MADS Overview

MADS (Model Analysis & Decision Support) is an open-source code designed as an integrated high performance computational framework executing a wide range of model-based analyses.

MADS is designed to be a user-friendly code utilizing adaptive rules and techniques which allows the model analyses to be performed with minimum user input. However, if needed, user can have full control on MADS performance by providing various keywords and control parameters.

MADS can be executed under different computational modes, which include:

MADS allows for coupled model parameters and regularization terms that are internally computed based on user-defined mathematical expressions (utilizing GNU library libmatheval).

MADS can be externally coupled with any existing model simulator through integrated modules that generate input files required by the model simulator and parse output files generated by the model simulator. This is performed using a set of template and instruction files.

MADS analyses can be performed directly using existing control (*.pst), template (*.tpl) and instruction (*.ins) files developed for the code PEST without any modifications or adjustments (example).

MADS provides internal coupling with a series of analytical simulators of contaminant transport in aquifers built in the code.

MADS can internally coupled with any other simulators using object-oriented programming.

MADS includes a series of test functions built in the code for performance (robustness and efficiency) analysis of existing model-analyses techniques.

MADS automatically detects and utilizes the available parallel resources; for the user, there is no difference between serial (using single processor) and parallel mode of execution. The automatic parallelization is performed using external system calls, MPI or POSIX threading.

MADS performs automatic bookkeeping of all the model results for efficient restart and rerun of previous jobs; for example, if the previous jobs were not completed.

MADS can perform different types of analyses based on model results accumulated and stored during previous MADS runs; for example, model runs obtained during model calibration can be utilized in Monte Carlo analyses.

MADS includes a wide range of techniques for model-based analyses:

MADS is build using a well-designed object-oriented programing style that allows for easy integration of new techniques for model-based analyses; code changes and developments are welcome, and after testing, they will be integrated in future MADS releases.

MADS is a unix-style code with command-line interface. All the analyses are performed by a single executable code; model analyses and their options are selected by command-line keywords (MADS execution examples).

MADS is an open-source object-oriented code written in C/C++ and tested on various platforms (Unix, Linux, Mac OS X, Microsoft Windows using Cygwin).

MADS supports scientifically defensible decision making and risk management based on model predictions.

MADS has been successfully applied to perform various model analyses related to environmental management of contamination sites. Examples include solutions of source identification problems, quantification of uncertainty, model calibration, and optimization of monitoring networks (see the lists of publications, presentations, reports, and projects).

MADS release includes a series of verification and test example problems.

MADS current stable version (v 1.1) has been released in January 2013 (download).

Professional software & codes with somewhat similar but not equivalent capabilities:

MADS website: LA-UR-11-11967

MADS code: LA-CC-10-055, LA-CC-11-035

Other project by our team:

SmartTensors: Web LANL GitHub Julia

MADS.jl LANL GitLab GitHub Julia Python


ChroTran: LANL GitHub Gitlab