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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Simulation Modeling Approach to Optimizing Nuclear Waste Dispositioning

The dispositioning of nuclear waste generated at facilities across the country is an ongoing battle that affects us all. National laboratories and research centers dealing in medical research, clean energy, and other nuclear activities such as the Department of Energy (DOE) facilities face the need to properly manage and dispose of nuclear waste. A dynamic modeling solution would enable the DOE and others to make decisions on waste disposal and technological options. In doing so, this research explores modeling techniques using available data to address these situations. The focus being on developing an initial robust and adaptable discrete event model using the ExtendSim tool. This modeling effort will target the dispositioning of transuranic waste at the Savannah River National Laboratory (SRNL) which can be expanded to represent the current state of disposition process for waste generated at other DOE facilities. The model aims to assess resource allocation and waste processing options to stabilize productivity and cut the backlog of nuclear waste. By assessing the results of different scenarios, this research aims to provide actionable insights for the DOE. This approach has the potential to significantly improve the management of radioactive waste, offering the capability of evaluating options for optimizing the process for nuclear waste disposal. The findings of this study can serve as a valuable resource for decision-makers and other national laboratories, or research entities engaged in nuclear operations by enabling them to make more informed choices.

Andaverde, Alexis↗
NASA NTRS2008

Status of the AIAA Modeling and Simulation Format Standard

The current draft AIAA Standard for flight simulation models represents an on-going effort to improve the productivity of practitioners of the art of digital flight simulation (one of the original digital computer applications). This initial release provides the capability for the efficient representation and exchange of an aerodynamic model in full fidelity; the DAVE-ML format can be easily imported (with development of site-specific import tools) in an unambiguous way with automatic verification. An attractive feature of the standard is the ability to coexist with existing legacy software or tools. The draft Standard is currently limited in scope to static elements of dynamic flight simulations; however, these static elements represent the bulk of typical flight simulation mathematical models. It is already seeing application within U.S. and Australian government agencies in an effort to improve productivity and reduce model rehosting overhead. An existing tool allows import of DAVE-ML models into a popular simulation modeling and analysis tool, and other community-contributed tools and libraries can simplify the use of DAVE-ML compliant models at compile- or run-time of high-fidelity flight simulation.

Jackson, E. Bruce↗
NASA NTRS2000

Implications of Simulation Conceptual Model Development for Simulation Management and Uncertainty Assessment

A simulation conceptual model is a simulation developers way of translating modeling requirements (i. e., what is to be represented by the simulation or its modification) into a detailed design framework (i. e., how it is to be done), from which the software, hardware, networks (in the case of distributed simulation), and systems/equipment that will make up the simulation can be built or modified. A conceptual model is the collection of information which describes a simulation developers concept about the simulation and its pieces. That information consists of assumptions, algorithms, characteristics, relationships, and data. Taken together, these describe how the simulation developer understands what is to be represented by the simulation (entities, actions, tasks, processes, interactions, etc.) and how that representation will satisfy the requirements to which the simulation responds. Thus the conceptual model is the basis for judgment about simulation fidelity and validity for any condition that is not specifically tested. The more perspicuous and precise the conceptual model, the more likely it is that the simulation development will both fully satisfy requirements and allow demonstration that the requirements are satisfied (i. e., validation). Methods used in simulation conceptual model development have significant implications for simulation management and for assessment of simulation uncertainty. This paper suggests how to develop and document a simulation conceptual model so that the simulation fidelity and validity can be most effectively determined. These ideas for conceptual model development apply to all simulation varieties. The paper relates these ideas to uncertainty assessments as they relate to simulation fidelity and validity. The paper also explores implications for simulation management from conceptual model development methods, especially relative to reuse of simulation components.

Pace, Dale K.↗