This paper describes the development and evaluation of a prototype decision support tool (DST) called the Probabilistic Modeling and Assessment Tool (PMAT). The DST is designed to help traffic management coordinators adjust the parameter settings of Traffic Management Advisor (TMA) in response to forecast changes in airport acceptance rate (AAR). Using an internal fast-time simulation of arrival operations, PMAT generates estimates of the delays arriving aircraft will experience based on the incoming demand and probabilistic AAR forecast. PMAT may accept forecast AAR from weather or non-weather based plans for managing airport capacity. When the probabilistic AAR forecast is due to weather, PMAT will provide the air traffic management DST portion of the ATM-Weather Integration Plan. The use of a DST for proactively responding to an AAR forecast has several novel elements including a forecast probability matrix, operational impact metrics, and presentation of metrics for multiple alternatives. These elements were evaluated in a set of Human-in-the-Loop (HITL) simulations employing traffic management coordinators at Los Angeles and Atlanta Air Route Traffic Control Centers (ZLA and ZTL, respectively) and Southern California and Charlotte Terminal Radar Approach Controls (SCT and CLT, respectively). Among the participants, 95 percent said that they would use PMAT to help them make decisions every day or whenever there was a potential weather disruption. Benefits that the HITL participants saw from a tool like PMAT included greater confidence to deliver high demand under marginal conditions when the potential airborne holding is reasonable for their facility, and improved coordination with other NAS stakeholders.
The ultimate goal of the Pipeline Inspection and Maintenance Optimization System (PIMOS) project is the development of a tool to assist natural gas transmission pipeline companies in planning the optimum inspection and maintenance strategies for their transmission pipelines. PIMOS is a cost effective, systematic, and consistent decision making tool for maintaning a safe and reliable pipeline network.
The report identifies types of gas transmission pipeline defects, inspection and maintenance options currently used to insure pipeline integrity, and data required for statistical analysis of corrosion defects. The report also presents decision trees developed to represent the various inspection and maintenance options. This information will be used in subsequent phases to develop a software tool for identifying optimum inspection and maintenance strategies for gas transmission pipelines.
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