Argonne’s SAS4A/SASSYS-1 safety analysis code system is a simulation tool that can perform deterministic transient safety analysis of anticipated operational events, as well as design-basis and beyond-design-basis accidents for advanced nuclear reactors. The original code development was for sodium-cooled fast reactors, and sodium boiling can be modeled. However, basic core thermal-hydraulics and systems analysis features are applicable to other liquid-metal cooled reactor concepts.

Applications

• Safety analysis of fast reactors
• Simulations for operational, design-basis and beyond-design-basis events
• Passive heat removal and natural circulation flow predictions
• Severe accident modeling with sodium boiling, fuel melting and pin failure

Features

The current version (version 5) features:

• Detailed code manual
• Single-pin assembly models for rapid evaluation of transients
• Detailed thermal-hydraulic sub-channel models for subassembly pin bundles
• Support for three-dimensional visualization of sub-channel temperatures
• Support for liquid-metal coolants such as sodium, NaK, lead and LBE, as well as other single-phase coolants
• Full-plant coolant system models to simulate passive heat removal and natural shutdown
• Oxide fuel models for fuel melting, in-pin motion, pin failure, and ex-pin fuel dispersal and freezing
• Metal fuel models for fuel-clad eutectic formation and cladding failure
• High-fidelity decay heat models
• Built-in support for ANS standard decay heat properties
• Built-in support for alternative coolants in decay heat removal loops
• Support for line-based comments in input files
• Support for an unlimited number of time steps
• Support for coupling to third-party computational fluid dynamics tools (such as STAR-CCM+) for representing thermal stratification in large volumes
• Support for coupling to DIF3D-K for reactor spatial kinetics

Technical Details/Requirements

• Executable versions are available for Linux, Mac OS X and Windows
• Source code is compliant with Fortran 90/95 free-formatted source format and can be compiled on a variety of operating systems including Unix, Linux, Mac OS X and Windows. A standards-compliant Fortran compiler is required.

It generates broad-group, cell-average microscopic cross sections from ENDF/B basic nuclear data.

MC2-3 handles the complicated resonance self-shielding in fast spectrum systems by directly accounting for the resonance interactions in detail and performing calculations (2082 ultrafine group + 400,000 hyperfine group) on conventional lattice cells or simplified R-Z core models. The resulting microscopic cross sections are used for fast reactor design and analysis calculations.

Applications

• Nuclear fast reactor simulations and analysis

Features

• Code library includes almost all isotopes of the ENDF/B-VII data.
• Resolved resonance self-shielding using the numerical integration of pointwise cross sections based on the narrow resonance approximation
• Unresolved resonance self-shielding using the generalized integral method with the increased number of energy grids
• Anisotropic inelastic scattering
• 1-Dimensional (1-D) transport calculation using ultrafine or hyperfine groups
• Improved equivalence theory for the 1D heterogeneity effect in resonance self-shielding
• Efficient algorithm for solving the hyperfine group transport equation
• Option to use 2-D transport solutions (TWODANT) for group condensation
• Fortran 90/95 memory structure
• Keyword-based input system and built-in data conversion capability

Technical Details/Requirements

Developed using the Compaq Visual Fortran on the Microsoft Windows operating system (OS), the MC2-3 code can be installed and executed on the Windows, Macintosh, Unix and Linux OS environments. The memory requirements depend upon the problem. The current version requires more than 1G byte of memory. The memory management system in the current version does not use scratch files to save memory. Thus, more than 4G byte of memory may be required for large problems with many isotopes, hyperfine groups, and/or one-dimensional geometry. A Fortran compiler is required to compile the included source code. Minor changes may be required for code compilation.

The software is written in Fortran 90/95 and can be run on a variety of operating systems including Unix, Linux, Mac OS and Windows. The software includes comments in the source code and the method/user/programmer manual with several examples. An engineer with neutronics experience can learn to run the code in anywhere from a day to a week.

JeoViewer can provide links to any object’s data and behaviors, and is optimized for spatial geometry representation. Unlike traditional ​“static” GIS systems, JeoViewer is dynamic and can be dynamically linked to objects, models and other live data streams.

JeoViewer’s object-oriented approach provides a more natural representation of spatial data. It can used as a stand-alone module or embedded in another framework. It is intended for web use and its Java programming makes it more practical, functional, and useful for Java programmers.

Applications

• Geographical information systems

Features

• Dynamic linking to objects
• More natural representation of spatial data
• Can be used alone or embedded in another framework
• Polygon to grid extensions
• Legend capabilities
• Thematic mapping (i.e., color coding)
• Practical for Java users

Technical Details/Requirements

• Runs on any platform supporting Java JDK 1.3 or higher with Windows 2000, XP, Solaris, or Linux operating systems
• Typical applications require 128 RAM and a Pentium III or higher CPU.
• C compiler required

Argonne’s Battery Life Estimator (BLE) software is a state-of-the-art tool kit for fitting battery aging data and for battery life estimation. It was designed to make life-cycle estimates using two years of aging data.

BLE helps answer key questions on how battery performance will change with calendar age, cycles, internal component aging, cell-to-cell manufacturing variations, summer and winter temperature extremes, differing anode and cathode materials, and electrolyte variations and additives.

The software employs a generalized statistical approach to fit data from accelerated aging experiments to a life equation. The BLE software is different from other curve-fitting routines as it employs robust fitting techniques and estimates battery life by using Monte Carlo techniques (which most generalized curve-fitting software does not consider).

Applications

• Fit battery aging data to life equations
• Estimate battery life

Features

• Easy to learn
• Fast run times
• Easy-to-use graphical user interface
• User guide includes examples and frequently asked questions

Technical Details/Requirements

• Requires PC computer with a Pentium 4 processor, 1 GB of memory and VGA graphics
• Operates on a Windows 2000 or later system and requires Microsoft .NET framework versions 1.1 through 3.5

BatPaC is a software modeling tool designed for policymakers and researchers who are interested in estimating the cost of lithium-ion batteries after they have reached a mature state of development and are being manufactured in high volumes. The tool captures the interplay between the design and cost of these batteries for transportation applications.

BatPaC comes with a library of several lithium-ion battery chemistries and default inputs for all the parameters specified in different manufacturing areas of a factory.

Applications

• Estimates the cost of manufacturing lithium-ion batteries
• Examines trade-offs that result from different user requirements such as power, energy, charging time, etc.

Features

• Supports simulation and design with precise battery mass and dimensions, cost performance characteristics, and battery pack values from bench-scale results
• Calculates battery pack-level quantities by adding together all the battery components that are designed to meet user-defined specifications
• Determines the performance of a given battery chemistry/cell/pack design in batteries for four types of electric vehicle applications

Technical Details/Requirements

• Microsoft Excel-based application

Autonomie is capable of:

• Model-in-the-Loop (MIL), Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL) and Rapid-Control-Prototyping (RCP)
• Integrating math-based engineering activities through all stages of development
• Mixing and matching models of different levels of abstraction with higher fidelity models where analysis and high-detail understanding is critical

Autonomie provides the environment and standard framework to make an entire engineering organization more efficient through the reuse and sharing of models and methods, and by leveraging modeling and control experts across different areas.

Autonomie gives your organization the capabilities for total control and integration of your multidisciplinary engineering design processes to ensure a quality design that is executed almost flawlessly from the first hardware build.

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Applications

• Automotive engineering
• Any simple or complex engineering application that requires the integration of many systems or subsystems

Features

• Provides for rapid and easy integration of models with varying levels of detail
• User-friendly graphical interface
• Supports customizable workflow
• Links with commercial off-the-shelf software applications for detailed, physically-based models, including GT-Power©, AMESim©, CarSim©, AVL-DRIVE©
• Provides configuration and database management
• Protects proprietary models and processes

Technical Details/Requirements

Autonomie requires:

• Windows XP, Vista
• MATLAB®
• Simulink®
• Stateflow®
• Microsoft .NET 2.0
• 1GB RAM

Licensing Information

Argonne offers first-line technical support as well as on-site training of Autonomie for companies, research institutions and universities.

If you are interested in licensing the Autonomie software, please the complete the Licensing Request Form. If you have questions, please contact autonomie-​licensing@​anl.​gov.

For technical support, please contact autonomie-​help@​anl.​gov.

Argonne provides support for U.S. Government activities at autonomie-​government-​support@​anl.​gov.

The patent-pending system, called ARG-US Remote Area Modular Monitoring, or RAMM, uses hig-tech sensors paired with redundant, self-healing communications platforms that can work even in the most challenging conditions.

The work is supported by the U.S. Department of Energy, Office of Environmental Management, and Packaging Certification Program.

Reference: 
SF-08-046(multiple); SF-17-016

The platform, which consists of a set of statistical algorithms to generate wind power point and uncertainty forecasts, can be used for systematic testing and comparison of different computational learning algorithms.

For wind power point forecasting, ARGUS-PRIMA uses concepts from information theoretic learning (ITL) for training a neural network. In tests on real-world data from two large-scale wind farms in the Midwestern United States, results showed distinct advantages of using ITL training criteria as compared to the traditional minimum square error criterion.

For wind power uncertainty forecasting, ARGUS-PRIMA enlists two methods for estimating uncertainty based on kernel density forecasting (KDF). Both KDF algorithms are suitable for online learning. The new algorithms have been tested on datasets from the Eastern Wind Integration and Transmission Study, as well as on two wind farms in the Midwestern United States. Testing shows that the KDF algorithms result in a better match to observed wind power distribution than results obtained using traditional quantile regression.

Applications

• Wind power point forecasting
• Wind power uncertainty forecasting

Features

• Inputs: Can use numerical weather prediction variables, weather observations and power output from wind power farms
• Outputs: wind power predictions (deterministic point forecasts or probability density functions)
• Standard forecast evaluation scores can be calculated

Technical Details/Requirements

Four software environments are used: a PostgreSQL relational database, a C++ neural network library, a kernel density forecast library and supporting algorithm codes. The ARGUS-PRIMA platform consists of source code without an explicit user interface. Users will need to possess considerable programming skills to set up and run the code.