-of-the-art solvers was incorporated and thus removed the dependence of Simulink.

Today, SSM uses Ecolego for the review of SKB's^[7] (the Swedish Nuclear Waste Management Company) license application for the siting and construction of a repository for the final disposal of spent nuclear fuel in Sweden.

Releases

December 2003: the first version, Ecolego 1.0, was released. In this early version, the software was dependent on Matlab/Simulink to perform simulations.

February 2006: Ecolego 2.1 was released. The user interface of Ecolego was completely remade, and now used a tiling window manager to improve model transparency.

2007: Ecolego 3 was released. Ecolego now featured a crude integrated calculation engine, reducing the dependence on Matlab/Simulink. The support for probabilistic analysis was greatly improved. A built-in database for parameter values and radionuclide properties was added. Support for hierarchical containers.

2008: Ecolego 4 was released. Ecolego 4 now incorporated state-of-the-art solvers for ordinary differential equations, making Matlab/Simulink redundant. The user interface was improved with many new windows for navigation, report generation and presentation of simulation results. Copy/paste functionality was added.

Fall of 2009: the current version of Ecolego, Ecolego 5, was released. Ecolego 5 added many features, such as unit checking, sub-version support and a model component library. The sensitivity analysis where extended, and a toolbox for advanced sensitivity analysis was created (see EIKOS).

Modeling environment

The initial idea of Ecolego was to facilitate creation of large and complex models and to be able to solve difficult numerical problems. With the purpose to make complicated models with many interconnections easier to overview, the models in Ecolego are represented with the help of interaction matrices instead of the traditional flow diagrams. Combined with hierarchical containers (sub-systems), the interaction matrix greatly facilitates construction and documentation of large and complex models. Objects can be assigned comments, images, units, and hyper links to other documents or Ecolego objects. Ecolego can also create reports that contain everything from interaction matrices, to parameter values, equations, decay chains, plots and tables. The report can be saved in many different formats, including PDF and HTML.

In order to increase the flexibility for the user, Ecolego has no restrictions on the order of creation – for instance, a parameter can be used in equations before it is defined. A real-time validation engine reports problems to the user, such as not-yet-defined objects, objects lacking values or having invalid equations.

Quality assurance

Modules can be created by defining inputs and outputs for sub-systems. By adding modules to the integrated library, a user can create a palette of validated building blocks that can be combined to form new models. The library can be exported, so that users with Ecolego Player can use it to create models without the need of an Ecolego license. Several other features in Ecolego promote quality assurance:

Unit checking
Version handling of models through subversion
Parameter databases (internal or external)
Integrated database for radionuclide properties

Simulations

The typical Ecolego model is a compartmental model which requires a solver of differential equations. There is a wide array of numerical solvers to choose from. Some are optimized for stiff and numerically difficult models, others for trivial models. With an extensive list of probability density functions, together with Monte Carlo and Latin hypercube sampling and parameter correlation settings, Ecolego holds all the required tools to perform advanced probabilistic analysis.

Ecolego Player

Ecolego Player^[8] is a free software tool that makes it possible to perform calculations with Ecolego models without having access to Ecolego.

The software features the same functionality as Ecolego, with the exception that the integral structure of the model cannot be changed. However, with a module library created in Ecolego, the user can assemble models by combining components from the library.

Ecolego Sensitivity Analysis Toolbox (Eikos)

Although it is possible to perform sensitivity analysis in Ecolego, the Sensitivity Analysis Toolbox^[9]^[10] is an optional module which gives a larger set of tools for this approach.

The Eikos Sensitivity Analysis toolbox supports state of the art sensitivity analysis methods (local as well as global). Sensitivity analysis (SA) is used to assess the influence of model parameters on model predictions.

Correlations between parameters may be induced by rank order correlation (method of Iman and Conover). The supported sampling techniques are: Monte carlo, Latin Hypercube and Quasi-random LPt.
The SA methods included are:

Morris screening method
Extended Fourier Amplitude Sensitivity Test (EFAST)
Sobol (first, custom and total order)
Random balance design
Local sensitivity
Garten’s method

Eikos provides a Graphical User Interface (GUI) which lets you:

Specify uncertain model parameters and model outputs of interest
Generate and inspect input samples
Export input and output samples generated in Eikos
Import input and outputs samples generated externally into Eikos
Simulate and inspect the model output samples
Perform Sensitivity Analysis of model predictions
Graphically review the results using pie charts, scatter plots, tornado graphs, etc.

External links

Ecolego official homepage: https://www.ecolego.se

AFRY homepage: https://www.afry.com

Related Research Articles

MATLAB is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks. MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.

Scilab is a free and open-source, cross-platform numerical computational package and a high-level, numerically oriented programming language. It can be used for signal processing, statistical analysis, image enhancement, fluid dynamics simulations, numerical optimization, and modeling, simulation of explicit and implicit dynamical systems and symbolic manipulations.

Hopsan is a free simulation environment for fluid and mechatronic systems, developed at Linköping University. Although originally developed for simulation of fluid power systems, it has also been adopted for other domains such as electric power, flight dynamics, and vehicle dynamics. It uses bi-directional delay lines to connect different components.

Dynamic simulation is the use of a computer program to model the time-varying behavior of a dynamical system. The systems are typically described by ordinary differential equations or partial differential equations. A simulation run solves the state-equation system to find the behavior of the state variables over a specified period of time. The equation is solved through numerical integration methods to produce the transient behavior of the state variables. Simulation of dynamic systems predicts the values of model-system state variables, as they are determined by the past state values. This relationship is found by creating a model of the system.

OptiY is a design environment software that provides modern optimization strategies and state of the art probabilistic algorithms for uncertainty, reliability, robustness, sensitivity analysis, data-mining and meta-modeling.

FEMtools is a multi-functional, cross-platform and solver-independent family of CAE software programs providing analysis and scripting solutions for many different types of engineering simulation applications. The program is developed, supported and licensed by Dynamic Design Solutions ("DDS") NV, located in Leuven, Belgium.

The Functional Mock-up Interface defines a standardized interface to be used in computer simulations to develop complex cyber-physical systems.

<span class="mw-page-title-main">20-sim</span>

20-sim is a commercial modeling and simulation program for multi-domain dynamic systems, which is developed by Controllab. With 20-sim, models can be entered as equations, block diagrams, bond graphs and physical components. 20-sim is widely used for modeling complex multi-domain systems and for the development of control systems.

Optimization Toolbox is an optimization software package developed by MathWorks. It is an add-on product to MATLAB, and provides a library of solvers that can be used from the MATLAB environment. The toolbox was first released for MATLAB in 1990.

The Robotics Toolbox is MATLAB toolbox software that supports research and teaching into arm-type and mobile robotics. While the Robotics Toolbox is free software, it requires the proprietary MATLAB environment in order to execute. The Toolbox forms the basis of the exercises in several textbooks.

pSeven is a DSE software platform that was developed by pSeven SAS that features design, simulation, and analysis capabilities and assists in design decisions. It provides integration with third-party CAD and CAE software tools; multi-objective and robust optimization algorithms; data analysis, and uncertainty quantification tools.

<span class="mw-page-title-main">OptiSLang</span>

optiSLang is a software platform for CAE-based sensitivity analysis, multi-disciplinary optimization (MDO) and robustness evaluation. It was originally developed by Dynardo GmbH and provides a framework for numerical Robust Design Optimization (RDO) and stochastic analysis by identifying variables which contribute most to a predefined optimization goal. This includes also the evaluation of robustness, i.e. the sensitivity towards scatter of design variables or random fluctuations of parameters. In 2019, Dynardo GmbH was acquired by Ansys.

Sensitivity analysis identifies how uncertainties in input parameters affect important measures of building performance, such as cost, indoor thermal comfort, or CO₂ emissions. Input parameters for buildings fall into roughly three categories:

<span class="mw-page-title-main">FEATool Multiphysics</span>

FEATool Multiphysics is a physics, finite element analysis (FEA), and partial differential equation (PDE) simulation toolbox. FEATool Multiphysics features the ability to model fully coupled heat transfer, fluid dynamics, chemical engineering, structural mechanics, fluid-structure interaction (FSI), electromagnetics, as well as user-defined and custom PDE problems in 1D, 2D (axisymmetry), or 3D, all within a graphical user interface (GUI) or optionally as script files. FEATool has been employed and used in academic research, teaching, and industrial engineering simulation contexts.

MSC ADAMS is a multibody dynamics simulation software system. It is currently owned by MSC Software Corporation. The simulation software solver runs mainly on Fortran and more recently C++ as well. According to the publisher, Adams is the most widely used multibody dynamics simulation software. The software package runs on both Windows and Linux.

SAAM II, short for "Simulation Analysis and Modeling" version 2.0, is a renowned computer program designed for scientific research in the field of bioscience. It is a descriptive and exploratory tool in drug development, tracers, metabolic disorders, and pharmacokinetics/pharmacodynamics research. It is grounded in the principles of multi-compartment model theory, which is a widely-used approach for modeling complex biological systems. SAAM II facilitates the construction and simulation of models, providing researchers with a friendly user interface allowing the quick run and multi-fitting of simple and complex structures and data. SAAM II is used by many Pharma and Pharmacy Schools as a drug development, research, and educational tool.

References

↑ ECOLEGO - A toolbox for radio ecological risk assessment, Proceedings of the International Conference on the Protection from the Effects of Ionizing Radiation’’, IAEA-CN-109/80. Stockholm: International Atomic Energy Agency. 229 - 232.
↑ Archived 2013-10-28 at the Wayback Machine 2-FUN - A project concerning full-chain and uncertainty approaches for assessing health risks in future environmental scenarios. EU 6th framework program.
↑ Archived 2012-11-05 at the Wayback Machine Swedish Radiation Protection Authority
↑ Further AMBER and Ecolego Inter-comparisons SKI Report 2004:05 SSI Report 2004:01
↑ , ‘’AMBER and Ecolego Intercomparisons using Calculations from SR 97 SKI Report 2003:28’’, SSI report 2003:11
↑ Archived 2013-02-23 at archive.today the Norwegian Radiation Protection Authority
↑ Archived 2011-01-12 at the Wayback Machine the Swedish Nuclear Waste Management Company
↑ ^[permanent dead link ]Ecolego Player
↑ Ecolego Sensitivity Analysis Toolbox (EIKOS)
↑ Ekström P-A, Broed R (2006), , Sensitivity Analysis Methods and a Biosphere Test Case Implemented in Eikos, Posiva Working Report 2006-31, 84 pp.

This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.

[IAEA-1] ECOLEGO - A toolbox for radio ecological risk assessment, Proceedings of the International Conference on the Protection from the Effects of Ionizing Radiation’’, IAEA-CN-109/80. Stockholm: International Atomic Energy Agency. 229 - 232.

[2-FUN_Project-2] Archived 2013-10-28 at the Wayback Machine 2-FUN - A project concerning full-chain and uncertainty approaches for assessing health risks in future environmental scenarios. EU 6th framework program.

[SSM-3] Archived 2012-11-05 at the Wayback Machine Swedish Radiation Protection Authority

[SSM1-4] Further AMBER and Ecolego Inter-comparisons SKI Report 2004:05 SSI Report 2004:01

[SSM2-5] , ‘’AMBER and Ecolego Intercomparisons using Calculations from SR 97 SKI Report 2003:28’’, SSI report 2003:11

[NRPA-6] Archived 2013-02-23 at archive.today the Norwegian Radiation Protection Authority

[SKB-7] Archived 2011-01-12 at the Wayback Machine the Swedish Nuclear Waste Management Company

[8] [permanent dead link ]Ecolego Player

[(EIKOS)-9] Ecolego Sensitivity Analysis Toolbox (EIKOS)

[Posiva-10] Ekström P-A, Broed R (2006), , Sensitivity Analysis Methods and a Biosphere Test Case Implemented in Eikos, Posiva Working Report 2006-31, 84 pp.

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]