Human Performance Modeling and Simulation for Launch Team Applications

This paper describes ongoing research into modeling and simulation of humans for launch team analysis, training, and evaluation. The initial research is sponsored by the National Aeronautics and Space Administration's (NASA)'s Office of Safety and Mission Assurance (OSMA) and NASA's Exploration Program and is focused on current and future launch team operations at Kennedy Space Center (KSC). The paper begins with a description of existing KSC launch team environments and procedures. It then describes the goals of new Simulation and Analysis of Launch Teams (SALT) research. The majority of this paper describes products from the SALT team's initial proof-of-concept effort. These products include a nominal case task analysis and a discrete event model and simulation of launch team performance during the final phase of a shuttle countdown; and a first proof-of-concept training demonstration of launch team communications in which the computer plays most roles, and the trainee plays a role of the trainee's choice. This paper then describes possible next steps for the research team and provides conclusions. This research is expected to have significant value to NASA's Exploration Program

Spring 1999 Transferring Ownership of ModSAF Behavioral Attributes

ABSTRACT: This paper describes an innovative advanced distributed simulation (ADS) architecture that provides improved behavioral representation of STRICOM’s Modular Semi-Automated Forces (ModSAF) entities without incorporating additional functionality within ModSAF. A significant shortcoming that has been identified by the ModSAF user community is the predictable nature of human/system performance. Currently, ModSAF entity performance does not vary or degrade as a function of battlefield conditions. In addition, as increased functionality has been placed within ModSAF, it has grown into an extremely complex development environment. The Realistic Entity AbiLity Simulation Suite (REALSS) presented here is an architecture that implements variable and degradable human/system performance for ModSAF entities by transferring the “ownership ” of the entity performance attributes to an external server. The methodology uses a Micro Saint task network crew model linked with a set of taxonomic degradation functions to predict performance. Through DIS PDUs or HLA objects, attributes and interactions,, the REALSS provides ModSAF entity performance parameters resulting from nuclear prompt radiation, blast, chemical, and biological environments for the AH64, M1, M2, M3, M109, M577, and T72 vehicles. The SBCCOM/DTRA Nuclear, Chemical, Biological, and Radiological (NCBR) Simulator provides the environmental representation of nuclear events on the synthetic battlefield. A REAL Performance Server uses these environments to determine exposure and system performance for the ModSAF entities. ModSAF entities then behave in a manner on the battlefield tha