DOE Office of Scientific and Technical Information (OSTI.GOV)
Shirley, Rachel; Smidts, Carol; Boring, Ronald
Information-Decision-Action Crew (IDAC) operator model simulations of a Steam Generator Tube Rupture are compared to student operator performance in studies conducted in the Ohio State University’s Nuclear Power Plant Simulator Facility. This study is presented as a prototype for conducting simulator studies to validate key aspects of Human Reliability Analysis (HRA) methods. Seven student operator crews are compared to simulation results for crews designed to demonstrate three different decision-making strategies. The IDAC model used in the simulations is modified slightly to capture novice behavior rather that expert operators. Operator actions and scenario pacing are compared. A preliminary review of availablemore » performance shaping factors (PSFs) is presented. After the scenario in the NPP Simulator Facility, student operators review a video of the scenario and evaluate six PSFs at pre-determined points in the scenario. This provides a dynamic record of the PSFs experienced by the OSU student operators. In this preliminary analysis, Time Constraint Load (TCL) calculated in the IDAC simulations is compared to TCL reported by student operators. We identify potential modifications to the IDAC model to develop an “IDAC Student Operator Model.” This analysis provides insights into how similar experiments could be conducted using expert operators to improve the fidelity of IDAC simulations.« less
Exchange Service Station Gasoline Pumping Operation Simulation.
1980-06-01
an event step simulation model of the Naval operation.s The model has been developed as a management tool and aid to decision making. The environment...has been developed as a management tool and aid to decision making. The environment in which the system operates is discussed and the significant...of the variables such as arrival rates; while others are primarily controlled by managerial decision making, for example the number of pumps available
A Simulation for Managing Complexity in Sales and Operations Planning Decisions
ERIC Educational Resources Information Center
DuHadway, Scott; Dreyfus, David
2017-01-01
Within the classroom it is often difficult to convey the complexities and intricacies that go into making sales and operations planning decisions. This article describes an in-class simulation that allows students to gain hands-on experience with the complexities in making forecasting, inventory, and supplier selection decisions as part of the…
Using Simulations to Investigate Decision Making in Airline Operations
NASA Technical Reports Server (NTRS)
Bruce, Peter J.; Gray, Judy H.
2003-01-01
This paper examines a range of methods to collect data for the investigation of decision-making in airline Operations Control Centres (OCCs). A study was conducted of 52 controllers in five OCCs of both domestic and international airlines in the Asia-Pacific region. A range of methods was used including: surveys, interviews, observations, simulations, and think-aloud protocol. The paper compares and evaluates the suitability of these techniques for gathering data and provides recommendations on the application of simulations. Keywords Data Collection, Decision-Making, Research Methods, Simulation, Think-Aloud Protocol.
Simulation of California's Major Reservoirs Outflow Using Data Mining Technique
NASA Astrophysics Data System (ADS)
Yang, T.; Gao, X.; Sorooshian, S.
2014-12-01
The reservoir's outflow is controlled by reservoir operators, which is different from the upstream inflow. The outflow is more important than the reservoir's inflow for the downstream water users. In order to simulate the complicated reservoir operation and extract the outflow decision making patterns for California's 12 major reservoirs, we build a data-driven, computer-based ("artificial intelligent") reservoir decision making tool, using decision regression and classification tree approach. This is a well-developed statistical and graphical modeling methodology in the field of data mining. A shuffled cross validation approach is also employed to extract the outflow decision making patterns and rules based on the selected decision variables (inflow amount, precipitation, timing, water type year etc.). To show the accuracy of the model, a verification study is carried out comparing the model-generated outflow decisions ("artificial intelligent" decisions) with that made by reservoir operators (human decisions). The simulation results show that the machine-generated outflow decisions are very similar to the real reservoir operators' decisions. This conclusion is based on statistical evaluations using the Nash-Sutcliffe test. The proposed model is able to detect the most influential variables and their weights when the reservoir operators make an outflow decision. While the proposed approach was firstly applied and tested on California's 12 major reservoirs, the method is universally adaptable to other reservoir systems.
Modeling and Simulation of Shuttle Launch and Range Operations
NASA Technical Reports Server (NTRS)
Bardina, Jorge; Thirumalainambi, Rajkumar
2004-01-01
The simulation and modeling test bed is based on a mockup of a space flight operations control suitable to experiment physical, procedural, software, hardware and psychological aspects of space flight operations. The test bed consists of a weather expert system to advise on the effect of weather to the launch operations. It also simulates toxic gas dispersion model, impact of human health risk, debris dispersion model in 3D visualization. Since all modeling and simulation is based on the internet, it could reduce the cost of operations of launch and range safety by conducting extensive research before a particular launch. Each model has an independent decision making module to derive the best decision for launch.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Greitzer, Frank L.; Podmore, Robin
2008-11-17
The focus of the present study is on improved training approaches to accelerate learning and improved methods for analyzing effectiveness of tools within a high-fidelity power grid simulated environment. A theory-based model has been developed to document and understand the mental processes that an expert power system operator uses when making critical decisions. The theoretical foundation for the method is based on the concepts of situation awareness, the methods of cognitive task analysis, and the naturalistic decision making (NDM) approach of Recognition Primed Decision Making. The method has been systematically explored and refined as part of a capability demonstration ofmore » a high-fidelity real-time power system simulator under normal and emergency conditions. To examine NDM processes, we analyzed transcripts of operator-to-operator conversations during the simulated scenario to reveal and assess NDM-based performance criteria. The results of the analysis indicate that the proposed framework can be used constructively to map or assess the Situation Awareness Level of the operators at each point in the scenario. We can also identify the mental models and mental simulations that the operators employ at different points in the scenario. This report documents the method, describes elements of the model, and provides appendices that document the simulation scenario and the associated mental models used by operators in the scenario.« less
A Multi-Operator Simulation for Investigation of Distributed Air Traffic Management Concepts
NASA Technical Reports Server (NTRS)
Peters, Mark E.; Ballin, Mark G.; Sakosky, John S.
2002-01-01
This paper discusses the current development of an air traffic operations simulation that supports feasibility research for advanced air traffic management concepts. The Air Traffic Operations Simulation (ATOS) supports the research of future concepts that provide a much greater role for the flight crew in traffic management decision-making. ATOS provides representations of the future communications, navigation, and surveillance (CNS) infrastructure, a future flight deck systems architecture, and advanced crew interfaces. ATOS also provides a platform for the development of advanced flight guidance and decision support systems that may be required for autonomous operations.
Distributed Web-Based Expert System for Launch Operations
NASA Technical Reports Server (NTRS)
Bardina, Jorge E.; Thirumalainambi, Rajkumar
2005-01-01
The simulation and modeling of launch operations is based on a representation of the organization of the operations suitable to experiment of the physical, procedural, software, hardware and psychological aspects of space flight operations. The virtual test bed consists of a weather expert system to advice on the effect of weather to the launch operations. It also simulates toxic gas dispersion model, and the risk impact on human health. Since all modeling and simulation is based on the internet, it could reduce the cost of operations of launch and range safety by conducting extensive research before a particular launch. Each model has an independent decision making module to derive the best decision for launch.
2004-06-01
Situation Understanding) Common Operational Pictures Planning & Decision Support Capabilities Message & Order Processing Common Operational...Pictures Planning & Decision Support Capabilities Message & Order Processing Common Languages & Data Models Modeling & Simulation Domain
A Cooperative Human-Adaptive Traffic Simulation (CHATS)
NASA Technical Reports Server (NTRS)
Phillips, Charles T.; Ballin, Mark G.
1999-01-01
NASA is considering the development of a Cooperative Human-Adaptive Traffic Simulation (CHATS), to examine and evaluate performance of the National Airspace System (NAS) as the aviation community moves toward free flight. CHATS will be specifically oriented toward simulating strategic decision-making by airspace users and by the service provider s traffic management personnel, within the context of different airspace and rules assumptions. It will use human teams to represent these interests and make decisions, and will rely on computer modeling and simulation to calculate the impacts of these decisions. The simulation objectives will be to examine: 1. evolution of airspace users and the service provider s strategies, through adaptation to new operational environments; 2. air carriers competitive and cooperative behavior; 3. expected benefits to airspace users and the service provider as compared to the current NAS; 4. operational limitations of free flight concepts due to congestion and safety concerns. This paper describes an operational concept for CHATS, and presents a high-level functional design which would utilize a combination of existing and new models and simulation capabilities.
Assessing the structure of non-routine decision processes in Airline Operations Control.
Richters, Floor; Schraagen, Jan Maarten; Heerkens, Hans
2016-03-01
Unfamiliar severe disruptions challenge Airline Operations Control professionals most, as their expertise is stretched to its limits. This study has elicited the structure of Airline Operations Control professionals' decision process during unfamiliar disruptions by mapping three macrocognitive activities on the decision ladder: sensemaking, option evaluation and action planning. The relationship between this structure and decision quality was measured. A simulated task was staged, based on which think-aloud protocols were obtained. Results show that the general decision process structure resembles the structure of experts working under routine conditions, in terms of the general structure of the macrocognitive activities, and the rule-based approach used to identify options and actions. Surprisingly, high quality of decision outcomes was found to relate to the use of rule-based strategies. This implies that successful professionals are capable of dealing with unfamiliar problems by reframing them into familiar ones, rather than to engage in knowledge-based processing. Practitioner Summary: We examined the macrocognitive structure of Airline Operations Control professionals' decision process during a simulated unfamiliar disruption in relation to decision quality. Results suggest that successful professionals are capable of dealing with unfamiliar problems by reframing them into familiar ones, rather than to engage in knowledge-based processing.
Discrete event simulation for healthcare organizations: a tool for decision making.
Hamrock, Eric; Paige, Kerrie; Parks, Jennifer; Scheulen, James; Levin, Scott
2013-01-01
Healthcare organizations face challenges in efficiently accommodating increased patient demand with limited resources and capacity. The modern reimbursement environment prioritizes the maximization of operational efficiency and the reduction of unnecessary costs (i.e., waste) while maintaining or improving quality. As healthcare organizations adapt, significant pressures are placed on leaders to make difficult operational and budgetary decisions. In lieu of hard data, decision makers often base these decisions on subjective information. Discrete event simulation (DES), a computerized method of imitating the operation of a real-world system (e.g., healthcare delivery facility) over time, can provide decision makers with an evidence-based tool to develop and objectively vet operational solutions prior to implementation. DES in healthcare commonly focuses on (1) improving patient flow, (2) managing bed capacity, (3) scheduling staff, (4) managing patient admission and scheduling procedures, and (5) using ancillary resources (e.g., labs, pharmacies). This article describes applicable scenarios, outlines DES concepts, and describes the steps required for development. An original DES model developed to examine crowding and patient flow for staffing decision making at an urban academic emergency department serves as a practical example.
Distributed decision support for the 21st century mission space
NASA Astrophysics Data System (ADS)
McQuay, William K.
2002-07-01
The past decade has produced significant changes in the conduct of military operations: increased humanitarian missions, asymmetric warfare, the reliance on coalitions and allies, stringent rules of engagement, concern about casualties, and the need for sustained air operations. Future mission commanders will need to assimilate a tremendous amount of information, make quick-response decisions, and quantify the effects of those decisions in the face of uncertainty. Integral to this process is creating situational assessment-understanding the mission space, simulation to analyze alternative futures, current capabilities, planning assessments, course-of-action assessments, and a common operational picture-keeping everyone on the same sheet of paper. Decision support tools in a distributed collaborative environment offer the capability of decomposing these complex multitask processes and distributing them over a dynamic set of execution assets. Decision support technologies can semi-automate activities, such as planning an operation, that have a reasonably well-defined process and provide machine-level interfaces to refine the myriad of information that is not currently fused. The marriage of information and simulation technologies provides the mission commander with a collaborative virtual environment for planning and decision support.
Embedding Human Expert Cognition Into Autonomous UAS Trajectory Planning.
Narayan, Pritesh; Meyer, Patrick; Campbell, Duncan
2013-04-01
This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.
Naturalistic Decision Making for Power System Operators
DOE Office of Scientific and Technical Information (OSTI.GOV)
Greitzer, Frank L.; Podmore, Robin; Robinson, Marck
2010-02-01
Motivation – Investigations of large-scale outages in the North American interconnected electric system often attribute the causes to three T’s: Trees, Training and Tools. To document and understand the mental processes used by expert operators when making critical decisions, a naturalistic decision making (NDM) model was developed. Transcripts of conversations were analyzed to reveal and assess NDM-based performance criteria. Findings/Design – An item analysis indicated that the operators’ Situation Awareness Levels, mental models, and mental simulations can be mapped at different points in the training scenario. This may identify improved training methods or analytical/ visualization tools. Originality/Value – This studymore » applies for the first time, the concepts of Recognition Primed Decision Making, Situation Awareness Levels and Cognitive Task Analysis to training of electric power system operators. Take away message – The NDM approach provides a viable framework for systematic training management to accelerate learning in simulator-based training scenarios for power system operators and teams.« less
NASA Technical Reports Server (NTRS)
Tartabini, Paul V.; Munk, Michelle M.; Powell, Richard W.
2002-01-01
The Mars 2001 Odyssey Orbiter successfully completed the aerobraking phase of its mission on January 11, 2002. This paper discusses the support provided by NASA's Langley Research Center to the navigation team at the Jet Propulsion Laboratory in the planning and operational support of Mars Odyssey Aerobraking. Specifically, the development of a three-degree-of-freedom aerobraking trajectory simulation and its application to pre-flight planning activities as well as operations is described. The importance of running the simulation in a Monte Carlo fashion to capture the effects of mission and atmospheric uncertainties is demonstrated, and the utility of including predictive logic within the simulation that could mimic operational maneuver decision-making is shown. A description is also provided of how the simulation was adapted to support flight operations as both a validation and risk reduction tool and as a means of obtaining a statistical basis for maneuver strategy decisions. This latter application was the first use of Monte Carlo trajectory analysis in an aerobraking mission.
Detroit deicing decision support tool : description, operation, and simulation results
DOT National Transportation Integrated Search
2006-01-01
The John A. Volpe National Transportation Systems Center, sponsored by the National Aeronautics and Space Administration, : developed a deicing decision support tool, for Detroit Metropolitan Wayne County Airport (DTW).1 The deicing decision support ...
NASA Technical Reports Server (NTRS)
Eun, Yeonju; Jeon, Daekeun; Lee, Hanbong; Zhu, Zhifan; Jung, Yoon C.; Jeong, Myeongsook; Kim, Hyounkyong; Oh, Eunmi; Hong, Sungkwon; Lee, Junwon
2016-01-01
Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5% per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM(Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas/Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte/Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration - 2 (ATD-2) project for technology demonstration of Integrated Arrival/Departure/Surface (ADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement)/KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.
NASA Technical Reports Server (NTRS)
Eun, Yeonju; Jeon, Daekeun; Lee, Hanbong; Zhu, Zhifan; Jung, Yoon C.; Jeong, Myeongsook; Kim, Hyounkyong; Oh, Eunmi; Hong, Sungkwon; Lee, Junwon
2016-01-01
Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5 percent per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM (Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas-Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte-Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration-2 (ATD-2) project for technology demonstration of Integrated Arrival-Departure-Surface (IADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement), KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.
Decision making in prioritization of required operational capabilities
NASA Astrophysics Data System (ADS)
Andreeva, P.; Karev, M.; Kovacheva, Ts.
2015-10-01
The paper describes an expert heuristic approach to prioritization of required operational capabilities in the field of defense. Based on expert assessment and by application of the method of Analytical Hierarchical Process, a methodology for their prioritization has been developed. It has been applied to practical simulation decision making games.
Naturalistic Decision Making For Power System Operators
DOE Office of Scientific and Technical Information (OSTI.GOV)
Greitzer, Frank L.; Podmore, Robin; Robinson, Marck
2009-06-23
Abstract: Motivation -- As indicated by the Blackout of 2003, the North American interconnected electric system is vulnerable to cascading outages and widespread blackouts. Investigations of large scale outages often attribute the causes to the three T’s: Trees, Training and Tools. A systematic approach has been developed to document and understand the mental processes that an expert power system operator uses when making critical decisions. The approach has been developed and refined as part of a capability demonstration of a high-fidelity real-time power system simulator under normal and emergency conditions. To examine naturalistic decision making (NDM) processes, transcripts of operator-to-operatormore » conversations are analyzed to reveal and assess NDM-based performance criteria. Findings/Design -- The results of the study indicate that we can map the Situation Awareness Level of the operators at each point in the scenario. We can also identify clearly what mental models and mental simulations are being performed at different points in the scenario. As a result of this research we expect that we can identify improved training methods and improved analytical and visualization tools for power system operators. Originality/Value -- The research applies for the first time, the concepts of Recognition Primed Decision Making, Situation Awareness Levels and Cognitive Task Analysis to training of electric power system operators. Take away message -- The NDM approach provides an ideal framework for systematic training management and mitigation to accelerate learning in team-based training scenarios with high-fidelity power grid simulators.« less
DECISION MAKING , * GROUP DYNAMICS, NAVAL TRAINING, TRANSFER OF TRAINING, SCIENTIFIC RESEARCH, CLASSIFICATION, PROBLEM SOLVING, MATHEMATICAL MODELS, SUBMARINES, SIMULATORS, PERFORMANCE(HUMAN), UNDERSEA WARFARE.
NASA Astrophysics Data System (ADS)
Coyne, Kevin Anthony
The safe operation of complex systems such as nuclear power plants requires close coordination between the human operators and plant systems. In order to maintain an adequate level of safety following an accident or other off-normal event, the operators often are called upon to perform complex tasks during dynamic situations with incomplete information. The safety of such complex systems can be greatly improved if the conditions that could lead operators to make poor decisions and commit erroneous actions during these situations can be predicted and mitigated. The primary goal of this research project was the development and validation of a cognitive model capable of simulating nuclear plant operator decision-making during accident conditions. Dynamic probabilistic risk assessment methods can improve the prediction of human error events by providing rich contextual information and an explicit consideration of feedback arising from man-machine interactions. The Accident Dynamics Simulator paired with the Information, Decision, and Action in a Crew context cognitive model (ADS-IDAC) shows promise for predicting situational contexts that might lead to human error events, particularly knowledge driven errors of commission. ADS-IDAC generates a discrete dynamic event tree (DDET) by applying simple branching rules that reflect variations in crew responses to plant events and system status changes. Branches can be generated to simulate slow or fast procedure execution speed, skipping of procedure steps, reliance on memorized information, activation of mental beliefs, variations in control inputs, and equipment failures. Complex operator mental models of plant behavior that guide crew actions can be represented within the ADS-IDAC mental belief framework and used to identify situational contexts that may lead to human error events. This research increased the capabilities of ADS-IDAC in several key areas. The ADS-IDAC computer code was improved to support additional branching events and provide a better representation of the IDAC cognitive model. An operator decision-making engine capable of responding to dynamic changes in situational context was implemented. The IDAC human performance model was fully integrated with a detailed nuclear plant model in order to realistically simulate plant accident scenarios. Finally, the improved ADS-IDAC model was calibrated, validated, and updated using actual nuclear plant crew performance data. This research led to the following general conclusions: (1) A relatively small number of branching rules are capable of efficiently capturing a wide spectrum of crew-to-crew variabilities. (2) Compared to traditional static risk assessment methods, ADS-IDAC can provide a more realistic and integrated assessment of human error events by directly determining the effect of operator behaviors on plant thermal hydraulic parameters. (3) The ADS-IDAC approach provides an efficient framework for capturing actual operator performance data such as timing of operator actions, mental models, and decision-making activities.
SARDA: An Integrated Concept for Airport Surface Operations Management
NASA Technical Reports Server (NTRS)
Gupta, Gautam; Hoang, Ty; Jung, Yoon Chul
2013-01-01
The Spot and Runway Departure Advisor (SARDA) is an integrated decision support tool for airlines and air traffic control tower enabling surface collaborative decision making (CDM) and departure metering in order to enhance efficiency of surface operations at congested airports. The presentation describes the concept and architecture of the SARDA as a CDM tool, and the results from a human-in-the-loop simulation of the tool conducted in 2012 at the FutureFlight Central, the tower simulation facility. Also, presented is the current activities and future plan for SARDA development. The presentation was given at the meeting with the FAA senior advisor of the Surface Operations Office.
Mission at Mubasi - A Simulation for Leadership Development
NASA Technical Reports Server (NTRS)
Cummings, Pau; Aude, Steven; Fallesen, Jon
2012-01-01
The United States Army is investing in simulations as a way of providing practice for leader decision making. Such simulations, grounded in lessons learned from deployment experienced leaders, place less experienced and more junior leaders in challenging situations they might soon be confronted with. And given increased demands on the Army to become more efficient, while maintaining acceptable levels of mission readiness, simulations offer a cost effective complement to live field training. So too, the design parameters of such a simulation can be made to reinforce specific behavior responses which teach leaders known theory and application of effective (and ineffective) decision making. With this in mind, the Center for Army Leadership (CAL) determined that decision-making was of critical importance. Specifically, the following aspects of decision-making were viewed as particularly important for today's Army leaders: 1) Decision dilemmas, in the form of equally appealing or equally unappealing choices, such that there is no clear "right" or "wrong" choice 2) Making decisions with incomplete or ambiguous information, and 3) Predicting and experiencing second- and third-order consequences of decisions. It is decision making in such a setting or environment that Army leaders are increasingly confronted with given the full spectrum of military operations they must be prepared for. This paper details the approach and development of this decision making simulation.
NEFP Decision Process: "A Computer Simulation for Planning School Finance Programs." User Manual.
ERIC Educational Resources Information Center
Boardman, Gerald R.; And Others
The National Educational Finance Project has developed a computerized model designed to simulate the consequences of alternative decisions in regard to the financing of public elementary and secondary education. This manual describes a users orientation to that model. The model was designed as an operational prototype for States to use in a…
Adhitya, Arief; Halim, Iskandar; Srinivasan, Rajagopalan
2011-12-01
As the issue of environmental sustainability is becoming an important business factor, companies are now looking for decision support tools to assess the fuller picture of the environmental impacts associated with their manufacturing operations and supply chain (SC) activities. Lifecycle assessment (LCA) is widely used to measure the environmental consequences assignable to a product. However, it is usually limited to a high-level snapshot of the environmental implications over the product value chain without consideration of the dynamics arising from the multitiered structure and the interactions along the SC. This paper proposes a framework for green supply chain management by integrating a SC dynamic simulation and LCA indicators to evaluate both the economic and environmental impacts of various SC decisions such as inventories, distribution network configuration, and ordering policy. The advantages of this framework are demonstrated through an industrially motivated case study involving diaper production. Three distinct scenarios are evaluated to highlight how the proposed approach enables integrated decision support for green SC design and operation.
Decision Support Systems for Operational Level Command and Control
1990-04-30
business -based. These definitions still have applicability to military command and control - the business of military operations. A synthesis of the...other hand, there are such studies that were conducted in business environments. An eight week empincal study39 was 37 bd, pp 8-1 I. 38 Ranesh Shada...pp 139-158. 19 conducted and the groups with access to decision support system made significantly more effective decisions :n a business simulation
ERIC Educational Resources Information Center
Dickinson, J. Barry; Dickinson, Carleen D.
2012-01-01
This study examines the impact that experienced mentoring has on business decisions in a higher education business school. Students, arranged in teams, were given the opportunity to operate virtual companies in a well-known, business simulation program called Capsim. They were required to make decisions concerning marketing, production, finance,…
Fuzzy logic controller optimization
Sepe, Jr., Raymond B; Miller, John Michael
2004-03-23
A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.
Smart Grid as Multi-layer Interacting System for Complex Decision Makings
NASA Astrophysics Data System (ADS)
Bompard, Ettore; Han, Bei; Masera, Marcelo; Pons, Enrico
This chapter presents an approach to the analysis of Smart Grids based on a multi-layer representation of their technical, cyber, social and decision-making aspects, as well as the related environmental constraints. In the Smart Grid paradigm, self-interested active customers (prosumers), system operators and market players interact among themselves making use of an extensive cyber infrastructure. In addition, policy decision makers define regulations, incentives and constraints to drive the behavior of the competing operators and prosumers, with the objective of ensuring the global desired performance (e.g. system stability, fair prices). For these reasons, the policy decision making is more complicated than in traditional power systems, and needs proper modeling and simulation tools for assessing "in vitro" and ex-ante the possible impacts of the decisions assumed. In this chapter, we consider the smart grids as multi-layered interacting complex systems. The intricacy of the framework, characterized by several interacting layers, cannot be captured by closed-form mathematical models. Therefore, a new approach using Multi Agent Simulation is described. With case studies we provide some indications about how to develop agent-based simulation tools presenting some preliminary examples.
NASA Astrophysics Data System (ADS)
Li, Yu; Giuliani, Matteo; Castelletti, Andrea
2016-04-01
Recent advances in modelling of coupled ocean-atmosphere dynamics significantly improved skills of long-term climate forecast from global circulation models (GCMs). These more accurate weather predictions are supposed to be a valuable support to farmers in optimizing farming operations (e.g. crop choice, cropping and watering time) and for more effectively coping with the adverse impacts of climate variability. Yet, assessing how actually valuable this information can be to a farmer is not straightforward and farmers' response must be taken into consideration. Indeed, in the context of agricultural systems potentially useful forecast information should alter stakeholders' expectation, modify their decisions, and ultimately produce an impact on their performance. Nevertheless, long-term forecast are mostly evaluated in terms of accuracy (i.e., forecast quality) by comparing hindcast and observed values and only few studies investigated the operational value of forecast looking at the gain of utility within the decision-making context, e.g. by considering the derivative of forecast information, such as simulated crop yields or simulated soil moisture, which are essential to farmers' decision-making process. In this study, we contribute a step further in the assessment of the operational value of long-term weather forecasts products by embedding these latter into farmers' behavioral models. This allows a more critical assessment of the forecast value mediated by the end-users' perspective, including farmers' risk attitudes and behavioral patterns. Specifically, we evaluate the operational value of thirteen state-of-the-art long-range forecast products against climatology forecast and empirical prediction (i.e. past year climate and historical average) within an integrated agronomic modeling framework embedding an implicit model of the farmers' decision-making process. Raw ensemble datasets are bias-corrected and downscaled using a stochastic weather generator, in order to address the mismatch of the spatio-temporal scale between forecast data from GCMs and our model. For each product, the experiment is composed by two cascade simulations: 1) an ex-ante simulation using forecast data, and 2) an ex-post simulation with observations. Multi-year simulations are performed to account for climate variability, and the operational value of the different forecast products is evaluated against the perfect foresight on the basis of expected crop productivity as well as the final decisions under different decision-making criterions. Our results show that not all products generate beneficial effects to farmers' performance, and the forecast errors might be amplified due to farmers' decision-making process and risk attitudes, yielding little or even worse performance compared with the empirical approaches.
Braathen, Sverre; Sendstad, Ole Jakob
2004-08-01
Possible techniques for representing automatic decision-making behavior approximating human experts in complex simulation model experiments are of interest. Here, fuzzy logic (FL) and constraint satisfaction problem (CSP) methods are applied in a hybrid design of automatic decision making in simulation game models. The decision processes of a military headquarters are used as a model for the FL/CSP decision agents choice of variables and rulebases. The hybrid decision agent design is applied in two different types of simulation games to test the general applicability of the design. The first application is a two-sided zero-sum sequential resource allocation game with imperfect information interpreted as an air campaign game. The second example is a network flow stochastic board game designed to capture important aspects of land manoeuvre operations. The proposed design is shown to perform well also in this complex game with a very large (billionsize) action set. Training of the automatic FL/CSP decision agents against selected performance measures is also shown and results are presented together with directions for future research.
Cyberwar XXI: quantifying the unquantifiable: adaptive AI for next-generation conflict simulations
NASA Astrophysics Data System (ADS)
Miranda, Joseph; von Kleinsmid, Peter; Zalewski, Tony
2004-08-01
The era of the "Revolution in Military Affairs," "4th Generation Warfare" and "Asymmetric War" requires novel approaches to modeling warfare at the operational and strategic level of modern conflict. For example, "What if, in response to our planned actions, the adversary reacts in such-and-such a manner? What will our response be? What are the possible unintended consequences?" Next generation conflict simulation tools are required to help create and test novel courses of action (COA's) in support of real-world operations. Conflict simulations allow non-lethal and cost-effective exploration of the "what-if" of COA development. The challenge has been to develop an automated decision-support software tool which allows competing COA"s to be compared in simulated dynamic environments. Principal Investigator Joseph Miranda's research is based on modeling an integrated military, economic, social, infrastructure and information (PMESII) environment. The main effort was to develop an adaptive AI engine which models agents operating within an operational-strategic conflict environment. This was implemented in Cyberwar XXI - a simulation which models COA selection in a PMESII environment. Within this framework, agents simulate decision-making processes and provide predictive capability of the potential behavior of Command Entities. The 2003 Iraq is the first scenario ready for V&V testing.
Hierarchical analytical and simulation modelling of human-machine systems with interference
NASA Astrophysics Data System (ADS)
Braginsky, M. Ya; Tarakanov, D. V.; Tsapko, S. G.; Tsapko, I. V.; Baglaeva, E. A.
2017-01-01
The article considers the principles of building the analytical and simulation model of the human operator and the industrial control system hardware and software. E-networks as the extension of Petri nets are used as the mathematical apparatus. This approach allows simulating complex parallel distributed processes in human-machine systems. The structural and hierarchical approach is used as the building method for the mathematical model of the human operator. The upper level of the human operator is represented by the logical dynamic model of decision making based on E-networks. The lower level reflects psychophysiological characteristics of the human-operator.
INTEGRATING DATA ANALYTICS AND SIMULATION METHODS TO SUPPORT MANUFACTURING DECISION MAKING
Kibira, Deogratias; Hatim, Qais; Kumara, Soundar; Shao, Guodong
2017-01-01
Modern manufacturing systems are installed with smart devices such as sensors that monitor system performance and collect data to manage uncertainties in their operations. However, multiple parameters and variables affect system performance, making it impossible for a human to make informed decisions without systematic methodologies and tools. Further, the large volume and variety of streaming data collected is beyond simulation analysis alone. Simulation models are run with well-prepared data. Novel approaches, combining different methods, are needed to use this data for making guided decisions. This paper proposes a methodology whereby parameters that most affect system performance are extracted from the data using data analytics methods. These parameters are used to develop scenarios for simulation inputs; system optimizations are performed on simulation data outputs. A case study of a machine shop demonstrates the proposed methodology. This paper also reviews candidate standards for data collection, simulation, and systems interfaces. PMID:28690363
Understanding the Marketplace: A Simulation
ERIC Educational Resources Information Center
Vickers, Carole A.
1978-01-01
Describes a marketplace simulation game to help students understand the role of competition and the rationale behind buying and selling food and restaurant services. Cutouts (given in the article) are used to simulate elements in the game. Emphasis is on making decisions in business operation and consumer purchases. (MF)
Ultra Low Energy Binary Decision Diagram Circuits Using Few Electron Transistors
NASA Astrophysics Data System (ADS)
Saripalli, Vinay; Narayanan, Vijay; Datta, Suman
Novel medical applications involving embedded sensors, require ultra low energy dissipation with low-to-moderate performance (10kHz-100MHz) driving the conventional MOSFETs into sub-threshold operation regime. In this paper, we present an alternate ultra-low power computing architecture using Binary Decision Diagram based logic circuits implemented using Single Electron Transistors (SETs) operating in the Coulomb blockade regime with very low supply voltages. We evaluate the energy - performance tradeoff metrics of such BDD circuits using time domain Monte Carlo simulations and compare them with the energy-optimized CMOS logic circuits. Simulation results show that the proposed approach achieves better energy-delay characteristics than CMOS realizations.
Simulation-based planning for theater air warfare
NASA Astrophysics Data System (ADS)
Popken, Douglas A.; Cox, Louis A., Jr.
2004-08-01
Planning for Theatre Air Warfare can be represented as a hierarchy of decisions. At the top level, surviving airframes must be assigned to roles (e.g., Air Defense, Counter Air, Close Air Support, and AAF Suppression) in each time period in response to changing enemy air defense capabilities, remaining targets, and roles of opposing aircraft. At the middle level, aircraft are allocated to specific targets to support their assigned roles. At the lowest level, routing and engagement decisions are made for individual missions. The decisions at each level form a set of time-sequenced Courses of Action taken by opposing forces. This paper introduces a set of simulation-based optimization heuristics operating within this planning hierarchy to optimize allocations of aircraft. The algorithms estimate distributions for stochastic outcomes of the pairs of Red/Blue decisions. Rather than using traditional stochastic dynamic programming to determine optimal strategies, we use an innovative combination of heuristics, simulation-optimization, and mathematical programming. Blue decisions are guided by a stochastic hill-climbing search algorithm while Red decisions are found by optimizing over a continuous representation of the decision space. Stochastic outcomes are then provided by fast, Lanchester-type attrition simulations. This paper summarizes preliminary results from top and middle level models.
Using Decision Trees to Detect and Isolate Simulated Leaks in the J-2X Rocket Engine
NASA Technical Reports Server (NTRS)
Schwabacher, Mark A.; Aguilar, Robert; Figueroa, Fernando F.
2009-01-01
The goal of this work was to use data-driven methods to automatically detect and isolate faults in the J-2X rocket engine. It was decided to use decision trees, since they tend to be easier to interpret than other data-driven methods. The decision tree algorithm automatically "learns" a decision tree by performing a search through the space of possible decision trees to find one that fits the training data. The particular decision tree algorithm used is known as C4.5. Simulated J-2X data from a high-fidelity simulator developed at Pratt & Whitney Rocketdyne and known as the Detailed Real-Time Model (DRTM) was used to "train" and test the decision tree. Fifty-six DRTM simulations were performed for this purpose, with different leak sizes, different leak locations, and different times of leak onset. To make the simulations as realistic as possible, they included simulated sensor noise, and included a gradual degradation in both fuel and oxidizer turbine efficiency. A decision tree was trained using 11 of these simulations, and tested using the remaining 45 simulations. In the training phase, the C4.5 algorithm was provided with labeled examples of data from nominal operation and data including leaks in each leak location. From the data, it "learned" a decision tree that can classify unseen data as having no leak or having a leak in one of the five leak locations. In the test phase, the decision tree produced very low false alarm rates and low missed detection rates on the unseen data. It had very good fault isolation rates for three of the five simulated leak locations, but it tended to confuse the remaining two locations, perhaps because a large leak at one of these two locations can look very similar to a small leak at the other location.
A Multiprocessor Operating System Simulator
NASA Technical Reports Server (NTRS)
Johnston, Gary M.; Campbell, Roy H.
1988-01-01
This paper describes a multiprocessor operating system simulator that was developed by the authors in the Fall semester of 1987. The simulator was built in response to the need to provide students with an environment in which to build and test operating system concepts as part of the coursework of a third-year undergraduate operating systems course. Written in C++, the simulator uses the co-routine style task package that is distributed with the AT&T C++ Translator to provide a hierarchy of classes that represents a broad range of operating system software and hardware components. The class hierarchy closely follows that of the 'Choices' family of operating systems for loosely- and tightly-coupled multiprocessors. During an operating system course, these classes are refined and specialized by students in homework assignments to facilitate experimentation with different aspects of operating system design and policy decisions. The current implementation runs on the IBM RT PC under 4.3bsd UNIX.
Helicopter simulation: Making it work
NASA Technical Reports Server (NTRS)
Payne, Barry
1992-01-01
The opportunities for improved training and checking by using helicopter simulators are greater than they are for airplane pilot training. Simulators permit the safe creation of training environments that are conducive to the development of pilot decision-making, situational awareness, and cockpit management. This paper defines specific attributes required in a simulator to meet a typical helicopter operator's training and checking objectives.
Distributed collaborative environments for predictive battlespace awareness
NASA Astrophysics Data System (ADS)
McQuay, William K.
2003-09-01
The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, make quick-response decisions, and quantify the effects of those decisions in the face of uncertainty. Situational assessment is crucial in understanding the battlespace. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Decision support technologies can semi-automate activities, such as analysis and planning, that have a reasonably well-defined process and provide machine-level interfaces to refine the myriad of information that the commander must fused. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing AFRL research efforts in applying distributed collaborative environments to predictive battlespace awareness.
The 14th Annual Conference on Manual Control. [digital simulation of human operator dynamics
NASA Technical Reports Server (NTRS)
1978-01-01
Human operator dynamics during actual manual control or while monitoring the automatic control systems involved in air-to-air tracking, automobile driving, the operator of undersea vehicles, and remote handling are examined. Optimal control models and the use of mathematical theory in representing man behavior in complex man machine system tasks are discussed with emphasis on eye/head tracking and scanning; perception and attention allocation; decision making; and motion simulation and effects.
Pilot interaction with automated airborne decision making systems
NASA Technical Reports Server (NTRS)
Hammer, John M.
1990-01-01
Ways in which computers can aid the decision making of an human operator of an aerospace system are investigated. The approach taken is to aid rather than replace the human operator, because operational experience has shown that humans can enhance the effectiveness of systems. As systems become more automated, the role of the operator has shifted to that of a manager and problem solver. This shift has created the research area of how to aid the human in this role. Published research in four areas is described. A discussion is presented of the DC-8 flight simulator at Georgia Tech.
Operational seasonal forecasting of crop performance.
Stone, Roger C; Meinke, Holger
2005-11-29
Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production.
Operational seasonal forecasting of crop performance
Stone, Roger C; Meinke, Holger
2005-01-01
Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production. PMID:16433097
Murji, Ally; Luketic, Lea; Sobel, Mara L; Kulasegaram, Kulamakan Mahan; Leyland, Nicholas; Posner, Glenn
2016-10-01
Answering telephone calls and pagers is common distraction in the operating room. We sought to evaluate the impact of distractions on patient care by (1) assessing the accuracy and safety of responses to clinical questions posed to a surgeon while operating and (2) determining whether pager distractions affect simulation-based surgical performance. We conducted a randomized crossover study of obstetrics and gynecology residents. After studying a patient sign-out list, subjects performed a virtual salpingectomy. They were randomized to a distraction phase followed by quiet phase or vice versa. In the distraction phase, a pager beeped and subjects were asked questions based on the sign-out list. Accuracy of responses and the number of unsafe responses were recorded. In the quiet phase, trainees performed the task uninterrupted. Measures of surgical performance were successful task completion, time to task completion and operative blood loss. The mean score for correct responses to clinical questions during the distracted phase was 80 % (SD ±14 %). Nineteen residents (63 %) made at least 1 unsafe clinical decision while operating on the simulator (range 0-3). Subjects were more likely to successfully complete the surgical task in the allotted time under the quiet compared to distraction condition (OR 11.3, p = 0.03). There was no difference between the conditions in paired analysis for mean time (seconds) to task completion [426 (SD 133) vs. 440 (SD 186), p = 0.61] and mean operative blood loss (mL) [73.14 (SD 106) vs. 112.70 (SD 358), p = 0.47]. Distractions in the operating room may have a profound impact on patient safety on the wards. While multitasking in a simulated setting, the majority of residents made at least one unsafe clinical decision. Pager distractions also hindered surgical residents' ability to complete a simulated laparoscopic task in the allotted time without affecting other variables of surgical performance.
M&S Decision/Role-Behavior Decompositions
2007-10-17
M &S Decision/Role-Behavior Decompositions Wargaming and Analysis Workshop Military Operations Research Society 17 October 2007 Paul Works, Methods...number. 1. REPORT DATE 17 OCT 2007 2. REPORT TYPE 3. DATES COVERED 00-00-2007 to 00-00-2007 4. TITLE AND SUBTITLE M &S Decision/Role-Behavior...transmission. • Combat models and simulations ( M &S) continue, in most cases, to model “effects-level” representations of SA, decisions, and behaviors. – M &S
The Computer in Educational Decision Making. An Introduction and Guide for School Administrators.
ERIC Educational Resources Information Center
Sanders, Susan; And Others
This text provides educational administrators with a working knowledge of the problem-solving techniques of PERT (planning, evaluation, and review technique), Linear Programming, Queueing Theory, and Simulation. The text includes an introduction to decision-making and operations research, four chapters consisting of indepth explanations of each…
System Performance of an Integrated Airborne Spacing Algorithm with Ground Automation
NASA Technical Reports Server (NTRS)
Swieringa, Kurt A.; Wilson, Sara R.; Baxley, Brian T.
2016-01-01
The National Aeronautics and Space Administration's (NASA's) first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature ATM technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise time-based scheduling in the Terminal airspace; Controller Managed Spacing (CMS), which provides controllers with decision support tools to enable precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain precise spacing behind another aircraft. Recent simulations and IM algorithm development at NASA have focused on trajectory-based IM operations where aircraft equipped with IM avionics are expected to achieve a spacing goal, assigned by air traffic controllers, at the final approach fix. The recently published IM Minimum Operational Performance Standards describe five types of IM operations. This paper discusses the results and conclusions of a human-in-the-loop simulation that investigated three of those IM operations. The results presented in this paper focus on system performance and integration metrics. Overall, the IM operations conducted in this simulation integrated well with ground-based decisions support tools and certain types of IM operational were able to provide improved spacing precision at the final approach fix; however, some issues were identified that should be addressed prior to implementing IM procedures into real-world operations.
Structuring modeling and simulation analysis for evacuation planning and operations.
DOT National Transportation Integrated Search
2009-06-01
This document is intended to provide guidance to decision-makers at agencies and jurisdictions considering the role of analytical tools in evacuation planning and operations. It is often unclear what kind of analytical approach may be of most value, ...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Meshkati, N.; Buller, B.J.; Azadeh, M.A.
1995-04-01
The goal of this research is threefold: (1) use of the Skill-, Rule-, and Knowledge-based levels of cognitive control -- the SRK framework -- to develop an integrated information processing conceptual framework (for integration of workstation, job, and team design); (2) to evaluate the user interface component of this framework -- the Ecological display; and (3) to analyze the effect of operators` individual information processing behavior and decision styles on handling plant disturbances plus their performance on, and preference for, Traditional and Ecological user interfaces. A series of studies were conducted. In Part I, a computer simulation model and amore » mathematical model were developed. In Part II, an experiment was designed and conducted at the EBR-II plant of the Argonne National Laboratory-West in Idaho Falls, Idaho. It is concluded that: the integrated SRK-based information processing model for control room operations is superior to the conventional rule-based model; operators` individual decision styles and the combination of their styles play a significant role in effective handling of nuclear power plant disturbances; use of the Ecological interface results in significantly more accurate event diagnosis and recall of various plant parameters, faster response to plant transients, and higher ratings of subject preference; and operators` decision styles affect on both their performance and preference for the Ecological interface.« less
Rovira, Ericka; Cross, Austin; Leitch, Evan; Bonaceto, Craig
2014-09-01
The impact of a decision support tool designed to embed contextual mission factors was investigated. Contextual information may enable operators to infer the appropriateness of data underlying the automation's algorithm. Research has shown the costs of imperfect automation are more detrimental than perfectly reliable automation when operators are provided with decision support tools. Operators may trust and rely on the automation more appropriately if they understand the automation's algorithm. The need to develop decision support tools that are understandable to the operator provides the rationale for the current experiment. A total of 17 participants performed a simulated rapid retasking of intelligence, surveillance, and reconnaissance (ISR) assets task with manual, decision automation, or contextual decision automation differing in two levels of task demand: low or high. Automation reliability was set at 80%, resulting in participants experiencing a mixture of reliable and automation failure trials. Dependent variables included ISR coverage and response time of replanning routes. Reliable automation significantly improved ISR coverage when compared with manual performance. Although performance suffered under imperfect automation, contextual decision automation helped to reduce some of the decrements in performance. Contextual information helps overcome the costs of imperfect decision automation. Designers may mitigate some of the performance decrements experienced with imperfect automation by providing operators with interfaces that display contextual information, that is, the state of factors that affect the reliability of the automation's recommendation.
ERIC Educational Resources Information Center
Roman, Richard Allan
The Information System for Vocational Decisions (ISVD) places Boocock's (1967) Life Career Game in the core of its operating system. This paper considers the types of interaction that will be required of the system, and discusses the role that a career decision game might play in its total context. The paper takes an into-the-future look at the…
A multiprocessor operating system simulator
DOE Office of Scientific and Technical Information (OSTI.GOV)
Johnston, G.M.; Campbell, R.H.
1988-01-01
This paper describes a multiprocessor operating system simulator that was developed by the authors in the Fall of 1987. The simulator was built in response to the need to provide students with an environment in which to build and test operating system concepts as part of the coursework of a third-year undergraduate operating systems course. Written in C++, the simulator uses the co-routine style task package that is distributed with the AT and T C++ Translator to provide a hierarchy of classes that represents a broad range of operating system software and hardware components. The class hierarchy closely follows thatmore » of the Choices family of operating systems for loosely and tightly coupled multiprocessors. During an operating system course, these classes are refined and specialized by students in homework assignments to facilitate experimentation with different aspects of operating system design and policy decisions. The current implementation runs on the IBM RT PC under 4.3bsd UNIX.« less
Optimization of Operations Resources via Discrete Event Simulation Modeling
NASA Technical Reports Server (NTRS)
Joshi, B.; Morris, D.; White, N.; Unal, R.
1996-01-01
The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration.
NASA Astrophysics Data System (ADS)
Lee, K. David; Colony, Mike
2011-06-01
Modeling and simulation has been established as a cost-effective means of supporting the development of requirements, exploring doctrinal alternatives, assessing system performance, and performing design trade-off analysis. The Army's constructive simulation for the evaluation of equipment effectiveness in small combat unit operations is currently limited to representation of situation awareness without inclusion of the many uncertainties associated with real world combat environments. The goal of this research is to provide an ability to model situation awareness and decision process uncertainties in order to improve evaluation of the impact of battlefield equipment on ground soldier and small combat unit decision processes. Our Army Probabilistic Inference and Decision Engine (Army-PRIDE) system provides this required uncertainty modeling through the application of two critical techniques that allow Bayesian network technology to be applied to real-time applications. (Object-Oriented Bayesian Network methodology and Object-Oriented Inference technique). In this research, we implement decision process and situation awareness models for a reference scenario using Army-PRIDE and demonstrate its ability to model a variety of uncertainty elements, including: confidence of source, information completeness, and information loss. We also demonstrate that Army-PRIDE improves the realism of the current constructive simulation's decision processes through Monte Carlo simulation.
Distributed collaborative decision support environments for predictive awareness
NASA Astrophysics Data System (ADS)
McQuay, William K.; Stilman, Boris; Yakhnis, Vlad
2005-05-01
The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, rapidly assess the enemy"s course of action (eCOA) or possible actions and promulgate their own course of action (COA) - a need for predictive awareness. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Revolutionary new approaches to strategy generation and assessment such as Linguistic Geometry (LG) permit the rapid development of COA vs. enemy COA (eCOA). LG tools automatically generate and permit the operators to take advantage of winning strategies and tactics for mission planning and execution in near real-time. LG is predictive and employs deep "look-ahead" from the current state and provides a realistic, reactive model of adversary reasoning and behavior. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing research efforts in applying distributed collaborative environments to decision support for predictive mission awareness.
University Macro Analytic Simulation Model.
ERIC Educational Resources Information Center
Baron, Robert; Gulko, Warren
The University Macro Analytic Simulation System (UMASS) has been designed as a forecasting tool to help university administrators budgeting decisions. Alternative budgeting strategies can be tested on a computer model and then an operational alternative can be selected on the basis of the most desirable projected outcome. UMASS uses readily…
The Evaluation of ERP Sandtable Simulation Based on AHP
NASA Astrophysics Data System (ADS)
Xu, Lan
Due to the trend of world globalization, many enterprises have extended their business to operate globally. Enterprise resource planning is a powerful management system providing the best business resources information. This paper proposed the theory of AHP, and presented ERP sandtable simulation evaluation to discuss how to make a decision using AHP. Using this method can make enterprises consider factors influence operation of enterprise adequately, including feedback and dependence among the factors.
Operate a Nuclear Power Plant.
ERIC Educational Resources Information Center
Frimpter, Bonnie J.; And Others
1983-01-01
Describes classroom use of a computer program originally published in Creative Computing magazine. "The Nuclear Power Plant" (runs on Apple II with 48K memory) simulates the operating of a nuclear generating station, requiring students to make decisions as they assume the task of managing the plant. (JN)
Pilot interaction with automated airborne decision making systems
NASA Technical Reports Server (NTRS)
Rouse, W. B.; Hammer, J. M.; Mitchell, C. M.; Morris, N. M.; Lewis, C. M.; Yoon, W. C.
1985-01-01
Progress was made in the three following areas. In the rule-based modeling area, two papers related to identification and significane testing of rule-based models were presented. In the area of operator aiding, research focused on aiding operators in novel failure situations; a discrete control modeling approach to aiding PLANT operators was developed; and a set of guidelines were developed for implementing automation. In the area of flight simulator hardware and software, the hardware will be completed within two months and initial simulation software will then be integrated and tested.
Optimization Research of Generation Investment Based on Linear Programming Model
NASA Astrophysics Data System (ADS)
Wu, Juan; Ge, Xueqian
Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.
Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.
Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana
2016-01-01
The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.
Risk Reduction and Training using Simulation Based Tools - 12180
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hall, Irin P.
2012-07-01
Process Modeling and Simulation (M and S) has been used for many years in manufacturing and similar domains, as part of an industrial engineer's tool box. Traditionally, however, this technique has been employed in small, isolated projects where models were created from scratch, often making it time and cost prohibitive. Newport News Shipbuilding (NNS) has recognized the value of this predictive technique and what it offers in terms of risk reduction, cost avoidance and on-schedule performance of highly complex work. To facilitate implementation, NNS has been maturing a process and the software to rapidly deploy and reuse M and Smore » based decision support tools in a variety of environments. Some examples of successful applications by NNS of this technique in the nuclear domain are a reactor refueling simulation based tool, a fuel handling facility simulation based tool and a tool for dynamic radiation exposure tracking. The next generation of M and S applications include expanding simulation based tools into immersive and interactive training. The applications discussed here take a tool box approach to creating simulation based decision support tools for maximum utility and return on investment. This approach involves creating a collection of simulation tools that can be used individually or integrated together for a larger application. The refueling simulation integrates with the fuel handling facility simulation to understand every aspect and dependency of the fuel handling evolutions. This approach translates nicely to other complex domains where real system experimentation is not feasible, such as nuclear fuel lifecycle and waste management. Similar concepts can also be applied to different types of simulation techniques. For example, a process simulation of liquid waste operations may be useful to streamline and plan operations, while a chemical model of the liquid waste composition is an important tool for making decisions with respect to waste disposition. Integrating these tools into a larger virtual system provides a tool for making larger strategic decisions. The key to integrating and creating these virtual environments is the software and the process used to build them. Although important steps in the direction of using simulation based tools for nuclear domain, the applications described here represent only a small cross section of possible benefits. The next generation of applications will, likely, focus on situational awareness and adaptive planning. Situational awareness refers to the ability to visualize in real time the state of operations. Some useful tools in this area are Geographic Information Systems (GIS), which help monitor and analyze geographically referenced information. Combined with such situational awareness capability, simulation tools can serve as the platform for adaptive planning tools. These are the tools that allow the decision maker to react to the changing environment in real time by synthesizing massive amounts of data into easily understood information. For the nuclear domains, this may mean creation of Virtual Nuclear Systems, from Virtual Waste Processing Plants to Virtual Nuclear Reactors. (authors)« less
An interactive driving simulation for driver control and decision-making research
NASA Technical Reports Server (NTRS)
Allen, R. W.; Hogge, J. R.; Schwartz, S. H.
1975-01-01
Display techniques and equations of motion for a relatively simple fixed base car simulation are described. The vehicle dynamics include simplified lateral (steering) and longitudinal (speed) degrees of freedom. Several simulator tasks are described which require a combination of operator control and decision making, including response to wind gust inputs, curved roads, traffic signal lights, and obstacles. Logic circuits are used to detect speeding, running red lights, and crashes. A variety of visual and auditory cues are used to give the driver appropriate performance feedback. The simulated equations of motion are reviewed and the technique for generating the line drawing CRT roadway display is discussed. On-line measurement capabilities and experimenter control features are presented, along with previous and current research results demonstrating simulation capabilities and applications.
Optimum Aggregation and Control of Spatially Distributed Flexible Resources in Smart Grid
Bhattarai, Bishnu; Mendaza, Iker Diaz de Cerio; Myers, Kurt S.; ...
2017-03-24
This paper presents an algorithm to optimally aggregate spatially distributed flexible resources at strategic microgrid/smart-grid locations. The aggregation reduces a distribution network having thousands of nodes to an equivalent network with a few aggregated nodes, thereby enabling distribution system operators (DSOs) to make faster operational decisions. Moreover, the aggregation enables flexibility from small distributed flexible resources to be traded to different power and energy markets. A hierarchical control architecture comprising a combination of centralized and decentralized control approaches is proposed to practically deploy the aggregated flexibility. The proposed method serves as a great operational tool for DSOs to decide themore » exact amount of required flexibilities from different network section(s) for solving grid constraint violations. The effectiveness of the proposed method is demonstrated through simulation of three operational scenarios in a real low voltage distribution system having high penetrations of electric vehicles and heat pumps. Finally, the simulation results demonstrated that the aggregation helps DSOs not only in taking faster operational decisions, but also in effectively utilizing the available flexibility.« less
Optimum Aggregation and Control of Spatially Distributed Flexible Resources in Smart Grid
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bhattarai, Bishnu; Mendaza, Iker Diaz de Cerio; Myers, Kurt S.
This paper presents an algorithm to optimally aggregate spatially distributed flexible resources at strategic microgrid/smart-grid locations. The aggregation reduces a distribution network having thousands of nodes to an equivalent network with a few aggregated nodes, thereby enabling distribution system operators (DSOs) to make faster operational decisions. Moreover, the aggregation enables flexibility from small distributed flexible resources to be traded to different power and energy markets. A hierarchical control architecture comprising a combination of centralized and decentralized control approaches is proposed to practically deploy the aggregated flexibility. The proposed method serves as a great operational tool for DSOs to decide themore » exact amount of required flexibilities from different network section(s) for solving grid constraint violations. The effectiveness of the proposed method is demonstrated through simulation of three operational scenarios in a real low voltage distribution system having high penetrations of electric vehicles and heat pumps. Finally, the simulation results demonstrated that the aggregation helps DSOs not only in taking faster operational decisions, but also in effectively utilizing the available flexibility.« less
2013-06-01
realistically representing the world in a simulation environment. A screenshot of the combat model used for this research is shown below. There are six...changes in use of technology (Ryan & Jons, 1992). Cost effectiveness and operational effectiveness are important, and it is extremely hard to achieve...effectiveness of ships using simulation and analytical models, to create a ship synthesis model, and most importantly, to develop decision making tools
Computer simulation of a single pilot flying a modern high-performance helicopter
NASA Technical Reports Server (NTRS)
Zipf, Mark E.; Vogt, William G.; Mickle, Marlin H.; Hoelzeman, Ronald G.; Kai, Fei; Mihaloew, James R.
1988-01-01
Presented is a computer simulation of a human response pilot model able to execute operational flight maneuvers and vehicle stabilization of a modern high-performance helicopter. Low-order, single-variable, human response mechanisms, integrated to form a multivariable pilot structure, provide a comprehensive operational control over the vehicle. Evaluations of the integrated pilot were performed by direct insertion into a nonlinear, total-force simulation environment provided by NASA Lewis. Comparisons between the integrated pilot structure and single-variable pilot mechanisms are presented. Static and dynamically alterable configurations of the pilot structure are introduced to simulate pilot activities during vehicle maneuvers. These configurations, in conjunction with higher level, decision-making processes, are considered for use where guidance and navigational procedures, operational mode transfers, and resource sharing are required.
A Description of the DoD Test and Evaluation Process for Electronic Warfare Systems
1994-06-13
Center J-MASS Joint Modeling and Simulation System A-2 MDA Milestone Decision Authority MNS Mission Need Statement MOE Measument of Effectivenes MOP...PSYCHOLOGICAL OPERATIONS (PSYOP) Planned operations to convey selected information and indicators to foreign audiences to influence their emotions, motive
Ground and Range Operations for a Heavy-Lift Vehicle: Preliminary Thoughts
NASA Technical Reports Server (NTRS)
Rabelo, Luis; Zhu, Yanshen; Compton, Jeppie; Bardina, Jorge
2011-01-01
This paper discusses the ground and range operations for a Shuttle derived Heavy-Lift Vehicle being launched from the Kennedy Space Center on the Eastern range. Comparisons will be made between the Shuttle and a heavy lift configuration (SLS-ETF MPCV April 2011) by contrasting their subsystems. The analysis will also describe a simulation configuration with the potential to be utilized for heavy lift vehicle processing/range simulation modeling and the development of decision-making systems utilized by the range. In addition, a simple simulation model is used to provide the required critical thinking foundations for this preliminary analysis.
Automated Interactive Simulation Model (AISIM) VAX Version 5.0 Training Manual.
1987-05-29
action, activity, decision , etc. that consumes time. The entity is automatically created by the system when an ACTION Primitive is placed. 1.3.2.4 The...MODELED SYSTEM 1.3.2.1 The Process Entity. A Process is used to represent the operations, decisions , actions or activities that can be decomposed and...is associated with the Action entity described below, is included in Process definitions to indicate the time a certain Action (or process, decision
Skrivanek, Zachary; Berry, Scott; Berry, Don; Chien, Jenny; Geiger, Mary Jane; Anderson, James H.; Gaydos, Brenda
2012-01-01
Background Dulaglutide (dula, LY2189265), a long-acting glucagon-like peptide-1 analog, is being developed to treat type 2 diabetes mellitus. Methods To foster the development of dula, we designed a two-stage adaptive, dose-finding, inferentially seamless phase 2/3 study. The Bayesian theoretical framework is used to adaptively randomize patients in stage 1 to 7 dula doses and, at the decision point, to either stop for futility or to select up to 2 dula doses for stage 2. After dose selection, patients continue to be randomized to the selected dula doses or comparator arms. Data from patients assigned the selected doses will be pooled across both stages and analyzed with an analysis of covariance model, using baseline hemoglobin A1c and country as covariates. The operating characteristics of the trial were assessed by extensive simulation studies. Results Simulations demonstrated that the adaptive design would identify the correct doses 88% of the time, compared to as low as 6% for a fixed-dose design (the latter value based on frequentist decision rules analogous to the Bayesian decision rules for adaptive design). Conclusions This article discusses the decision rules used to select the dula dose(s); the mathematical details of the adaptive algorithm—including a description of the clinical utility index used to mathematically quantify the desirability of a dose based on safety and efficacy measurements; and a description of the simulation process and results that quantify the operating characteristics of the design. PMID:23294775
Multiagent Modeling and Simulation in Human-Robot Mission Operations Work System Design
NASA Technical Reports Server (NTRS)
Sierhuis, Maarten; Clancey, William J.; Sims, Michael H.; Shafto, Michael (Technical Monitor)
2001-01-01
This paper describes a collaborative multiagent modeling and simulation approach for designing work systems. The Brahms environment is used to model mission operations for a semi-autonomous robot mission to the Moon at the work practice level. It shows the impact of human-decision making on the activities and energy consumption of a robot. A collaborative work systems design methodology is described that allows informal models, created with users and stakeholders, to be used as input to the development of formal computational models.
Information prioritization for control and automation of space operations
NASA Technical Reports Server (NTRS)
Ray, Asock; Joshi, Suresh M.; Whitney, Cynthia K.; Jow, Hong N.
1987-01-01
The applicability of a real-time information prioritization technique to the development of a decision support system for control and automation of Space Station operations is considered. The steps involved in the technique are described, including the definition of abnormal scenarios and of attributes, measures of individual attributes, formulation and optimization of a cost function, simulation of test cases on the basis of the cost function, and examination of the simulation scenerios. A list is given comparing the intrinsic importances of various Space Station information data.
Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model
2016-01-01
The omnipresent need for optimisation requires constant improvements of companies’ business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and “what-if” scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results. PMID:26871694
Simulation-optimization model for production planning in the blood supply chain.
Osorio, Andres F; Brailsford, Sally C; Smith, Honora K; Forero-Matiz, Sonia P; Camacho-Rodríguez, Bernardo A
2017-12-01
Production planning in the blood supply chain is a challenging task. Many complex factors such as uncertain supply and demand, blood group proportions, shelf life constraints and different collection and production methods have to be taken into account, and thus advanced methodologies are required for decision making. This paper presents an integrated simulation-optimization model to support both strategic and operational decisions in production planning. Discrete-event simulation is used to represent the flows through the supply chain, incorporating collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling planning horizon is used to support daily decisions, such as the required number of donors, collection methods and production planning. This approach is evaluated using real data from a blood center in Colombia. The results show that, using the proposed model, key indicators such as shortages, outdated units, donors required and cost are improved.
David C. Calkin; Mark A. Finney; Alan A. Ager; Matthew P. Thompson; Krista M. Gebert
2011-01-01
In this paper we review progress towards the implementation of a riskmanagement framework for US federal wildland fire policy and operations. We first describe new developments in wildfire simulation technology that catalyzed the development of risk-based decision support systems for strategic wildfire management. These systems include new analytical methods to measure...
Advanced Productivity Analysis Methods for Air Traffic Control Operations
1976-12-01
Routine Work ............................... 37 4.2.2. Surveillance Work .......................... 40 4.2.3. Conflict Prcessing Work ................... 41...crossing and overtake conflicts) includes potential- conflict recognition, assessment, and resolution decision making and A/N voice communications...makers to utilize £ .quantitative and dynamic analysis as a tool for decision - making. 1.1.3 Types of Simulation Models Although there are many ways to
InterSpread Plus: a spatial and stochastic simulation model of disease in animal populations.
Stevenson, M A; Sanson, R L; Stern, M W; O'Leary, B D; Sujau, M; Moles-Benfell, N; Morris, R S
2013-04-01
We describe the spatially explicit, stochastic simulation model of disease spread, InterSpread Plus, in terms of its epidemiological framework, operation, and mode of use. The input data required by the model, the method for simulating contact and infection spread, and methods for simulating disease control measures are described. Data and parameters that are essential for disease simulation modelling using InterSpread Plus are distinguished from those that are non-essential, and it is suggested that a rational approach to simulating disease epidemics using this tool is to start with core data and parameters, adding additional layers of complexity if and when the specific requirements of the simulation exercise require it. We recommend that simulation models of disease are best developed as part of epidemic contingency planning so decision makers are familiar with model outputs and assumptions and are well-positioned to evaluate their strengths and weaknesses to make informed decisions in times of crisis. Copyright © 2012 Elsevier B.V. All rights reserved.
An Evolutionary Complex Systems Decision-Support Tool for the Management of Operations
NASA Astrophysics Data System (ADS)
Baldwin, J. S.; Allen, P. M.; Ridgway, K.
2011-12-01
This research aimed to add both to the development of complex systems thinking in the subject area of Operations and Production Management and to the limited number of applications of computational models and simulations from the science of complex systems. The latter potentially offer helpful decision-support tools for operations and production managers. A mechanical engineering firm was used as a case study where a combined qualitative and quantitative methodological approach was employed to extract the required data from four senior managers. Company performance measures as well as firm technologies, practices and policies, and their relation and interaction with one another, were elicited. The data were subjected to an evolutionary complex systems model resulting in a series of simulations. The findings included both reassuring and some unexpected results. The simulation based on the CEO's opinions led the most cohesive and synergistic collection of practices describing the firm, closely followed by the Marketing and R&D Managers. The Manufacturing Manager's responses led to the most extreme evolutionary trajectory where the integrity of the entire firm came into question particularly when considering how employees were utilised. By drawing directly from the opinions and views of managers rather than from logical 'if-then' rules and averaged mathematical representations of agents that characterise agent-based and other self-organisational models, this work builds on previous applications by capturing a micro-level description of diversity and a learning effect that has been problematical not only in terms of theory but also in application. This approach can be used as a decision-support tool for operations and other managers providing a forum with which to explore a) the strengths, weaknesses and consequences of different decision-making capacities within the firm; b) the introduction of new manufacturing technologies, practices and policies; and, c) the different evolutionary trajectories that a firm can take.
Desktop microsimulation: a tool to improve efficiency in the medical office practice.
Montgomery, James B; Linville, Beth A; Slonim, Anthony D
2013-01-01
Because the economic crisis in the United States continues to have an impact on healthcare organizations, industry leaders must optimize their decision making. Discrete-event computer simulation is a quality tool with a demonstrated track record of improving the precision of analysis for process redesign. However, the use of simulation to consolidate practices and design efficiencies into an unfinished medical office building was a unique task. A discrete-event computer simulation package was used to model the operations and forecast future results for four orthopedic surgery practices. The scenarios were created to allow an evaluation of the impact of process change on the output variables of exam room utilization, patient queue size, and staff utilization. The model helped with decisions regarding space allocation and efficient exam room use by demonstrating the impact of process changes in patient queues at check-in/out, x-ray, and cast room locations when compared to the status quo model. The analysis impacted decisions on facility layout, patient flow, and staff functions in this newly consolidated practice. Simulation was found to be a useful tool for process redesign and decision making even prior to building occupancy. © 2011 National Association for Healthcare Quality.
A Cryogenic Fluid System Simulation in Support of Integrated Systems Health Management
NASA Technical Reports Server (NTRS)
Barber, John P.; Johnston, Kyle B.; Daigle, Matthew
2013-01-01
Simulations serve as important tools throughout the design and operation of engineering systems. In the context of sys-tems health management, simulations serve many uses. For one, the underlying physical models can be used by model-based health management tools to develop diagnostic and prognostic models. These simulations should incorporate both nominal and faulty behavior with the ability to inject various faults into the system. Such simulations can there-fore be used for operator training, for both nominal and faulty situations, as well as for developing and prototyping health management algorithms. In this paper, we describe a methodology for building such simulations. We discuss the design decisions and tools used to build a simulation of a cryogenic fluid test bed, and how it serves as a core technology for systems health management development and maturation.
Spot and Runway Departure Advisor
NASA Technical Reports Server (NTRS)
Jung, Yoon Chul
2013-01-01
The Spot and Runway Departure Advisor (SARDA) is a research prototype of a decision support tool for ATC tower controllers to assist in manging and controlling traffic on the surface of an airport. SARDA employs a scheduler to generate an optimal runway schedule and gate push-back - spot release sequence and schedule that improves efficiency of surface operations. The advisories for ATC tower controllers are displayed on an Electronic Flight Strip (EFS) system. The human-in-the-loop simulation of the SARDA tool was conducted for east operations of Dallas-Ft. Worth International Airport (DFW) to evaluate performance of the SARDA tool and human factors, such as situational awareness and workload. The results indicates noticeable taxi delay reduction and fuel savings by using the SARDA tool. Reduction in controller workload were also observed throughout the scenario runs. The future plan includes modeling and simulation of the ramp operations of the Charlotte International Airport, and develop a decision support tool for the ramp controllers.
Integration of Dynamic Models in Range Operations
NASA Technical Reports Server (NTRS)
Bardina, Jorge; Thirumalainambi, Rajkumar
2004-01-01
This work addresses the various model interactions in real-time to make an efficient internet based decision making tool for Shuttle launch. The decision making tool depends on the launch commit criteria coupled with physical models. Dynamic interaction between a wide variety of simulation applications and techniques, embedded algorithms, and data visualizations are needed to exploit the full potential of modeling and simulation. This paper also discusses in depth details of web based 3-D graphics and applications to range safety. The advantages of this dynamic model integration are secure accessibility and distribution of real time information to other NASA centers.
1978-07-24
will include an implicit air function that will perform the air planning and requesting associated with the various headquarters. The decision structure...air headquarters (The ATAF/TAA) will be included in the CIC to perform the implementation of the decisions /goals of the C21 elements, 1-4...realistic fashion. Once the AMPs have been formed, the operational process of launching, mission implementation etc. is no longer keyed to the decision cycle
Investigation of roughing machining simulation by using visual basic programming in NX CAM system
NASA Astrophysics Data System (ADS)
Hafiz Mohamad, Mohamad; Nafis Osman Zahid, Muhammed
2018-03-01
This paper outlines a simulation study to investigate the characteristic of roughing machining simulation in 4th axis milling processes by utilizing visual basic programming in NX CAM systems. The selection and optimization of cutting orientation in rough milling operation is critical in 4th axis machining. The main purpose of roughing operation is to approximately shape the machined parts into finished form by removing the bulk of material from workpieces. In this paper, the simulations are executed by manipulating a set of different cutting orientation to generate estimated volume removed from the machine parts. The cutting orientation with high volume removal is denoted as an optimum value and chosen to execute a roughing operation. In order to run the simulation, customized software is developed to assist the routines. Operations build-up instructions in NX CAM interface are translated into programming codes via advanced tool available in the Visual Basic Studio. The codes is customized and equipped with decision making tools to run and control the simulations. It permits the integration with any independent program files to execute specific operations. This paper aims to discuss about the simulation program and identifies optimum cutting orientations for roughing processes. The output of this study will broaden up the simulation routines performed in NX CAM systems.
NASA Astrophysics Data System (ADS)
Zwink, A. B.; Morris, D.; Ware, P. J.; Ernst, S.; Holcomb, B.; Riley, S.; Hardy, J.; Mullens, S.; Bowlan, M.; Payne, C.; Bates, A.; Williams, B.
2016-12-01
For several years, employees at the Cooperative Institute of Mesoscale Meteorological Studies at the University of Oklahoma (OU) that are affiliated with Warning Decision Training Division (WDTD) of the National Weather Service (NWS) provided training simulations to students from OU's School of Meteorology (SoM). These simulations focused on warning decision making using Dual-Pol radar data products in an AWIPS-1 environment. Building on these previous experiences, CIMMS/WDTD recently continued the collaboration with the SoM Oklahoma Weather Lab (OWL) by holding a warning decision workshop simulating a NWS Weather Forecast Office (WFO) experience. The workshop took place in the WDTD AWIPS-2 computer laboratory with 25 AWIPS-2 workstations and the WES-2 Bridge (Weather Event Simulator) software which replayed AWIPS-2 data. Using the WES-2 Bridge and the WESSL-2 (WES Scripting Language) event display, this computer lab has the state-of-the-art ability to simulate severe weather events and recreate WFO warning operations. OWL Student forecasters attending the workshop worked in teams in a multi-player simulation of the Hastings, Nebraska WFO on May 6th, 2015, where thunderstorms across the service area produced large hail, damaging winds, and multiple tornadoes. This paper will discuss the design and goals of the WDTD/OWL workshop, as well as plans for holding similar workshops in the future.
CROMAX : a crosscut-first computer simulation program to determine cutting yield
Pamela J. Giese; Jeanne D. Danielson
1983-01-01
CROMAX simulates crosscut-first, then rip operations as commonly practiced in furniture manufacture. This program calculates cutting yields from individual boards based on board size and defect location. Such information can be useful in predicting yield from various grades and grade mixes thereby allowing for better management decisions in the rough mill. The computer...
Learning Reverse Engineering and Simulation with Design Visualization
NASA Technical Reports Server (NTRS)
Hemsworth, Paul J.
2018-01-01
The Design Visualization (DV) group supports work at the Kennedy Space Center by utilizing metrology data with Computer-Aided Design (CAD) models and simulations to provide accurate visual representations that aid in decision-making. The capability to measure and simulate objects in real time helps to predict and avoid potential problems before they become expensive in addition to facilitating the planning of operations. I had the opportunity to work on existing and new models and simulations in support of DV and NASA’s Exploration Ground Systems (EGS).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shahidehpour, Mohammad
Integrating 20% or more wind energy into the system and transmitting large sums of wind energy over long distances will require a decision making capability that can handle very large scale power systems with tens of thousands of buses and lines. There is a need to explore innovative analytical and implementation solutions for continuing reliable operations with the most economical integration of additional wind energy in power systems. A number of wind integration solution paths involve the adoption of new operating policies, dynamic scheduling of wind power across interties, pooling integration services, and adopting new transmission scheduling practices. Such practicesmore » can be examined by the decision tool developed by this project. This project developed a very efficient decision tool called Wind INtegration Simulator (WINS) and applied WINS to facilitate wind energy integration studies. WINS focused on augmenting the existing power utility capabilities to support collaborative planning, analysis, and wind integration project implementations. WINS also had the capability of simulating energy storage facilities so that feasibility studies of integrated wind energy system applications can be performed for systems with high wind energy penetrations. The development of WINS represents a major expansion of a very efficient decision tool called POwer Market Simulator (POMS), which was developed by IIT and has been used extensively for power system studies for decades. Specifically, WINS provides the following superiorities; (1) An integrated framework is included in WINS for the comprehensive modeling of DC transmission configurations, including mono-pole, bi-pole, tri-pole, back-to-back, and multi-terminal connection, as well as AC/DC converter models including current source converters (CSC) and voltage source converters (VSC); (2) An existing shortcoming of traditional decision tools for wind integration is the limited availability of user interface, i.e., decision results are often text-based demonstrations. WINS includes a powerful visualization tool and user interface capability for transmission analyses, planning, and assessment, which will be of great interest to power market participants, power system planners and operators, and state and federal regulatory entities; and (3) WINS can handle extended transmission models for wind integration studies. WINS models include limitations on transmission flow as well as bus voltage for analyzing power system states. The existing decision tools often consider transmission flow constraints (dc power flow) alone which could result in the over-utilization of existing resources when analyzing wind integration. WINS can be used to assist power market participants including transmission companies, independent system operators, power system operators in vertically integrated utilities, wind energy developers, and regulatory agencies to analyze economics, security, and reliability of various options for wind integration including transmission upgrades and the planning of new transmission facilities. WINS can also be used by industry for the offline training of reliability and operation personnel when analyzing wind integration uncertainties, identifying critical spots in power system operation, analyzing power system vulnerabilities, and providing credible decisions for examining operation and planning options for wind integration. Researches in this project on wind integration included (1) Development of WINS; (2) Transmission Congestion Analysis in the Eastern Interconnection; (3) Analysis of 2030 Large-Scale Wind Energy Integration in the Eastern Interconnection; (4) Large-scale Analysis of 2018 Wind Energy Integration in the Eastern U.S. Interconnection. The research resulted in 33 papers, 9 presentations, 9 PhD degrees, 4 MS degrees, and 7 awards. The education activities in this project on wind energy included (1) Wind Energy Training Facility Development; (2) Wind Energy Course Development.« less
A decision model for planetary missions
NASA Technical Reports Server (NTRS)
Hazelrigg, G. A., Jr.; Brigadier, W. L.
1976-01-01
Many techniques developed for the solution of problems in economics and operations research are directly applicable to problems involving engineering trade-offs. This paper investigates the use of utility theory for decision making in planetary exploration space missions. A decision model is derived that accounts for the objectives of the mission - science - the cost of flying the mission and the risk of mission failure. A simulation methodology for obtaining the probability distribution of science value and costs as a function spacecraft and mission design is presented and an example application of the decision methodology is given for various potential alternatives in a comet Encke mission.
Decision Aids for Airborne Intercept Operations in Advanced Aircrafts
NASA Technical Reports Server (NTRS)
Madni, A.; Freedy, A.
1981-01-01
A tactical decision aid (TDA) for the F-14 aircrew, i.e., the naval flight officer and pilot, in conducting a multitarget attack during the performance of a Combat Air Patrol (CAP) role is presented. The TDA employs hierarchical multiattribute utility models for characterizing mission objectives in operationally measurable terms, rule based AI-models for tactical posture selection, and fast time simulation for maneuver consequence prediction. The TDA makes aspect maneuver recommendations, selects and displays the optimum mission posture, evaluates attackable and potentially attackable subsets, and recommends the 'best' attackable subset along with the required course perturbation.
A Simulation Testbed for Airborne Merging and Spacing
NASA Technical Reports Server (NTRS)
Santos, Michel; Manikonda, Vikram; Feinberg, Art; Lohr, Gary
2008-01-01
The key innovation in this effort is the development of a simulation testbed for airborne merging and spacing (AM&S). We focus on concepts related to airports with Super Dense Operations where new airport runway configurations (e.g. parallel runways), sequencing, merging, and spacing are some of the concepts considered. We focus on modeling and simulating a complementary airborne and ground system for AM&S to increase efficiency and capacity of these high density terminal areas. From a ground systems perspective, a scheduling decision support tool generates arrival sequences and spacing requirements that are fed to the AM&S system operating on the flight deck. We enhanced NASA's Airspace Concept Evaluation Systems (ACES) software to model and simulate AM&S concepts and algorithms.
A Bayesian model averaging method for the derivation of reservoir operating rules
NASA Astrophysics Data System (ADS)
Zhang, Jingwen; Liu, Pan; Wang, Hao; Lei, Xiaohui; Zhou, Yanlai
2015-09-01
Because the intrinsic dynamics among optimal decision making, inflow processes and reservoir characteristics are complex, functional forms of reservoir operating rules are always determined subjectively. As a result, the uncertainty of selecting form and/or model involved in reservoir operating rules must be analyzed and evaluated. In this study, we analyze the uncertainty of reservoir operating rules using the Bayesian model averaging (BMA) model. Three popular operating rules, namely piecewise linear regression, surface fitting and a least-squares support vector machine, are established based on the optimal deterministic reservoir operation. These individual models provide three-member decisions for the BMA combination, enabling the 90% release interval to be estimated by the Markov Chain Monte Carlo simulation. A case study of China's the Baise reservoir shows that: (1) the optimal deterministic reservoir operation, superior to any reservoir operating rules, is used as the samples to derive the rules; (2) the least-squares support vector machine model is more effective than both piecewise linear regression and surface fitting; (3) BMA outperforms any individual model of operating rules based on the optimal trajectories. It is revealed that the proposed model can reduce the uncertainty of operating rules, which is of great potential benefit in evaluating the confidence interval of decisions.
M.E.T.R.O.-Apex Gaming Simulation, Volume 28 (OS/360 Version).
ERIC Educational Resources Information Center
Michigan Univ., Ann Arbor. Environmental Simulation Lab.
Operator's instructions and technical support materials needed for processing the M.E.T.R.O.-APEX (Air Pollution Exercise) game decisions on an IBM 360 computer are compiled in this volume. M.E.T.R.O.-APEX is a computerized college and professional level "real world" simulation of a community with urban and rural problems, industrial activities,…
2009-09-01
69 VI. CONCLUSIONS AND RECOMMENDATIONS ........................73 A. CONCLUSION ........................................73 1. Benefits of Off...simulation software results and similar results produced from the thesis work conducted by Ozdemir (2009). This study directly benefits decision makers...interested in identifying and benefiting from a cost- effective, readily available aggregated learning tool, with the potential to provide tactical
Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques
NASA Technical Reports Server (NTRS)
Lee, Hanbong
2016-01-01
Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.
NASA Astrophysics Data System (ADS)
Okamoto, Taro; Taniguchi, Eiichi; Yamada, Tadashi
In Japan, the network of urban expressway has been expanding with the development of urban areas. However, the patrol systems in the urban expressway has not been operated on the basis of scientific evidence, but of conformity and experience. It is therefore crucial to efficiently operate such systems, not only to facilitate the rapid recovery of decreased expressway functionality, but also to acquire the income that supports the operation of privatized expressway companies. Therefore, we develop a multiagent simulation model consisting of the decision-making of four agents, including expressway company, highway patol company, road network users and road authority. These agents determines their schemes depending on their profit obtained. Results of the simulation identyfies the schemes that could offer the profits to the expressway companies in terms of the convenience of the users and the improvement of their operation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Radojcic, Riko; Nowak, Matt; Nakamoto, Mark
The status of the development of a Design-for-Stress simulation flow that captures the stress effects in packaged 3D-stacked Si products like integrated circuits (ICs) using advanced via-middle Through Si Via technology is outlined. The next set of challenges required to proliferate the methodology and to deploy it for making and dispositioning real Si product decisions are described here. These include the adoption and support of a Process Design Kit (PDK) that includes the relevant material properties, the development of stress simulation methodologies that operate at higher levels of abstraction in a design flow, and the development and adoption of suitablemore » models required to make real product reliability decisions.« less
NASA Technical Reports Server (NTRS)
Entin, Elliot E.; Kerrigan, Caroline; Serfaty, Daniel; Young, Philip
1998-01-01
The goals of this project were to identify and investigate aspects of team and individual decision-making and risk-taking behaviors hypothesized to be most affected by prolonged isolation. A key premise driving our research approach is that effects of stressors that impact individual and team cognitive processes in an isolated, confined, and hazardous environment will be projected onto the performance of a simulation task. To elicit and investigate these team behaviors we developed a search and rescue task concept as a scenario domain that would be relevant for isolated crews. We modified the Distributed Dynamic Decision-making (DDD) simulator, a platform that has been extensively used for empirical research in team processes and taskwork performance, to portray the features of a search and rescue scenario and present the task components incorporated into that scenario. The resulting software is called DD-Search and Rescue (Version 1.0). To support the use of the DDD-Search and Rescue simulator in isolated experiment settings, we wrote a player's manual for teaching team members to operate the simulator and play the scenario. We then developed a research design and experiment plan that would allow quantitative measures of individual and team decision making skills using the DDD-Search and Rescue simulator as the experiment platform. A description of these activities and the associated materials that were produced under this contract are contained in this report.
Palpation Simulator of Beating Aorta for Cardiovascular Surgery Training
NASA Astrophysics Data System (ADS)
Yamamoto, Yasuhiro; Nakao, Megumi; Kuroda, Tomohiro; Oyama, Hiroshi; Komori, Masaru; Matsuda, Tetsuya; Sakaguchi, Genichi; Komeda, Masashi; Takahashi, Takashi
In field of cardiovascular surgeries, palpation of aorta plays important roles in decision of surgical site.This paper develops palpation simulator of aorta based on a finite element based physical model.The proposed model calculates soft tissue deformation according to the affection of inner pressure and the operation of a surgeon.The proposed method is implemented on a prototype with dual PHANToM device.Experimental results confirmed our model achieves real time simulation of the surgical palpation.
Moral imagination: Facilitating prosocial decision-making through scene imagery and theory of mind.
Gaesser, Brendan; Keeler, Kerri; Young, Liane
2018-02-01
How we imagine and subjectively experience the future can inform how we make decisions in the present. Here, we examined a prosocial effect of imagining future episodes in motivating moral decisions about helping others in need, as well as the underlying cognitive mechanisms. Across three experiments we found that people are more willing to help others in specific situations after imagining helping them in those situations. Manipulating the spatial representation of imagined future episodes in particular was effective at increasing intentions to help others, suggesting that scene imagery plays an important role in the prosocial effect of episodic simulation. Path modeling analyses revealed that episodic simulation interacts with theory of mind in facilitating prosocial responses but can also operate independently. Moreover, we found that our manipulations of the imagined helping episode increased actual prosocial behavior, which also correlated with changes in reported willingness to help. Based on these findings, we propose a new model that begins to capture the multifaceted mechanisms by which episodic simulation contributes to prosocial decision-making, highlighting boundaries and promising future directions to explore. Implications for research in moral cognition, imagination, and patients with impairments in episodic simulation are discussed. Copyright © 2017 Elsevier B.V. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cormier, Dallas; Edra, Sherwin; Espinoza, Michael
This project will enable utilities to develop long-term strategic plans that integrate high levels of renewable energy generation, and to better plan power system operations under high renewable penetration. The program developed forecast data streams for decision support and effective integration of centralized and distributed solar power generation in utility operations. This toolset focused on real time simulation of distributed power generation within utility grids with the emphasis on potential applications in day ahead (market) and real time (reliability) utility operations. The project team developed and demonstrated methodologies for quantifying the impact of distributed solar generation on core utility operations,more » identified protocols for internal data communication requirements, and worked with utility personnel to adapt the new distributed generation (DG) forecasts seamlessly within existing Load and Generation procedures through a sophisticated DMS. This project supported the objectives of the SunShot Initiative and SUNRISE by enabling core utility operations to enhance their simulation capability to analyze and prepare for the impacts of high penetrations of solar on the power grid. The impact of high penetration solar PV on utility operations is not only limited to control centers, but across many core operations. Benefits of an enhanced DMS using state-of-the-art solar forecast data were demonstrated within this project and have had an immediate direct operational cost savings for Energy Marketing for Day Ahead generation commitments, Real Time Operations, Load Forecasting (at an aggregate system level for Day Ahead), Demand Response, Long term Planning (asset management), Distribution Operations, and core ancillary services as required for balancing and reliability. This provided power system operators with the necessary tools and processes to operate the grid in a reliable manner under high renewable penetration.« less
NASA Astrophysics Data System (ADS)
Andreu, J.; Capilla, J.; Sanchís, E.
1996-04-01
This paper describes a generic decision-support system (DSS) which was originally designed for the planning stage of dicision-making associated with complex river basins. Subsequently, it was expanded to incorporate modules relating to the operational stage of decision-making. Computer-assisted design modules allow any complex water-resource system to be represented in graphical form, giving access to geographically referenced databases and knowledge bases. The modelling capability includes basin simulation and optimization modules, an aquifer flow modelling module and two modules for risk assessment. The Segura and Tagus river basins have been used as case studies in the development and validation phases. The value of this DSS is demonstrated by the fact that both River Basin Agencies currently use a version for the efficient management of their water resources.
Enhanced Handover Decision Algorithm in Heterogeneous Wireless Network
Abdullah, Radhwan Mohamed; Zukarnain, Zuriati Ahmad
2017-01-01
Transferring a huge amount of data between different network locations over the network links depends on the network’s traffic capacity and data rate. Traditionally, a mobile device may be moved to achieve the operations of vertical handover, considering only one criterion, that is the Received Signal Strength (RSS). The use of a single criterion may cause service interruption, an unbalanced network load and an inefficient vertical handover. In this paper, we propose an enhanced vertical handover decision algorithm based on multiple criteria in the heterogeneous wireless network. The algorithm consists of three technology interfaces: Long-Term Evolution (LTE), Worldwide interoperability for Microwave Access (WiMAX) and Wireless Local Area Network (WLAN). It also employs three types of vertical handover decision algorithms: equal priority, mobile priority and network priority. The simulation results illustrate that the three types of decision algorithms outperform the traditional network decision algorithm in terms of handover number probability and the handover failure probability. In addition, it is noticed that the network priority handover decision algorithm produces better results compared to the equal priority and the mobile priority handover decision algorithm. Finally, the simulation results are validated by the analytical model. PMID:28708067
Practice Options and Decision Making for Dental Students.
ERIC Educational Resources Information Center
Manski, Richard J.
1987-01-01
One dental school implemented in its fourth-year curriculum an intensive simulation exercise to teach students the application of fundamental economic concepts such as capital costs, leasehold improvements, operating expenses, working capital, and financial risk in dental practice. (MSE)
NASA Technical Reports Server (NTRS)
Chung, William W.; Ingram, Carla D.; Ahlquist, Douglas Kurt; Chachad, Girish H.
2016-01-01
"Gate Turnaround" plays a key role in the National Air Space (NAS) gate-to-gate performance by receiving aircraft when they reach their destination airport, and delivering aircraft into the NAS upon departing from the gate and subsequent takeoff. The time spent at the gate in meeting the planned departure time is influenced by many factors and often with considerable uncertainties. Uncertainties such as weather, early or late arrivals, disembarking and boarding passengers, unloading/reloading cargo, aircraft logistics/maintenance services and ground handling, traffic in ramp and movement areas for taxi-in and taxi-out, and departure queue management for takeoff are likely encountered on the daily basis. The Integrated Gate Turnaround Management (IGTM) concept is leveraging relevant historical data to support optimization of the gate operations, which include arrival, at the gate, departure based on constraints (e.g., available gates at the arrival, ground crew and equipment for the gate turnaround, and over capacity demand upon departure), and collaborative decision-making. The IGTM concept provides effective information services and decision tools to the stakeholders, such as airline dispatchers, gate agents, airport operators, ramp controllers, and air traffic control (ATC) traffic managers and ground controllers to mitigate uncertainties arising from both nominal and off-nominal airport gate operations. IGTM will provide NAS stakeholders customized decision making tools through a User Interface (UI) by leveraging historical data (Big Data), net-enabled Air Traffic Management (ATM) live data, and analytics according to dependencies among NAS parameters for the stakeholders to manage and optimize the NAS performance in the gate turnaround domain. The application will give stakeholders predictable results based on the past and current NAS performance according to selected decision trees through the UI. The predictable results are generated based on analysis of the unique airport attributes (e.g., runway, taxiway, terminal, and gate configurations and tenants), and combined statistics from past data and live data based on a specific set of ATM concept-of-operations (ConOps) and operational parameters via systems analysis using an analytic network learning model. The IGTM tool will then bound the uncertainties that arise from nominal and off-nominal operational conditions with direct assessment of the gate turnaround status and the impact of a certain operational decision on the NAS performance, and provide a set of recommended actions to optimize the NAS performance by allowing stakeholders to take mitigation actions to reduce uncertainty and time deviation of planned operational events. An IGTM prototype was developed at NASA Ames Simulation Laboratories (SimLabs) to demonstrate the benefits and applicability of the concept. A data network, using the System Wide Information Management (SWIM)-like messaging application using the ActiveMQ message service, was connected to the simulated data warehouse, scheduled flight plans, a fast-time airport simulator, and a graphic UI. A fast-time simulation was integrated with the data warehouse or Big Data/Analytics (BAI), scheduled flight plans from Aeronautical Operational Control AOC, IGTM Controller, and a UI via a SWIM-like data messaging network using the ActiveMQ message service, illustrated in Figure 1, to demonstrate selected use-cases showing the benefits of the IGTM concept on the NAS performance.
Dawe, Susan R; Windsor, John A; Broeders, Joris A J L; Cregan, Patrick C; Hewett, Peter J; Maddern, Guy J
2014-02-01
A systematic review to determine whether skills acquired through simulation-based training transfer to the operating room for the procedures of laparoscopic cholecystectomy and endoscopy. Simulation-based training assumes that skills are directly transferable to the operation room, but only a few studies have investigated the effect of simulation-based training on surgical performance. A systematic search strategy that was used in 2006 was updated to retrieve relevant studies. Inclusion of articles was determined using a predetermined protocol, independent assessment by 2 reviewers, and a final consensus decision. Seventeen randomized controlled trials and 3 nonrandomized comparative studies were included in this review. In most cases, simulation-based training was in addition to patient-based training programs. Only 2 studies directly compared simulation-based training in isolation with patient-based training. For laparoscopic cholecystectomy (n = 10 studies) and endoscopy (n = 10 studies), participants who reached simulation-based skills proficiency before undergoing patient-based assessment performed with higher global assessment scores and fewer errors in the operating room than their counterparts who did not receive simulation training. Not all parameters measured were improved. Two of the endoscopic studies compared simulation-based training in isolation with patient-based training with different results: for sigmoidoscopy, patient-based training was more effective, whereas for colonoscopy, simulation-based training was equally effective. Skills acquired by simulation-based training seem to be transferable to the operative setting for laparoscopic cholecystectomy and endoscopy. Future research will strengthen these conclusions by evaluating predetermined competency levels on the same simulators and using objective validated global rating scales to measure operative performance.
Bringing simulation to engineers in the field: a Web 2.0 approach.
Haines, Robert; Khan, Kashif; Brooke, John
2009-07-13
Field engineers working on water distribution systems have to implement day-to-day operational decisions. Since pipe networks are highly interconnected, the effects of such decisions are correlated with hydraulic and water quality conditions elsewhere in the network. This makes the provision of predictive decision support tools (DSTs) for field engineers critical to optimizing the engineering work on the network. We describe how we created DSTs to run on lightweight mobile devices by using the Web 2.0 technique known as Software as a Service. We designed our system following the architectural style of representational state transfer. The system not only displays static geographical information system data for pipe networks, but also dynamic information and prediction of network state, by invoking and displaying the results of simulations running on more powerful remote resources.
NASA Technical Reports Server (NTRS)
Phillips, Dave; Haas, William; Barth, Tim; Benjamin, Perakath; Graul, Michael; Bagatourova, Olga
2005-01-01
Range Process Simulation Tool (RPST) is a computer program that assists managers in rapidly predicting and quantitatively assessing the operational effects of proposed technological additions to, and/or upgrades of, complex facilities and engineering systems such as the Eastern Test Range. Originally designed for application to space transportation systems, RPST is also suitable for assessing effects of proposed changes in industrial facilities and large organizations. RPST follows a model-based approach that includes finite-capacity schedule analysis and discrete-event process simulation. A component-based, scalable, open architecture makes RPST easily and rapidly tailorable for diverse applications. Specific RPST functions include: (1) definition of analysis objectives and performance metrics; (2) selection of process templates from a processtemplate library; (3) configuration of process models for detailed simulation and schedule analysis; (4) design of operations- analysis experiments; (5) schedule and simulation-based process analysis; and (6) optimization of performance by use of genetic algorithms and simulated annealing. The main benefits afforded by RPST are provision of information that can be used to reduce costs of operation and maintenance, and the capability for affordable, accurate, and reliable prediction and exploration of the consequences of many alternative proposed decisions.
NASA Technical Reports Server (NTRS)
1973-01-01
Ways in which human intelligence might be simulated onboard an unmanned mission to achieve some of the decision making capability or adaptability of the manned mission are examined. The relative cost and simplicity advantages of the unmanned spacecraft missions are emphasized. Reliable techniques for making onboard decisions and for modifying mission science operations in response to the findings are analyzed.
NASA Astrophysics Data System (ADS)
Clark, P. E.; Rilee, M. L.; Curtis, S. A.; Bailin, S.
2012-03-01
We are developing Frontier, a highly adaptable, stably reconfigurable, web-accessible intelligent decision engine capable of optimizing design as well as the simulating operation of complex systems in response to evolving needs and environment.
Hemmerich, Joshua A; Elstein, Arthur S; Schwarze, Margaret L; Moliski, Elizabeth G; Dale, William
2013-01-01
The present study tested predictions derived from the Risk as Feelings hypothesis about the effects of prior patients' negative treatment outcomes on physicians' subsequent treatment decisions. Two experiments at The University of Chicago, U.S.A., utilized a computer simulation of an abdominal aortic aneurysm (AAA) patient with enhanced realism to present participants with one of three experimental conditions: AAA rupture causing a watchful waiting death (WWD), perioperative death (PD), or a successful operation (SO), as well as the statistical treatment guidelines for AAA. Experiment 1 tested effects of these simulated outcomes on (n=76) laboratory participants' (university student sample) self-reported emotions, and their ratings of valence and arousal of the AAA rupture simulation and other emotion inducing picture stimuli. Experiment 2 tested two hypotheses: 1) that experiencing a patient WWD in the practice trial's experimental condition would lead physicians to choose surgery earlier, and 2) experiencing a patient PD would lead physicians to choose surgery later with the next patient. Experiment 2 presented (n=132) physicians (surgeons and geriatricians) with the same experimental manipulation and a second simulated AAA patient. Physicians then chose to either go to surgery or continue watchful waiting. The results of Experiment 1 demonstrated that the WWD experimental condition significantly increased anxiety, and was rated similarly to other negative and arousing pictures. The results of Experiment 2 demonstrated that, after controlling for demographics, baseline anxiety, intolerance for uncertainty, risk attitudes, and the influence of simulation characteristics, the WWD experimental condition significantly expedited decisions to choose surgery for the next patient. The results support the Risk as Feelings hypothesis on physicians' treatment decisions in a realistic AAA patient computer simulation. Bad outcomes affected emotions and decisions, even with statistical AAA rupture risk guidance present. These results suggest that bad patient outcomes cause physicians to experience anxiety and regret that influences their subsequent treatment decision-making for the next patient. PMID:22571890
Hemmerich, Joshua A; Elstein, Arthur S; Schwarze, Margaret L; Moliski, Elizabeth Ghini; Dale, William
2012-07-01
The present study tested predictions derived from the Risk as Feelings hypothesis about the effects of prior patients' negative treatment outcomes on physicians' subsequent treatment decisions. Two experiments at The University of Chicago, U.S.A., utilized a computer simulation of an abdominal aortic aneurysm (AAA) patient with enhanced realism to present participants with one of three experimental conditions: AAA rupture causing a watchful waiting death (WWD), perioperative death (PD), or a successful operation (SO), as well as the statistical treatment guidelines for AAA. Experiment 1 tested effects of these simulated outcomes on (n = 76) laboratory participants' (university student sample) self-reported emotions, and their ratings of valence and arousal of the AAA rupture simulation and other emotion-inducing picture stimuli. Experiment 2 tested two hypotheses: 1) that experiencing a patient WWD in the practice trial's experimental condition would lead physicians to choose surgery earlier, and 2) experiencing a patient PD would lead physicians to choose surgery later with the next patient. Experiment 2 presented (n = 132) physicians (surgeons and geriatricians) with the same experimental manipulation and a second simulated AAA patient. Physicians then chose to either go to surgery or continue watchful waiting. The results of Experiment 1 demonstrated that the WWD experimental condition significantly increased anxiety, and was rated similarly to other negative and arousing pictures. The results of Experiment 2 demonstrated that, after controlling for demographics, baseline anxiety, intolerance for uncertainty, risk attitudes, and the influence of simulation characteristics, the WWD experimental condition significantly expedited decisions to choose surgery for the next patient. The results support the Risk as Feelings hypothesis on physicians' treatment decisions in a realistic AAA patient computer simulation. Bad outcomes affected emotions and decisions, even with statistical AAA rupture risk guidance present. These results suggest that bad patient outcomes cause physicians to experience anxiety and regret that influences their subsequent treatment decision-making for the next patient. Copyright © 2012 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Utama, D. N.; Triana, Y. S.; Iqbal, M. M.; Iksal, M.; Fikri, I.; Dharmawan, T.
2018-03-01
Mosque, for Muslim, is not only a place for daily worshipping, however as a center of culture as well. It is an important and valuable building to be well managed. For a responsible department or institution (such as Religion or Plan Department in Indonesia), to practically manage a lot of mosques is not simple task to handle. The challenge is in relation to data number and characteristic problems tackled. Specifically for renovating and rehabilitating the damaged mosques, a decision to determine the first damaged mosque priority to be renovated and rehabilitated is problematic. Through two types of optimization method, simulated-annealing and hill-climbing, a decision support model for mosque renovation and rehabilitation was systematically constructed. The method fuzzy-logic was also operated to establish the priority of eleven selected parameters. The constructed model is able to simulate an efficiency comparison between two optimization methods used and suggest the most objective decision coming from 196 generated alternatives.
NASA Astrophysics Data System (ADS)
Macian-Sorribes, Hector; Pulido-Velazquez, Manuel
2013-04-01
Water resources systems are operated, mostly, using a set of pre-defined rules not regarding, usually, to an optimal allocation in terms of water use or economic benefits, but to historical and institutional reasons. These operating policies are reproduced, commonly, as hedging rules, pack rules or zone-based operations, and simulation models can be used to test their performance under a wide range of hydrological and/or socio-economic hypothesis. Despite the high degree of acceptation and testing that these models have achieved, the actual operation of water resources systems hardly follows all the time the pre-defined rules with the consequent uncertainty on the system performance. Real-world reservoir operation is very complex, affected by input uncertainty (imprecision in forecast inflow, seepage and evaporation losses, etc.), filtered by the reservoir operator's experience and natural risk-aversion, while considering the different physical and legal/institutional constraints in order to meet the different demands and system requirements. The aim of this work is to expose a fuzzy logic approach to derive and assess the historical operation of a system. This framework uses a fuzzy rule-based system to reproduce pre-defined rules and also to match as close as possible the actual decisions made by managers. After built up, the fuzzy rule-based system can be integrated in a water resources management model, making possible to assess the system performance at the basin scale. The case study of the Mijares basin (eastern Spain) is used to illustrate the method. A reservoir operating curve regulates the two main reservoir releases (operated in a conjunctive way) with the purpose of guaranteeing a high realiability of supply to the traditional irrigation districts with higher priority (more senior demands that funded the reservoir construction). A fuzzy rule-based system has been created to reproduce the operating curve's performance, defining the system state (total water stored in the reservoirs) and the month of the year as inputs; and the demand deliveries as outputs. The developed simulation management model integrates the fuzzy-ruled system of the operation of the two main reservoirs of the basin with the corresponding mass balance equations, the physical or boundary conditions and the water allocation rules among the competing demands. Historical information on inflow time series is used as inputs to the model simulation, being trained and validated using historical information on reservoir storage level and flow in several streams of the Mijares river. This methodology provides a more flexible and close to real policies approach. The model is easy to develop and to understand due to its rule-based structure, which mimics the human way of thinking. This can improve cooperation and negotiation between managers, decision-makers and stakeholders. The approach can be also applied to analyze the historical operation of the reservoir (what we have called a reservoir operation "audit").
Multidimensional Simulation Applied to Water Resources Management
NASA Astrophysics Data System (ADS)
Camara, A. S.; Ferreira, F. C.; Loucks, D. P.; Seixas, M. J.
1990-09-01
A framework for an integrated decision aiding simulation (IDEAS) methodology using numerical, linguistic, and pictorial entities and operations is introduced. IDEAS relies upon traditional numerical formulations, logical rules to handle linguistic entities with linguistic values, and a set of pictorial operations. Pictorial entities are defined by their shape, size, color, and position. Pictorial operators include reproduction (copy of a pictorial entity), mutation (expansion, rotation, translation, change in color), fertile encounters (intersection, reunion), and sterile encounters (absorption). Interaction between numerical, linguistic, and pictorial entities is handled through logical rules or a simplified vector calculus operation. This approach is shown to be applicable to various environmental and water resources management analyses using a model to assess the impacts of an oil spill. Future developments, including IDEAS implementation on parallel processing machines, are also discussed.
Wright, Scott A.; Grams, Paul E.
2010-01-01
This report describes numerical modeling simulations of sand transport and sand budgets for reaches of the Colorado River below Glen Canyon Dam. Two hypothetical Water Year 2011 annual release volumes were each evaluated with six hypothetical operational scenarios. The six operational scenarios include the current operation, scenarios with modifications to the monthly distribution of releases, and scenarios with modifications to daily flow fluctuations. Uncertainties in model predictions were evaluated by conducting simulations with error estimates for tributary inputs and mainstem transport rates. The modeling results illustrate the dependence of sand transport rates and sand budgets on the annual release volumes as well as the within year operating rules. The six operational scenarios were ranked with respect to the predicted annual sand budgets for Marble Canyon and eastern Grand Canyon reaches. While the actual WY 2011 annual release volume and levels of tributary inputs are unknown, the hypothetical conditions simulated and reported herein provide reasonable comparisons between the operational scenarios, in a relative sense, that may be used by decision makers within the Glen Canyon Dam Adaptive Management Program.
NASA Astrophysics Data System (ADS)
Kuo, Y.-H.; Leung, J. M. Y.; Graham, C. A.
2015-05-01
In this paper, we present a case study of modelling and analyzing the patient flow of a hospital emergency department in Hong Kong. The emergency department is facing the challenge of overcrowding and the patients there usually experience a long waiting time. Our project team was requested by a senior consultant of the emergency department to analyze the patient flow and provide a decision support tool to help improve their operations. We adopt a simulation approach to mimic their daily operations. With the simulation model, we conduct a computational study to examine the effect of physician heterogeneity on the emergency department performance. We found that physician heterogeneity has a great impact on the operational efficiency and thus should be considered when developing simulation models. Our computational results show that, with the same average of service rates among the physicians, variation in the rates can improve overcrowding situation. This suggests that emergency departments may consider having some efficient physicians to speed up the overall service rate in return for more time for patients who need extra medical care.
NASA Technical Reports Server (NTRS)
Murphy, M. R.; Awe, C. A.
1986-01-01
Six professionally active, retired captains rated the coordination and decisionmaking performances of sixteen aircrews while viewing videotapes of a simulated commercial air transport operation. The scenario featured a required diversion and a probable minimum fuel situation. Seven point Likert-type scales were used in rating variables on the basis of a model of crew coordination and decisionmaking. The variables were based on concepts of, for example, decision difficulty, efficiency, and outcome quality; and leader-subordin ate concepts such as person and task-oriented leader behavior, and competency motivation of subordinate crewmembers. Five-front-end variables of the model were in turn dependent variables for a hierarchical regression procedure. The variance in safety performance was explained 46%, by decision efficiency, command reversal, and decision quality. The variance of decision quality, an alternative substantive dependent variable to safety performance, was explained 60% by decision efficiency and the captain's quality of within-crew communications. The variance of decision efficiency, crew coordination, and command reversal were in turn explained 78%, 80%, and 60% by small numbers of preceding independent variables. A principle component, varimax factor analysis supported the model structure suggested by regression analyses.
DOT National Transportation Integrated Search
1982-06-01
In order to examine specific Automated Guideway Transit (AGT) developments and concepts, and to build a better knowledge base for future decision-making, the Urban Mass Transportation Administration (UMTA) undertook a new program of studies and techn...
Surface Traffic Management Research
NASA Technical Reports Server (NTRS)
Jung, Yoo Chul
2012-01-01
This presentation discusses an overview of the surface traffic management research conducted by NASA Ames. The concept and human-in-the-loop simulation of the Spot and Runway Departure Advisor (SARDA), an integrated decision support tool for the tower controllers and airline ramp operators, is also discussed.
Seventh symposium on systems analysis in forest resources; 1997 May 28-31; Traverse City, MI.
J. Michael Vasievich; Jeremy S. Fried; Larry A. Leefers
2000-01-01
This international symposium included presentations by representatives from government, academic, and private institutions. Topics covered management objectives; information systems: modeling, optimization, simulation and decision support techniques; spatial methods; timber supply; and economic and operational analyses.
Volk, Mark S; Ward, Jessica; Irias, Noel; Navedo, Andres; Pollart, Jennifer; Weinstock, Peter H
2011-07-01
Develop a course to use in situ high-fidelity medical simulation (HFS) in an actual operating room (OR) to (1) teach teamwork and crisis resource management (CRM) skills simultaneously to otolaryngology and anesthesia trainees and OR nurses and (2) provide decision-making experience to ear, nose, and throat residents and OR teams in simulated high-risk, low-frequency airway emergencies. A simulation-based, in situ CRM course was developed to teach airway management and CRM in the OR. Upon completion of each course, the participants were surveyed using questions with (1-5) scale answers. The simulated clinical scenarios took place in the intensive care unit and OR at Children's Hospital Boston. The participants consisted of pediatric otolaryngology fellows, otolaryngology residents, anesthesiology residents, fellows, and certified registered nurse anesthetists as well as OR nurses. Fifty-nine individuals participated in 9 simulation-based courses given between October 2008 and May 2010. The team members participated together in 3 simulated medical crises that centered on airway and anesthesia issues. Each simulated crisis was followed by a structured debriefing session conducted by trained debriefers. Embedded within the course were didactics on CRM principles. The participants' responses on the survey included General Course Organization, Realism, Debriefing, and Relevance to Future Practice. Ninety percent of the responses were favorable or very favorable. Using a newly developed, in situ HFS-based course, clinical decision-making skills and teamwork can be effectively taught concurrently to members of an OR team.
epiDMS: Data Management and Analytics for Decision-Making From Epidemic Spread Simulation Ensembles.
Liu, Sicong; Poccia, Silvestro; Candan, K Selçuk; Chowell, Gerardo; Sapino, Maria Luisa
2016-12-01
Carefully calibrated large-scale computational models of epidemic spread represent a powerful tool to support the decision-making process during epidemic emergencies. Epidemic models are being increasingly used for generating forecasts of the spatial-temporal progression of epidemics at different spatial scales and for assessing the likely impact of different intervention strategies. However, the management and analysis of simulation ensembles stemming from large-scale computational models pose challenges, particularly when dealing with multiple interdependent parameters, spanning multiple layers and geospatial frames, affected by complex dynamic processes operating at different resolutions. We describe and illustrate with examples a novel epidemic simulation data management system, epiDMS, that was developed to address the challenges that arise from the need to generate, search, visualize, and analyze, in a scalable manner, large volumes of epidemic simulation ensembles and observations during the progression of an epidemic. epiDMS is a publicly available system that facilitates management and analysis of large epidemic simulation ensembles. epiDMS aims to fill an important hole in decision-making during healthcare emergencies by enabling critical services with significant economic and health impact. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.
Pretel, R; Shoener, B D; Ferrer, J; Guest, J S
2015-12-15
Anaerobic membrane bioreactors (AnMBRs) enable energy recovery from wastewater while simultaneously achieving high levels of treatment. The objective of this study was to elucidate how detailed design and operational decisions of submerged AnMBRs influence the technological, environmental, and economic sustainability of the system across its life cycle. Specific design and operational decisions evaluated included: solids retention time (SRT), mixed liquor suspended solids (MLSS) concentration, sludge recycling ratio (r), flux (J), and specific gas demand per membrane area (SGD). The possibility of methane recovery (both as biogas and as soluble methane in reactor effluent) and bioenergy production, nutrient recovery, and final destination of the sludge (land application, landfill, or incineration) were also evaluated. The implications of these design and operational decisions were characterized by leveraging a quantitative sustainable design (QSD) framework which integrated steady-state performance modeling across seasonal temperatures (using pilot-scale experimental data and the simulating software DESASS), life cycle cost (LCC) analysis, and life cycle assessment (LCA). Sensitivity and uncertainty analyses were used to characterize the relative importance of individual design decisions, and to navigate trade-offs across environmental, economic, and technological criteria. Based on this analysis, there are design and operational conditions under which submerged AnMBRs could be net energy positive and contribute to the pursuit of carbon negative wastewater treatment. Copyright © 2015 Elsevier Ltd. All rights reserved.
Optimizing Disaster Relief: Real-Time Operational and Tactical Decision Support
1993-01-01
efficiencies in completing the tAsks. Allocations recognize task priorities and the logistica l effects of geographic prox- imity, In addition...as if they ar~ collocated. Arcs connect loc-•I J>airs of zones to represent feasible dTrect point-to-point transportation and bear cost> ror...data to thl.’ de >~red level of aggregation. We have tested ARES manuall)’ ;mtl by replacins tbc deci~ion maker wrlh the decision simulator which
Simulating rotational grazing management.
Cros, M J; Duru, M; Garcia, F; Martin-Clouaire, R
2001-09-01
Dairy systems predominantly based on rotational grazing are notoriously hard to manage. In order to ensure profitability, this type of production requires quite good organisation, planning, and operating capability on the part of the farmer. A simulation-based decision support system, called SEPATOU, has been developed for this purpose. At the core of the decision support approach lies an explicit and rigorous modelling of the management strategy that underlies a dairy farmer's decision-making behaviour (real or hypothetical). The SEPATOU system is a discrete-event simulator that reproduces the day-to-day dynamics of the farmer's decision process and the response of the controlled biophysical system for which models of grass growth, animal consumption, and milk production are used. SEPATOU provides the means to evaluate and compare tentative strategies by simulating their application throughout the production season under different hypothetical weather conditions. The relative worth of a strategy can be assessed by analysing the effects on the biophysical system and their variability across the representative range of possible conditions that is considered. The activities to be managed concern the type and amount of conserved feed, where to fertilise and how much, the choice of fields to harvest, and most importantly, which field to graze next. Typically, SEPATOU is designed to be used by extension services and farming system scientists. It is implemented in C++ and is currently undergoing a validation process with the intended users.
Using Computational Cognitive Modeling to Diagnose Possible Sources of Aviation Error
NASA Technical Reports Server (NTRS)
Byrne, M. D.; Kirlik, Alex
2003-01-01
We present a computational model of a closed-loop, pilot-aircraft-visual scene-taxiway system created to shed light on possible sources of taxi error. Creating the cognitive aspects of the model using ACT-R required us to conduct studies with subject matter experts to identify experiential adaptations pilots bring to taxiing. Five decision strategies were found, ranging from cognitively-intensive but precise, to fast, frugal but robust. We provide evidence for the model by comparing its behavior to a NASA Ames Research Center simulation of Chicago O'Hare surface operations. Decision horizons were highly variable; the model selected the most accurate strategy given time available. We found a signature in the simulation data of the use of globally robust heuristics to cope with short decision horizons as revealed by errors occurring most frequently at atypical taxiway geometries or clearance routes. These data provided empirical support for the model.
Configuration Management, Capacity Planning Decision Support, Modeling and Simulation
1988-12-01
flow includes both top-down and bottom-up requirements. The flow also includes hardware, software and transfer acquisition, installation, operation ... management and upgrade as required. Satisfaction of a users needs and requirements is a difficult and detailed process. The key assumptions at this
Software Tools For Building Decision-support Models For Flood Emergency Situations
NASA Astrophysics Data System (ADS)
Garrote, L.; Molina, M.; Ruiz, J. M.; Mosquera, J. C.
The SAIDA decision-support system was developed by the Spanish Ministry of the Environment to provide assistance to decision-makers during flood situations. SAIDA has been tentatively implemented in two test basins: Jucar and Guadalhorce, and the Ministry is currently planning to have it implemented in all major Spanish basins in a few years' time. During the development cycle of SAIDA, the need for providing as- sistance to end-users in model definition and calibration was clearly identified. System developers usually emphasise abstraction and generality with the goal of providing a versatile software environment. End users, on the other hand, require concretion and specificity to adapt the general model to their local basins. As decision-support models become more complex, the gap between model developers and users gets wider: Who takes care of model definition, calibration and validation?. Initially, model developers perform these tasks, but the scope is usually limited to a few small test basins. Before the model enters operational stage, end users must get involved in model construction and calibration, in order to gain confidence in the model recommendations. However, getting the users involved in these activities is a difficult task. The goal of this re- search is to develop representation techniques for simulation and management models in order to define, develop and validate a mechanism, supported by a software envi- ronment, oriented to provide assistance to the end-user in building decision models for the prediction and management of river floods in real time. The system is based on three main building blocks: A library of simulators of the physical system, an editor to assist the user in building simulation models, and a machine learning method to calibrate decision models based on the simulation models provided by the user.
Alves-Pinto, A.; Sollini, J.; Sumner, C.J.
2012-01-01
Signal detection theory (SDT) provides a framework for interpreting psychophysical experiments, separating the putative internal sensory representation and the decision process. SDT was used to analyse ferret behavioural responses in a (yes–no) tone-in-noise detection task. Instead of measuring the receiver-operating characteristic (ROC), we tested SDT by comparing responses collected using two common psychophysical data collection methods. These (Constant Stimuli, Limits) differ in the set of signal levels presented within and across behavioural sessions. The results support the use of SDT as a method of analysis: SDT sensory component was unchanged between the two methods, even though decisions depended on the stimuli presented within a behavioural session. Decision criterion varied trial-by-trial: a ‘yes’ response was more likely after a correct rejection trial than a hit trial. Simulation using an SDT model with several decision components reproduced the experimental observations accurately, leaving only ∼10% of the variance unaccounted for. The model also showed that trial-by-trial dependencies were unlikely to influence measured psychometric functions or thresholds. An additional model component suggested that inattention did not contribute substantially. Further analysis showed that ferrets were changing their decision criteria, almost optimally, to maximise the reward obtained in a session. The data suggest trial-by-trial reward-driven optimization of the decision process. Understanding the factors determining behavioural responses is important for correlating neural activity and behaviour. SDT provides a good account of animal psychoacoustics, and can be validated using standard psychophysical methods and computer simulations, without recourse to ROC measurements. PMID:22698686
Research on crude oil storage and transportation based on optimization algorithm
NASA Astrophysics Data System (ADS)
Yuan, Xuhua
2018-04-01
At present, the optimization theory and method have been widely used in the optimization scheduling and optimal operation scheme of complex production systems. Based on C++Builder 6 program development platform, the theoretical research results are implemented by computer. The simulation and intelligent decision system of crude oil storage and transportation inventory scheduling are designed. The system includes modules of project management, data management, graphics processing, simulation of oil depot operation scheme. It can realize the optimization of the scheduling scheme of crude oil storage and transportation system. A multi-point temperature measuring system for monitoring the temperature field of floating roof oil storage tank is developed. The results show that by optimizing operating parameters such as tank operating mode and temperature, the total transportation scheduling costs of the storage and transportation system can be reduced by 9.1%. Therefore, this method can realize safe and stable operation of crude oil storage and transportation system.
A cognitive prosthesis for complex decision-making.
Tremblay, Sébastien; Gagnon, Jean-François; Lafond, Daniel; Hodgetts, Helen M; Doiron, Maxime; Jeuniaux, Patrick P J M H
2017-01-01
While simple heuristics can be ecologically rational and effective in naturalistic decision making contexts, complex situations require analytical decision making strategies, hypothesis-testing and learning. Sub-optimal decision strategies - using simplified as opposed to analytic decision rules - have been reported in domains such as healthcare, military operational planning, and government policy making. We investigate the potential of a computational toolkit called "IMAGE" to improve decision-making by developing structural knowledge and increasing understanding of complex situations. IMAGE is tested within the context of a complex military convoy management task through (a) interactive simulations, and (b) visualization and knowledge representation capabilities. We assess the usefulness of two versions of IMAGE (desktop and immersive) compared to a baseline. Results suggest that the prosthesis helped analysts in making better decisions, but failed to increase their structural knowledge about the situation once the cognitive prosthesis is removed. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Adeleye, Sanya; Chung, Christopher
2006-01-01
Commercial aircraft undergo a significant number of maintenance and logistical activities during the turnaround operation at the departure gate. By analyzing the sequencing of these activities, more effective turnaround contingency plans may be developed for logistical and maintenance disruptions. Turnaround contingency plans are particularly important as any kind of delay in a hub based system may cascade into further delays with subsequent connections. The contingency sequencing of the maintenance and logistical turnaround activities were analyzed using a combined network and computer simulation modeling approach. Experimental analysis of both current and alternative policies provides a framework to aid in more effective tactical decision making.
Computer-automated opponent for manned air-to-air combat simulations
NASA Technical Reports Server (NTRS)
Hankins, W. W., III
1979-01-01
Two versions of a real-time digital-computer program that operates a fighter airplane interactively against a human pilot in simulated air combat were evaluated. They function by replacing one of two pilots in the Langley differential maneuvering simulator. Both versions make maneuvering decisions from identical information and logic; they differ essentially in the aerodynamic models that they control. One is very complete, but the other is much simpler, primarily characterizing the airplane's performance (lift, drag, and thrust). Both models competed extremely well against highly trained U.S. fighter pilots.
Evaluation of Cost Leadership Strategy in Shipping Enterprises with Simulation Model
NASA Astrophysics Data System (ADS)
Ferfeli, Maria V.; Vaxevanou, Anthi Z.; Damianos, Sakas P.
2009-08-01
The present study will attempt the evaluation of cost leadership strategy that prevails in certain shipping enterprises and the creation of simulation models based on strategic model STAIR. The above model is an alternative method of strategic applications evaluation. This is held in order to be realised if the strategy of cost leadership creates competitive advantage [1] and this will be achieved via the technical simulation which appreciates the interactions between the operations of an enterprise and the decision-making strategy in conditions of uncertainty with reduction of undertaken risk.
A negotiation methodology and its application to cogeneration planning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, S.M.; Liu, C.C.; Luu, S.
Power system planning has become a complex process in utilities today. This paper presents a methodology for integrated planning with multiple objectives. The methodology uses a graphical representation (Goal-Decision Network) to capture the planning knowledge. The planning process is viewed as a negotiation process that applies three negotiation operators to search for beneficial decisions in a GDN. Also, the negotiation framework is applied to the problem of planning for cogeneration interconnection. The simulation results are presented to illustrate the cogeneration planning process.
Cognitive Performance in Operational Environments
NASA Technical Reports Server (NTRS)
Russo, Michael; McGhee, James; Friedler, Edna; Thomas, Maria
2005-01-01
Optimal cognition during complex and sustained operations is a critical component for success in current and future military operations. "Cognitive Performance, Judgment, and Decision-making" (CPJD) is a newly organized U.S. Army Medical Research and Materiel Command research program focused on sustaining operational effectiveness of Future Force Warriors by developing paradigms through which militarily-relevant, higher-order cognitive performance, judgment, and decision-making can be assessed and sustained in individuals, small teams, and leaders of network-centric fighting units. CPJD evaluates the impact of stressors intrinsic to military operational environments (e.g., sleep deprivation, workload, fatigue, temperature extremes, altitude, environmental/physiological disruption) on military performance, evaluates noninvasive automated methods for monitoring and predicting cognitive performance, and investigates pharmaceutical strategies (e.g., stimulant countermeasures, hypnotics) to mitigate performance decrements. This manuscript describes the CPJD program, discusses the metrics utilized to relate militarily applied research findings to academic research, and discusses how the simulated combat capabilities of a synthetic battle laboratory may facilitate future cognitive performance research.
A model for simulating adaptive, dynamic flows on networks: Application to petroleum infrastructure
Corbet, Thomas F.; Beyeler, Walt; Wilson, Michael L.; ...
2017-10-03
Simulation models can greatly improve decisions meant to control the consequences of disruptions to critical infrastructures. We describe a dynamic flow model on networks purposed to inform analyses by those concerned about consequences of disruptions to infrastructures and to help policy makers design robust mitigations. We conceptualize the adaptive responses of infrastructure networks to perturbations as market transactions and business decisions of operators. We approximate commodity flows in these networks by a diffusion equation, with nonlinearities introduced to model capacity limits. To illustrate the behavior and scalability of the model, we show its application first on two simple networks, thenmore » on petroleum infrastructure in the United States, where we analyze the effects of a hypothesized earthquake.« less
A model for simulating adaptive, dynamic flows on networks: Application to petroleum infrastructure
DOE Office of Scientific and Technical Information (OSTI.GOV)
Corbet, Thomas F.; Beyeler, Walt; Wilson, Michael L.
Simulation models can greatly improve decisions meant to control the consequences of disruptions to critical infrastructures. We describe a dynamic flow model on networks purposed to inform analyses by those concerned about consequences of disruptions to infrastructures and to help policy makers design robust mitigations. We conceptualize the adaptive responses of infrastructure networks to perturbations as market transactions and business decisions of operators. We approximate commodity flows in these networks by a diffusion equation, with nonlinearities introduced to model capacity limits. To illustrate the behavior and scalability of the model, we show its application first on two simple networks, thenmore » on petroleum infrastructure in the United States, where we analyze the effects of a hypothesized earthquake.« less
Real time simulation of computer-assisted sequencing of terminal area operations
NASA Technical Reports Server (NTRS)
Dear, R. G.
1981-01-01
A simulation was developed to investigate the utilization of computer assisted decision making for the task of sequencing and scheduling aircraft in a high density terminal area. The simulation incorporates a decision methodology termed Constrained Position Shifting. This methodology accounts for aircraft velocity profiles, routes, and weight classes in dynamically sequencing and scheduling arriving aircraft. A sample demonstration of Constrained Position Shifting is presented where six aircraft types (including both light and heavy aircraft) are sequenced to land at Denver's Stapleton International Airport. A graphical display is utilized and Constrained Position Shifting with a maximum shift of four positions (rearward or forward) is compared to first come, first serve with respect to arrival at the runway. The implementation of computer assisted sequencing and scheduling methodologies is investigated. A time based control concept will be required and design considerations for such a system are discussed.
NASA Astrophysics Data System (ADS)
Medellin-Azuara, J.; Fraga, C. C. S.; Marques, G.; Mendes, C. A.
2015-12-01
The expansion and operation of urban water supply systems under rapidly growing demands, hydrologic uncertainty, and scarce water supplies requires a strategic combination of various supply sources for added reliability, reduced costs and improved operational flexibility. The design and operation of such portfolio of water supply sources merits decisions of what and when to expand, and how much to use of each available sources accounting for interest rates, economies of scale and hydrologic variability. The present research provides a framework and an integrated methodology that optimizes the expansion of various water supply alternatives using dynamic programming and combining both short term and long term optimization of water use and simulation of water allocation. A case study in Bahia Do Rio Dos Sinos in Southern Brazil is presented. The framework couples an optimization model with quadratic programming model in GAMS with WEAP, a rain runoff simulation models that hosts the water supply infrastructure features and hydrologic conditions. Results allow (a) identification of trade offs between cost and reliability of different expansion paths and water use decisions and (b) evaluation of potential gains by reducing water system losses as a portfolio component. The latter is critical in several developing countries where water supply system losses are high and often neglected in favor of more system expansion. Results also highlight the potential of various water supply alternatives including, conservation, groundwater, and infrastructural enhancements over time. The framework proves its usefulness for planning its transferability to similarly urbanized systems.
Denham, Charles R; Guilloteau, Franck R
2012-09-01
The ultimate objective of this program is to provide an approach to understanding and communicating health-care harm and cost to compel health-care provider leadership teams to vote "yes" to investments in patient safety initiatives, with the confidence that clinical, financial, and operational performance will be improved by such programs. Through a coordinated combination of literature evaluations, careful mapping of high impact scenarios using simulated patients and consensus review of clinical, operational, and financial factors, we confirmed value in such approaches to decision support information for hospital leadership teams to invest in patient safety projects. The study resulted in the following preliminary findings: ·Communication between hospital quality and finance departments can be much improved by direct collaborative relationships through regular meetings to help both clarify direct costs, indirect costs, and the savings of waste and harm to patients by avoidance of infections. ·Governance leaders and the professional administrative leaders should consider establishing the structures and systems necessary to act on risks and hazards as they evolve to deploy resources to areas of harm and risk. ·Quality and Infection Control Professionals can best wage their war on healthcare waste and harm by keeping abreast of the latest literature regarding the latest measures, standards, and safe practices for healthcare-acquired infections and hospital-acquired conditions. ·Regular reviews of patients with health-careYassociated infections, with direct attention to the attributable cost of treatment and how financial waste and harm to patients may be avoided, may provide hospital leaders with new insights for improvement. ·If hospitals developed their own risk scenarios to determine impact of harm and waste from hospital-acquired conditions in addition to impact scenarios for specific processes through technology and process innovations, they would have more clear guidance for improvement efforts. ·Tools such as impact calculators, performance models, and simulated patient trajectories are no more tied to the reality of running a hospital or treating a patient as jet simulator metrics are to taking a real flight with real weather and real aircraftVthey provide a view to enhance decision making but do NOT provide the answers. The final result of this project was to demonstrate a prototype leadership decision-support investment model approach that addresses clinical, operational, and financial performance for typical hospitals.
NASA Astrophysics Data System (ADS)
Carrico, T.; Langster, T.; Carrico, J.; Alfano, S.; Loucks, M.; Vallado, D.
The authors present several spacecraft rendezvous and close proximity maneuvering techniques modeled with a high-precision numerical integrator using full force models and closed loop control with a Fuzzy Logic intelligent controller to command the engines. The authors document and compare the maneuvers, fuel use, and other parameters. This paper presents an innovative application of an existing capability to design, simulate and analyze proximity maneuvers; already in use for operational satellites performing other maneuvers. The system has been extended to demonstrate the capability to develop closed loop control laws to maneuver spacecraft in close proximity to another, including stand-off, docking, lunar landing and other operations applicable to space situational awareness, space based surveillance, and operational satellite modeling. The fully integrated end-to-end trajectory ephemerides are available from the authors in electronic ASCII text by request. The benefits of this system include: A realistic physics-based simulation for the development and validation of control laws A collaborative engineering environment for the design, development and tuning of spacecraft law parameters, sizing actuators (i.e., rocket engines), and sensor suite selection. An accurate simulation and visualization to communicate the complexity, criticality, and risk of spacecraft operations. A precise mathematical environment for research and development of future spacecraft maneuvering engineering tasks, operational planning and forensic analysis. A closed loop, knowledge-based control example for proximity operations. This proximity operations modeling and simulation environment will provide a valuable adjunct to programs in military space control, space situational awareness and civil space exploration engineering and decision making processes.
MATREX: A Unifying Modeling and Simulation Architecture for Live-Virtual-Constructive Applications
2007-05-23
Deployment Systems Acquisition Operations & Support B C Sustainment FRP Decision Review FOC LRIP/IOT& ECritical Design Review Pre-Systems...CMS2 – Comprehensive Munitions & Sensor Server • CSAT – C4ISR Static Analysis Tool • C4ISR – Command & Control, Communications, Computers
Bennett, Casey C; Hauser, Kris
2013-01-01
In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal decisions even in complex and uncertain environments. Future work is described that outlines potential lines of research and integration of machine learning algorithms for personalized medicine. Copyright © 2012 Elsevier B.V. All rights reserved.
Expanded envelope concepts for aircraft control-element failure detection and identification
NASA Technical Reports Server (NTRS)
Weiss, Jerold L.; Hsu, John Y.
1988-01-01
The purpose of this effort was to develop and demonstrate concepts for expanding the envelope of failure detection and isolation (FDI) algorithms for aircraft-path failures. An algorithm which uses analytic-redundancy in the form of aerodynamic force and moment balance equations was used. Because aircraft-path FDI uses analytical models, there is a tradeoff between accuracy and the ability to detect and isolate failures. For single flight condition operation, design and analysis methods are developed to deal with this robustness problem. When the departure from the single flight condition is significant, algorithm adaptation is necessary. Adaptation requirements for the residual generation portion of the FDI algorithm are interpreted as the need for accurate, large-motion aero-models, over a broad range of velocity and altitude conditions. For the decision-making part of the algorithm, adaptation may require modifications to filtering operations, thresholds, and projection vectors that define the various hypothesis tests performed in the decision mechanism. Methods of obtaining and evaluating adequate residual generation and decision-making designs have been developed. The application of the residual generation ideas to a high-performance fighter is demonstrated by developing adaptive residuals for the AFTI-F-16 and simulating their behavior under a variety of maneuvers using the results of a NASA F-16 simulation.
Expanding the base for teaching of percutaneous coronary interventions: the explicit approach.
Lanzer, Peter; Prechelt, Lutz
2011-02-15
Accelerate and improve the training and learning process of operators performing percutaneous coronary interventions (PCI). Operator cognitive, in particular decision-making skills and technical skills are a major factor for the success of coronary interventions. Currently, cognitive skills are commonly developed by three methods: (1) Cognitive learning of rules for which statistical evidence is available. This is very incomprehensive and isolates cognitive learning from skill acquisition. (2) Informal tutoring received from experienced operators, and (3) personal experience by trial-and-error are both very slow. We propose in this concept article a conceptual framework to elicit, capture, and transfer expert PCI skills to complement the current approach. This includes the development of an in-depth understanding of the nature of PCI skills, terminology, and nomenclature needed to streamline communication, propensity of reproducible performance assessment, and in particular an explication of intervention planning and intra-intervention decision-making. We illustrate the impact of improved decision-making by simulation results based on a stochastic model of intervention risk. We identify several key concepts that form the basis of this conceptual framework, in particular different risk types and the notions of strategy, interventional module, and tactic. The increasing complexity of cases have brought PCI to the point where the decision-making skills of master operators need to be made explicit to make them systematically learnable such that the skills of beginner and intermediate operators can be improved much faster than is currently possible. Copyright © 2010 Wiley-Liss, Inc.
Improving the performance of surgery-based clinical pathways: a simulation-optimization approach.
Ozcan, Yasar A; Tànfani, Elena; Testi, Angela
2017-03-01
This paper aims to improve the performance of clinical processes using clinical pathways (CPs). The specific goal of this research is to develop a decision support tool, based on a simulation-optimization approach, which identify the proper adjustment and alignment of resources to achieve better performance for both the patients and the health-care facility. When multiple perspectives are present in a decision problem, critical issues arise and often require the balancing of goals. In our approach, meeting patients' clinical needs in a timely manner, and to avoid worsening of clinical conditions, we assess the level of appropriate resources. The simulation-optimization model seeks and evaluates alternative resource configurations aimed at balancing the two main objectives-meeting patient needs and optimal utilization of beds and operating rooms.Using primary data collected at a Department of Surgery of a public hospital located in Genoa, Italy. The simulation-optimization modelling approach in this study has been applied to evaluate the thyroid surgical treatment together with the other surgery-based CPs. The low rate of bed utilization and the long elective waiting lists of the specialty under study indicates that the wards were oversized while the operating room capacity was the bottleneck of the system. The model enables hospital managers determine which objective has to be given priority, as well as the corresponding opportunity costs.
A computer simulation experiment of supervisory control of remote manipulation. M.S. Thesis
NASA Technical Reports Server (NTRS)
Mccandlish, S. G.
1966-01-01
A computer simulation of a remote manipulation task and a rate-controlled manipulator is described. Some low-level automatic decision making ability which could be used at the operator's discretion to augment his direct continuous control was built into the manipulator. Experiments were made on the effect of transmission delay, dynamic lag, and intermittent vision on human manipulative ability. Delay does not make remote manipulation impossible. Intermittent visual feedback, and the absence of rate information in the display presented to the operator do not seem to impair the operator's performance. A small-capacity visual feedback channel may be sufficient for remote manipulation tasks, or one channel might be time-shared between several operators. In other experiments the operator called in sequence various on-site automatic control programs of the machine, and thereby acted as a supervisor. The supervisory mode of operation has some advantages when the task to be performed is difficult for a human controlling directly.
Using simulation to design a central sterilization department.
Lin, Feng; Lawley, Mark; Spry, Charlie; McCarthy, Kelly; Coyle-Rogers, Patricia G; Yih, Yuehwern
2008-10-01
A simulation project was performed to assist with redesign of the surgery department of a large tertiary hospital and to help administrators make the best decisions about relocating, staffing, and equipping the central sterilization department. A simulation model was created to analyze department configurations, staff schedules, equipment capacities, and cart-washing requirements. Performance measures examined include tray turnaround time, surgery-delay rate, and work-in-process levels. The analysis provides significant insight into how the proposed system will perform, allowing planning for expected patient volume increases. This work illustrates how simulation can facilitate the design of a central sterilization department and improve surgical sterilization operations.
Understanding Crew Decision-Making in the Presence of Complexity: A Flight Simulation Experiment
NASA Technical Reports Server (NTRS)
Young, Steven D.; Daniels, Taumi S.; Evans, Emory; deHaag, Maarten Uijt; Duan, Pengfei
2013-01-01
Crew decision making and response have long been leading causal and contributing factors associated with aircraft accidents. Further, it is anticipated that future aircraft and operational environments will increase exposure to risks related to these factors if proactive steps are not taken to account for ever-increasing complexity. A flight simulation study was designed to collect data to help in understanding how complexity can, or may, be manifest. More specifically, an experimental apparatus was constructed that allowed for manipulation of information complexity and uncertainty, while also manipulating operational complexity and uncertainty. Through these manipulations, and the aid of experienced airline pilots, several issues have been discovered, related most prominently to the influence of information content, quality, and management. Flight crews were immersed in an environment that included new operational complexities suggested for the future air transportation system as well as new technological complexities (e.g. electronic flight bags, expanded data link services, synthetic and enhanced vision systems, and interval management automation). In addition, a set of off-nominal situations were emulated. These included, for example, adverse weather conditions, traffic deviations, equipment failures, poor data quality, communication errors, and unexpected clearances, or changes to flight plans. Each situation was based on one or more reference events from past accidents or incidents, or on a similar case that had been used in previous developmental tests or studies. Over the course of the study, 10 twopilot airline crews participated, completing over 230 flights. Each flight consisted of an approach beginning at 10,000 ft. Based on the recorded data and pilot and research observations, preliminary results are presented regarding decision-making issues in the presence of the operational and technological complexities encountered during the flights.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cappelli, M.; Gadomski, A. M.; Sepiellis, M.
In the field of nuclear power plant (NPP) safety modeling, the perception of the role of socio-cognitive engineering (SCE) is continuously increasing. Today, the focus is especially on the identification of human and organization decisional errors caused by operators and managers under high-risk conditions, as evident by analyzing reports on nuclear incidents occurred in the past. At present, the engineering and social safety requirements need to enlarge their domain of interest in such a way to include all possible losses generating events that could be the consequences of an abnormal state of a NPP. Socio-cognitive modeling of Integrated Nuclear Safetymore » Management (INSM) using the TOGA meta-theory has been discussed during the ICCAP 2011 Conference. In this paper, more detailed aspects of the cognitive decision-making and its possible human errors and organizational vulnerability are presented. The formal TOGA-based network model for cognitive decision-making enables to indicate and analyze nodes and arcs in which plant operators and managers errors may appear. The TOGA's multi-level IPK (Information, Preferences, Knowledge) model of abstract intelligent agents (AIAs) is applied. In the NPP context, super-safety approach is also discussed, by taking under consideration unexpected events and managing them from a systemic perspective. As the nature of human errors depends on the specific properties of the decision-maker and the decisional context of operation, a classification of decision-making using IPK is suggested. Several types of initial situations of decision-making useful for the diagnosis of NPP operators and managers errors are considered. The developed models can be used as a basis for applications to NPP educational or engineering simulators to be used for training the NPP executive staff. (authors)« less
Temporal logics meet telerobotics
NASA Technical Reports Server (NTRS)
Rutten, Eric; Marce, Lionel
1989-01-01
The specificity of telerobotics being the presence of a human operator, decision assistance tools are necessary for the operator, especially in hostile environments. In order to reduce execution hazards due to a degraded ability for quick and efficient recovery of unexpected dangerous situations, it is of importance to have the opportunity, amongst others, to simulate the possible consequences of a plan before its actual execution, in order to detect these problematic situations. Hence the idea of providing the operator with a simulator enabling him to verify the temporal and logical coherence of his plans. Therefore, the power of logical formalisms is used for representation and deduction purposes. Starting from the class of situations that are represented, a STRIPS (the STanford Research Institute Problem Solver)-like formalism and its underlying logic are adapted to the simulation of plans of actions in time. The choice of a temporal logic enables to build a world representation, on which the effects of plans, grouping actions into control structures, will be transcribed by the simulation, resulting in a verdict and information about the plan's coherence.
IFC BIM-Based Methodology for Semi-Automated Building Energy Performance Simulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bazjanac, Vladimir
2008-07-01
Building energy performance (BEP) simulation is still rarely used in building design, commissioning and operations. The process is too costly and too labor intensive, and it takes too long to deliver results. Its quantitative results are not reproducible due to arbitrary decisions and assumptions made in simulation model definition, and can be trusted only under special circumstances. A methodology to semi-automate BEP simulation preparation and execution makes this process much more effective. It incorporates principles of information science and aims to eliminate inappropriate human intervention that results in subjective and arbitrary decisions. This is achieved by automating every part ofmore » the BEP modeling and simulation process that can be automated, by relying on data from original sources, and by making any necessary data transformation rule-based and automated. This paper describes the new methodology and its relationship to IFC-based BIM and software interoperability. It identifies five steps that are critical to its implementation, and shows what part of the methodology can be applied today. The paper concludes with a discussion of application to simulation with EnergyPlus, and describes data transformation rules embedded in the new Geometry Simplification Tool (GST).« less
Jackson, Simon A; Kleitman, Sabina; Aidman, Eugene
2014-01-01
The present study investigated the effects of low cognitive workload and the absence of arousal induced via external physical stimulation (motion) on practice-related improvements in executive (inhibitory) control, short-term memory, metacognitive monitoring and decision making. A total of 70 office workers performed low and moderately engaging passenger tasks in two successive 20-minute simulated drives and repeated a battery of decision making and inhibitory control tests three times—before, between and after these drives. For half the participants, visual simulation was synchronised with (moderately arousing) motion generated through LAnd Motion Platform, with vibration levels corresponding to a well-maintained unsealed road. The other half performed the same simulated drive without motion. Participants' performance significantly improved over the three test blocks, which is indicative of typical practice effects. The magnitude of these improvements was the highest when both motion and moderate cognitive load were present. The same effects declined either in the absence of motion (low arousal) or following a low cognitive workload task, thus suggesting two distinct pathways through which practice-related improvements in cognitive performance may be hampered. Practice, however, degraded certain aspects of metacognitive performance, as participants became less likely to detect incorrect decisions in the decision-making test with each subsequent test block. Implications include consideration of low cognitive load and arousal as factors responsible for performance decline and targets for the development of interventions/strategies in low load/arousal conditions such as autonomous vehicle operations and highway driving.
Creating virtual humans for simulation-based training and planning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stansfield, S.; Sobel, A.
1998-05-12
Sandia National Laboratories has developed a distributed, high fidelity simulation system for training and planning small team Operations. The system provides an immersive environment populated by virtual objects and humans capable of displaying complex behaviors. The work has focused on developing the behaviors required to carry out complex tasks and decision making under stress. Central to this work are techniques for creating behaviors for virtual humans and for dynamically assigning behaviors to CGF to allow scenarios without fixed outcomes. Two prototype systems have been developed that illustrate these capabilities: MediSim, a trainer for battlefield medics and VRaptor, a system formore » planning, rehearsing and training assault operations.« less
Wind Turbine Contingency Control Through Generator De-Rating
NASA Technical Reports Server (NTRS)
Frost, Susan; Goebel, Kai; Balas, Mark
2013-01-01
Maximizing turbine up-time and reducing maintenance costs are key technology drivers for wind turbine operators. Components within wind turbines are subject to considerable stresses due to unpredictable environmental conditions resulting from rapidly changing local dynamics. In that context, systems health management has the aim to assess the state-of-health of components within a wind turbine, to estimate remaining life, and to aid in autonomous decision-making to minimize damage to the turbine. Advanced contingency control is one way to enable autonomous decision-making by providing the mechanism to enable safe and efficient turbine operation. The work reported herein explores the integration of condition monitoring of wind turbines with contingency control to balance the trade-offs between maintaining system health and energy capture. The contingency control involves de-rating the generator operating point to achieve reduced loads on the wind turbine. Results are demonstrated using a high fidelity simulator of a utility-scale wind turbine.
Thermal area effectiveness for future aircraft
NASA Technical Reports Server (NTRS)
Happ, W. W.
1975-01-01
Problem areas in airport planning, design, and operations identified by a decision matrix developed to display various airport functions interfaced with facilities and an extensive literature survey were investigated. Areas considered include: site selection and growth potential; emissions and noise control/containment for airports; financial and legal aspects of airport planning, contruction, and operation; intra-airport transportation and other passenger flow facilitators; simulation and modeling for airports; guidelines for airport multimodal access planning. Results are summarized and a bibliography is included.
Decision Support from Genetic Algorithms for Ship Collision Avoidance Route Planning and Alerts
NASA Astrophysics Data System (ADS)
Tsou, Ming-Cheng; Kao, Sheng-Long; Su, Chien-Min
When an officer of the watch (OOW) faces complicated marine traffic, a suitable decision support tool could be employed in support of collision avoidance decisions, to reduce the burden and greatly improve the safety of marine traffic. Decisions on routes to avoid collisions could also consider economy as well as safety. Through simulating the biological evolution model, this research adopts the genetic algorithm used in artificial intelligence to find a theoretically safety-critical recommendation for the shortest route of collision avoidance from an economic viewpoint, combining the international regulations for preventing collisions at sea (COLREGS) and the safety domain of a ship. Based on this recommendation, an optimal safe avoidance turning angle, navigation restoration time and navigational restoration angle will also be provided. A Geographic Information System (GIS) will be used as the platform for display and operation. In order to achieve advance notice of alerts and due preparation for collision avoidance, a Vessel Traffic Services (VTS) operator and the OOW can use this system as a reference to assess collision avoidance at present location.
NASA Technical Reports Server (NTRS)
Rosenberg, L. S.; Revere, W. R.; Selcuk, M. K.
1981-01-01
Small solar thermal power systems (up to 10 MWe in size) were tested. The solar thermal power plant ranking study was performed to aid in experiment activity and support decisions for the selection of the most appropriate technological approach. The cost and performance were determined for insolation conditions by utilizing the Solar Energy Simulation computer code (SESII). This model optimizes the size of the collector field and energy storage subsystem for given engine generator and energy transport characteristics. The development of the simulation tool, its operation, and the results achieved from the analysis are discussed.
Cross-Milieu Terrorist Collaboration: Using Game Theory to Assess the Risk of a Novel Threat.
Ackerman, Gary A; Zhuang, Jun; Weerasuriya, Sitara
2017-02-01
This article uses a game-theoretic approach to analyze the risk of cross-milieu terrorist collaboration-the possibility that, despite marked ideological differences, extremist groups from very different milieus might align to a degree where operational collaboration against Western societies becomes possible. Based upon theoretical insights drawn from a variety of literatures, a bargaining model is constructed that reflects the various benefits and costs for terrorists' collaboration across ideological milieus. Analyzed in both sequential and simultaneous decision-making contexts and through numerical simulations, the model confirms several theoretical arguments. The most important of these is that although likely to be quite rare, successful collaboration across terrorist milieus is indeed feasible in certain circumstances. The model also highlights several structural elements that might play a larger role than previously recognized in the collaboration decision, including that the prospect of nonmaterial gains (amplification of terror and reputational boost) plays at least as important a role in the decision to collaborate as potential increased capabilities does. Numerical simulation further suggests that prospects for successful collaboration over most scenarios (including operational) increase when a large, effective Islamist terrorist organization initiates collaboration with a smaller right-wing group, as compared with the other scenarios considered. Although the small number of historical cases precludes robust statistical validation, the simulation results are supported by existing empirical evidence of collaboration between Islamists and right- or left-wing extremists. The game-theoretic approach, therefore, provides guidance regarding the circumstances under which such an unholy alliance of violent actors is likely to succeed. © 2016 Society for Risk Analysis.
A Geographical Heuristic Routing Protocol for VANETs
Urquiza-Aguiar, Luis; Tripp-Barba, Carolina; Aguilar Igartua, Mónica
2016-01-01
Vehicular ad hoc networks (VANETs) leverage the communication system of Intelligent Transportation Systems (ITS). Recently, Delay-Tolerant Network (DTN) routing protocols have increased their popularity among the research community for being used in non-safety VANET applications and services like traffic reporting. Vehicular DTN protocols use geographical and local information to make forwarding decisions. However, current proposals only consider the selection of the best candidate based on a local-search. In this paper, we propose a generic Geographical Heuristic Routing (GHR) protocol that can be applied to any DTN geographical routing protocol that makes forwarding decisions hop by hop. GHR includes in its operation adaptations simulated annealing and Tabu-search meta-heuristics, which have largely been used to improve local-search results in discrete optimization. We include a complete performance evaluation of GHR in a multi-hop VANET simulation scenario for a reporting service. Our study analyzes all of the meaningful configurations of GHR and offers a statistical analysis of our findings by means of MANOVA tests. Our results indicate that the use of a Tabu list contributes to improving the packet delivery ratio by around 5% to 10%. Moreover, if Tabu is used, then the simulated annealing routing strategy gets a better performance than the selection of the best node used with carry and forwarding (default operation). PMID:27669254
A Geographical Heuristic Routing Protocol for VANETs.
Urquiza-Aguiar, Luis; Tripp-Barba, Carolina; Aguilar Igartua, Mónica
2016-09-23
Vehicular ad hoc networks (VANETs) leverage the communication system of Intelligent Transportation Systems (ITS). Recently, Delay-Tolerant Network (DTN) routing protocols have increased their popularity among the research community for being used in non-safety VANET applications and services like traffic reporting. Vehicular DTN protocols use geographical and local information to make forwarding decisions. However, current proposals only consider the selection of the best candidate based on a local-search. In this paper, we propose a generic Geographical Heuristic Routing (GHR) protocol that can be applied to any DTN geographical routing protocol that makes forwarding decisions hop by hop. GHR includes in its operation adaptations simulated annealing and Tabu-search meta-heuristics, which have largely been used to improve local-search results in discrete optimization. We include a complete performance evaluation of GHR in a multi-hop VANET simulation scenario for a reporting service. Our study analyzes all of the meaningful configurations of GHR and offers a statistical analysis of our findings by means of MANOVA tests. Our results indicate that the use of a Tabu list contributes to improving the packet delivery ratio by around 5% to 10%. Moreover, if Tabu is used, then the simulated annealing routing strategy gets a better performance than the selection of the best node used with carry and forwarding (default operation).
Innovative Tools for Water Quality/Quantity Management: New York City's Operations Support Tool
NASA Astrophysics Data System (ADS)
Wang, L.; Schaake, J. C.; Day, G. N.; Porter, J.; Sheer, D. P.; Pyke, G.
2011-12-01
The New York City Department of Environmental Protection (DEP) manages New York City's water supply, which is comprised of over 20 reservoirs and supplies more than 1 billion gallons of water per day to over 9 million customers. Recently, DEP has initiated design of an Operations Support Tool (OST), a state-of-the-art decision support system to provide computational and predictive support for water supply operations and planning. This presentation describes the technical structure of OST, including the underlying water supply and water quality models, data sources and database management, reservoir inflow forecasts, and the functionalities required to meet the needs of a diverse group of end users. OST is a major upgrade of DEP's current water supply - water quality model, developed to evaluate alternatives for controlling turbidity in NYC's Catskill reservoirs. While the current model relies on historical hydrologic and meteorological data, OST can be driven by forecasted future conditions. It will receive a variety of near-real-time data from a number of sources. OST will support two major types of simulations: long-term, for evaluating policy or infrastructure changes over an extended period of time; and short-term "position analysis" (PA) simulations, consisting of multiple short simulations, all starting from the same initial conditions. Typically, the starting conditions for a PA run will represent those for the current day and traces of forecasted hydrology will drive the model for the duration of the simulation period. The result of these simulations will be a distribution of future system states based on system operating rules and the range of input ensemble streamflow predictions. DEP managers will analyze the output distributions and make operation decisions using risk-based metrics such as probability of refill. Currently, in the developmental stages of OST, forecasts are based on antecedent hydrologic conditions and are statistical in nature. The statistical algorithm is a relatively simple and versatile, but lacks short-term skill critical for water quality and spill management. To improve short-term skill, OST will ultimately operate with meteorologically driven hydrologic forecasts provided by the National Weather Service (NWS). OST functionalities will support a wide range of DEP uses, including short term operational projections, outage planning and emergency management, operating rule development, and water supply planning. A core use of OST will be to inform reservoir management strategies to control and mitigate turbidity events while ensuring water supply reliability. OST will also allow DEP to manage its complex reservoir system to meet multiple objectives, including ecological flows, tailwater fisheries and recreational releases, and peak flow mitigation for downstream communities.
NASA Technical Reports Server (NTRS)
Buchanan, H.; Nixon, D.; Joyce, R.
1974-01-01
A simulation of the Skylab attitude and pointing control system (APCS) is outlined and discussed. Implementation is via a large hybrid computer and includes those factors affecting system momentum management, propellant consumption, and overall vehicle performance. The important features of the flight system are discussed; the mathematical models necessary for this treatment are outlined; and the decisions involved in implementation are discussed. A brief summary of the goals and capabilities of this tool is also included.
NASA Astrophysics Data System (ADS)
Uysal, G.; Sensoy, A.; Yavuz, O.; Sorman, A. A.; Gezgin, T.
2012-04-01
Effective management of a controlled reservoir system where it involves multiple and sometimes conflicting objectives is a complex problem especially in real time operations. Yuvacık Dam Reservoir, located in the Marmara region of Turkey, is built to supply annual demand of 142 hm3 water for Kocaeli city requires such a complex management strategy since it has relatively small (51 hm3) effective capacity. On the other hand, the drainage basin is fed by both rainfall and snowmelt since the elevation ranges between 80 - 1548 m. Excessive water must be stored behind the radial gates between February and May in terms of sustainability especially for summer and autumn periods. Moreover, the downstream channel physical conditions constraint the spillway releases up to 100 m3/s although the spillway is large enough to handle major floods. Thus, this situation makes short term release decisions the challenging task. Long term water supply curves, based on historical inflows and annual water demand, are in conflict with flood regulation (control) levels, based on flood attenuation and routing curves, for this reservoir. A guide curve, that is generated using both water supply and flood control of downstream channel, generally corresponds to upper elevation of conservation pool for simulation of a reservoir. However, sometimes current operation necessitates exceeding this target elevation. Since guide curves can be developed as a function of external variables, the water potential of a basin can be an indicator to explain current conditions and decide on the further strategies. Besides, releases with respect to guide curve are managed and restricted by user-defined rules. Although the managers operate the reservoir due to several variable conditions and predictions, still the simulation model using variable guide curve is an urgent need to test alternatives quickly. To that end, using HEC-ResSim, the several variable guide curves are defined to meet the requirements by taking inflow, elevation, precipitation and snow water equivalent into consideration to propose alternative simulations as a decision support system. After that, the releases are subjected to user-defined rules. Thus, previous year reservoir simulations are compared with observed reservoir levels and releases. Hypothetical flood scenarios are tested in case of different storm event timing and sizing. Numerical weather prediction data of Mesoscale Model 5 (MM5) can be used for temperature and precipitation forecasts that will form the inputs for a hydrological model. The estimated flows can be used for real time short term decisions for reservoir simulation based on variable guide curve and user defined rules.
Pilot interaction with automated airborne decision making systems
NASA Technical Reports Server (NTRS)
Rouse, W. B.; Hammer, J. M.; Morris, N. M.; Brown, E. N.; Yoon, W. C.
1983-01-01
The use of advanced software engineering methods (e.g., from artificial intelligence) to aid aircraft crews in procedure selection and execution is investigated. Human problem solving in dynamic environments as effected by the human's level of knowledge of system operations is examined. Progress on the development of full scale simulation facilities is also discussed.
1997-12-01
of the DoD environmental science community to identify cloud modeling and other environmental capabilities that support or could potentially support...benefit of the DoD environmental science community. STC determined the detailed requirements for weather effects products and decision aids for specific Air Force operational electro-optical systems.
On-the-fly scheduling as a manifestation of partial-order planning and dynamic task values.
Hannah, Samuel D; Neal, Andrew
2014-09-01
The aim of this study was to develop a computational account of the spontaneous task ordering that occurs within jobs as work unfolds ("on-the-fly task scheduling"). Air traffic control is an example of work in which operators have to schedule their tasks as a partially predictable work flow emerges. To date, little attention has been paid to such on-the-fly scheduling situations. We present a series of discrete-event models fit to conflict resolution decision data collected from experienced controllers operating in a high-fidelity simulation. Our simulations reveal air traffic controllers' scheduling decisions as examples of the partial-order planning approach of Hayes-Roth and Hayes-Roth. The most successful model uses opportunistic first-come-first-served scheduling to select tasks from a queue. Tasks with short deadlines are executed immediately. Tasks with long deadlines are evaluated to assess whether they need to be executed immediately or deferred. On-the-fly task scheduling is computationally tractable despite its surface complexity and understandable as an example of both the partial-order planning strategy and the dynamic-value approach to prioritization.
NASA Technical Reports Server (NTRS)
Santana, Erico Soriano Martins; Mueller, Carlos
2003-01-01
The occurrence of flight delays in Brazil, mostly verified at the ground (airfield), is responsible for serious disruptions at the airport level but also for the unchaining of problems in all the airport system, affecting also the airspace. The present study develops an analysis of delay and travel times at Sao Paulo International Airport/ Guarulhos (AISP/GRU) airfield based on simulation model. Different airport physical and operational scenarios had been analyzed by means of simulation. SIMMOD Plus 4.0, the computational tool developed to represent aircraft operation in the airspace and airside of airports, was used to perform these analysis. The study was mainly focused on aircraft operations on ground, at the airport runway, taxi-lanes and aprons. The visualization of the operations with increasing demand facilitated the analyses. The results generated in this work certify the viability of the methodology, they also indicated the solutions capable to solve the delay problem by travel time analysis, thus diminishing the costs for users mainly airport authority. It also indicated alternatives for airport operations, assisting the decision-making process and in the appropriate timing of the proposed changes in the existing infrastructure.
Gunay, Osman; Toreyin, Behçet Ugur; Kose, Kivanc; Cetin, A Enis
2012-05-01
In this paper, an entropy-functional-based online adaptive decision fusion (EADF) framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several subalgorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular subalgorithm. Decision values are linearly combined with weights that are updated online according to an active fusion method based on performing entropic projections onto convex sets describing subalgorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video-based wildfire detection system was developed to evaluate the performance of the decision fusion algorithm. In this case, image data arrive sequentially, and the oracle is the security guard of the forest lookout tower, verifying the decision of the combined algorithm. The simulation results are presented.
Crew decision making under stress
NASA Technical Reports Server (NTRS)
Orasanu, J.
1992-01-01
Flight crews must make decisions and take action when systems fail or emergencies arise during flight. These situations may involve high stress. Full-missiion flight simulation studies have shown that crews differ in how effectively they cope in these circumstances, judged by operational errors and crew coordination. The present study analyzed the problem solving and decision making strategies used by crews led by captains fitting three different personality profiles. Our goal was to identify more and less effective strategies that could serve as the basis for crew selection or training. Methods: Twelve 3-member B-727 crews flew a 5-leg mission simulated flight over 1 1/2 days. Two legs included 4 abnormal events that required decisions during high workload periods. Transcripts of videotapes were analyzed to describe decision making strategies. Crew performance (errors and coordination) was judged on-line and from videotapes by check airmen. Results: Based on a median split of crew performance errors, analyses to date indicate a difference in general strategy between crews who make more or less errors. Higher performance crews showed greater situational awareness - they responded quickly to cues and interpreted them appropriately. They requested more decision relevant information and took into account more constraints. Lower performing crews showed poorer situational awareness, planning, constraint sensitivity, and coordination. The major difference between higher and lower performing crews was that poorer crews made quick decisions and then collected information to confirm their decision. Conclusion: Differences in overall crew performance were associated with differences in situational awareness, information management, and decision strategy. Captain personality profiles were associated with these differences, a finding with implications for crew selection and training.
Considering social and environmental concerns as reservoir operating objectives
NASA Astrophysics Data System (ADS)
Tilmant, A.; Georis, B.; Doulliez, P.
2003-04-01
Sustainability principles are now widely recognized as key criteria for water resource development schemes, such as hydroelectric and multipurpose reservoirs. Development decisions no longer rely solely on economic grounds, but also consider environmental and social concerns through the so-called environmental and social impact assessments. The objective of this paper is to show that environmental and social concerns can also be addressed in the management (operation) of existing or projected reservoir schemes. By either adequately exploiting the results of environmental and social impact assessments, or by carrying out survey of water users, experts and managers, efficient (Pareto optimal) reservoir operating rules can be derived using flexible mathematical programming techniques. By reformulating the problem as a multistage flexible constraint satisfaction problem, incommensurable and subjective operating objectives can contribute, along with classical economic objectives, to the determination of optimal release decisions. Employed in a simulation mode, the results can be used to assess the long-term impacts of various operating rules on the social well-being of affected populations as well as on the integrity of the environment. The methodology is illustrated with a reservoir reallocation problem in Chile.
NASA Astrophysics Data System (ADS)
Shirley, Rachel Elizabeth
Nuclear power plant (NPP) simulators are proliferating in academic research institutions and national laboratories in response to the availability of affordable, digital simulator platforms. Accompanying the new research facilities is a renewed interest in using data collected in NPP simulators for Human Reliability Analysis (HRA) research. An experiment conducted in The Ohio State University (OSU) NPP Simulator Facility develops data collection methods and analytical tools to improve use of simulator data in HRA. In the pilot experiment, student operators respond to design basis accidents in the OSU NPP Simulator Facility. Thirty-three undergraduate and graduate engineering students participated in the research. Following each accident scenario, student operators completed a survey about perceived simulator biases and watched a video of the scenario. During the video, they periodically recorded their perceived strength of significant Performance Shaping Factors (PSFs) such as Stress. This dissertation reviews three aspects of simulator-based research using the data collected in the OSU NPP Simulator Facility: First, a qualitative comparison of student operator performance to computer simulations of expected operator performance generated by the Information Decision Action Crew (IDAC) HRA method. Areas of comparison include procedure steps, timing of operator actions, and PSFs. Second, development of a quantitative model of the simulator bias introduced by the simulator environment. Two types of bias are defined: Environmental Bias and Motivational Bias. This research examines Motivational Bias--that is, the effect of the simulator environment on an operator's motivations, goals, and priorities. A bias causal map is introduced to model motivational bias interactions in the OSU experiment. Data collected in the OSU NPP Simulator Facility are analyzed using Structural Equation Modeling (SEM). Data include crew characteristics, operator surveys, and time to recognize and diagnose the accident in the scenario. These models estimate how the effects of the scenario conditions are mediated by simulator bias, and demonstrate how to quantify the strength of the simulator bias. Third, development of a quantitative model of subjective PSFs based on objective data (plant parameters, alarms, etc.) and PSF values reported by student operators. The objective PSF model is based on the PSF network in the IDAC HRA method. The final model is a mixed effects Bayesian hierarchical linear regression model. The subjective PSF model includes three factors: The Environmental PSF, the simulator Bias, and the Context. The Environmental Bias is mediated by an operator sensitivity coefficient that captures the variation in operator reactions to plant conditions. The data collected in the pilot experiments are not expected to reflect professional NPP operator performance, because the students are still novice operators. However, the models used in this research and the methods developed to analyze them demonstrate how to consider simulator bias in experiment design and how to use simulator data to enhance the technical basis of a complex HRA method. The contributions of the research include a framework for discussing simulator bias, a quantitative method for estimating simulator bias, a method for obtaining operator-reported PSF values, and a quantitative method for incorporating the variability in operator perception into PSF models. The research demonstrates applications of Structural Equation Modeling and hierarchical Bayesian linear regression models in HRA. Finally, the research demonstrates the benefits of using student operators as a test platform for HRA research.
Dexter, Franklin; Willemsen-Dunlap, Ann; Lee, John D
2007-08-01
There are three basic types of decision aids to facilitate operating room (OR) management decision-making on the day of surgery. Decision makers can rely on passive status displays (e.g., big screens or whiteboards), active status displays (e.g., text pager notification), and/or command displays (e.g., text recommendations about what to do). Anesthesiologists, OR nurses, and housekeepers were given nine simulated scenarios (vignettes) involving multiple ORs to study their decision-making. Participants were randomized to one of four groups, all with an updated paper OR schedule: with/without command display and with/without passive status display. Participants making decisions without command displays performed no better than random chance in terms of increasing the predictability of work hours, reducing over-utilized OR time, and increasing OR efficiency. Status displays had no effect on these end-points, whereas command displays improved the quality of decisions. In the scenarios for which the command displays provided recommendations that adversely affected safety, participants appropriately ignored advice. Anesthesia providers and nursing staff made decisions that increased clinical work per unit time in each OR, even when doing so resulted in an increase in over-utilized OR time, higher staffing costs, unpredictable work hours, and/or mandatory overtime. Organizational culture and socialization during clinical training may be a cause. Command displays showed promise in mitigating this tendency. Additional investigations are in our companion paper.
NASA Astrophysics Data System (ADS)
Onken, Jeffrey
This dissertation introduces a multidisciplinary framework for the enabling of future research and analysis of alternatives for control centers for real-time operations of safety-critical systems. The multidisciplinary framework integrates functional and computational models that describe the dynamics in fundamental concepts of previously disparate engineering and psychology research disciplines, such as group performance and processes, supervisory control, situation awareness, events and delays, and expertise. The application in this dissertation is the real-time operations within the NASA Mission Control Center in Houston, TX. This dissertation operationalizes the framework into a model and simulation, which simulates the functional and computational models in the framework according to user-configured scenarios for a NASA human-spaceflight mission. The model and simulation generates data according to the effectiveness of the mission-control team in supporting the completion of mission objectives and detecting, isolating, and recovering from anomalies. Accompanying the multidisciplinary framework is a proof of concept, which demonstrates the feasibility of such a framework. The proof of concept demonstrates that variability occurs where expected based on the models. The proof of concept also demonstrates that the data generated from the model and simulation is useful for analyzing and comparing MCC configuration alternatives because an investigator can give a diverse set of scenarios to the simulation and the output compared in detail to inform decisions about the effect of MCC configurations on mission operations performance.
NASA Technical Reports Server (NTRS)
Bowen, Brent (Editor); Gudmundsson, Sveinn (Editor); Oum, Tae (Editor)
2003-01-01
Volume 3 of the 2003 Air Transport Reserch Society (ATRS) World Conference includes papers on topics relevant to airline operations worldwide. Specific topics include: European Union and civil aviation regimens;simulating decision making in airline operations, passenger points of view on convenient airports; route monopolies and nonlinear pricing; cooperation among airports in Europe; fleet modernizaiton in Brazil;the effects of deregulation on the growth of air transportation in Europe and the United States.
1985-10-03
Electrospace Systems, Inc. (ESI). ESI con- ducted a market search for training systems that would enhance unit level training, minimize cost-prohibitive...can be reprogrammed to simulate the UGC -129 keyboard. This keyboard is the standard keyboard used for data transmission on board the EC-135 and E-4B...with the appropriate technical order, and the functions and operation of the AN/ UGC -129 (ASR) terminals used with the AN/ASC-21 AFSATCOM system. In
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mumaw, R.J.
1994-08-01
Operational personnel may be exposed to significant levels of stress during unexpected changes in plant state an plant emergencies. The decision making that identifies operational actions, which is strongly determined by procedures, may be affected by stress, and performance may be impaired. ER report analyzes potential effects of stress in nuclear power plant (NPP) settings, especially in the context of severe accident management (SAM). First, potential sources of stress in the NPP setting are identified. This analysis is followed by a review of the ways in which stress is likely to affect performance, with an emphasis on performance of cognitivemore » skills that are linked to operational decision making. Finally, potential training approaches for reducing or eliminating stress effects are identified. Several training approaches have the potential to eliminate or mitigate stress effects on cognitive skill performance. First, the use of simulated events for training can reduce the novelty and uncertainty that can lead to stress and performance impairments. Second, training to make cognitive processing more efficient and less reliant on attention and memory resources can offset the reductions in these resources that occur under stressful conditions. Third, training that targets crew communications skills can reduce the likelihood that communications will fail under stress.« less
Applications of graphics to support a testbed for autonomous space vehicle operations
NASA Technical Reports Server (NTRS)
Schmeckpeper, K. R.; Aldridge, J. P.; Benson, S.; Horner, S.; Kullman, A.; Mulder, T.; Parrott, W.; Roman, D.; Watts, G.; Bochsler, Daniel C.
1989-01-01
Researchers describe their experience using graphics tools and utilities while building an application, AUTOPS, that uses a graphical Machintosh (TM)-like interface for the input and display of data, and animation graphics to enhance the presentation of results of autonomous space vehicle operations simulations. AUTOPS is a test bed for evaluating decisions for intelligent control systems for autonomous vehicles. Decisions made by an intelligent control system, e.g., a revised mission plan, might be displayed to the user in textual format or he can witness the effects of those decisions via out of window graphics animations. Although a textual description conveys essentials, a graphics animation conveys the replanning results in a more convincing way. Similarily, iconic and menu-driven screen interfaces provide the user with more meaningful options and displays. Presented here are experiences with the SunView and TAE Plus graphics tools used for interface design, and the Johnson Space Center Interactive Graphics Laboratory animation graphics tools used for generating out out of the window graphics.
Control Characteristics of Alcohol-Impaired Operators
NASA Technical Reports Server (NTRS)
Jex, Henry R.; McRuer, Duane T.; Allen, R. Wade; Klein, Richard H.
1974-01-01
Although the operation of vehicles like airplanes, cars, and bicycles involves a complex array of perceptual, decision and control activities, most accident statistics clearly show that intoxicated operators are a dominant cause of accidents, and not the difficulty of the task itself. This paper summarizes some recent research on the nature of the impairment of operator control under blood alcohol concentrations (BAC) up to above 0.16 percent. Alcohol toxicity is shown to be quite specific with respect to visual-motor functions involved in control of a vehicle, and experiments with a generalized workload task and special driving simulator show how these are reflected in terms of changes in operator control parameters such as response latency, gains, stability margins, and coherency.
NASA Astrophysics Data System (ADS)
LI, Y.; Castelletti, A.; Giuliani, M.
2014-12-01
Over recent years, long-term climate forecast from global circulation models (GCMs) has been demonstrated to show increasing skills over the climatology, thanks to the advances in the modelling of coupled ocean-atmosphere dynamics. Improved information from long-term forecast is supposed to be a valuable support to farmers in optimizing farming operations (e.g. crop choice, cropping time) and for more effectively coping with the adverse impacts of climate variability. Yet, evaluating how valuable this information can be is not straightforward and farmers' response must be taken into consideration. Indeed, while long-range forecast are traditionally evaluated in terms of accuracy by comparison of hindcast and observed values, in the context of agricultural systems, potentially useful forecast information should alter the stakeholders' expectation, modify their decisions and ultimately have an impact on their annual benefit. Therefore, it is more desirable to assess the value of those long-term forecasts via decision-making models so as to extract direct indication of probable decision outcomes from farmers, i.e. from an end-to-end perspective. In this work, we evaluate the operational value of thirteen state-of-the-art long-range forecast ensembles against climatology forecast and subjective prediction (i.e. past year climate and historical average) within an integrated agronomic modeling framework embedding an implicit model of farmers' behavior. Collected ensemble datasets are bias-corrected and downscaled using a stochastic weather generator, in order to address the mismatch of the spatio-temporal scale between forecast data from GCMs and distributed crop simulation model. The agronomic model is first simulated using the forecast information (ex-ante), followed by a second run with actual climate (ex-post). Multi-year simulations are performed to account for climate variability and the value of the different climate forecast is evaluated against the perfect foresight scenario based on the expected crop productivity as well as the land-use decisions. Our results show that not all the products generate beneficial effects to farmers and that the forecast errors might be amplified by the farmers decisions.
NASA Technical Reports Server (NTRS)
Hale, Joseph P.
2006-01-01
Models and simulations (M&S) are critical resources in the exploration of space. They support program management, systems engineering, integration, analysis, test, and operations and provide critical information and data supporting key analyses and decisions (technical, cost and schedule). Consequently, there is a clear need to establish a solid understanding of M&S strengths and weaknesses, and the bounds within which they can credibly support decision-making. Their usage requires the implementation of a rigorous approach to verification, validation and accreditation (W&A) and establishment of formal process and practices associated with their application. To ensure decision-making is suitably supported by information (data, models, test beds) from activities (studies, exercises) from M&S applications that are understood and characterized, ESMD is establishing formal, tailored W&A processes and practices. In addition, to ensure the successful application of M&S within ESMD, a formal process for the certification of analysts that use M&S is being implemented. This presentation will highlight NASA's Exploration Systems Mission Directorate (ESMD) management approach for M&S W&A to ensure decision-makers receive timely information on the model's fidelity, credibility, and quality.
NASA Astrophysics Data System (ADS)
Shawwash, Ziad Khaled Elias
2000-10-01
The electricity supply market is rapidly changing from a monopolistic to a competitive environment. Being able to operate their system of reservoirs and generating facilities to get maximum benefits out of existing assets and resources is important to the British Columbia Hydro Authority (B.C. Hydro). A decision support system has been developed to help B.C. Hydro operate their system in an optimal way. The system is operational and is one of the tools that are currently used by the B.C. Hydro system operations engineers to determine optimal schedules that meet the hourly domestic load and also maximize the value B.C. Hydro obtains from spot transactions in the Western U.S. and Alberta electricity markets. This dissertation describes the development and implementation of the decision support system in production mode. The decision support system consists of six components: the input data preparation routines, the graphical user interface (GUI), the communication protocols, the hydraulic simulation model, the optimization model, and the results display software. A major part of this work involved the development and implementation of a practical and detailed large-scale optimization model that determines the optimal tradeoff between the long-term value of water and the returns from spot trading transactions in real-time operations. The postmortem-testing phase showed that the gains in value from using the model accounted for 0.25% to 1.0% of the revenues obtained. The financial returns from using the decision support system greatly outweigh the costs of building it. Other benefits are the savings in the time needed to prepare the generation and trading schedules. The system operations engineers now can use the time saved to focus on other important aspects of their job. The operators are currently experimenting with the system in production mode, and are gradually gaining confidence that the advice it provides is accurate, reliable and sensible. The main lesson learned from developing and implementing the system was that there is no alternative to working very closely with the intended end-users of the system, and with the people who have deep knowledge, experience and understanding of how the system is and should be operated.
Bayramzadeh, Sara; Joseph, Anjali; Allison, David; Shultz, Jonas; Abernathy, James
2018-07-01
This paper describes the process and tools developed as part of a multidisciplinary collaborative simulation-based approach for iterative design and evaluation of operating room (OR) prototypes. Full-scale physical mock-ups of healthcare spaces offer an opportunity to actively communicate with and to engage multidisciplinary stakeholders in the design process. While mock-ups are increasingly being used in healthcare facility design projects, they are rarely evaluated in a manner to support active user feedback and engagement. Researchers and architecture students worked closely with clinicians and architects to develop OR design prototypes and engaged clinical end-users in simulated scenarios. An evaluation toolkit was developed to compare design prototypes. The mock-up evaluation helped the team make key decisions about room size, location of OR table, intra-room zoning, and doors location. Structured simulation based mock-up evaluations conducted in the design process can help stakeholders visualize their future workspace and provide active feedback. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Lebacqz, J. V.; Forrest, R. D.; Gerdes, R. M.
1982-01-01
A ground-simulation experiment was conducted to investigate the influence and interaction of flight-control system, fight-director display, and crew-loading situation on helicopter flying qualities during terminal area operations in instrument conditions. The experiment was conducted on the Flight Simulator for Advanced Aircraft at Ames Research Center. Six levels of control complexity, ranging from angular rate damping to velocity augmented longitudinal and vertical axes, were implemented on a representative helicopter model. The six levels of augmentation were examined with display variations consisting of raw elevation and azimuth data only, and of raw data plus one-, two-, and three-cue flight directors. Crew-loading situations simulated for the control-display combinations were dual-pilot operation (representative auxiliary tasks of navigation, communications, and decision-making). Four pilots performed a total of 150 evaluations of combinations of these parameters for a representative microwave landing system (MLS) approach task.
Pedestrians’ behavior in emergency evacuation: Modeling and simulation
NASA Astrophysics Data System (ADS)
Wang, Lei; Zheng, Jie-Hui; Zhang, Xiao-Shuang; Zhang, Jian-Lin; Wang, Qiu-Zhen; Zhang, Qian
2016-11-01
The social force model has been widely used to simulate pedestrian evacuation by analyzing attractive, repulsive, driving, and fluctuating forces among pedestrians. Many researchers have improved its limitations in simulating behaviors of large-scale population. This study modifies the well-accepted social force model by considering the impacts of interaction among companions and further develops a comprehensive model by combining that with a multi-exit utility function. Then numerical simulations of evacuations based on the comprehensive model are implemented in the waiting hall of the Wulin Square Subway Station in Hangzhou, China. The results provide safety thresholds of pedestrian density and panic levels in different operation situations. In spite of the operation situation and the panic level, a larger friend-group size results in lower evacuation efficiency. Our study makes important contributions to building a comprehensive multi-exit social force model and to applying it to actual scenarios, which produces data to facilitate decision making in contingency plans and emergency treatment. Project supported by the National Natural Science Foundation of China (Grant No. 71471163).
A Petri-net coordination model for an intelligent mobile robot
NASA Technical Reports Server (NTRS)
Wang, F.-Y.; Kyriakopoulos, K. J.; Tsolkas, A.; Saridis, G. N.
1990-01-01
The authors present a Petri net model of the coordination level of an intelligent mobile robot system (IMRS). The purpose of this model is to specify the integration of the individual efforts on path planning, supervisory motion control, and vision systems that are necessary for the autonomous operation of the mobile robot in a structured dynamic environment. This is achieved by analytically modeling the various units of the system as Petri net transducers and explicitly representing the task precedence and information dependence among them. The model can also be used to simulate the task processing and to evaluate the efficiency of operations and the responsibility of decisions in the coordination level of the IMRS. Some simulation results on the task processing and learning are presented.
Jackson, Simon A.; Kleitman, Sabina; Aidman, Eugene
2014-01-01
The present study investigated the effects of low cognitive workload and the absence of arousal induced via external physical stimulation (motion) on practice-related improvements in executive (inhibitory) control, short-term memory, metacognitive monitoring and decision making. A total of 70 office workers performed low and moderately engaging passenger tasks in two successive 20-minute simulated drives and repeated a battery of decision making and inhibitory control tests three times – before, between and after these drives. For half the participants, visual simulation was synchronised with (moderately arousing) motion generated through LAnd Motion Platform, with vibration levels corresponding to a well-maintained unsealed road. The other half performed the same simulated drive without motion. Participants’ performance significantly improved over the three test blocks, which is indicative of typical practice effects. The magnitude of these improvements was the highest when both motion and moderate cognitive load were present. The same effects declined either in the absence of motion (low arousal) or following a low cognitive workload task, thus suggesting two distinct pathways through which practice-related improvements in cognitive performance may be hampered. Practice, however, degraded certain aspects of metacognitive performance, as participants became less likely to detect incorrect decisions in the decision-making test with each subsequent test block. Implications include consideration of low cognitive load and arousal as factors responsible for performance decline and targets for the development of interventions/strategies in low load/arousal conditions such as autonomous vehicle operations and highway driving. PMID:25549327
Collaborative Arrival Planning: Data Sharing and User Preference Tools
NASA Technical Reports Server (NTRS)
Zelenka, Richard E.; Edwards, Thomas A. (Technical Monitor)
1998-01-01
Air traffic growth and air carrier economic pressures have motivated efforts to increase the flexibility of the air traffic management process and change the relationship between the air traffic control service provider and the system user. One of the most visible of these efforts is the U.S. government/industry "free flight" initiative, in which the service provider concentrates on safety and cross-airline fairness, and the user on their business objectives and operating preferences, including selecting their own path and speed in real-time. In the terminal arrival phase of flight, severe restrictions and rigid control are currently placed on system users, typically without regard for individual user operational preferences. Airborne delays applied to arriving aircraft into capacity constrained airports are imposed on a first-come, first-serve basis, and thus do not allow the system user to plan for or prioritize late arrivals, or to economically optimize their arrival sequence. A central tenant of the free-flight operating paradigm is collaboration between service providers and users in reaching air traffic management decisions. Such collaboration would be particularly beneficial to an airline's "hub" operation, where off-schedule arrival aircraft are a consistent problem, as they cause serious air-port ramp difficulties, rippling airline scheduling effects, and result in large economic inefficiencies. Greater collaboration can also lead to increased airport capacity and decrease the severity of over-capacity rush periods. In the NASA Collaborative Arrival Planning (CAP) project, both independent exchange of real-time data between the service provider and system user and collaborative decision support tools are addressed. Data exchange of real-time arrival scheduling, airspace management, and air carrier fleet data between the FAA service provider and an air carrier is being conducted and evaluated. Collaborative arrival decision support tools to allow intra-airline arrival preferences are being developed and simulated. The CAP project is part of and leveraged from the NASA/FAA Center TRACON Automation System (CTAS), a fielded set of decision support tools that provide computer generated advisories for both enroute and terminal area controllers to manage and control arrival traffic more efficiently. In this paper, the NASA Collaborative Arrival Planning project is outlined and recent results detailed, including the real-time use of CTAS arrival scheduling data by a major air carrier and simulations of tactical and strategic user preference decision support tools.
ERIC Educational Resources Information Center
Bessent, E. Wailand; And Others
Provided in the manual are background material, problems, and worksheets designed for graduate students involved in a computer assisted instruction (CAI) approach to supervisor training. Included are a faculty handbook for a simulated school in a mythical community, a practice problem to familiarize the student with terminal operation, and eight…
The Effect of Computer-Based Simulation Training on Fire Ground Incident Commander Decision Making
ERIC Educational Resources Information Center
Hall, Kurt A.
2010-01-01
Since the establishment of the first volunteer fire brigades in the United States, firefighters have lost their lives in fire fighting operations at emergency incidents and live-fire training activities. While there are various reasons for these firefighter deaths and injuries, the United States Fire Administration (2002) reported that many of…
NASA Astrophysics Data System (ADS)
Ibrahim, Ireen Munira; Liong, Choong-Yeun; Bakar, Sakhinah Abu; Ahmad, Norazura; Najmuddin, Ahmad Farid
2015-12-01
The Emergency Department (ED) is a very complex system with limited resources to support increase in demand. ED services are considered as good quality if they can meet the patient's expectation. Long waiting times and length of stay is always the main problem faced by the management. The management of ED should give greater emphasis on their capacity of resources in order to increase the quality of services, which conforms to patient satisfaction. This paper is a review of work in progress of a study being conducted in a government hospital in Selangor, Malaysia. This paper proposed a simulation optimization model framework which is used to study ED operations and problems as well as to find an optimal solution to the problems. The integration of simulation and optimization is hoped can assist management in decision making process regarding their resource capacity planning in order to improve current and future ED operations.
Decision Support Model for Optimal Management of Coastal Gate
NASA Astrophysics Data System (ADS)
Ditthakit, Pakorn; Chittaladakorn, Suwatana
2010-05-01
The coastal areas are intensely settled by human beings owing to their fertility of natural resources. However, at present those areas are facing with water scarcity problems: inadequate water and poor water quality as a result of saltwater intrusion and inappropriate land-use management. To solve these problems, several measures have been exploited. The coastal gate construction is a structural measure widely performed in several countries. This manner requires the plan for suitably operating coastal gates. Coastal gate operation is a complicated task and usually concerns with the management of multiple purposes, which are generally conflicted one another. This paper delineates the methodology and used theories for developing decision support modeling for coastal gate operation scheduling. The developed model was based on coupling simulation and optimization model. The weighting optimization technique based on Differential Evolution (DE) was selected herein for solving multiple objective problems. The hydrodynamic and water quality models were repeatedly invoked during searching the optimal gate operations. In addition, two forecasting models:- Auto Regressive model (AR model) and Harmonic Analysis model (HA model) were applied for forecasting water levels and tide levels, respectively. To demonstrate the applicability of the developed model, it was applied to plan the operations for hypothetical system of Pak Phanang coastal gate system, located in Nakhon Si Thammarat province, southern part of Thailand. It was found that the proposed model could satisfyingly assist decision-makers for operating coastal gates under various environmental, ecological and hydraulic conditions.
NASA Astrophysics Data System (ADS)
Song, Yanpo; Peng, Xiaoqi; Tang, Ying; Hu, Zhikun
2013-07-01
To improve the operation level of copper converter, the approach to optimal decision making modeling for coppermatte converting process based on data mining is studied: in view of the characteristics of the process data, such as containing noise, small sample size and so on, a new robust improved ANN (artificial neural network) modeling method is proposed; taking into account the application purpose of decision making model, three new evaluation indexes named support, confidence and relative confidence are proposed; using real production data and the methods mentioned above, optimal decision making model for blowing time of S1 period (the 1st slag producing period) are developed. Simulation results show that this model can significantly improve the converting quality of S1 period, increase the optimal probability from about 70% to about 85%.
Fault trees for decision making in systems analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lambert, Howard E.
1975-10-09
The application of fault tree analysis (FTA) to system safety and reliability is presented within the framework of system safety analysis. The concepts and techniques involved in manual and automated fault tree construction are described and their differences noted. The theory of mathematical reliability pertinent to FTA is presented with emphasis on engineering applications. An outline of the quantitative reliability techniques of the Reactor Safety Study is given. Concepts of probabilistic importance are presented within the fault tree framework and applied to the areas of system design, diagnosis and simulation. The computer code IMPORTANCE ranks basic events and cut setsmore » according to a sensitivity analysis. A useful feature of the IMPORTANCE code is that it can accept relative failure data as input. The output of the IMPORTANCE code can assist an analyst in finding weaknesses in system design and operation, suggest the most optimal course of system upgrade, and determine the optimal location of sensors within a system. A general simulation model of system failure in terms of fault tree logic is described. The model is intended for efficient diagnosis of the causes of system failure in the event of a system breakdown. It can also be used to assist an operator in making decisions under a time constraint regarding the future course of operations. The model is well suited for computer implementation. New results incorporated in the simulation model include an algorithm to generate repair checklists on the basis of fault tree logic and a one-step-ahead optimization procedure that minimizes the expected time to diagnose system failure.« less
NASA Astrophysics Data System (ADS)
Delaney, C.; Hartman, R. K.; Mendoza, J.; Whitin, B.
2017-12-01
Forecast informed reservoir operations (FIRO) is a methodology that incorporates short to mid-range precipitation and flow forecasts to inform the flood operations of reservoirs. The Ensemble Forecast Operations (EFO) alternative is a probabilistic approach of FIRO that incorporates ensemble streamflow predictions (ESPs) made by NOAA's California-Nevada River Forecast Center (CNRFC). With the EFO approach, release decisions are made to manage forecasted risk of reaching critical operational thresholds. A water management model was developed for Lake Mendocino, a 111,000 acre-foot reservoir located near Ukiah, California, to evaluate the viability of the EFO alternative to improve water supply reliability but not increase downstream flood risk. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United States Army Corps of Engineers and is operated for water supply by the Sonoma County Water Agency. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has suffered from water supply reliability issues since 2007. The EFO alternative was simulated using a 26-year (1985-2010) ESP hindcast generated by the CNRFC. The ESP hindcast was developed using Global Ensemble Forecast System version 10 precipitation reforecasts processed with the Hydrologic Ensemble Forecast System to generate daily reforecasts of 61 flow ensemble members for a 15-day forecast horizon. Model simulation results demonstrate that the EFO alternative may improve water supply reliability for Lake Mendocino yet not increase flood risk for downstream areas. The developed operations framework can directly leverage improved skill in the second week of the forecast and is extendable into the S2S time domain given the demonstration of improved skill through a reliable reforecast of adequate historical duration and consistent with operationally available numerical weather predictions.
NASA Astrophysics Data System (ADS)
Van Opstal, J.; Neale, C. M. U.; Lecina, S.
2014-12-01
Irrigation management is a dynamic process that adapts according to weather conditions and water availability, as well as socio-economic influences. The goal of water users is to adapt their management to achieve maximum profits. However, these decisions should take into account the environmental impact on the surroundings. Agricultural irrigation systems need to be viewed as a system that is an integral part of a watershed. Therefore changes in the infrastructure, operation and management of an irrigated area, has an impact on the water quantity and quality available for other water users. A strategy can be developed for decision-makers using an irrigation system modelling tool. Such a tool can simulate the impact of the infrastructure, operation and management of an irrigation area on its hydrology and agricultural productivity. This combination of factors is successfully simulated with the Ador model, which is able to reproduce on-farm irrigation and water delivery by a canal system. Model simulations for this study are supported with spatial analysis tools using GIS and remote sensing. Continuous measurements of drainage water will be added to indicate the water quality aspects. The Bear River Canal Company located in Northern Utah (U.S.A.) is used as a case study for this research. The irrigation area encompasses 26,000 ha and grows mainly alfalfa, grains, corn and onions. The model allows the simulation of different strategies related to water delivery, on-farm water use, crop rotations, and reservoirs and networks capacities under different weather and water availability conditions. Such changes in the irrigation area will have consequences for farmers in the study area regarding crop production, and for downstream users concerning both the quantity and quality of outflows. The findings from this study give insight to decision-makers and water users for changing irrigation water delivery strategies to improve the sustainability and profitability of agriculture in the future.
Spares Management : Optimizing Hardware Usage for the Space Shuttle Main Engine
NASA Technical Reports Server (NTRS)
Gulbrandsen, K. A.
1999-01-01
The complexity of the Space Shuttle Main Engine (SSME), combined with mounting requirements to reduce operations costs have increased demands for accurate tracking, maintenance, and projections of SSME assets. The SSME Logistics Team is developing an integrated asset management process. This PC-based tool provides a user-friendly asset database for daily decision making, plus a variable-input hardware usage simulation with complex logic yielding output that addresses essential asset management issues. Cycle times on critical tasks are significantly reduced. Associated costs have decreased as asset data quality and decision-making capability has increased.
2011-09-01
Frequency Division Multiplexing OLSR Optimized Link State Routing OODA Observe, Orient, Decide, Act (from John Boyd’s OODA-loop) OPP Operational...Colonel John Boyd [15]. The essence in the OODA-loop is to maintain initiative and tempo so that your decision cycle (Kill-Chain) is faster than that...Author, 1986. [16] “Intro to Command and Control,” class notes for CC3000, Naval Postgraduate School, December 2010. 86 [17] D. S. Fadok, John Boyd
Mass balances for a biological life support system simulation model
NASA Technical Reports Server (NTRS)
Volk, Tyler; Rumel, John D.
1987-01-01
Design decisions to aid the development of future space-based biological life support systems (BLSS) can be made with simulation models. Here the biochemical stoichiometry is developed for: (1) protein, carbohydrate, fat, fiber, and lignin production in the edible and inedible parts of plants; (2) food consumption and production of organic solids in urine, feces, and wash water by the humans; and (3) operation of the waste processor. Flux values for all components are derived for a steady-state system with wheat as the sole food source.
Estimating patient-specific soft-tissue properties in a TKA knee.
Ewing, Joseph A; Kaufman, Michelle K; Hutter, Erin E; Granger, Jeffrey F; Beal, Matthew D; Piazza, Stephen J; Siston, Robert A
2016-03-01
Surgical technique is one factor that has been identified as critical to success of total knee arthroplasty. Researchers have shown that computer simulations can aid in determining how decisions in the operating room generally affect post-operative outcomes. However, to use simulations to make clinically relevant predictions about knee forces and motions for a specific total knee patient, patient-specific models are needed. This study introduces a methodology for estimating knee soft-tissue properties of an individual total knee patient. A custom surgical navigation system and stability device were used to measure the force-displacement relationship of the knee. Soft-tissue properties were estimated using a parameter optimization that matched simulated tibiofemoral kinematics with experimental tibiofemoral kinematics. Simulations using optimized ligament properties had an average root mean square error of 3.5° across all tests while simulations using generic ligament properties taken from literature had an average root mean square error of 8.4°. Specimens showed large variability among ligament properties regardless of similarities in prosthetic component alignment and measured knee laxity. These results demonstrate the importance of soft-tissue properties in determining knee stability, and suggest that to make clinically relevant predictions of post-operative knee motions and forces using computer simulations, patient-specific soft-tissue properties are needed. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.
Effect of Training in Rational Decision Making on the Quality of Simulated Career Decisions.
ERIC Educational Resources Information Center
Krumboltz, John D.; And Others
1982-01-01
Determined if training in rational decision making improves the quality of simulated career decisions. Training in rational decision making resulted in superior performance for females on one subscore of the knowledge measure. It also resulted in superior simulated career choices by females and younger males. (Author)
Automated control of hierarchical systems using value-driven methods
NASA Technical Reports Server (NTRS)
Pugh, George E.; Burke, Thomas E.
1990-01-01
An introduction is given to the Value-driven methodology, which has been successfully applied to solve a variety of difficult decision, control, and optimization problems. Many real-world decision processes (e.g., those encountered in scheduling, allocation, and command and control) involve a hierarchy of complex planning considerations. For such problems it is virtually impossible to define a fixed set of rules that will operate satisfactorily over the full range of probable contingencies. Decision Science Applications' value-driven methodology offers a systematic way of automating the intuitive, common-sense approach used by human planners. The inherent responsiveness of value-driven systems to user-controlled priorities makes them particularly suitable for semi-automated applications in which the user must remain in command of the systems operation. Three examples of the practical application of the approach in the automation of hierarchical decision processes are discussed: the TAC Brawler air-to-air combat simulation is a four-level computerized hierarchy; the autonomous underwater vehicle mission planning system is a three-level control system; and the Space Station Freedom electrical power control and scheduling system is designed as a two-level hierarchy. The methodology is compared with rule-based systems and with other more widely-known optimization techniques.
Noonan, Vanessa K; Soril, Lesley; Atkins, Derek; Lewis, Rachel; Santos, Argelio; Fehlings, Michael G; Burns, Anthony S; Singh, Anoushka; Dvorak, Marcel F
2012-09-01
The long-term impact of spinal cord injury (SCI) on the health care system imposes a need for greater efficiency in the use of resources and the management of care. The Access to Care and Timing (ACT) project was developed to model the health care delivery system in Canada for patients with traumatic SCI. Techniques from Operations Research, such as simulation modeling, were used to predict the impact of best practices and policy initiatives on outcomes related to both the system and patients. These methods have been used to solve similar problems in business and engineering and may offer a unique solution to the complexities encountered in SCI care delivery. Findings from various simulated scenarios, from the patients' point of injury to community re-integration, can be used to inform decisions on optimizing practice across the care continuum. This article describes specifically the methodology and implications of producing such simulations for the care of traumatic SCI in Canada. Future publications will report on specific practices pertaining to the access to specialized services and the timing of interventions evaluated using the ACT model. Results from this type of research will provide the evidence required to support clinical decision making, inform standards of care, and provide an opportunity to engage policymakers.
Noonan, Vanessa K.; Soril, Lesley; Atkins, Derek; Lewis, Rachel; Santos, Argelio; Fehlings, Michael G.; Burns, Anthony S.; Singh, Anoushka
2012-01-01
Abstract The long-term impact of spinal cord injury (SCI) on the health care system imposes a need for greater efficiency in the use of resources and the management of care. The Access to Care and Timing (ACT) project was developed to model the health care delivery system in Canada for patients with traumatic SCI. Techniques from Operations Research, such as simulation modeling, were used to predict the impact of best practices and policy initiatives on outcomes related to both the system and patients. These methods have been used to solve similar problems in business and engineering and may offer a unique solution to the complexities encountered in SCI care delivery. Findings from various simulated scenarios, from the patients' point of injury to community re-integration, can be used to inform decisions on optimizing practice across the care continuum. This article describes specifically the methodology and implications of producing such simulations for the care of traumatic SCI in Canada. Future publications will report on specific practices pertaining to the access to specialized services and the timing of interventions evaluated using the ACT model. Results from this type of research will provide the evidence required to support clinical decision making, inform standards of care, and provide an opportunity to engage policymakers. PMID:22800432
HNS-MS : Improving Member States preparedness to face an HNS pollution of the Marine System
NASA Astrophysics Data System (ADS)
Legrand, Sebastien; Le Floch, Stéphane; Aprin, Laurent; Parthenay, Valérie; Donnay, Eric; Parmentier, Koen; Ovidio, Fabrice; Schallier, Ronny; Poncet, Florence; Chataing, Sophie; Poupon, Emmanuelle; Hellouvry, Yann-Hervé
2016-04-01
When dealing with a HNS pollution incident, one of the priority requirements is the identification of the hazard and an assessment of the risk posed to the public and responder safety, the environment and socioeconomic assets upon which a state or coastal community depend. The primary factors which determine the safety, environmental and socioeconomic impact of the released substance(s) relate to their physico-chemical properties and fate in the environment. Until now, preparedness actions at various levels have primarily aimed at classifying the general environmental or public health hazard of an HNS, or at performing a risk analysis of HNS transported in European marine regions. Operational datasheets have been (MIDSIS-TROCS) or are being (MAR-CIS) developed collating detailed, substance-specific information for responders and covering information needs at the first stage of an incident. However, contrary to oil pollution preparedness and response tools, only few decision-support tools used by Member State authorities (Coastguard agencies or other) integrate 3D models that are able to simulate the drift, fate and behaviour of HNS spills in the marine environment. When they do, they usually consider simplified or steady-state environmental conditions. Moreover, the above-mentioned available HNS information is currently not sufficiently detailed or not suitably classified to be used as an input for an advanced HNS support decision tool. HNS-MS aims at developing a 'one-stop shop' integrated HNS decision-support tool that is able to predict the drift, behaviour and Fate of HNS spills under realistic environmental conditions and at providing key product information - drawing upon and in complement to existing studies and databases - to improve the understanding and evaluation of a HNS spill situation in the field and the environmental and safety-related issues at stake. The 3D HNS drift and fate model and decision-support tool will also be useful at the preparedness stage. The expected results will be an operational HNS decision-support tool (prototype) for the Bonn Agreement area that can also be viewed as a demonstrator tool for other European marine regions. The developed tool will have a similar operational level as OSERIT, the Belgian oil spill drift model. The HNS decision-support tool will integrate the following features: 1. A database containing the physico-chemical parameters needed to compute the behaviour in the marine environment of 100+ relevant HNS; 2. A database of environmental and socioeconomic HNS-sensitive features; 3. A three dimensional HNS spill drift and fate model able to simulate HNS behaviour in the marine environment (including floaters, sinkers, evaporators and dissolvers). 4. A user-friendly web-based interface allowing Coastguard stations to launch a HNS drift simulation and visualize post-processed results in support of an incident evaluation and decision-making process. In this contribution, we will present the methodology followed to develop these four features.
NASA Astrophysics Data System (ADS)
Raseman, W. J.; Kasprzyk, J. R.; Rosario-Ortiz, F.; Summers, R. S.; Stewart, J.; Livneh, B.
2016-12-01
To promote public health, the United States Environmental Protection Agency (US EPA), and similar entities around the world enact strict laws to regulate drinking water quality. These laws, such as the Stage 1 and 2 Disinfectants and Disinfection Byproducts (D/DBP) Rules, come at a cost to water treatment plants (WTPs) which must alter their operations and designs to meet more stringent standards and the regulation of new contaminants of concern. Moreover, external factors such as changing influent water quality due to climate extremes and climate change, may force WTPs to adapt their treatment methods. To grapple with these issues, decision support systems (DSSs) have been developed to aid WTP operation and planning. However, there is a critical need to better address long-term decision making for WTPs. In this poster, we propose a DSS framework for WTPs for long-term planning, which improves upon the current treatment of deep uncertainties within the overall potable water system including the impact of climate on influent water quality and uncertainties in treatment process efficiencies. We present preliminary results exploring how a multi-objective evolutionary algorithm (MOEA) search can be coupled with models of WTP processes to identify high-performing plans for their design and operation. This coupled simulation-optimization technique uses Borg MOEA, an auto-adaptive algorithm, and the Water Treatment Plant Model, a simulation model developed by the US EPA to assist in creating the D/DBP Rules. Additionally, Monte Carlo sampling methods were used to study the impact of uncertainty of influent water quality on WTP decision-making and generate plans for robust WTP performance.
Methods for optimizing solutions when considering group arguments by team of experts
NASA Astrophysics Data System (ADS)
Chernyi, Sergei; Budnik, Vlad
2017-11-01
The article is devoted to methods of expert evaluation. The technology of expert evaluation is presented from the standpoint of precedent structures. In this paper, an aspect of the mathematical basis for constructing a component of decision analysis is considered. In fact, this approach leaves out any identification of their knowledge and skills of simulating organizational and manufacturing situations and taking efficient managerial decisions; it doesn't enable any identification and assessment of their knowledge on the basis of multi-informational and least loss-making methods and information technologies. Hence the problem is to research and develop a methodology for systemic identification of professional problem-focused knowledge acquired by employees operating adaptive automated systems of training management (AASTM operators), which shall also further the theory and practice of the intelligence-related aspects thereof.
Technical Basis for Physical Fidelity of NRC Control Room Training Simulators for Advanced Reactors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Minsk, Brian S.; Branch, Kristi M.; Bates, Edward K.
2009-10-09
The objective of this study is to determine how simulator physical fidelity influences the effectiveness of training the regulatory personnel responsible for examination and oversight of operating personnel and inspection of technical systems at nuclear power reactors. It seeks to contribute to the U.S. Nuclear Regulatory Commission’s (NRC’s) understanding of the physical fidelity requirements of training simulators. The goal of the study is to provide an analytic framework, data, and analyses that inform NRC decisions about the physical fidelity requirements of the simulators it will need to train its staff for assignment at advanced reactors. These staff are expected tomore » come from increasingly diverse educational and experiential backgrounds.« less
NASA Astrophysics Data System (ADS)
Murphy, Elizabeth Drummond
As advances in technology are applied in complex, semi-automated domains, human controllers are distanced from the controlled process. This physical and psychological distance may both facilitate and degrade human performance. To investigate cognitive issues in spacecraft ground-control operations, the present experimental research was undertaken. The primary issue concerned the ability of operations analysts who do not monitor operations to make timely, accurate decisions when autonomous software calls for human help. Another key issue involved the potential effects of spatial-visualization ability (SVA) in environments that present data in graphical formats. Hypotheses were derived largely from previous findings and predictions in the literature. Undergraduate psychology students were assigned at random to a monitoring condition or an on-call condition in a scaled environment. The experimental task required subjects to decide on the veracity of a problem diagnosis delivered by a software process on-board a simulated spacecraft. To support decision-making, tabular and graphical data displays presented information on system status. A level of software confidence in the problem diagnosis was displayed, and subjects reported their own level of confidence in their decisions. Contrary to expectations, the performance of on-call subjects did not differ significantly from that of continuous monitors. Analysis yielded a significant interaction of sex and condition: Females in the on-call condition had the lowest mean accuracy. Results included a preference for bar charts over line graphs and faster performance with tables than with line graphs. A significant correlation was found between subjective confidence and decision accuracy. SVA was found to be predictive of accuracy but not speed; and SVA was found to be a stronger predictor of performance for males than for females. Low-SVA subjects reported that they relied more on software confidence than did medium- or high-SVA subjects. These and other findings have implications for the design of user interfaces to support human decision-making in on-call situations and to accommodate low-SVA users.
The Space Environmental Impact System
NASA Astrophysics Data System (ADS)
Kihn, E. A.
2009-12-01
The Space Environmental Impact System (SEIS) is an operational tool for incorporating environmental data sets into DoD Modeling and Simulation (M&S) which allows for enhanced decision making regarding acquisitions, testing, operations and planning. The SEIS system creates, from the environmental archives and developed rule-base, a tool for describing the effects of the space environment on particular military systems, both historically and in real-time. The system uses data available over the web, and in particular data provided by NASA’s virtual observatory network, as well as modeled data generated specifically for this purpose. The rule base system developed to support SEIS is an open XML based model which can be extended to events from any environmental domain. This presentation will show how the SEIS tool allows users to easily and accurately evaluate the effect of space weather in terms that are meaningful to them as well as discuss the relevant standards used in its construction and go over lessons learned from fielding an operational environmental decision tool.
Modeling Energy Efficiency As A Green Logistics Component In Vehicle Assembly Line
NASA Astrophysics Data System (ADS)
Oumer, Abduaziz; Mekbib Atnaw, Samson; Kie Cheng, Jack; Singh, Lakveer
2016-11-01
This paper uses System Dynamics (SD) simulation to investigate the concept green logistics in terms of energy efficiency in automotive industry. The car manufacturing industry is considered to be one of the highest energy consuming industries. An efficient decision making model is proposed that capture the impacts of strategic decisions on energy consumption and environmental sustainability. The sources of energy considered in this research are electricity and fuel; which are the two main types of energy sources used in a typical vehicle assembly plant. The model depicts the performance measurement for process- specific energy measures of painting, welding, and assembling processes. SD is the chosen simulation method and the main green logistics issues considered are Carbon Dioxide (CO2) emission and energy utilization. The model will assist decision makers acquire an in-depth understanding of relationship between high level planning and low level operation activities on production, environmental impacts and costs associated. The results of the SD model signify the existence of positive trade-offs between green practices of energy efficiency and the reduction of CO2 emission.
A new fit-for-purpose model testing framework: Decision Crash Tests
NASA Astrophysics Data System (ADS)
Tolson, Bryan; Craig, James
2016-04-01
Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building decisions. In one case, we show the set of model building decisions has a low probability to correctly support the upgrade decision. In the other case, we show evidence suggesting another set of model building decisions has a high probability to correctly support the decision. The proposed DCT framework focuses on what model users typically care about: the management decision in question. The DCT framework will often be very strict and will produce easy to interpret results enabling clear unsuitability determinations. In the past, hydrologic modelling progress has necessarily meant new models and model building methods. Continued progress in hydrologic modelling requires finding clear evidence to motivate researchers to disregard unproductive models and methods and the DCT framework is built to produce this kind of evidence. References: Andréassian, V., C. Perrin, L. Berthet, N. Le Moine, J. Lerat, C. Loumagne, L. Oudin, T. Mathevet, M.-H. Ramos, and A. Valéry (2009), Crash tests for a standardized evaluation of hydrological models. Hydrology and Earth System Sciences, 13, 1757-1764. Klemeš, V. (1986), Operational testing of hydrological simulation models. Hydrological Sciences Journal, 31 (1), 13-24.
Distributed Decision Making in a Dynamic Network Environment
1990-01-01
protocols, particularly when traffic arrival statistics are varying or unknown, and loads are high. Both nonpreemptive and preemptive repeat disciplines are...The simulation model allows general value functions, continuous time operation, and preemptive or nonpreemptive service. For reasons of tractability... nonpreemptive LIFO, (4) nonpreemptive LIFO with discarding, (5) nonpreemptive HOL, (6) nonpreemp- tive HOL with discarding, (7) preemptive repeat HOL, (8
Dave Calkin; Matthew P. Thompson; Alan A. Ager; Mark Finney
2010-01-01
In this presentation we review progress towards the implementation of a risk-based management framework for U.S. Federal wildland fire policy and operations. We first describe new developments in wildfire simulation technology that catalyzed the development of risk-based decision support systems for strategic wildfire management. These systems include new analytical...
Investigation of injury data at a detonator facility
Cournoyer, Michael E.; Apodaca, Marylou; Bustamante, Robert A.; ...
2016-05-01
This paper focuses on the collection of injury data; incorporation of this information into a visual format that DET management uses to make decisions to improving operations. Results from this 1 study include of the following: chemical exposure cases have declined because the Hazard Assessment of each DET operation has been formally reviewed; Slip/Trip/Fall factors have decreased due to Slip Simulator training; and work station evaluations have led to fewer injuries with Lift/Push/Pull factors. Rotation of employees, ergonomically friendly balances, automatic powder dispensers, and other equipment procurements will lower ergonomic injuries.
Investigation of injury data at a detonator facility
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cournoyer, Michael E.; Apodaca, Marylou; Bustamante, Robert A.
This paper focuses on the collection of injury data; incorporation of this information into a visual format that DET management uses to make decisions to improving operations. Results from this 1 study include of the following: chemical exposure cases have declined because the Hazard Assessment of each DET operation has been formally reviewed; Slip/Trip/Fall factors have decreased due to Slip Simulator training; and work station evaluations have led to fewer injuries with Lift/Push/Pull factors. Rotation of employees, ergonomically friendly balances, automatic powder dispensers, and other equipment procurements will lower ergonomic injuries.
NASA Astrophysics Data System (ADS)
Si, Y.; Li, X.; Li, T.; Huang, Y.; Yin, D.
2016-12-01
The cascade reservoirs in Upper Yellow River (UYR), one of the largest hydropower bases in China, play a vital role in peak load and frequency regulation for Northwest China Power Grid. The joint operation of this system has been put forward for years whereas has not come into effect due to management difficulties and inflow uncertainties, and thus there is still considerable improvement room for hydropower production. This study presents a decision support framework incorporating long- and short-term operation of the reservoir system. For long-term operation, we maximize hydropower production of the reservoir system using historical hydrological data of multiple years, and derive operating rule curves for storage reservoirs. For short-term operation, we develop a program consisting of three modules, namely hydrologic forecast module, reservoir operation module and coordination module. The coordination module is responsible for calling the hydrologic forecast module to acquire predicted inflow within a short-term horizon, and transferring the information to the reservoir operation module to generate optimal release decision. With the hydrologic forecast information updated, the rolling short-term optimization is iterated until the end of operation period, where the long-term operating curves serve as the ending storage target. As an application, the Digital Yellow River Integrated Model (referred to as "DYRIM", which is specially designed for runoff-sediment simulation in the Yellow River basin by Tsinghua University) is used in the hydrologic forecast module, and the successive linear programming (SLP) in the reservoir operation module. The application in the reservoir system of UYR demonstrates that the framework can effectively support real-time decision making, and ensure both computational accuracy and speed. Furthermore, it is worth noting that the general framework can be extended to any other reservoir system with any or combination of hydrological model(s) to forecast and any solver to optimize the operation of reservoir system.
NASA Technical Reports Server (NTRS)
Kramer, Lynda J.; Bailey, Randall E.; Prinzel, Lawrence J., III
2007-01-01
NASA is investigating revolutionary crew-vehicle interface technologies that strive to proactively overcome aircraft safety barriers that would otherwise constrain the full realization of the next-generation air transportation system. A fixed-based piloted simulation experiment was conducted to evaluate the complementary use of Synthetic and Enhanced Vision technologies. Specific focus was placed on new techniques for integration and/or fusion of Enhanced and Synthetic Vision and its impact within a two-crew flight deck on the crew's decision-making process during low-visibility approach and landing operations. Overall, the experimental data showed that significant improvements in situation awareness, without concomitant increases in workload and display clutter, could be provided by the integration and/or fusion of synthetic and enhanced vision technologies for the pilot-flying and the pilot-not-flying. During non-normal operations, the ability of the crew to handle substantial navigational errors and runway incursions were neither improved nor adversely impacted by the display concepts. The addition of Enhanced Vision may not, unto itself, provide an improvement in runway incursion detection without being specifically tailored for this application. Existing enhanced vision system procedures were effectively used in the crew decision-making process during approach and missed approach operations but having to forcibly transition from an excellent FLIR image to natural vision by 100 ft above field level was awkward for the pilot-flying.
NASA Astrophysics Data System (ADS)
Pulido-Velazquez, Manuel; Macian-Sorribes, Hector; María Benlliure-Moreno, Jose; Fullana-Montoro, Juan
2015-04-01
Water resources systems in areas with a strong tradition in water use are complex to manage by the high amount of constraints that overlap in time and space, creating a complicated framework in which past, present and future collide between them. In addition, it is usual to find "hidden constraints" in system operations, which condition operation decisions being unnoticed by anyone but the river managers and users. Being aware of those hidden constraints requires usually years of experience and a degree of involvement in that system's management operations normally beyond the possibilities of technicians. However, their impact in the management decisions is strongly imprinted in the historical data records available. The purpose of this contribution is to present a methodology capable of assessing operating rules in complex water resources systems combining historical records and expert criteria. Both sources are coupled using fuzzy logic. The procedure stages are: 1) organize expert-technicians preliminary meetings to let the first explain how they manage the system; 2) set up a fuzzy rule-based system (FRB) structure according to the way the system is managed; 3) use the historical records available to estimate the inputs' fuzzy numbers, to assign preliminary output values to the FRB rules and to train and validate these rules; 4) organize expert-technician meetings to discuss the rule structure and the input's quantification, returning if required to the second stage; 5) once the FRB structure is accepted, its output values must be refined and completed with the aid of the experts by using meetings, workshops or surveys; 6) combine the FRB with a Decision Support System (DSS) to simulate the effect of those management decisions; 7) compare its results with the ones offered by the historical records and/or simulation or optimization models; and 8) discuss with the stakeholders the model performance returning, if it's required, to the fifth or the second stage. The methodology proposed has been applied to the Jucar River Basin (Spain). This basin has 3 reservoirs, 4 headwaters, 11 demands and 5 environmental flows; which form together a complex constraint set. After the preliminary meetings, one 81-rule FRB was created, using as inputs the system state variables at the start of the hydrologic year, and as outputs the target reservoir release schedule. The inputs' fuzzy numbers were estimated jointly using surveys. Fifteen years of historical records were used to train the system's outputs. The obtained FRB was then refined during additional expert-technician meetings. After that, the resulting FRB was introduced into a DSS simulating the effect of those management rules for different hydrological conditions. Three additional FRB's were created using: 1) exclusively the historical records; 2) a stochastic optimization model; and 3) a deterministic optimization model. The results proved to be consistent with the expectations, with the stakeholder's FRB performance located between the data-driven simulation and the stochastic optimization FRB's; and reflect the stakeholders' major goals and concerns about the river management. ACKNOWLEDGEMENT: This study has been partially supported by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) funds.
Integrating Solar PV in Utility System Operations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mills, A.; Botterud, A.; Wu, J.
2013-10-31
This study develops a systematic framework for estimating the increase in operating costs due to uncertainty and variability in renewable resources, uses the framework to quantify the integration costs associated with sub-hourly solar power variability and uncertainty, and shows how changes in system operations may affect these costs. Toward this end, we present a statistical method for estimating the required balancing reserves to maintain system reliability along with a model for commitment and dispatch of the portfolio of thermal and renewable resources at different stages of system operations. We estimate the costs of sub-hourly solar variability, short-term forecast errors, andmore » day-ahead (DA) forecast errors as the difference in production costs between a case with “realistic” PV (i.e., subhourly solar variability and uncertainty are fully included in the modeling) and a case with “well behaved” PV (i.e., PV is assumed to have no sub-hourly variability and can be perfectly forecasted). In addition, we highlight current practices that allow utilities to compensate for the issues encountered at the sub-hourly time frame with increased levels of PV penetration. In this analysis we use the analytical framework to simulate utility operations with increasing deployment of PV in a case study of Arizona Public Service Company (APS), a utility in the southwestern United States. In our analysis, we focus on three processes that are important in understanding the management of PV variability and uncertainty in power system operations. First, we represent the decisions made the day before the operating day through a DA commitment model that relies on imperfect DA forecasts of load and wind as well as PV generation. Second, we represent the decisions made by schedulers in the operating day through hour-ahead (HA) scheduling. Peaking units can be committed or decommitted in the HA schedules and online units can be redispatched using forecasts that are improved relative to DA forecasts, but still imperfect. Finally, we represent decisions within the operating hour by schedulers and transmission system operators as real-time (RT) balancing. We simulate the DA and HA scheduling processes with a detailed unit-commitment (UC) and economic dispatch (ED) optimization model. This model creates a least-cost dispatch and commitment plan for the conventional generating units using forecasts and reserve requirements as inputs. We consider only the generation units and load of the utility in this analysis; we do not consider opportunities to trade power with neighboring utilities. We also do not consider provision of reserves from renewables or from demand-side options. We estimate dynamic reserve requirements in order to meet reliability requirements in the RT operations, considering the uncertainty and variability in load, solar PV, and wind resources. Balancing reserve requirements are based on the 2.5th and 97.5th percentile of 1-min deviations from the HA schedule in a previous year. We then simulate RT deployment of balancing reserves using a separate minute-by-minute simulation of deviations from the HA schedules in the operating year. In the simulations we assume that balancing reserves can be fully deployed in 10 min. The minute-by-minute deviations account for HA forecasting errors and the actual variability of the load, wind, and solar generation. Using these minute-by-minute deviations and deployment of balancing reserves, we evaluate the impact of PV on system reliability through the calculation of the standard reliability metric called Control Performance Standard 2 (CPS2). Broadly speaking, the CPS2 score measures the percentage of 10-min periods in which a balancing area is able to balance supply and demand within a specific threshold. Compliance with the North American Electric Reliability Corporation (NERC) reliability standards requires that the CPS2 score must exceed 90% (i.e., the balancing area must maintain adequate balance for 90% of the 10-min periods). The combination of representing DA forecast errors in the DA commitments, using 1-min PV data to simulate RT balancing, and estimates of reliability performance through the CPS2 metric, all factors that are important to operating systems with increasing amounts of PV, makes this study unique in its scope.« less
The effect of simulated narratives that leverage EMR data on shared decision-making: a pilot study.
Zeng-Treitler, Qing; Gibson, Bryan; Hill, Brent; Butler, Jorie; Christensen, Carrie; Redd, Douglas; Shao, Yijun; Bray, Bruce
2016-07-22
Shared decision-making can improve patient satisfaction and outcomes. To participate in shared decision-making, patients need information about the potential risks and benefits of treatment options. Our team has developed a novel prototype tool for shared decision-making called hearts like mine (HLM) that leverages EHR data to provide personalized information to patients regarding potential outcomes of different treatments. These potential outcomes are presented through an Icon array and/or simulated narratives for each "person" in the display. In this pilot project we sought to determine whether the inclusion of simulated narratives in the display affects individuals' decision-making. Thirty subjects participated in this block-randomized study in which they used a version of HLM with simulated narratives and a version without (or in the opposite order) to make a hypothetical therapeutic decision. After each decision, participants completed a questionnaire that measured decisional confidence. We used Chi square tests to compare decisions across conditions and Mann-Whitney U tests to examine the effects of narratives on decisional confidence. Finally, we calculated the mean of subjects' post-experiment rating of whether narratives were helpful in their decision-making. In this study, there was no effect of simulated narratives on treatment decisions (decision 1: Chi squared = 0, p = 1.0; decision 2: Chi squared = 0.574, p = 0.44) or Decisional confidence (decision 1, w = 105.5, p = 0.78; decision 2, w = 86.5, p = 0.28). Post-experiment, participants reported that narratives helped them to make decisions (mean = 3.3/4). We found that simulated narratives had no measurable effect on decisional confidence or decisions and most participants felt that the narratives were helpful to them in making therapeutic decisions. The use of simulated stories holds promise for promoting shared decision-making while minimizing their potential biasing effect.
NASA Astrophysics Data System (ADS)
Arnold, Jeffrey; Clark, Martyn; Gutmann, Ethan; Wood, Andy; Nijssen, Bart; Rasmussen, Roy
2016-04-01
The United States Army Corps of Engineers (USACE) has had primary responsibility for multi-purpose water resource operations on most of the major river systems in the U.S. for more than 200 years. In that time, the USACE projects and programs making up those operations have proved mostly robust against the range of natural climate variability encountered over their operating life spans. However, in some watersheds and for some variables, climate change now is known to be shifting the hydroclimatic baseline around which that natural variability occurs and changing the range of that variability as well. This makes historical stationarity an inappropriate basis for assessing continued project operations under climate-changed futures. That means new hydroclimatic projections are required at multiple scales to inform decisions about specific threats and impacts, and for possible adaptation responses to limit water-resource vulnerabilities and enhance operational resilience. However, projections of possible future hydroclimatologies have myriad complex uncertainties that require explicit guidance for interpreting and using them to inform those decisions about climate vulnerabilities and resilience. Moreover, many of these uncertainties overlap and interact. Recent work, for example, has shown the importance of assessing the uncertainties from multiple sources including: global model structure [Meehl et al., 2005; Knutti and Sedlacek, 2013]; internal climate variability [Deser et al., 2012; Kay et al., 2014]; climate downscaling methods [Gutmann et al., 2012; Mearns et al., 2013]; and hydrologic models [Addor et al., 2014; Vano et al., 2014; Mendoza et al., 2015]. Revealing, reducing, and representing these uncertainties is essential for defining the plausible quantitative climate change narratives required to inform water-resource decision-making. And to be useful, such quantitative narratives, or storylines, of climate change threats and hydrologic impacts must sample from the full range of uncertainties associated with all parts of the simulation chain, from global climate models with simulations of natural climate variability, through regional climate downscaling, and on to modeling of affected hydrologic processes and downstream water resources impacts. This talk will present part of the work underway now both to reveal and reduce some important uncertainties and to develop explicit guidance for future generation of quantitative hydroclimatic storylines. Topics will include: 1- model structural and parameter-set limitations of some methods widely used to quantify climate impacts to hydrologic processes [Gutmann et al., 2014; Newman et al., 2015]; 2- development and evaluation of new, spatially consistent, U.S. national-scale climate downscaling and hydrologic simulation capabilities directly relevant at the multiple scales of water-resource decision-making [Newman et al., 2015; Mizukami et al., 2015; Gutmann et al., 2016]; and 3- development and evaluation of advanced streamflow forecasting methods to reduce and represent integrated uncertainties in a tractable way [Wood et al., 2014; Wood et al., 2015]. A key focus will be areas where climatologic and hydrologic science is currently under-developed to inform decisions - or is perhaps wrongly scaled or misapplied in practice - indicating the need for additional fundamental science and interpretation.
The Cumberland River Flood of 2010 and Corps Reservoir Operations
NASA Astrophysics Data System (ADS)
Charley, W.; Hanbali, F.; Rohrbach, B.
2010-12-01
On Saturday, May 1, 2010, heavy rain began falling in the Cumberland River Valley and continued through the following day. 13.5 inches was measured at Nashville, an unprecedented amount that doubled the previous 2-day record, and exceeded the May monthly total record of 11 inches. Elsewhere in the valley, amounts of over 19 inches were measured. The frequency of this storm was estimated to exceed the one-thousand year event. This historic rainfall brought large scale flooding to the Cumberland-Ohio-Tennessee River Valleys, and caused over 2 billion dollars in damages, despite the numerous flood control projects in the area, including eight U.S. Army Corps of Engineers projects. The vast majority of rainfall occurred in drainage areas that are uncontrolled by Corps flood control projects, which lead to the wide area flooding. However, preliminary analysis indicates that operations of the Corps projects reduced the Cumberland River flood crest in Nashville by approximately five feet. With funding from the American Recovery and Reinvestment Act (ARRA) of 2009, hydrologic, hydraulic and reservoir simulation models have just been completed for the Cumberland-Ohio-Tennessee River Valleys. These models are being implemented in the Corps Water Management System (CWMS), a comprehensive data acquisition and hydrologic modeling system for short-term decision support of water control operations in real time. The CWMS modeling component uses observed rainfall and forecasted rainfall to compute forecasts of river flows into and downstream of reservoirs, using HEC-HMS. Simulation of reservoir operations, utilizing either the HEC-ResSim or CADSWES RiverWare program, uses these flow scenarios to provide operational decision information for the engineer. The river hydraulics program, HEC-RAS, computes river stages and water surface profiles for these scenarios. An inundation boundary and depth map of water in the flood plain can be calculated from the HEC-RAS results using ArcInfo. The economic impacts of the different inundation depths are computed by HEC-FIA. The user-configurable sequence of modeling software allows engineers to evaluate operational decisions for reservoirs and other control structures, and view and compare hydraulic and economic impacts for various “what if?” scenarios. This paper reviews the Cumberland River May 2010 event, the impact of Corps reservoirs and reservoir operations and the expected future benefits and effects of the ARRA funded models and CWMS on future events for this area.
Ex post power economic analysis of record of decision operational restrictions at Glen Canyon Dam.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Veselka, T. D.; Poch, L. A.; Palmer, C. S.
On October 9, 1996, Bruce Babbitt, then-Secretary of the U.S. Department of the Interior signed the Record of Decision (ROD) on operating criteria for the Glen Canyon Dam (GCD). Criteria selected were based on the Modified Low Fluctuating Flow (MLFF) Alternative as described in the Operation of Glen Canyon Dam, Colorado River Storage Project, Arizona, Final Environmental Impact Statement (EIS) (Reclamation 1995). These restrictions reduced the operating flexibility of the hydroelectric power plant and therefore its economic value. The EIS provided impact information to support the ROD, including an analysis of operating criteria alternatives on power system economics. This exmore » post study reevaluates ROD power economic impacts and compares these results to the economic analysis performed prior (ex ante) to the ROD for the MLFF Alternative. On the basis of the methodology used in the ex ante analysis, anticipated annual economic impacts of the ROD were estimated to range from approximately $15.1 million to $44.2 million in terms of 1991 dollars ($1991). This ex post analysis incorporates historical events that took place between 1997 and 2005, including the evolution of power markets in the Western Electricity Coordinating Council as reflected in market prices for capacity and energy. Prompted by ROD operational restrictions, this analysis also incorporates a decision made by the Western Area Power Administration to modify commitments that it made to its customers. Simulated operations of GCD were based on the premise that hourly production patterns would maximize the economic value of the hydropower resource. On the basis of this assumption, it was estimated that economic impacts were on average $26.3 million in $1991, or $39 million in $2009.« less
Simulation Evaluation of Synthetic Vision as an Enabling Technology for Equivalent Visual Operations
NASA Technical Reports Server (NTRS)
Kramer, Lynda J.; Williams, Steven P.; Bailey, Randall E.
2008-01-01
Enhanced Vision (EV) and synthetic vision (SV) systems may serve as enabling technologies to meet the challenges of the Next Generation Air Transportation System (NextGen) Equivalent Visual Operations (EVO) concept ? that is, the ability to achieve or even improve on the safety of Visual Flight Rules (VFR) operations, maintain the operational tempos of VFR, and even, perhaps, retain VFR procedures independent of actual weather and visibility conditions. One significant challenge lies in the definition of required equipage on the aircraft and on the airport to enable the EVO concept objective. A piloted simulation experiment was conducted to evaluate the effects of the presence or absence of Synthetic Vision, the location of this information during an instrument approach (i.e., on a Head-Up or Head-Down Primary Flight Display), and the type of airport lighting information on landing minima. The quantitative data from this experiment were analyzed to begin the definition of performance-based criteria for all-weather approach and landing operations. Objective results from the present study showed that better approach performance was attainable with the head-up display (HUD) compared to the head-down display (HDD). A slight performance improvement in HDD performance was shown when SV was added, as the pilots descended below 200 ft to a 100 ft decision altitude, but this performance was not tested for statistical significance (nor was it expected to be statistically significant). The touchdown data showed that regardless of the display concept flown (SV HUD, Baseline HUD, SV HDD, Baseline HDD) a majority of the runs were within the performance-based defined approach and landing criteria in all the visibility levels, approach lighting systems, and decision altitudes tested. For this visual flight maneuver, RVR appeared to be the most significant influence in touchdown performance. The approach lighting system clearly impacted the pilot's ability to descend to 100 ft height above touchdown based on existing Federal Aviation Regulation (FAR) 91.175 using a 200 ft decision height, but did not appear to influence touchdown performance or approach path maintenance
NASA Astrophysics Data System (ADS)
Chen, L. Leon; Ulmer, Stephan; Deisboeck, Thomas S.
2010-01-01
We present an application of a previously developed agent-based glioma model (Chen et al 2009 Biosystems 95 234-42) for predicting spatio-temporal tumor progression using a patient-specific MRI lattice derived from apparent diffusion coefficient (ADC) data. Agents representing collections of migrating glioma cells are initialized based upon voxels at the outer border of the tumor identified on T1-weighted (Gd+) MRI at an initial time point. These simulated migratory cells exhibit a specific biologically inspired spatial search paradigm, representing a weighting of the differential contribution from haptotactic permission and biomechanical resistance on the migration decision process. ADC data from 9 months after the initial tumor resection were used to select the best search paradigm for the simulation, which was initiated using data from 6 months after the initial operation. Using this search paradigm, 100 simulations were performed to derive a probabilistic map of tumor invasion locations. The simulation was able to successfully predict a recurrence in the dorsal/posterior aspect long before it was depicted on T1-weighted MRI, 18 months after the initial operation.
Chen, L Leon; Ulmer, Stephan; Deisboeck, Thomas S
2010-01-21
We present an application of a previously developed agent-based glioma model (Chen et al 2009 Biosystems 95 234-42) for predicting spatio-temporal tumor progression using a patient-specific MRI lattice derived from apparent diffusion coefficient (ADC) data. Agents representing collections of migrating glioma cells are initialized based upon voxels at the outer border of the tumor identified on T1-weighted (Gd+) MRI at an initial time point. These simulated migratory cells exhibit a specific biologically inspired spatial search paradigm, representing a weighting of the differential contribution from haptotactic permission and biomechanical resistance on the migration decision process. ADC data from 9 months after the initial tumor resection were used to select the best search paradigm for the simulation, which was initiated using data from 6 months after the initial operation. Using this search paradigm, 100 simulations were performed to derive a probabilistic map of tumor invasion locations. The simulation was able to successfully predict a recurrence in the dorsal/posterior aspect long before it was depicted on T1-weighted MRI, 18 months after the initial operation.
Human interaction with an intelligent computer in multi-task situations
NASA Technical Reports Server (NTRS)
Rouse, W. B.
1975-01-01
A general formulation of human decision making in multiple task situations is presented. It includes a description of the state, event, and action space in which the multiple task supervisor operates. A specific application to a failure detection and correction situation is discussed and results of a simulation experiment presented. Issues considered include static vs. dynamic allocation of responsibility and competitive vs. cooperative intelligence.
Situation assessment in the Paladin tactical decision generation system
NASA Technical Reports Server (NTRS)
Mcmanus, John W.; Chappell, Alan R.; Arbuckle, P. Douglas
1992-01-01
Paladin is a real-time tactical decision generator for air combat engagements. Paladin uses specialized knowledge-based systems and other Artificial Intelligence (AI) programming techniques to address the modern air combat environment and agile aircraft in a clear and concise manner. Paladin is designed to provide insight into both the tactical benefits and the costs of enhanced agility. The system was developed using the Lisp programming language on a specialized AI workstation. Paladin utilizes a set of air combat rules, an active throttle controller, and a situation assessment module that have been implemented as a set of highly specialized knowledge-based systems. The situation assessment module was developed to determine the tactical mode of operation (aggressive, defensive, neutral, evasive, or disengagement) used by Paladin at each decision point in the air combat engagement. Paladin uses the situation assessment module; the situationally dependent modes of operation to more accurately represent the complex decision-making process of human pilots. This allows Paladin to adapt its tactics to the current situation and improves system performance. Discussed here are the details of Paladin's situation assessment and modes of operation. The results of simulation testing showing the error introduced into the situation assessment module due to estimation errors in positional and geometric data for the opponent aircraft are presented. Implementation issues for real-time performance are discussed and several solutions are presented, including Paladin's use of an inference engine designed for real-time execution.
NASA Astrophysics Data System (ADS)
Podimata, Marianthi V.; Yannopoulos, Panayotis C.
2015-04-01
Water managers, decision-makers, water practitioners and others involved in Integrated Water Resources Management often encounter the problem of finding a joint agreement among stakeholders concerning the management of a common water body. Handling conflict situations/disputes over water issues and finding an acceptable joint solution remain a thorny issue in water negotiation processes, since finding a formula for wise, fair and sustainable management of a water resource is a complex process that includes environmental, economic, technical, socio-political criteria and their uncertainties. Decision Support Systems and Adaptive Management are increasingly used in that direction. To assist decision makers in handling water disputes and execute negotiations, a conceptual tool is required. The Graph Model for Conflict Resolution is a Decision Support flexible tool for negotiation support regarding water conflicts. It includes efficient algorithms for estimating strategic moves of water stakeholders, even though there is a lack of detail concerning their real motives and prospects. It calculates the stability of their states and encourages what-if analyses. This paper presents a case study of water decision makers' evaluations concerning the management of up-coming technical infrastructure Peiros-Parapeiros Dam, in Achaia Region (Greece). The continuous consultations between institutions and representatives revealed that the formation of a joint agreement between stakeholders is not easy, due to arising conflicts and contradictions regarding the jurisdiction and legal status of the dam operator and the cost undertaking of the dam operation. This paper analyzes the positions of the parties involved in the consultation process and examines possible conflict resolution states, using GMCR II. This methodology tries to minimize uncertainty to a certain extent concerning the possible moves/decisions of involved parties regarding the operation and management of the dam by developing and simulating potential strategic interactions and multilateral negotiations and finding confidence-building cooperation schemes (cooperative arrangements) over water use and management.
NASA Technical Reports Server (NTRS)
Simpson, Robert W.
1993-01-01
This presentation outlines a concept for an adaptive, interactive decision support system to assist controllers at a busy airport in achieving efficient use of multiple runways. The concept is being implemented as a computer code called FASA (Final Approach Spacing for Aircraft), and will be tested and demonstrated in ATCSIM, a high fidelity simulation of terminal area airspace and airport surface operations. Objectives are: (1) to provide automated cues to assist controllers in the sequencing and spacing of landing and takeoff aircraft; (2) to provide the controller with a limited ability to modify the sequence and spacings between aircraft, and to insert takeoffs and missed approach aircraft in the landing flows; (3) to increase spacing accuracy using more complex and precise separation criteria while reducing controller workload; and (4) achieve higher operational takeoff and landing rates on multiple runways in poor visibility.
Russo, Michael B; Stetz, Melba C; Thomas, Maria L
2005-07-01
Judgment, decision making, and situational awareness are higher-order mental abilities critically important to operational cognitive performance. Higher-order mental abilities rely on intact functioning of multiple brain regions, including the prefrontal, thalamus, and parietal areas. Real-time monitoring of individuals for cognitive performance capacity via an approach based on sampling multiple neurophysiologic signals and integrating those signals with performance prediction models potentially provides a method of supporting warfighters' and commanders' decision making and other operationally relevant mental processes and is consistent with the goals of augmented cognition. Cognitive neurophysiological assessments that directly measure brain function and subsequent cognition include positron emission tomography, functional magnetic resonance imaging, mass spectroscopy, near-infrared spectroscopy, magnetoencephalography, and electroencephalography (EEG); however, most direct measures are not practical to use in operational environments. More practical, albeit indirect measures that are generated by, but removed from the actual neural sources, are movement activity, oculometrics, heart rate, and voice stress signals. The goal of the papers in this section is to describe advances in selected direct and indirect cognitive neurophysiologic monitoring techniques as applied for the ultimate purpose of preventing operational performance failures. These papers present data acquired in a wide variety of environments, including laboratory, simulator, and clinical arenas. The papers discuss cognitive neurophysiologic measures such as digital signal processing wrist-mounted actigraphy; oculometrics including blinks, saccadic eye movements, pupillary movements, the pupil light reflex; and high-frequency EEG. These neurophysiological indices are related to cognitive performance as measured through standard test batteries and simulators with conditions including sleep loss, time on task, and aviation flight-induced fatigue.
NASA Technical Reports Server (NTRS)
2003-01-01
The same software controlling autonomous and crew-assisted operations for the International Space Station (ISS) is enabling commercial enterprises to integrate and automate manual operations, also known as decision logic, in real time across complex and disparate networked applications, databases, servers, and other devices, all with quantifiable business benefits. Auspice Corporation, of Framingham, Massachusetts, developed the Auspice TLX (The Logical Extension) software platform to effectively mimic the human decision-making process. Auspice TLX automates operations across extended enterprise systems, where any given infrastructure can include thousands of computers, servers, switches, and modems that are connected, and therefore, dependent upon each other. The concept behind the Auspice software spawned from a computer program originally developed in 1981 by Cambridge, Massachusetts-based Draper Laboratory for simulating tasks performed by astronauts aboard the Space Shuttle. At the time, the Space Shuttle Program was dependent upon paper-based procedures for its manned space missions, which typically averaged 2 weeks in duration. As the Shuttle Program progressed, NASA began increasing the length of manned missions in preparation for a more permanent space habitat. Acknowledging the need to relinquish paper-based procedures in favor of an electronic processing format to properly monitor and manage the complexities of these longer missions, NASA realized that Draper's task simulation software could be applied to its vision of year-round space occupancy. In 1992, Draper was awarded a NASA contract to build User Interface Language software to enable autonomous operations of a multitude of functions on Space Station Freedom (the station was redesigned in 1993 and converted into the international venture known today as the ISS)
Entry, Descent, and Landing Operations Analysis for the Mars Phoenix Lander
NASA Technical Reports Server (NTRS)
Prince, Jill L.; Desai, Prasun N.; Queen, Eric M.; Grover, Myron R.
2008-01-01
The Mars Phoenix lander was launched August 4, 2007 and remained in cruise for ten months before landing in the northern plains of Mars in May 2008. The one-month Entry, Descent, and Landing (EDL) operations phase prior to entry consisted of daily analyses, meetings, and decisions necessary to determine if trajectory correction maneuvers and environmental parameter updates to the spacecraft were required. An overview of the Phoenix EDL trajectory simulation and analysis that was performed during the EDL approach and operations phase is described in detail. The evolution of the Monte Carlo statistics and footprint ellipse during the final approach phase is also provided. The EDL operations effort accurately delivered the Phoenix lander to the desired landing region on May 25, 2008.
Yule, Steven; Parker, Sarah Henrickson; Wilkinson, Jill; McKinley, Aileen; MacDonald, Jamie; Neill, Adrian; McAdam, Tim
2015-01-01
To investigate the effect of coaching on non-technical skills and performance during laparoscopic cholecystectomy in a simulated operating room (OR). Non-technical skills (situation awareness, decision making, teamwork, and leadership) underpin technical ability and are critical to the success of operations and the safety of patients in the OR. The rate of developing assessment tools in this area has outpaced development of workable interventions to improve non-technical skills in surgical training and beyond. A randomized trial was conducted with senior surgical residents (n = 16). Participants were randomized to receive either non-technical skills coaching (intervention) or to self-reflect (control) after each of 5 simulated operations. Coaching was based on the Non-Technical Skills For Surgeons (NOTSS) behavior observation system. Surgeon-coaches trained in this method coached participants in the intervention group for 10 minutes after each simulation. Primary outcome measure was non-technical skills, assessed from video by a surgeon using the NOTSS system. Secondary outcomes were time to call for help during bleeding, operative time, and path length of laparoscopic instruments. Non-technical skills improved in the intervention group from scenario 1 to scenario 5 compared with those in the control group (p = 0.04). The intervention group was faster to call for help when faced with unstoppable bleeding in the final scenario (no. 5; p = 0.03). Coaching improved residents' non-technical skills in the simulated OR compared with those in the control group. Important next steps are to implement non-technical skills coaching in the real OR and assess effect on clinically important process measures and patient outcomes. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.
Hydrodynamics Analysis and CFD Simulation of Portal Venous System by TIPS and LS.
Wang, Meng; Zhou, Hongyu; Huang, Yaozhen; Gong, Piyun; Peng, Bing; Zhou, Shichun
2015-06-01
In cirrhotic patients, portal hypertension is often associated with a hyperdynamic changes. Transjugular Intrahepatic Portosystemic Shunt (TIPS) and Laparoscopic splenectomy are both treatments for liver cirrhosis due to portal hypertension. While, the two different interventions have different effects on hemodynamics after operation and the possibilities of triggering PVT are different. How hemodynamics of portal vein system evolving with two different operations remain unknown. Based on ultrasound and established numerical methods, CFD technique is applied to analyze hemodynamic changes after TIPS and Laparoscopic splenectomy. In this paper, we applied two 3-D flow models to the hemodynamic analysis for two patients who received a TIPS and a laparoscopic splenectomy, both therapies for treating portal hypertension induced diseases. The current computer simulations give a quantitative analysis of the interplay between hemodynamics and TIPS or splenectomy. In conclusion, the presented computational model can be used for the theoretical analysis of TIPS and laparoscopic splenectomy, clinical decisions could be made based on the simulation results with personal properly treatment.
NASA Technical Reports Server (NTRS)
Corker, Kevin M.; Labacqz, J. Victor (Technical Monitor)
1997-01-01
The Man-Machine Interaction Design and Analysis System (MIDAS) under joint U.S. Army and NASA cooperative is intended to assist designers of complex human/automation systems in successfully incorporating human performance capabilities and limitations into decision and action support systems. MIDAS is a computational representation of multiple human operators, selected perceptual, cognitive, and physical functions of those operators, and the physical/functional representation of the equipment with which they operate. MIDAS has been used as an integrated predictive framework for the investigation of human/machine systems, particularly in situations with high demands on the operators. We have extended the human performance models to include representation of both human operators and intelligent aiding systems in flight management, and air traffic service. The focus of this development is to predict human performance in response to aiding system developed to identify aircraft conflict and to assist in the shared authority for resolution. The demands of this application requires representation of many intelligent agents sharing world-models, coordinating action/intention, and cooperative scheduling of goals and action in an somewhat unpredictable world of operations. In recent applications to airborne systems development, MIDAS has demonstrated an ability to predict flight crew decision-making and procedural behavior when interacting with automated flight management systems and Air Traffic Control. In this paper, we describe two enhancements to MIDAS. The first involves the addition of working memory in the form of an articulatory buffer for verbal communication protocols and a visuo-spatial buffer for communications via digital datalink. The second enhancement is a representation of multiple operators working as a team. This enhanced model was used to predict the performance of human flight crews and their level of compliance with commercial aviation communication procedures. We show how the data produced by MIDAS compares with flight crew performance data from full mission simulations. Finally, we discuss the use of these features to study communication issues connected with aircraft-based separation assurance.
NASA Astrophysics Data System (ADS)
Charley, W. J.; Luna, M.
2007-12-01
The U.S. Army Corps of Engineers Corps Water Management System (CWMS) is a comprehensive data acquisition and hydrologic modeling system for short-term decision support of water control operations in real time. It encompasses data collection, validation and transformation, data storage, visualization, real time model simulation for decision-making support, and data dissemination. CWMS uses an Oracle database and Sun Solaris workstations for data processes, storage and the execution of models, with a client application (the Control and Visualization Interface, or CAVI) that can run on a Windows PC. CWMS was used by the Lower Colorado River Authority (LCRA) to make hydrologic forecasts of flows on the Lower Colorado River and operate reservoirs during the June 2007 event in Texas. The LCRA receives real-time observed gridded spatial rainfall data from OneRain, Inc. that which is a result of adjusting NexRad rainfall data with precipitation gages. This data is used, along with future precipitation estimates, for hydrologic forecasting by the rainfall-runoff modeling program HEC-HMS. Forecasted flows from HEC-HMS and combined with observed flows and reservoir information to simulate LCRA's reservoir operations and help engineers make release decisions based on the results. The river hydraulics program, HEC-RAS, computes river stages and water surface profiles for the computed flow. An inundation boundary and depth map of water in the flood plain can be calculated from the HEC-RAS results using ArcInfo. By varying future precipitation and releases, engineers can evaluate different "What if?" scenarios. What was described as an "extraordinary cluster of thunderstorms" that stalled over Burnet and Llano counties in Texas on June 27, 2007, dropped 17 to 19 inches of rainfall over a 6-hour period. The storm was classified over a 500-year event and the resulting flow over some of the smaller tributaries as a 100-year or better. CWMS was used by LCRA for flood forecasting and reservoir operations. The models accurately forecasting the flows and allowed engineers to determine that only four floodgates needed to be opened for Mansfield dam, in the Chain of Highland lakes. CWMS also forecasted the peak of the flood well before it happened. Smaller rain storms continued for a period of weeks and CWMS was used throughout the event calculating lake levels, closing of gates along with a hydro-generation schedule.
Self-Averaging Property of Minimal Investment Risk of Mean-Variance Model.
Shinzato, Takashi
2015-01-01
In portfolio optimization problems, the minimum expected investment risk is not always smaller than the expected minimal investment risk. That is, using a well-known approach from operations research, it is possible to derive a strategy that minimizes the expected investment risk, but this strategy does not always result in the best rate of return on assets. Prior to making investment decisions, it is important to an investor to know the potential minimal investment risk (or the expected minimal investment risk) and to determine the strategy that will maximize the return on assets. We use the self-averaging property to analyze the potential minimal investment risk and the concentrated investment level for the strategy that gives the best rate of return. We compare the results from our method with the results obtained by the operations research approach and with those obtained by a numerical simulation using the optimal portfolio. The results of our method and the numerical simulation are in agreement, but they differ from that of the operations research approach.
[Effect of alcohol intake on the ability to pilot aircraft].
Ushakov, I B; Egorov, S V
1996-01-01
During the initial 4 hours after alcohol intake at a dose of 1.9 g/kg aircraft operators displayed disturbances in the psychic processes and functions responsible for each (from information reception and processing up to decision-making and building-up the controlling actions) structural elements in their activity resulting in considerable limitation or a complete failure to pilot aircraft. Main disorders included inability to correctly analyse flight situation and loss of skills to automatically control simulator, a sudden depletion of psychophysiological reserves and deterioration of operator's reliability. Less elaborated professional skills appear to be the most vulnerable.
2002-05-20
this transition will have on the CSEPP communities using a risk-based simulation suite. 34 Arms Control & Proliferation WG-3 Chir To Mcian USDprmn f3tt...conjunction with the Army Office of the Surgeon General (OTSG). 166 Measures of Effectiveness WG-24 Chir MA ar . zl,UM The following abstracts are...the effects on resources and budgets that result from major force, support and infrastructure changes. 193 Decision Analysis WG-28 Chir Gwe F.Dln,J A
Multidisciplinary crisis simulations: the way forward for training surgical teams.
Undre, Shabnam; Koutantji, Maria; Sevdalis, Nick; Gautama, Sanjay; Selvapatt, Nowlan; Williams, Samantha; Sains, Parvinderpal; McCulloch, Peter; Darzi, Ara; Vincent, Charles
2007-09-01
High-reliability organizations have stressed the importance of non-technical skills for safety and of regularly providing such training to their teams. Recently safety skills training has been applied in the practice of medicine. In this study, we developed and piloted a module using multidisciplinary crisis scenarios in a simulated operating theatre to train entire surgical teams. Twenty teams participated (n = 80); each consisted of a trainee surgeon, anesthetist, operating department practitioner (ODP), and scrub nurse. Crisis scenarios such as difficult intubation, hemorrhage, or cardiac arrest were simulated. Technical and non-technical skills (leadership, communication, team skills, decision making, and vigilance), were assessed by clinical experts and by two psychologists using relevant technical and human factors rating scales. Participants received technical and non-technical feedback, and the whole team received feedback on teamwork. Trainees assessed the training favorably. For technical skills there were no differences between surgical trainees' assessment scores and the assessment scores of the trainers. However, nurses overrated their technical skill. Regarding non-technical skills, leadership and decision making were scored lower than the other three non-technical skills (communication, team skills, and vigilance). Surgeons scored lower than nurses on communication and teamwork skills. Surgeons and anesthetists scored lower than nurses on leadership. Multidisciplinary simulation-based team training is feasible and well received by surgical teams. Non-technical skills can be assessed alongside technical skills, and differences in performance indicate where there is a need for further training. Future work should focus on developing team performance measures for training and on the development and evaluation of systematic training for technical and non-technical skills to enhance team performance and safety in surgery.
NASA Astrophysics Data System (ADS)
Feng, Jun-shu; Jin, Yan-ming; Hao, Wei-hua
2017-01-01
Based on modelling the environmental influence index of power transmission and transformation project and energy-saving and emission-reducing index of source-grid-load of power system, this paper establishes an objective decision model of power grid environmental protection, with constraints of power grid environmental protection objectives being legal and economical, and considering both positive and negative influences of grid on the environmental in all-life grid cycle. This model can be used to guide the programming work of power grid environmental protection. A numerical simulation of Jiangsu province’s power grid environmental protection objective decision model has been operated, and the results shows that the maximum goal of energy-saving and emission-reducing benefits would be reached firstly as investment increasing, and then the minimum goal of environmental influence.
Experiments in pilot decision-making during simulated low visibility approaches
NASA Technical Reports Server (NTRS)
Curry, R. E.; Lauber, J. K.; Billings, C. E.
1975-01-01
A simulation task is reported which incorporates both kinds of variables, informational and psychological, to successfully study pilot decision making behavior in the laboratory. Preliminary experiments in the measurement of decisions and the inducement of stress in simulated low visibility approaches are described.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tahvili, Sahar; Österberg, Jonas; Silvestrov, Sergei
One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms ofmore » a suggested framework model based on discrete event simulation.« less
Towards process-informed bias correction of climate change simulations
NASA Astrophysics Data System (ADS)
Maraun, Douglas; Shepherd, Theodore G.; Widmann, Martin; Zappa, Giuseppe; Walton, Daniel; Gutiérrez, José M.; Hagemann, Stefan; Richter, Ingo; Soares, Pedro M. M.; Hall, Alex; Mearns, Linda O.
2017-11-01
Biases in climate model simulations introduce biases in subsequent impact simulations. Therefore, bias correction methods are operationally used to post-process regional climate projections. However, many problems have been identified, and some researchers question the very basis of the approach. Here we demonstrate that a typical cross-validation is unable to identify improper use of bias correction. Several examples show the limited ability of bias correction to correct and to downscale variability, and demonstrate that bias correction can cause implausible climate change signals. Bias correction cannot overcome major model errors, and naive application might result in ill-informed adaptation decisions. We conclude with a list of recommendations and suggestions for future research to reduce, post-process, and cope with climate model biases.
Drought allocations using the Systems Impact Assessment Model: Klamath River
Flug, M.; Campbell, S.G.
2005-01-01
Water supply and allocation scenarios for the Klamath River, Ore. and Calif., were evaluated using the Systems Impact Assessment Model (SIAM), a decision support system developed by the U.S. Geological Survey. SIAM is a set of models with a graphical user interface that simulates water supply and delivery in a managed river system, water quality, and fish production. Simulation results are presented for drought conditions, one aspect of Klamath River water operations. The Klamath River Basin has experienced critically dry conditions in 1992, 1994, and 2001. Drought simulations are useful to estimate the impacts of specific legal or institutional flow constraints. In addition, simulations help to identify potential adverse water quality consequences including evaluating the potential for reducing adverse temperature impacts on anadromous fish. In all drought simulations, water supply was insufficient to fully meet upstream and downstream targets for endangered species.
NASA Astrophysics Data System (ADS)
Schulte, Peter Z.; Spencer, David A.
2016-01-01
This paper describes the development and validation process of a highly automated Guidance, Navigation, & Control subsystem for a small satellite on-orbit inspection application, enabling proximity operations without human-in-the-loop interaction. The paper focuses on the integration and testing of Guidance, Navigation, & Control software and the development of decision logic to address the question of how such a system can be effectively implemented for full automation. This process is unique because a multitude of operational scenarios must be considered and a set of complex interactions between subsystem algorithms must be defined to achieve the automation goal. The Prox-1 mission is currently under development within the Space Systems Design Laboratory at the Georgia Institute of Technology. The mission involves the characterization of new small satellite component technologies, deployment of the LightSail 3U CubeSat, entering into a trailing orbit relative to LightSail using ground-in-the-loop commands, and demonstration of automated proximity operations through formation flight and natural motion circumnavigation maneuvers. Operations such as these may be utilized for many scenarios including on-orbit inspection, refueling, repair, construction, reconnaissance, docking, and debris mitigation activities. Prox-1 uses onboard sensors and imaging instruments to perform Guidance, Navigation, & Control operations during on-orbit inspection of LightSail. Navigation filters perform relative orbit determination based on images of the target spacecraft, and guidance algorithms conduct automated maneuver planning. A slew and tracking controller sends attitude actuation commands to a set of control moment gyroscopes, and other controllers manage desaturation, detumble, thruster firing, and target acquisition/recovery. All Guidance, Navigation, & Control algorithms are developed in a MATLAB/Simulink six degree-of-freedom simulation environment and are integrated using decision logic to autonomously determine when actions should be performed. The complexity of this decision logic is the primary challenge of the automated process, and the Stateflow tool in Simulink is used to establish logical relationships and manage data flow between each of the individual hardware and software components. Once the integrated simulation is fully developed in MATLAB/Simulink, the algorithms are autocoded to C/C++ and integrated into flight software. Hardware-in-the-loop testing provides validation of the Guidance, Navigation, & Control subsystem performance.
Siirala, Eriikka; Peltonen, Laura-Maria; Lundgrén-Laine, Heljä; Salanterä, Sanna; Junttila, Kristiina
2016-09-01
To describe the tactical and the operational decisions made by nurse managers when managing the daily unit operation in peri-operative settings. Management is challenging as situations change rapidly and decisions are constantly made. Understanding decision-making in this complex environment helps to develop decision support systems to support nurse managers' operative and tactical decision-making. Descriptive cross-sectional design. Data were collected from 20 nurse managers with the think-aloud method during the busiest working hours and analysed using thematic content analysis. Nurse managers made over 700 decisions; either ad hoc (n = 289), near future (n = 268) or long-term (n = 187) by nature. Decisions were often made simultaneously with many interruptions. Ad hoc decisions covered staff allocation, ensuring adequate staff, rescheduling surgical procedures, confirmation tangible resources and following-up the daily unit operation. Decisions in the near future were: planning of surgical procedures and tangible resources, and planning staff allocation. Long-term decisions were: human recourses, nursing development, supplies and equipment, and finances in the unit. Decision-making was vulnerable to interruptions, which sometimes complicated the managing tasks. The results can be used when planning decision support systems and when defining the nurse managers' tasks in peri-operative settings. © 2016 John Wiley & Sons Ltd.
An intelligent agent for optimal river-reservoir system management
NASA Astrophysics Data System (ADS)
Rieker, Jeffrey D.; Labadie, John W.
2012-09-01
A generalized software package is presented for developing an intelligent agent for stochastic optimization of complex river-reservoir system management and operations. Reinforcement learning is an approach to artificial intelligence for developing a decision-making agent that learns the best operational policies without the need for explicit probabilistic models of hydrologic system behavior. The agent learns these strategies experientially in a Markov decision process through observational interaction with the environment and simulation of the river-reservoir system using well-calibrated models. The graphical user interface for the reinforcement learning process controller includes numerous learning method options and dynamic displays for visualizing the adaptive behavior of the agent. As a case study, the generalized reinforcement learning software is applied to developing an intelligent agent for optimal management of water stored in the Truckee river-reservoir system of California and Nevada for the purpose of streamflow augmentation for water quality enhancement. The intelligent agent successfully learns long-term reservoir operational policies that specifically focus on mitigating water temperature extremes during persistent drought periods that jeopardize the survival of threatened and endangered fish species.
A stochastic discrete optimization model for designing container terminal facilities
NASA Astrophysics Data System (ADS)
Zukhruf, Febri; Frazila, Russ Bona; Burhani, Jzolanda Tsavalista
2017-11-01
As uncertainty essentially affect the total transportation cost, it remains important in the container terminal that incorporates several modes and transshipments process. This paper then presents a stochastic discrete optimization model for designing the container terminal, which involves the decision of facilities improvement action. The container terminal operation model is constructed by accounting the variation of demand and facilities performance. In addition, for illustrating the conflicting issue that practically raises in the terminal operation, the model also takes into account the possible increment delay of facilities due to the increasing number of equipment, especially the container truck. Those variations expectantly reflect the uncertainty issue in the container terminal operation. A Monte Carlo simulation is invoked to propagate the variations by following the observed distribution. The problem is constructed within the framework of the combinatorial optimization problem for investigating the optimal decision of facilities improvement. A new variant of glow-worm swarm optimization (GSO) is thus proposed for solving the optimization, which is rarely explored in the transportation field. The model applicability is tested by considering the actual characteristics of the container terminal.
Adaptive automation of human-machine system information-processing functions.
Kaber, David B; Wright, Melanie C; Prinzel, Lawrence J; Clamann, Michael P
2005-01-01
The goal of this research was to describe the ability of human operators to interact with adaptive automation (AA) applied to various stages of complex systems information processing, defined in a model of human-automation interaction. Forty participants operated a simulation of an air traffic control task. Automated assistance was adaptively applied to information acquisition, information analysis, decision making, and action implementation aspects of the task based on operator workload states, which were measured using a secondary task. The differential effects of the forms of automation were determined and compared with a manual control condition. Results of two 20-min trials of AA or manual control revealed a significant effect of the type of automation on performance, particularly during manual control periods as part of the adaptive conditions. Humans appear to better adapt to AA applied to sensory and psychomotor information-processing functions (action implementation) than to AA applied to cognitive functions (information analysis and decision making), and AA is superior to completely manual control. Potential applications of this research include the design of automation to support air traffic controller information processing.
Social cognitive theory, metacognition, and simulation learning in nursing education.
Burke, Helen; Mancuso, Lorraine
2012-10-01
Simulation learning encompasses simple, introductory scenarios requiring response to patients' needs during basic hygienic care and during situations demanding complex decision making. Simulation integrates principles of social cognitive theory (SCT) into an interactive approach to learning that encompasses the core principles of intentionality, forethought, self-reactiveness, and self-reflectiveness. Effective simulation requires an environment conducive to learning and introduces activities that foster symbolic coding operations and mastery of new skills; debriefing builds self-efficacy and supports self-regulation of behavior. Tailoring the level of difficulty to students' mastery level supports successful outcomes and motivation to set higher standards. Mindful selection of simulation complexity and structure matches course learning objectives and supports progressive development of metacognition. Theory-based facilitation of simulated learning optimizes efficacy of this learning method to foster maturation of cognitive processes of SCT, metacognition, and self-directedness. Examples of metacognition that are supported through mindful, theory-based implementation of simulation learning are provided. Copyright 2012, SLACK Incorporated.
Hu, E; Liao, T. W.; Tiersch, T. R.
2013-01-01
Emerging commercial-level technology for aquatic sperm cryopreservation has not been modeled by computer simulation. Commercially available software (ARENA, Rockwell Automation, Inc. Milwaukee, WI) was applied to simulate high-throughput sperm cryopreservation of blue catfish (Ictalurus furcatus) based on existing processing capabilities. The goal was to develop a simulation model suitable for production planning and decision making. The objectives were to: 1) predict the maximum output for 8-hr workday; 2) analyze the bottlenecks within the process, and 3) estimate operational costs when run for daily maximum output. High-throughput cryopreservation was divided into six major steps modeled with time, resources and logic structures. The modeled production processed 18 fish and produced 1164 ± 33 (mean ± SD) 0.5-ml straws containing one billion cryopreserved sperm. Two such production lines could support all hybrid catfish production in the US and 15 such lines could support the entire channel catfish industry if it were to adopt artificial spawning techniques. Evaluations were made to improve efficiency, such as increasing scale, optimizing resources, and eliminating underutilized equipment. This model can serve as a template for other aquatic species and assist decision making in industrial application of aquatic germplasm in aquaculture, stock enhancement, conservation, and biomedical model fishes. PMID:25580079
Tracking Expected Improvements of Decadal Prediction in Climate Services
NASA Astrophysics Data System (ADS)
Suckling, E.; Thompson, E.; Smith, L. A.
2013-12-01
Physics-based simulation models are ultimately expected to provide the best available (decision-relevant) probabilistic climate predictions, as they can capture the dynamics of the Earth System across a range of situations, situations for which observations for the construction of empirical models are scant if not nonexistent. This fact in itself provides neither evidence that predictions from today's Earth Systems Models will outperform today's empirical models, nor a guide to the space and time scales on which today's model predictions are adequate for a given purpose. Empirical (data-based) models are employed to make probability forecasts on decadal timescales. The skill of these forecasts is contrasted with that of state-of-the-art climate models, and the challenges faced by each approach are discussed. The focus is on providing decision-relevant probability forecasts for decision support. An empirical model, known as Dynamic Climatology is shown to be competitive with CMIP5 climate models on decadal scale probability forecasts. Contrasting the skill of simulation models not only with each other but also with empirical models can reveal the space and time scales on which a generation of simulation models exploits their physical basis effectively. It can also quantify their ability to add information in the formation of operational forecasts. Difficulties (i) of information contamination (ii) of the interpretation of probabilistic skill and (iii) of artificial skill complicate each modelling approach, and are discussed. "Physics free" empirical models provide fixed, quantitative benchmarks for the evaluation of ever more complex climate models, that is not available from (inter)comparisons restricted to only complex models. At present, empirical models can also provide a background term for blending in the formation of probability forecasts from ensembles of simulation models. In weather forecasting this role is filled by the climatological distribution, and can significantly enhance the value of longer lead-time weather forecasts to those who use them. It is suggested that the direct comparison of simulation models with empirical models become a regular component of large model forecast intercomparison and evaluation. This would clarify the extent to which a given generation of state-of-the-art simulation models provide information beyond that available from simpler empirical models. It would also clarify current limitations in using simulation forecasting for decision support. No model-based probability forecast is complete without a quantitative estimate if its own irrelevance; this estimate is likely to increase as a function of lead time. A lack of decision-relevant quantitative skill would not bring the science-based foundation of anthropogenic warming into doubt. Similar levels of skill with empirical models does suggest a clear quantification of limits, as a function of lead time, for spatial and temporal scales on which decisions based on such model output are expected to prove maladaptive. Failing to clearly state such weaknesses of a given generation of simulation models, while clearly stating their strength and their foundation, risks the credibility of science in support of policy in the long term.
Human Factors in Training - Space Flight Resource Management Training
NASA Technical Reports Server (NTRS)
Bryne, Vicky; Connell, Erin; Barshi, Immanuel; Arsintescu, L.
2009-01-01
Accidents and incidents show that high workload-induced stress and poor teamwork skills lead to performance decrements and errors. Research on teamwork shows that effective teams are able to adapt to stressful situations, and to reduce workload by using successful strategies for communication and decision making, and through dynamic redistribution of tasks among team members. Furthermore, superior teams are able to recognize signs and symptoms of workload-induced stress early, and to adapt their coordination and communication strategies to the high workload, or stress conditions. Mission Control Center (MCC) teams often face demanding situations in which they must operate as an effective team to solve problems with crew and vehicle during onorbit operations. To be successful as a team, flight controllers (FCers) must learn effective teamwork strategies. Such strategies are the focus of Space Flight Resource Management (SFRM) training. SFRM training in MOD has been structured to include some classroom presentations of basic concepts and case studies, with the assumption that skill development happens in mission simulation. Integrated mission simulations do provide excellent opportunities for FCers to practice teamwork, but also require extensive technical knowledge of vehicle systems, mission operations, and crew actions. Such technical knowledge requires lengthy training. When SFRM training is relegated to integrated simulations, FCers can only practice SFRM after they have already mastered the technical knowledge necessary for these simulations. Given the centrality of teamwork to the success of MCC, holding SFRM training till late in the flow is inefficient. But to be able to train SFRM earlier in the flow, the training cannot rely on extensive mission-specific technical knowledge. Hence, the need for a generic SFRM training framework that would allow FCers to develop basic teamwork skills which are mission relevant, but without the required mission knowledge. Work on SFRM training has been conducted in collaboration with the Expedition Vehicle Division at the Mission Operations Directorate (MOD) and with United Space Alliance (USA) which provides training to Flight Controllers. The space flight resource management training work is part of the Human Factors in Training Directed Research Project (DRP) of the Space Human Factors Engineering (SHFE) Project under the Space Human Factors and Habitability (SHFH) Element of the Human Research Program (HRP). Human factors researchers at the Ames Research Center have been investigating team work and distributed decision making processes to develop a generic SFRM training framework for flight controllers. The work proposed for FY10 continues to build on this strong collaboration with MOD and the USA Training Group as well as previous research in relevant domains such as aviation. In FY10, the work focuses on documenting and analyzing problem solving strategies and decision making processes used in MCC by experienced FCers.
Acute Exposure to Low-to-Moderate Carbon Dioxide Levels and Submariner Decision Making.
Rodeheffer, Christopher D; Chabal, Sarah; Clarke, John M; Fothergill, David M
2018-06-01
Submarines routinely operate with higher levels of ambient carbon dioxide (CO2) (i.e., 2000 - 5000 ppm) than what is typically considered normal (i.e., 400 - 600 ppm). Although significant cognitive impairments are rarely reported at these elevated CO2 levels, recent studies using the Strategic Management Simulation (SMS) test have found impairments in decision-making performance during acute CO2 exposure at levels as low as 1000 ppm. This is a potential concern for submarine operations, as personnel regularly make mission-critical decisions that affect the safety and efficiency of the vessel and its crew while exposed to similar levels of CO2. The objective of this study was to determine if submariner decision-making performance is impacted by acute exposure to levels of CO2 routinely present in the submarine atmosphere during sea patrols. Using a subject-blinded balanced design, 36 submarine-qualified sailors were randomly assigned to receive 1 of 3 CO2 exposure conditions (600, 2500, or 15,000 ppm). After a 45-min atmospheric acclimation period, participants completed an 80-min computer-administered SMS test as a measure of decision making. There were no significant differences for any of the nine SMS measures of decision making between the CO2 exposure conditions. In contrast to recent research demonstrating cognitive deficits on the SMS test in students and professional-grade office workers, we were unable to replicate this effect in a submariner population-even with acute CO2 exposures more than an order of magnitude greater than those used in previous studies that demonstrated such effects.Rodeheffer CD, Chabal S, Clarke JM, Fothergill DM. Acute exposure to low-to-moderate carbon dioxide levels and submariner decision making. Aerosp Med Hum Perform. 2018; 89(6):520-525.
The impact of simulation sequencing on perceived clinical decision making.
Woda, Aimee; Hansen, Jamie; Paquette, Mary; Topp, Robert
2017-09-01
An emerging nursing education trend is to utilize simulated learning experiences as a means to optimize competency and decision making skills. The purpose of this study was to examine differences in students' perception of clinical decision making and clinical decision making-related self-confidence and anxiety based on the sequence (order) in which they participated in a block of simulated versus hospital-based learning experiences. A quasi-experimental crossover design was used. Between and within group differences were found relative to self-confidence with the decision making process. When comparing groups, at baseline the simulation followed by hospital group had significantly higher self-confidence scores, however, at 14-weeks both groups were not significantly different. Significant within group differences were found in the simulation followed by hospital group only, demonstrating a significant decrease in clinical decision making related anxiety across the semester. Finally, there were no significant difference in; perceived clinical decision making within or between the groups at the two measurement points. Preliminary findings suggest that simulated learning experiences can be offered with alternating sequences without impacting the process, anxiety or confidence with clinical decision making. This study provides beginning evidence to guide curriculum development and allow flexibility based on student needs and available resources. Copyright © 2017. Published by Elsevier Ltd.
NASA Astrophysics Data System (ADS)
Li, Yu; Giuliani, Matteo; Castelletti, Andrea
2017-09-01
Recent advances in weather and climate (W&C) services are showing increasing forecast skills over seasonal and longer timescales, potentially providing valuable support in informing decisions in a variety of economic sectors. Quantifying this value, however, might not be straightforward as better forecast quality does not necessarily imply better decisions by the end users, especially when forecasts do not reach their final users, when providers are not trusted, or when forecasts are not appropriately understood. In this study, we contribute an assessment framework to evaluate the operational value of W&C services for informing agricultural practices by complementing traditional forecast quality assessments with a coupled human-natural system behavioural model which reproduces farmers' decisions. This allows a more critical assessment of the forecast value mediated by the end users' perspective, including farmers' risk attitudes and behavioural factors. The application to an agricultural area in northern Italy shows that the quality of state-of-the-art W&C services is still limited in predicting the weather and the crop yield of the incoming agricultural season, with ECMWF annual products simulated by the IFS/HOPE model resulting in the most skillful product in the study area. However, we also show that the accuracy of estimating crop yield and the probability of making optimal decisions are not necessarily linearly correlated, with the overall assessment procedure being strongly impacted by the behavioural attitudes of farmers, which can produce rank reversals in the quantification of the W&C services operational value depending on the different perceptions of risk and uncertainty.
NASA Technical Reports Server (NTRS)
Callantine, Todd J.; Cabrall, Christopher; Kupfer, Michael; Omar, Faisal G.; Prevot, Thomas
2012-01-01
NASA?s Air Traffic Management Demonstration-1 (ATD-1) is a multi-year effort to demonstrate high-throughput, fuel-efficient arrivals at a major U.S. airport using NASA-developed scheduling automation, controller decision-support tools, and ADS-B-enabled Flight-Deck Interval Management (FIM) avionics. First-year accomplishments include the development of a concept of operations for managing scheduled arrivals flying Optimized Profile Descents with equipped aircraft conducting FIM operations, and the integration of laboratory prototypes of the core ATD-1 technologies. Following each integration phase, a human-in-the-loop simulation was conducted to evaluate and refine controller tools, procedures, and clearance phraseology. From a ground-side perspective, the results indicate the concept is viable and the operations are safe and acceptable. Additional training is required for smooth operations that yield notable benefits, particularly in the areas of FIM operations and clearance phraseology.
Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System
NASA Astrophysics Data System (ADS)
Ben Rabah, N.; Saddem, R.; Ben Hmida, F.; Carre-Menetrier, V.; Tagina, M.
2017-01-01
Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach.
Behavior analysis of container ship in maritime accident in order to redefine the operating criteria
NASA Astrophysics Data System (ADS)
Ancuţa, C.; Stanca, C.; Andrei, C.; Acomi, N.
2017-08-01
In order to enhance the efficiency of maritime transport, container ships operators proceeded to increase the sizes of ships. The latest generation of ships in operation has 19,000 TEU capacity and the perspective is 21,000 TEU within the next years. The increasing of the sizes of container ships involves risks of maritime accidents occurrences. Nowadays, the general rules on operational security, tend to be adjusted as a result of the evaluation for each vessel. To create the premises for making an informed decision, the captain have to be aware of ships behavior in such situations. Not less important is to assure permanent review of the procedures for operation of ship, including the specific procedures in special areas, confined waters or separation schemes. This paper aims at analysing the behavior of the vessel and the respond of the structure of a container ship in maritime accident, in order to redefine the operating criteria. The method selected by authors for carrying out the research is computer simulations. Computer program provides the responses of the container ship model in various situations. Therefore, the simulations allow acquisition of a large category of data, in the scope of improving the prevention of accidents or mitigation of effects as much as possible. Simulations and assessments of certain situations that the ship might experience will be carried out to redefine the operating criteria. The envisaged scenarios are: introducing of maneuver speed for specific areas with high risk of collision or grounding, introducing of flooding scenarios of some compartments in loading programs, conducting of complex simulations in various situations for each vessel type. The main results of this work are documented proposals for operating criteria, intended to improve the safety in case of marine accidents, collisions and groundings. Introducing of such measures requires complex cost benefit analysis, that should not neglect the extreme economic impact that may result from such casualties.
Large-screen display technology assessment for military applications
NASA Astrophysics Data System (ADS)
Blaha, Richard J.
1990-08-01
Full-color, large screen display systems can enhance military applications that require group presentation, coordinated decisions, or interaction between decision makers. The technology already plays an important role in operations centers, simulation facilities, conference rooms, and training centers. Some applications display situational, status, or briefing information, while others portray instructional material for procedural training or depict realistic panoramic scenes that are used in simulators. While each specific application requires unique values of luminance, resolution, response time, reliability, and the video interface, suitable performance can be achieved with available commercial large screen displays. Advances in the technology of large screen displays are driven by the commercial applications because the military applications do not provide the significant market share enjoyed by high definition television (HDTV), entertainment, advertisement, training, and industrial applications. This paper reviews the status of full-color, large screen display technologies and includes the performance and cost metrics of available systems. For this discussion, performance data is based upon either measurements made by our personnel or extractions from vendors' data sheets.
Ji, Yanqing; Ying, Hao; Farber, Margo S.; Yen, John; Dews, Peter; Miller, Richard E.; Massanari, R. Michael
2014-01-01
Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is of great importance. The current approach to postmarketing surveillance primarily relies on spontaneous reporting. It is a passive surveillance system and limited by gross underreporting (<10% reporting rate), latency, and inconsistent reporting. We propose a novel team-based intelligent agent software system approach for proactively monitoring and detecting potential ADRs of interest using electronic patient records. We designed such a system and named it ADRMonitor. The intelligent agents, operating on computers located in different places, are capable of continuously and autonomously collaborating with each other and assisting the human users (e.g., the food and drug administration (FDA), drug safety professionals, and physicians). The agents should enhance current systems and accelerate early ADR identification. To evaluate the performance of the ADRMonitor with respect to the current spontaneous reporting approach, we conducted simulation experiments on identification of ADR signal pairs (i.e., potential links between drugs and apparent adverse reactions) under various conditions. The experiments involved over 275 000 simulated patients created on the basis of more than 1000 real patients treated by the drug cisapride that was on the market for seven years until its withdrawal by the FDA in 2000 due to serious ADRs. Healthcare professionals utilizing the spontaneous reporting approach and the ADRMonitor were separately simulated by decision-making models derived from a general cognitive decision model called fuzzy recognition-primed decision (RPD) model that we recently developed. The quantitative simulation results show that 1) the number of true ADR signal pairs detected by the ADRMonitor is 6.6 times higher than that by the spontaneous reporting strategy; 2) the ADR detection rate of the ADRMonitor agents with even moderate decision-making skills is five times higher than that of spontaneous reporting; and 3) as the number of patient cases increases, ADRs could be detected significantly earlier by the ADRMonitor. PMID:20007038
Auble, Gregor T.; Wondzell, Mark; Talbert, Colin
2009-01-01
This report describes and documents a decision support system for the Gunnison River in Black Canyon of the Gunnison National Park. It is a macro-embedded EXCEL program that calculates and displays indicators representing valued characteristics or processes in the Black Canyon based on daily flows of the Gunnison River. The program is designed to easily accept input from downloaded stream gage records or output from the RIVERWARE reservoir operations model being used for the upstream Aspinall Unit. The decision support system is structured to compare as many as eight alternative flow regimes, where each alternative is represented by a daily sequence of at least 20 calendar years of streamflow. Indicators include selected flow statistics, riparian plant community distribution, clearing of box elder by inundation and scour, several measures of sediment mobilization, trout fry habitat, and federal reserved water rights. Calculation of variables representing National Park Service federal reserved water rights requires additional secondary input files pertaining to forecast and actual basin inflows and storage levels in Blue Mesa reservoir. Example input files representing a range of situations including historical, reconstructed natural, and simulated alternative reservoir operations are provided with the software.
NASA Technical Reports Server (NTRS)
Hayashi, Miwa; Hoang, Ty; Jung, Yoon C.; Malik, Waqar; Lee, Hanbong; Dulchinos, Victoria L.
2015-01-01
This paper proposes a new departure pushback decision-support tool (DST) for airport ramp-tower controllers. It is based on NASA's Spot and Runway Departure Advisor (SARDA) collaborative decision-making concept, except with the modification that the gate releases now are controlled by tactical pushback (or gate-hold) advisories instead of strategic pre-assignments of target pushback times to individual departure flights. The proposed ramp DST relies on data exchange with the airport traffic control tower (ATCT) to coordinate pushbacks with the ATCT's flow-management intentions under current operational constraints, such as Traffic Management Initiative constraints. Airlines would benefit in reduced taxi delay and fuel burn. The concept was evaluated in a human-in-the-loop simulation experiment with current ramp-tower controllers at the Charlotte Douglas International Airport as participants. The results showed that the tool helped reduce taxi time by one minute per flight and overall departure flight fuel consumption by 10-12% without reducing runway throughput. Expect Departure Clearance Time (EDCT) conformance also was improved when advisories were provided. These benefits were attained without increasing the ramp-tower controllers' workload. Additionally, the advisories reduced the ATCT controllers' workload.
Fuzzy set methods for object recognition in space applications
NASA Technical Reports Server (NTRS)
Keller, James M.
1991-01-01
Progress on the following tasks is reported: (1) fuzzy set-based decision making methodologies; (2) feature calculation; (3) clustering for curve and surface fitting; and (4) acquisition of images. The general structure for networks based on fuzzy set connectives which are being used for information fusion and decision making in space applications is described. The structure and training techniques for such networks consisting of generalized means and gamma-operators are described. The use of other hybrid operators in multicriteria decision making is currently being examined. Numerous classical features on image regions such as gray level statistics, edge and curve primitives, texture measures from cooccurrance matrix, and size and shape parameters were implemented. Several fractal geometric features which may have a considerable impact on characterizing cluttered background, such as clouds, dense star patterns, or some planetary surfaces, were used. A new approach to a fuzzy C-shell algorithm is addressed. NASA personnel are in the process of acquiring suitable simulation data and hopefully videotaped actual shuttle imagery. Photographs have been digitized to use in the algorithms. Also, a model of the shuttle was assembled and a mechanism to orient this model in 3-D to digitize for experiments on pose estimation is being constructed.
A fuzzy decision tree for fault classification.
Zio, Enrico; Baraldi, Piero; Popescu, Irina C
2008-02-01
In plant accident management, the control room operators are required to identify the causes of the accident, based on the different patterns of evolution of the monitored process variables thereby developing. This task is often quite challenging, given the large number of process parameters monitored and the intense emotional states under which it is performed. To aid the operators, various techniques of fault classification have been engineered. An important requirement for their practical application is the physical interpretability of the relationships among the process variables underpinning the fault classification. In this view, the present work propounds a fuzzy approach to fault classification, which relies on fuzzy if-then rules inferred from the clustering of available preclassified signal data, which are then organized in a logical and transparent decision tree structure. The advantages offered by the proposed approach are precisely that a transparent fault classification model is mined out of the signal data and that the underlying physical relationships among the process variables are easily interpretable as linguistic if-then rules that can be explicitly visualized in the decision tree structure. The approach is applied to a case study regarding the classification of simulated faults in the feedwater system of a boiling water reactor.
Chen, T N; Yin, X T; Li, X G; Zhao, J; Wang, L; Mu, N; Ma, K; Huo, K; Liu, D; Gao, B Y; Feng, H; Li, F
2018-05-08
Objective: To explore the clinical and teaching application value of virtual reality technology in preoperative planning and intraoperative guide of glioma located in central sulcus region. Method: Ten patients with glioma in the central sulcus region were proposed to surgical treatment. The neuro-imaging data, including CT, CTA, DSA, MRI, fMRI were input to 3dgo sczhry workstation for image fusion and 3D reconstruction. Spatial relationships between the lesions and the surrounding structures on the virtual reality image were obtained. These images were applied to the operative approach design, operation process simulation, intraoperative auxiliary decision and the training of specialist physician. Results: Intraoperative founding of 10 patients were highly consistent with preoperative simulation with virtual reality technology. Preoperative 3D reconstruction virtual reality images improved the feasibility of operation planning and operation accuracy. This technology had not only shown the advantages for neurological function protection and lesion resection during surgery, but also improved the training efficiency and effectiveness of dedicated physician by turning the abstract comprehension to virtual reality. Conclusion: Image fusion and 3D reconstruction based virtual reality technology in glioma resection is helpful for formulating the operation plan, improving the operation safety, increasing the total resection rate, and facilitating the teaching and training of the specialist physician.
Bucknall, Tracey K; Forbes, Helen; Phillips, Nicole M; Hewitt, Nicky A; Cooper, Simon; Bogossian, Fiona
2016-10-01
The aim of this study was to examine the decision-making of nursing students during team based simulations on patient deterioration to determine the sources of information, the types of decisions made and the influences underpinning their decisions. Missed, misinterpreted or mismanaged physiological signs of deterioration in hospitalized patients lead to costly serious adverse events. Not surprisingly, an increased focus on clinical education and graduate nurse work readiness has resulted. A descriptive exploratory design. Clinical simulation laboratories in three Australian universities were used to run team based simulations with a patient actor. A convenience sample of 97 final-year nursing students completed simulations, with three students forming a team. Four teams from each university were randomly selected for detailed analysis. Cued recall during video review of team based simulation exercises to elicit descriptions of individual and team based decision-making and reflections on performance were audio-recorded post simulation (2012) and transcribed. Students recalled 11 types of decisions, including: information seeking; patient assessment; diagnostic; intervention/treatment; evaluation; escalation; prediction; planning; collaboration; communication and reflective. Patient distress, uncertainty and a lack of knowledge were frequently recalled influences on decisions. Incomplete information, premature diagnosis and a failure to consider alternatives when caring for patients is likely to lead to poor quality decisions. All health professionals have a responsibility in recognizing and responding to clinical deterioration within their scope of practice. A typology of nursing students' decision-making in teams, in this context, highlights the importance of individual knowledge, leadership and communication. © 2016 John Wiley & Sons Ltd.
Benefits Assessment of Algorithmically Combining Generic High Altitude Airspace Sectors
NASA Technical Reports Server (NTRS)
Bloem, Michael; Gupta, Pramod; Lai, Chok Fung; Kopardekar, Parimal
2009-01-01
In today's air traffic control operations, sectors that have traffic demand below capacity are combined so that fewer controller teams are required to manage air traffic. Controllers in current operations are certified to control a group of six to eight sectors, known as an area of specialization. Sector combinations are restricted to occur within areas of specialization. Since there are few sector combination possibilities in each area of specialization, human supervisors can effectively make sector combination decisions. In the future, automation and procedures will allow any appropriately trained controller to control any of a large set of generic sectors. The primary benefit of this will be increased controller staffing flexibility. Generic sectors will also allow more options for combining sectors, making sector combination decisions difficult for human supervisors. A sector-combining algorithm can assist supervisors as they make generic sector combination decisions. A heuristic algorithm for combining under-utilized air space sectors to conserve air traffic control resources has been described and analyzed. Analysis of the algorithm and comparisons with operational sector combinations indicate that this algorithm could more efficiently utilize air traffic control resources than current sector combinations. This paper investigates the benefits of using the sector-combining algorithm proposed in previous research to combine high altitude generic airspace sectors. Simulations are conducted in which all the high altitude sectors in a center are allowed to combine, as will be possible in generic high altitude airspace. Furthermore, the algorithm is adjusted to use a version of the simplified dynamic density (SDD) workload metric that has been modified to account for workload reductions due to automatic handoffs and Automatic Dependent Surveillance Broadcast (ADS-B). This modified metric is referred to here as future simplified dynamic density (FSDD). Finally, traffic demand sets with increased air traffic demand are used in the simulations to capture the expected growth in air traffic demand by the mid-term.
NASA Astrophysics Data System (ADS)
Bürger, Adrian; Sawant, Parantapa; Bohlayer, Markus; Altmann-Dieses, Angelika; Braun, Marco; Diehl, Moritz
2017-10-01
Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.
NASA Technical Reports Server (NTRS)
2002-01-01
Ames Research Center granted Reality Capture Technologies (RCT), Inc., a license to further develop NASA's Mars Map software platform. The company incorporated NASA#s innovation into software that uses the Virtual Plant Model (VPM)(TM) to structure, modify, and implement the construction sites of industrial facilities, as well as develop, validate, and train operators on procedures. The VPM orchestrates the exchange of information between engineering, production, and business transaction systems. This enables users to simulate, control, and optimize work processes while increasing the reliability of critical business decisions. Engineers can complete the construction process and test various aspects of it in virtual reality before building the actual structure. With virtual access to and simulation of the construction site, project personnel can manage, access control, and respond to changes on complex constructions more effectively. Engineers can also create operating procedures, training, and documentation. Virtual Plant Model(TM) is a trademark of Reality Capture Technologies, Inc.
A three-stage birandom program for unit commitment with wind power uncertainty.
Zhang, Na; Li, Weidong; Liu, Rao; Lv, Quan; Sun, Liang
2014-01-01
The integration of large-scale wind power adds a significant uncertainty to power system planning and operating. The wind forecast error is decreased with the forecast horizon, particularly when it is from one day to several hours ahead. Integrating intraday unit commitment (UC) adjustment process based on updated ultra-short term wind forecast information is one way to improve the dispatching results. A novel three-stage UC decision method, in which the day-ahead UC decisions are determined in the first stage, the intraday UC adjustment decisions of subfast start units are determined in the second stage, and the UC decisions of fast-start units and dispatching decisions are determined in the third stage is presented. Accordingly, a three-stage birandom UC model is presented, in which the intraday hours-ahead forecasted wind power is formulated as a birandom variable, and the intraday UC adjustment event is formulated as a birandom event. The equilibrium chance constraint is employed to ensure the reliability requirement. A birandom simulation based hybrid genetic algorithm is designed to solve the proposed model. Some computational results indicate that the proposed model provides UC decisions with lower expected total costs.
2011-06-01
Books. Dawkins , R. (1989), The Selfish Gene , 2 nd ed., Oxford University Press. Dekker, A.H. (2010), “Agent-Based Simulation for Counter-IED: A...memes” ( Dawkins , 1989; Gabora, 1995; Boal & Schultz, 2007). As Weeks & Galunic (2003) point out: “Memes are the replicators in cultural evolution...expression) create the macro-level patterns of culture. … Memes are the genes of culture.” Because genetic programs express beliefs, decision
Science in 60 â Simulating Flames Helps Tame Future Wildfires
Lin, Rod
2018-01-16
FIRETEC presents a new way of studying fire and learning how to better manage and cope with it. The model provides additional scientific input for decisions by policymakers working in land management, water resources and energy. The team hopes it will eventually assist fire and fuel management operations. This research is done in partnership with the USDA Forest Service, Air Force Wildland Fire Center, INRA and Canadian Forest Service.
Why pilots are least likely to get good decision making precisely when they need it most
NASA Technical Reports Server (NTRS)
Maher, John W.
1991-01-01
Studies of commercial aircraft incidents and accidents indicate that, in flight conditions not covered by standard operating procedures, as well as when the environment is saturated with information or unmanaged stress, cognitive shortcuts dominate aircrews' decisionmaking processes. Multidisciplinary research on such situations with high-fidelity simulators becomes critically important, as do psychometric tools which examine vigilance, personality resiliency before stressful conditions, and decisional and interpersonal mind-sets.
Rosetta CONSERT operations and data analysis preparation: simulation software tools.
NASA Astrophysics Data System (ADS)
Rogez, Yves; Hérique, Alain; Cardiet, Maël; Zine, Sonia; Westphal, Mathieu; Micallef, Mickael; Berquin, Yann; Kofman, Wlodek
2014-05-01
The CONSERT experiment onboard Rosetta and Philae will perform the tomography of the 67P/CG comet nucleus by measuring radio waves transmission from the Rosetta S/C to the Philae Lander. The accurate analysis of travel time measurements will deliver unique knowledge of the nucleus interior dielectric properties. The challenging complexity of CONSERT operations requirements, combining both Rosetta and Philae, allows only a few set of opportunities to acquire data. Thus, we need a fine analysis of the impact of Rosetta trajectory, Philae position and comet shape on CONSERT measurements, in order to take optimal decisions in a short time. The integration of simulation results and mission parameters provides synthetic information to evaluate performances and risks for each opportunity. The preparation of CONSERT measurements before space operations is a key to achieve the best science return of the experiment. In addition, during Rosetta space operations, these software tools will allow a "real-time" first analysis of the latest measurements to improve the next acquisition sequences. The software tools themselves are built around a 3D electromagnetic radio wave simulation, taking into account the signal polarization. It is based on ray-tracing algorithms specifically designed for quick orbit analysis and radar signal generation. This allows computation on big domains relatively to the wavelength. The extensive use of 3D visualization tools provides comprehensive and synthetic views of the results. The software suite is designed to be extended, after Rosetta operations, to the full 3D measurement data analysis using inversion methods.
Miller, Keith W; Wolf, Marty J; Grodzinsky, Frances
2017-04-01
In this paper we address the question of when a researcher is justified in describing his or her artificial agent as demonstrating ethical decision-making. The paper is motivated by the amount of research being done that attempts to imbue artificial agents with expertise in ethical decision-making. It seems clear that computing systems make decisions, in that they make choices between different options; and there is scholarship in philosophy that addresses the distinction between ethical decision-making and general decision-making. Essentially, the qualitative difference between ethical decisions and general decisions is that ethical decisions must be part of the process of developing ethical expertise within an agent. We use this distinction in examining publicity surrounding a particular experiment in which a simulated robot attempted to safeguard simulated humans from falling into a hole. We conclude that any suggestions that this simulated robot was making ethical decisions were misleading.
The Teaching Decisions Simulation: An Interactive Vehicle for Mapping Teaching Decisions.
ERIC Educational Resources Information Center
Strang, Harold R.
1996-01-01
Describes the Teaching Decisions Simulation, a program that allows participants to make decisions regarding lesson plan activities and student and teacher spatial arrangement or interactions. Postlesson feedback includes variables such as completion time and performance measures. Experienced teachers exhibited more deliberation in completing the…
Risk analysis theory applied to fishing operations: A new approach on the decision-making problem
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cunha, J.C.S.
1994-12-31
In the past the decisions concerning whether to continue or interrupt a fishing operation were based primarily on the operator`s previous experience. This procedure often led to wrong decisions and unnecessary loss of money and time. This paper describes a decision-making method based on risk analysis theory and previous operation results from a field under study. The method leads to more accurate decisions on a daily basis allowing the operator to verify each day of the operation if the decision being carried out is the one with the highest probability to conduct to the best economical result. An example ofmore » the method application is provided at the end of the paper.« less
Fews-Risk: A step towards risk-based flood forecasting
NASA Astrophysics Data System (ADS)
Bachmann, Daniel; Eilander, Dirk; de Leeuw, Annemargreet; Diermanse, Ferdinand; Weerts, Albrecht; de Bruijn, Karin; Beckers, Joost; Boelee, Leonore; Brown, Emma; Hazlewood, Caroline
2015-04-01
Operational flood prediction and the assessment of flood risk are important components of flood management. Currently, the model-based prediction of discharge and/or water level in a river is common practice for operational flood forecasting. Based on the prediction of these values decisions about specific emergency measures are made within operational flood management. However, the information provided for decision support is restricted to pure hydrological or hydraulic aspects of a flood. Information about weak sections within the flood defences, flood prone areas and assets at risk in the protected areas are rarely used in a model-based flood forecasting system. This information is often available for strategic planning, but is not in an appropriate format for operational purposes. The idea of FEWS-Risk is the extension of existing flood forecasting systems with elements of strategic flood risk analysis, such as probabilistic failure analysis, two dimensional flood spreading simulation and the analysis of flood impacts and consequences. Thus, additional information is provided to the decision makers, such as: • Location, timing and probability of failure of defined sections of the flood defence line; • Flood spreading, extent and hydraulic values in the hinterland caused by an overflow or a breach flow • Impacts and consequences in case of flooding in the protected areas, such as injuries or casualties and/or damages to critical infrastructure or economy. In contrast with purely hydraulic-based operational information, these additional data focus upon decision support for answering crucial questions within an operational flood forecasting framework, such as: • Where should I reinforce my flood defence system? • What type of action can I take to mend a weak spot in my flood defences? • What are the consequences of a breach? • Which areas should I evacuate first? This presentation outlines the additional required workflows towards risk-based flood forecasting systems. In a cooperation between HR Wallingford and Deltares, the extended workflows are being integrated into the Delft-FEWS software system. Delft-FEWS provides modules for managing the data handling and forecasting process. Results of a pilot study that demonstrates the new tools are presented. The value of the newly generated information for decision support during a flood event is discussed.
Walker, Robert; Arima, Eugenio; Messina, Joe; Soares-Filho, Britaldo; Perz, Stephen; Vergara, Dante; Sales, Marcio; Pereira, Ritaumaria; Castro, Williams
2013-01-01
This article addresses the spatial decision-making of loggers and implications for forest fragmentation in the Amazon basin. It provides a behavioral explanation for fragmentation by modeling how loggers build road networks, typically abandoned upon removal of hardwoods. Logging road networks provide access to land, and the settlers who take advantage of them clear fields and pastures that accentuate their spatial signatures. In shaping agricultural activities, these networks organize emergent patterns of forest fragmentation, even though the loggers move elsewhere. The goal of the article is to explicate how loggers shape their road networks, in order to theoretically explain an important type of forest fragmentation found in the Amazon basin, particularly in Brazil. This is accomplished by adapting graph theory to represent the spatial decision-making of loggers, and by implementing computational algorithms that build graphs interpretable as logging road networks. The economic behavior of loggers is conceptualized as a profit maximization problem, and translated into spatial decision-making by establishing a formal correspondence between mathematical graphs and road networks. New computational approaches, adapted from operations research, are used to construct graphs and simulate spatial decision-making as a function of discount rates, land tenure, and topographic constraints. The algorithms employed bracket a range of behavioral settings appropriate for areas of terras de volutas, public lands that have not been set aside for environmental protection, indigenous peoples, or colonization. The simulation target sites are located in or near so-called Terra do Meio, once a major logging frontier in the lower Amazon Basin. Simulation networks are compared to empirical ones identified by remote sensing and then used to draw inferences about factors influencing the spatial behavior of loggers. Results overall suggest that Amazonia's logging road networks induce more fragmentation than necessary to access fixed quantities of wood. The paper concludes by considering implications of the approach and findings for Brazil's move to a system of concession logging.
Improved CDMA Performance Using Parallel Interference Cancellation
NASA Technical Reports Server (NTRS)
Simon, Marvin; Divsalar, Dariush
1995-01-01
This report considers a general parallel interference cancellation scheme that significantly reduces the degradation effect of user interference but with a lesser implementation complexity than the maximum-likelihood technique. The scheme operates on the fact that parallel processing simultaneously removes from each user the interference produced by the remaining users accessing the channel in an amount proportional to their reliability. The parallel processing can be done in multiple stages. The proposed scheme uses tentative decision devices with different optimum thresholds at the multiple stages to produce the most reliably received data for generation and cancellation of user interference. The 1-stage interference cancellation is analyzed for three types of tentative decision devices, namely, hard, null zone, and soft decision, and two types of user power distribution, namely, equal and unequal powers. Simulation results are given for a multitude of different situations, in particular, those cases for which the analysis is too complex.
A Decision Support System for Mitigating Stream Temperature Impacts in the Sacramento River
NASA Astrophysics Data System (ADS)
Caldwell, R. J.; Zagona, E. A.; Rajagopalan, B.
2014-12-01
Increasing demands on the limited and variable water supply across the West can result in insufficient streamflow to sustain healthy fish habitat. We develop an integrated decision support system (DSS) for modeling and mitigating stream temperature impacts and demonstrate it on the Sacramento River system in California. Water management in the Sacramento River is a complex task with a diverse set of demands ranging from municipal supply to mitigation of fisheries impacts due to high water temperatures. Current operations utilize the temperature control device (TCD) structure at Shasta Dam to mitigate these high water temperatures downstream at designated compliance points. The TCD structure at Shasta Dam offers a rather unique opportunity to mitigate water temperature violations through adjustments to both release volume and temperature. In this study, we develop and evaluate a model-based DSS with four broad components that are coupled to produce the decision tool for stream temperature mitigation: (i) a suite of statistical models for modeling stream temperature attributes using hydrology and climate variables of critical importance to fish habitat; (ii) a reservoir thermal model for modeling the thermal structure and, consequently, the water release temperature, (iii) a stochastic weather generator to simulate weather sequences consistent with seasonal outlooks; and, (iv) a set of decision rules (i.e., 'rubric') for reservoir water releases in response to outputs from the above components. Multiple options for modifying releases at Shasta Dam were considered in the DSS, including mixing water from multiple elevations through the TCD and using different acceptable levels of risk. The DSS also incorporates forecast uncertainties and reservoir operating options to help mitigate stream temperature impacts for fish habitat, while efficiently using the reservoir water supply and cold pool storage. The use of these coupled tools in simulating impacts of future climate on stream temperature variability is also demonstrated. Results indicate that the DSS could substantially reduce the number of violations of thermal criteria, while ensuring maintenance of the cold pool storage throughout the summer.
Chang, Ni-Bin; Ning, Shu-Kuang; Chen, Jen-Chang
2006-08-01
Due to increasing environmental consciousness in most countries, every utility that owns a commercial nuclear power plant has been required to have both an on-site and off-site emergency response plan since the 1980s. A radiation monitoring network, viewed as part of the emergency response plan, can provide information regarding the radiation dosage emitted from a nuclear power plant in a regular operational period and/or abnormal measurements in an emergency event. Such monitoring information might help field operators and decision-makers to provide accurate responses or make decisions to protect the public health and safety. This study aims to conduct an integrated simulation and optimization analysis looking for the relocation strategy of a long-term regular off-site monitoring network at a nuclear power plant. The planning goal is to downsize the current monitoring network but maintain its monitoring capacity as much as possible. The monitoring sensors considered in this study include the thermoluminescence dosimetry (TLD) and air sampling system (AP) simultaneously. It is designed for detecting the radionuclide accumulative concentration, the frequency of violation, and the possible population affected by a long-term impact in the surrounding area regularly while it can also be used in an accidental release event. With the aid of the calibrated Industrial Source Complex-Plume Rise Model Enhancements (ISC-PRIME) simulation model to track down the possible radionuclide diffusion, dispersion, transport, and transformation process in the atmospheric environment, a multiobjective evaluation process can be applied to achieve the screening of monitoring stations for the nuclear power plant located at Hengchun Peninsula, South Taiwan. To account for multiple objectives, this study calculated preference weights to linearly combine objective functions leading to decision-making with exposure assessment in an optimization context. Final suggestions should be useful for narrowing the set of scenarios that decision-makers need to consider in this relocation process.
Evaluation of power system security and development of transmission pricing method
NASA Astrophysics Data System (ADS)
Kim, Hyungchul
The electric power utility industry is presently undergoing a change towards the deregulated environment. This has resulted in unbundling of generation, transmission and distribution services. The introduction of competition into unbundled electricity services may lead system operation closer to its security boundaries resulting in smaller operating safety margins. The competitive environment is expected to lead to lower price rates for customers and higher efficiency for power suppliers in the long run. Under this deregulated environment, security assessment and pricing of transmission services have become important issues in power systems. This dissertation provides new methods for power system security assessment and transmission pricing. In power system security assessment, the following issues are discussed (1) The description of probabilistic methods for power system security assessment; (2) The computation time of simulation methods; (3) on-line security assessment for operation. A probabilistic method using Monte-Carlo simulation is proposed for power system security assessment. This method takes into account dynamic and static effects corresponding to contingencies. Two different Kohonen networks, Self-Organizing Maps and Learning Vector Quantization, are employed to speed up the probabilistic method. The combination of Kohonen networks and Monte-Carlo simulation can reduce computation time in comparison with straight Monte-Carlo simulation. A technique for security assessment employing Bayes classifier is also proposed. This method can be useful for system operators to make security decisions during on-line power system operation. This dissertation also suggests an approach for allocating transmission transaction costs based on reliability benefits in transmission services. The proposed method shows the transmission transaction cost of reliability benefits when transmission line capacities are considered. The ratio between allocation by transmission line capacity-use and allocation by reliability benefits is computed using the probability of system failure.
Decision support system for the operating room rescheduling problem.
van Essen, J Theresia; Hurink, Johann L; Hartholt, Woutske; van den Akker, Bernd J
2012-12-01
Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.
NASA Technical Reports Server (NTRS)
Zang, Thomas A.; Luckring, James M.; Morrison, Joseph H.; Blattnig, Steve R.; Green, Lawrence L.; Tripathi, Ram K.
2007-01-01
The National Aeronautics and Space Administration (NASA) recently issued an interim version of the Standard for Models and Simulations (M&S Standard) [1]. The action to develop the M&S Standard was identified in an internal assessment [2] of agency-wide changes needed in the wake of the Columbia Accident [3]. The primary goal of this standard is to ensure that the credibility of M&S results is properly conveyed to those making decisions affecting human safety or mission success criteria. The secondary goal is to assure that the credibility of the results from models and simulations meets the project requirements (for credibility). This presentation explains the motivation and key aspects of the M&S Standard, with a special focus on the requirements for verification, validation and uncertainty quantification. Some pilot applications of this standard to computational fluid dynamics applications will be provided as illustrations. The authors of this paper are the members of the team that developed the initial three drafts of the standard, the last of which benefited from extensive comments from most of the NASA Centers. The current version (number 4) incorporates modifications made by a team representing 9 of the 10 NASA Centers. A permanent version of the M&S Standard is expected by December 2007. The scope of the M&S Standard is confined to those uses of M&S that support program and project decisions that may affect human safety or mission success criteria. Such decisions occur, in decreasing order of importance, in the operations, the test & evaluation, and the design & analysis phases. Requirements are placed on (1) program and project management, (2) models, (3) simulations and analyses, (4) verification, validation and uncertainty quantification (VV&UQ), (5) recommended practices, (6) training, (7) credibility assessment, and (8) reporting results to decision makers. A key component of (7) and (8) is the use of a Credibility Assessment Scale, some of the details of which were developed in consultation with William Oberkampf, David Peercy and Timothy Trocano of Sandia National Laboratories. The focus of most of the requirements, including those for VV&UQ, is on the documentation of what was done and the reporting, using the Credibility Assessment Scale, of the level of rigor that was followed. The aspects of one option for the Credibilty Assessment Scale are (1) code verification, (2) solution verification, (3) validation, (4) predictive capability, (5) technical review, (6) process control, and (7) operator and analyst qualification.
Making Decisions about an Educational Game, Simulation or Workshop: A 'Game Theory' Perspective.
ERIC Educational Resources Information Center
Cryer, Patricia
1988-01-01
Uses game theory to help practitioners make decisions about educational games, simulations, or workshops whose outcomes depend to some extent on chance. Highlights include principles for making decisions involving risk; elementary laws of probability; utility theory; and principles for making decisions involving uncertainty. (eight references)…
Can't Get No (Dis)satisfaction: The "Statecraft" Simulation's Effect on Student Decision Making
ERIC Educational Resources Information Center
Raymond, Chad
2014-01-01
Simulations are often employed as content-teaching tools in political science, but their effect on students' reasoning skills is rarely assessed. This article explores what effect the "Statecraft" simulation might have on undergraduate students' perceptions of their decision making. Decisions are often evaluated on the basis of…
The ISS as a platform for a fully simulated mars voyage
NASA Astrophysics Data System (ADS)
Narici, Livio; Reitz, Guenther
2016-07-01
The ISS can mimic the impact of microgravity, radiation, living and psychological conditions that astronauts will face during a deep space cruise, for example to Mars. This suggests the ISS as the most valuable "analogue" for deep space exploration. NASA has indeed suggested a 'full-up deep space simulation on last available ISS Mission: 6/7 crew for one year duration; full simulation of time delays & autonomous operations'. This idea should be pushed further. It is indeed conceivable to use the ISS as the final "analogue", performing a real 'dry-run' of a deep space mission (such as a mission to Mars), as close as reasonably possible to what will be the real voyage. This Mars ISS dry run (ISS4Mars) would last 500-800 days, mimicking most of the challenges which will be undertaken such as length, isolation, food provision, decision making, time delays, health monitoring diagnostic and therapeutic actions and more: not a collection of "single experiments", but a complete exploration simulation were all the pieces will come together for the first in space simulated Mars voyage. Most of these challenges are the same that those that will be encountered during a Moon voyage, with the most evident exceptions being the duration and the communication delay. At the time of the Mars ISS dry run all the science and technological challenges will have to be mostly solved by dedicated works. These solutions will be synergistically deployed in the dry run which will simulate all the different aspects of the voyage, the trip to Mars, the permanence on the planet and the return to Earth. During the dry run i) There will be no arrivals/departure of spacecrafts; 2) Proper communications delay with ground will be simulated; 3) Decision processes will migrate from Ground to ISS; 4) Permanence on Mars will be simulated. Mars ISS dry run will use just a portion of the ISS which will be totally isolated from the rest of the ISS, leaving to the other ISS portions the task to provide the needed operational support for the ISS survival as well as the support for emergency situations. Beside helping in focusing the attention of the many space and space related programs to the quest for Mars, ISS4Mars will maintain a high level of attention of the funding institutions and provide an important focus for the general public. This talk will present the many scientific issues still open to be addressed (see for example the disciplinary reports of the THESEUS project#), some example of the challenging tests that could be performed, some of the operational challenges, as well as list some of the issues not likely/possible to be simulated. # http://www.theseus-eu.org
Twelfth Annual Conference on Manual Control
NASA Technical Reports Server (NTRS)
Wempe, T. E.
1976-01-01
Main topics discussed cover multi-task decision making, attention allocation and workload measurement, displays and controls, nonvisual displays, tracking and other psychomotor tasks, automobile driving, handling qualities and pilot ratings, remote manipulation, system identification, control models, and motion and visual cues. Sixty-five papers are included with presentations on results of analytical studies to develop and evaluate human operator models for a range of control task, vehicle dynamics and display situations; results of tests of physiological control systems and applications to medical problems; and on results of simulator and flight tests to determine display, control and dynamics effects on operator performance and workload for aircraft, automobile, and remote control systems.
Plant operation planning and scheduling
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jammar, R.J.
When properly designed, planning and scheduling can actually add millions of dollars per year to the bottom line. Planning and scheduling is a continuum of decisions starting with crude selection and ending with establishing short-term targets for crude processing and blending. It also includes maintaining optimization and operation simulation models. It is thought that conservatively, a refinery may save from $5 million to $10 million a year if it pays more attention to the processes behind proper planning and scheduling. Of course, the amount of savings can reach staggering proportions for companies now at the bottom of the Solomon Associatesmore » Inc. refinery performance ranking.« less
Combined Economic and Hydrologic Modeling to Support Collaborative Decision Making Processes
NASA Astrophysics Data System (ADS)
Sheer, D. P.
2008-12-01
For more than a decade, the core concept of the author's efforts in support of collaborative decision making has been a combination of hydrologic simulation and multi-objective optimization. The modeling has generally been used to support collaborative decision making processes. The OASIS model developed by HydroLogics Inc. solves a multi-objective optimization at each time step using a mixed integer linear program (MILP). The MILP can be configured to include any user defined objective, including but not limited too economic objectives. For example, an estimated marginal value for water for crops and M&I use were included in the objective function to drive trades in a model of the lower Rio Grande. The formulation of the MILP, constraints and objectives, in any time step is conditional: it changes based on the value of state variables and dynamic external forcing functions, such as rainfall, hydrology, market prices, arrival of migratory fish, water temperature, etc. It therefore acts as a dynamic short term multi-objective economic optimization for each time step. MILP is capable of solving a general problem that includes a very realistic representation of the physical system characteristics in addition to the normal multi-objective optimization objectives and constraints included in economic models. In all of these models, the short term objective function is a surrogate for achieving long term multi-objective results. The long term performance for any alternative (especially including operating strategies) is evaluated by simulation. An operating rule is the combination of conditions, parameters, constraints and objectives used to determine the formulation of the short term optimization in each time step. Heuristic wrappers for the simulation program have been developed improve the parameters of an operating rule, and are initiating research on a wrapper that will allow us to employ a genetic algorithm to improve the form of the rule (conditions, constraints, and short term objectives) as well. In the models operating rules represent different models of human behavior, and the objective of the modeling is to find rules for human behavior that perform well in terms of long term human objectives. The conceptual model used to represent human behavior incorporates economic multi-objective optimization for surrogate objectives, and rules that set those objectives based on current conditions and accounting for uncertainty, at least implicitly. The author asserts that real world operating rules follow this form and have evolved because they have been perceived as successful in the past. Thus, the modeling efforts focus on human behavior in much the same way that economic models focus on human behavior. This paper illustrates the above concepts with real world examples.
Tools and Techniques for Basin-Scale Climate Change Assessment
NASA Astrophysics Data System (ADS)
Zagona, E.; Rajagopalan, B.; Oakley, W.; Wilson, N.; Weinstein, P.; Verdin, A.; Jerla, C.; Prairie, J. R.
2012-12-01
The Department of Interior's WaterSMART Program seeks to secure and stretch water supplies to benefit future generations and identify adaptive measures to address climate change. Under WaterSMART, Basin Studies are comprehensive water studies to explore options for meeting projected imbalances in water supply and demand in specific basins. Such studies could be most beneficial with application of recent scientific advances in climate projections, stochastic simulation, operational modeling and robust decision-making, as well as computational techniques to organize and analyze many alternatives. A new integrated set of tools and techniques to facilitate these studies includes the following components: Future supply scenarios are produced by the Hydrology Simulator, which uses non-parametric K-nearest neighbor resampling techniques to generate ensembles of hydrologic traces based on historical data, optionally conditioned on long paleo reconstructed data using various Markov Chain techniuqes. Resampling can also be conditioned on climate change projections from e.g., downscaled GCM projections to capture increased variability; spatial and temporal disaggregation is also provided. The simulations produced are ensembles of hydrologic inputs to the RiverWare operations/infrastucture decision modeling software. Alternative demand scenarios can be produced with the Demand Input Tool (DIT), an Excel-based tool that allows modifying future demands by groups such as states; sectors, e.g., agriculture, municipal, energy; and hydrologic basins. The demands can be scaled at future dates or changes ramped over specified time periods. Resulting data is imported directly into the decision model. Different model files can represent infrastructure alternatives and different Policy Sets represent alternative operating policies, including options for noticing when conditions point to unacceptable vulnerabilities, which trigger dynamically executing changes in operations or other options. The over-arching Study Manager provides a graphical tool to create combinations of future supply scenarios, demand scenarios, infrastructure and operating policy alternatives; each scenario is executed as an ensemble of RiverWare runs, driven by the hydrologic supply. The Study Manager sets up and manages multiple executions on multi-core hardware. The sizeable are typically direct model outputs, or post-processed indicators of performance based on model outputs. Post processing statistical analysis of the outputs are possible using the Graphical Policy Analysis Tool or other statistical packages. Several Basin Studies undertaken have used RiverWare to evaluate future scenarios. The Colorado River Basin Study, the most complex and extensive to date, has taken advantage of these tools and techniques to generate supply scenarios, produce alternative demand scenarios and to set up and execute the many combinations of supplies, demands, policies, and infrastructure alternatives. The tools and techniques will be described with example applications.
NASA Astrophysics Data System (ADS)
Athmer, Keith; Gaughan, Chris; McDonnell, Joseph S.; Leach, Robert; Davis, Bert; Truong, Kiet; Borum, Howard; Leslie, Richard; Ma, Lein
2012-05-01
The development of an Integrated Base Defense (IBD) is a significant challenge for the Army with many analytical gaps. The IBD problem space is complex, with evolving requirements and a large stakeholder base. In order to evaluate and analyze IBD decisions, the Training & Doctrine Command (TRADOC) Maneuver Support Center of Excellence (MSCoE) led and continues to lead a series of IBD focused experiments and wargames. Modeling and Simulation (M&S) significantly contributes to this effort. To improve IBD M&S capabilities, a collaborative demonstration with the Research, Development and Engineering Command's (RDECOM's) M&S Decision Support Environment (MSDSE) was held in September 2011. The results of this demonstration provided key input to MSCoE IBD related concepts and technologies. Moreover, it established an initial M&S toolset that will significantly improve force protection in combat zones and Army installations worldwide by providing leaders a capability to conduct analysis of defense and mission rehearsals. The demonstration was executed with a "human in the loop" Battle Captain, who was aided by mission command assets such as Base Expeditionary Targeting and Surveillance Sensors-Combined (BETSS-C). The Common Operating Picture was populated and stimulated using Science & Technology (S&T) M&S, allowing for a realistic representation of physical phenomena without the need for real systems. Novel methods were used for simulation orchestration, and for initializing the simulations and Opposing Force (OPFOR) activities. Ultimately, this demonstration showed that the MSDSE is suitable to support TRADOC IBD analyses and that S&T M&S is ready to be used in a demanding simulation environment. This paper will highlight the event's outcomes and lessons identified.
Maneval, Rhonda; Fowler, Kimberly A; Kays, John A; Boyd, Tiffany M; Shuey, Jennifer; Harne-Britner, Sarah; Mastrine, Cynthia
2012-03-01
This study was conducted to determine whether the addition of high-fidelity patient simulation to new nurse orientation enhanced critical thinking and clinical decision-making skills. A pretest-posttest design was used to assess critical thinking and clinical decision-making skills in two groups of graduate nurses. Compared with the control group, the high-fidelity patient simulation group did not show significant improvement in mean critical thinking or clinical decision-making scores. When mean scores were analyzed, both groups showed an increase in critical thinking scores from pretest to posttest, with the high-fidelity patient simulation group showing greater gains in overall scores. However, neither group showed a statistically significant increase in mean test scores. The effect of high-fidelity patient simulation on critical thinking and clinical decision-making skills remains unclear. Copyright 2012, SLACK Incorporated.
Implications of Perioperative Team Setups for Operating Room Management Decisions.
Doll, Dietrich; Kauf, Peter; Wieferich, Katharina; Schiffer, Ralf; Luedi, Markus M
2017-01-01
Team performance has been studied extensively in the perioperative setting, but the managerial impact of interprofessional team performance remains unclear. We hypothesized that the interplay between anesthesiologists and surgeons would affect operating room turnaround times, and teams that worked together over time would become more efficient. We analyzed 13,632 surgical cases at our hospital that involved 64 surgeons and 48 anesthesiologists. We detrended and adjusted the data for potential confounders including age, American Society of Anesthesiologists physical status, and surgical list (scheduled cases of specific surgical specialties). The surgical lists were categorized as ear, nose, and throat surgery; trauma surgery; general surgery; and gynecology. We assessed the relationship between turnaround times and assignment of different anesthesiologists to specific surgeons using a Monte Carlo simulation. We found significant differences in team performances among the different surgical lists but no team learning. We constructed managerial decision tables for the assignment of anesthesiologists to specific surgeons at our hospital. We defined a decision algorithm based on these tables. Our analysis indicated that had this algorithm been used in staffing the operating room for the surgical cases represented in our data, median turnaround times would have a reduction potential of 6.8% (95% confidence interval 6.3% to 7.1%). A surgeon is usually predefined for scheduled surgeries (surgical list). Allocation of the right anesthesiologist to a list and to a surgeon can affect the team performance; thus, this assignment has managerial implications regarding the operating room efficiency affecting turnaround times and thus potentially overutilized time of a list at our hospital.
Water-resources optimization model for Santa Barbara, California
Nishikawa, Tracy
1998-01-01
A simulation-optimization model has been developed for the optimal management of the city of Santa Barbara's water resources during a drought. The model, which links groundwater simulation with linear programming, has a planning horizon of 5 years. The objective is to minimize the cost of water supply subject to: water demand constraints, hydraulic head constraints to control seawater intrusion, and water capacity constraints. The decision variables are montly water deliveries from surface water and groundwater. The state variables are hydraulic heads. The drought of 1947-51 is the city's worst drought on record, and simulated surface-water supplies for this period were used as a basis for testing optimal management of current water resources under drought conditions. The simulation-optimization model was applied using three reservoir operation rules. In addition, the model's sensitivity to demand, carry over [the storage of water in one year for use in the later year(s)], head constraints, and capacity constraints was tested.
Joint Seasonal ARMA Approach for Modeling of Load Forecast Errors in Planning Studies
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.
2014-04-14
To make informed and robust decisions in the probabilistic power system operation and planning process, it is critical to conduct multiple simulations of the generated combinations of wind and load parameters and their forecast errors to handle the variability and uncertainty of these time series. In order for the simulation results to be trustworthy, the simulated series must preserve the salient statistical characteristics of the real series. In this paper, we analyze day-ahead load forecast error data from multiple balancing authority locations and characterize statistical properties such as mean, standard deviation, autocorrelation, correlation between series, time-of-day bias, and time-of-day autocorrelation.more » We then construct and validate a seasonal autoregressive moving average (ARMA) model to model these characteristics, and use the model to jointly simulate day-ahead load forecast error series for all BAs.« less
[Stimulation and evaluation on maxillary distraction osteogenesis using CASSOS 2001].
Zhu, Min; Qiu, Wei-liu; Tang, You-sheng; Li, Qing-yun
2002-09-01
To simulate maxillary distraction osteogenesis and evaluate the change of soft and hard tissue before and after treatment, using Computer-Assisted Simulation System for Orthognathic Surgery( CASSOS 2001). A fourteen-year-old boy with severe maxillary hypoplasia, due to unilateral cleft lip and palate, was analysed by cephalometric analysis. The simulations of maxillary distraction osteogenesis (Le Fort I osteotomy and Le Fort II osteotomy) were re-analysed. After the treatment, cephalometric analysis was preformed again. The data were compared. The maxillary hypoplasia was well treated using maxillary distraction osteogenesis; Compared with Le fort I osteotomy, more satisfactory results can be obtained by Le fort I distraction osteogenesis. Maxillary distraction osteogenesis is a better way to treat severe maxillary hypoplasia with operated CLP than maxillary osteotomy. CASSOS 2001 can help surgeons and patients on simulation and evaluation of maxillary distraction osteogenesis, and on decision of treatment plan.
NASA Astrophysics Data System (ADS)
Marques, G.; Fraga, C. C. S.; Medellin-Azuara, J.
2016-12-01
The expansion and operation of urban water supply systems under growing demands, hydrologic uncertainty and water scarcity requires a strategic combination of supply sources for reliability, reduced costs and improved operational flexibility. The design and operation of such portfolio of water supply sources involves integration of long and short term planning to determine what and when to expand, and how much to use of each supply source accounting for interest rates, economies of scale and hydrologic variability. This research presents an integrated methodology coupling dynamic programming optimization with quadratic programming to optimize the expansion (long term) and operations (short term) of multiple water supply alternatives. Lagrange Multipliers produced by the short-term model provide a signal about the marginal opportunity cost of expansion to the long-term model, in an iterative procedure. A simulation model hosts the water supply infrastructure and hydrologic conditions. Results allow (a) identification of trade offs between cost and reliability of different expansion paths and water use decisions; (b) evaluation of water transfers between urban supply systems; and (c) evaluation of potential gains by reducing water system losses as a portfolio component. The latter is critical in several developing countries where water supply system losses are high and often neglected in favor of more system expansion.
NASA Astrophysics Data System (ADS)
Murphy, K. W.; Ellis, A. W.; Skindlov, J. A.
2015-12-01
Water resource systems have provided vital support to transformative growth in the Southwest United States and the Phoenix, Arizona metropolitan area where the Salt River Project (SRP) currently satisfies 40% of the area's water demand from reservoir storage and groundwater. Large natural variability and expectations of climate changes have sensitized water management to risks posed by future periods of excess and drought. The conventional approach to impacts assessment has been downscaled climate model simulations translated through hydrologic models; but, scenario ranges enlarge as uncertainties propagate through sequential levels of modeling complexity. The research often does not reach the stage of specific impact assessments, rendering future projections frustratingly uncertain and unsuitable for complex decision-making. Alternatively, this study inverts the common approach by beginning with the threatened water system and proceeding backwards to the uncertain climate future. The methodology is built upon reservoir system response modeling to exhaustive time series of climate-driven net basin supply. A reservoir operations model, developed with SRP guidance, assesses cumulative response to inflow variability and change. Complete statistical analyses of long-term historical watershed climate and runoff data are employed for 10,000-year stochastic simulations, rendering the entire range of multi-year extremes with full probabilistic characterization. Sets of climate change projections are then translated by temperature sensitivity and precipitation elasticity into future inflow distributions that are comparatively assessed with the reservoir operations model. This approach provides specific risk assessments in pragmatic terms familiar to decision makers, interpretable within the context of long-range planning and revealing a clearer meaning of climate change projections for the region. As a transferable example achieving actionable findings, the approach can guide other communities confronting water resource planning challenges.
Sleep Disruption Medical Intervention Forecasting (SDMIF) Module for the Integrated Medical Model
NASA Technical Reports Server (NTRS)
Lewandowski, Beth; Brooker, John; Mallis, Melissa; Hursh, Steve; Caldwell, Lynn; Myers, Jerry
2011-01-01
The NASA Integrated Medical Model (IMM) assesses the risk, including likelihood and impact of occurrence, of all credible in-flight medical conditions. Fatigue due to sleep disruption is a condition that could lead to operational errors, potentially resulting in loss of mission or crew. Pharmacological consumables are mitigation strategies used to manage the risks associated with sleep deficits. The likelihood of medical intervention due to sleep disruption was estimated with a well validated sleep model and a Monte Carlo computer simulation in an effort to optimize the quantity of consumables. METHODS: The key components of the model are the mission parameter program, the calculation of sleep intensity and the diagnosis and decision module. The mission parameter program was used to create simulated daily sleep/wake schedules for an ISS increment. The hypothetical schedules included critical events such as dockings and extravehicular activities and included actual sleep time and sleep quality. The schedules were used as inputs to the Sleep, Activity, Fatigue and Task Effectiveness (SAFTE) Model (IBR Inc., Baltimore MD), which calculated sleep intensity. Sleep data from an ISS study was used to relate calculated sleep intensity to the probability of sleep medication use, using a generalized linear model for binomial regression. A human yes/no decision process using a binomial random number was also factored into sleep medication use probability. RESULTS: These probability calculations were repeated 5000 times resulting in an estimate of the most likely amount of sleep aids used during an ISS mission and a 95% confidence interval. CONCLUSIONS: These results were transferred to the parent IMM for further weighting and integration with other medical conditions, to help inform operational decisions. This model is a potential planning tool for ensuring adequate sleep during sleep disrupted periods of a mission.
Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making
Schöner, Gregor; Gail, Alexander
2012-01-01
According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations. PMID:23166483
Enhanced and Synthetic Vision for Terminal Maneuvering Area NextGen Operations
NASA Technical Reports Server (NTRS)
Kramer, Lynda J.; Bailey, Randall E.; Ellis, Kyle K. E.; Norman, R. Michael; Williams, Steven P.; Arthur, Jarvis J., III; Shelton, Kevin J.; Prinzel, Lawrence J., III
2011-01-01
Synthetic Vision Systems and Enhanced Flight Vision System (SVS/EFVS) technologies have the potential to provide additional margins of safety for aircrew performance and enable operational improvements for low visibility operations in the terminal area environment with equivalent efficiency as visual operations. To meet this potential, research is needed for effective technology development and implementation of regulatory and design guidance to support introduction and use of SVS/EFVS advanced cockpit vision technologies in Next Generation Air Transportation System (NextGen) operations. A fixed-base pilot-in-the-loop simulation test was conducted at NASA Langley Research Center that evaluated the use of SVS/EFVS in NextGen low visibility ground (taxi) operations and approach/landing operations. Twelve crews flew approach and landing operations in a simulated NextGen Chicago O Hare environment. Various scenarios tested the potential for EFVS for operations in visibility as low as 1000 ft runway visibility range (RVR) and SVS to enable lower decision heights (DH) than can currently be flown today. Expanding the EFVS visual segment from DH to the runway in visibilities as low as 1000 RVR appears to be viable as touchdown performance was excellent without any workload penalties noted for the EFVS concept tested. A lower DH to 150 ft and/or possibly reduced visibility minima by virtue of SVS equipage appears to be viable when implemented on a Head-Up Display, but the landing data suggests further study for head-down implementations.
Metaheuristic simulation optimisation for the stochastic multi-retailer supply chain
NASA Astrophysics Data System (ADS)
Omar, Marina; Mustaffa, Noorfa Haszlinna H.; Othman, Siti Norsyahida
2013-04-01
Supply Chain Management (SCM) is an important activity in all producing facilities and in many organizations to enable vendors, manufacturers and suppliers to interact gainfully and plan optimally their flow of goods and services. A simulation optimization approach has been widely used in research nowadays on finding the best solution for decision-making process in Supply Chain Management (SCM) that generally faced a complexity with large sources of uncertainty and various decision factors. Metahueristic method is the most popular simulation optimization approach. However, very few researches have applied this approach in optimizing the simulation model for supply chains. Thus, this paper interested in evaluating the performance of metahueristic method for stochastic supply chains in determining the best flexible inventory replenishment parameters that minimize the total operating cost. The simulation optimization model is proposed based on the Bees algorithm (BA) which has been widely applied in engineering application such as training neural networks for pattern recognition. BA is a new member of meta-heuristics. BA tries to model natural behavior of honey bees in food foraging. Honey bees use several mechanisms like waggle dance to optimally locate food sources and to search new ones. This makes them a good candidate for developing new algorithms for solving optimization problems. This model considers an outbound centralised distribution system consisting of one supplier and 3 identical retailers and is assumed to be independent and identically distributed with unlimited supply capacity at supplier.
Self-Averaging Property of Minimal Investment Risk of Mean-Variance Model
Shinzato, Takashi
2015-01-01
In portfolio optimization problems, the minimum expected investment risk is not always smaller than the expected minimal investment risk. That is, using a well-known approach from operations research, it is possible to derive a strategy that minimizes the expected investment risk, but this strategy does not always result in the best rate of return on assets. Prior to making investment decisions, it is important to an investor to know the potential minimal investment risk (or the expected minimal investment risk) and to determine the strategy that will maximize the return on assets. We use the self-averaging property to analyze the potential minimal investment risk and the concentrated investment level for the strategy that gives the best rate of return. We compare the results from our method with the results obtained by the operations research approach and with those obtained by a numerical simulation using the optimal portfolio. The results of our method and the numerical simulation are in agreement, but they differ from that of the operations research approach. PMID:26225761
Managing the wildlife tourism commons.
Pirotta, Enrico; Lusseau, David
2015-04-01
The nonlethal effects of wildlife tourism can threaten the conservation status of targeted animal populations. In turn, such resource depletion can compromise the economic viability of the industry. Therefore, wildlife tourism exploits resources that can become common pool and that should be managed accordingly. We used a simulation approach to test whether different management regimes (tax, tax and subsidy, cap, cap and trade) could provide socioecologically sustainable solutions. Such schemes are sensitive to errors in estimated management targets. We determined the sensitivity of each scenario to various realistic uncertainties in management implementation and in our knowledge of the population. Scenarios where time quotas were enforced using a tax and subsidy approach, or they were traded between operators were more likely to be sustainable. Importantly, sustainability could be achieved even when operators were assumed to make simple rational economic decisions. We suggest that a combination of the two regimes might offer a robust solution, especially on a small spatial scale and under the control of a self-organized, operator-level institution. Our simulation platform could be parameterized to mimic local conditions and provide a test bed for experimenting different governance solutions in specific case studies.
NASA Astrophysics Data System (ADS)
Quirion, Nate
Unmanned Aerial Systems (UASs) today are fulfilling more roles than ever before. There is a general push to have these systems feature more advanced autonomous capabilities in the near future. To achieve autonomous behavior requires some unique approaches to control and decision making. More advanced versions of these approaches are able to adapt their own behavior and examine their past experiences to increase their future mission performance. To achieve adaptive behavior and decision making capabilities this study used Reinforcement Learning algorithms. In this research the effects of sensor performance, as modeled through Signal Detection Theory (SDT), on the ability of RL algorithms to accomplish a target localization task are examined. Three levels of sensor sensitivity are simulated and compared to the results of the same system using a perfect sensor. To accomplish the target localization task, a hierarchical architecture used two distinct agents. A simulated human operator is assumed to be a perfect decision maker, and is used in the system feedback. An evaluation of the system is performed using multiple metrics, including episodic reward curves and the time taken to locate all targets. Statistical analyses are employed to detect significant differences in the comparison of steady-state behavior of different systems.
Creating a Realistic Weather Environment for Motion-Based Piloted Flight Simulation
NASA Technical Reports Server (NTRS)
Daniels, Taumi S.; Schaffner, Philip R.; Evans, Emory T.; Neece, Robert T.; Young, Steve D.
2012-01-01
A flight simulation environment is being enhanced to facilitate experiments that evaluate research prototypes of advanced onboard weather radar, hazard/integrity monitoring (HIM), and integrated alerting and notification (IAN) concepts in adverse weather conditions. The simulation environment uses weather data based on real weather events to support operational scenarios in a terminal area. A simulated atmospheric environment was realized by using numerical weather data sets. These were produced from the High-Resolution Rapid Refresh (HRRR) model hosted and run by the National Oceanic and Atmospheric Administration (NOAA). To align with the planned flight simulation experiment requirements, several HRRR data sets were acquired courtesy of NOAA. These data sets coincided with severe weather events at the Memphis International Airport (MEM) in Memphis, TN. In addition, representative flight tracks for approaches and departures at MEM were generated and used to develop and test simulations of (1) what onboard sensors such as the weather radar would observe; (2) what datalinks of weather information would provide; and (3) what atmospheric conditions the aircraft would experience (e.g. turbulence, winds, and icing). The simulation includes a weather radar display that provides weather and turbulence modes, derived from the modeled weather along the flight track. The radar capabilities and the pilots controls simulate current-generation commercial weather radar systems. Appropriate data-linked weather advisories (e.g., SIGMET) were derived from the HRRR weather models and provided to the pilot consistent with NextGen concepts of use for Aeronautical Information Service (AIS) and Meteorological (MET) data link products. The net result of this simulation development was the creation of an environment that supports investigations of new flight deck information systems, methods for incorporation of better weather information, and pilot interface and operational improvements for better aviation safety. This research is part of a larger effort at NASA to study the impact of the growing complexity of operations, information, and systems on crew decision-making and response effectiveness; and then to recommend methods for improving future designs.
VO2sim 0.1: Using Simulation to Understand Measurement Error in Indirect Calorimetry
2015-08-01
illness. The Army has recognized the importance of understanding oxygen consumption in the field and is developing models to aid in operational decision...acclimatize to high altitude (Amann et al. 2013) and hypoxia (Self et al. 2013). The Army has recognized the importance of understanding oxygen consumption ...minimum detectable change using the K4b2: oxygen consumption , gait efficiency, and heart rate for healthy adults during submaximal walking. Res Q Exerc
1985-04-01
and equipment whose operation can be verified with a visual or aural check. The sequence of outputs shall be cyclic, with provisions to stop the...private memory. The decision to provide spare, expansion capability, or a combination of both shall be based on life cycle cost (to the best extent...Computational System should be determined in conjunction with a computer expert (if possible). In any event, it is best to postpone completing - this
Advanced Simulation in Undergraduate Pilot Training: Visual Display Development
1975-12-01
properties of each member were calculated manually and were inserted by means of punched cards, thus it was relatively easy (but time consuming ) to...investigations leading to the decision to employ an all-glass approach which consisted of a two-part glass funnel produced by Corning Glass Wo ks... consuming . After complete sets of materials were selected they had to be cemented into a final assembly. This had to be done in two operations because of the
Adding Four- Dimensional Data Assimilation (aka grid ...
Adding four-dimensional data assimilation (a.k.a. grid nudging) to MPAS.The U.S. Environmental Protection Agency is investigating the use of MPAS as the meteorological driver for its next-generation air quality model. To function as such, MPAS needs to operate in a diagnostic mode in much the same manner as the current meteorological driver, the Weather Research and Forecasting (WRF) model. The WRF operates in diagnostic mode using Four-Dimensional Data Assimilation, also known as "grid nudging". MPAS version 4.0 has been modified with the addition of an FDDA routine to the standard physics drivers to nudge the state variables for wind, temperature and water vapor towards MPAS initialization fields defined at 6-hour intervals from GFS-derived data. The results to be shown demonstrate the ability to constrain MPAS simulations to known historical conditions and thus provide the U.S. EPA with a practical meteorological driver for global-scale air quality simulations. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use bo
Instantiating the art of war for effects-based operations
NASA Astrophysics Data System (ADS)
Burns, Carla L.
2002-07-01
Effects-Based Operations (EBO) is a mindset, a philosophy and an approach for planning, executing and assessing military operations for the effects they produce rather than the targets or even objectives they deal with. An EBO approach strives to provide economy of force, dynamic tasking, and reduced collateral damage. The notion of EBO is not new. Military Commanders certainly have desired effects in mind when conducting military operations. However, to date EBO has been an art of war that lacks automated techniques and tools that enable effects-based analysis and assessment. Modeling and simulation is at the heart of this challenge. The Air Force Research Laboratory (AFRL) EBO Program is developing modeling techniques and corresponding tool capabilities that can be brought to bear against the challenges presented by effects-based analysis and assessment. Effects-based course-of-action development, center of gravity/target system analysis, and wargaming capabilities are being developed and integrated to help give Commanders the information decision support required to achieve desired national security objectives. This paper presents an introduction to effects-based operations, discusses the benefits of an EBO approach, and focuses on modeling and analysis for effects-based strategy development. An overview of modeling and simulation challenges for EBO is presented, setting the stage for the detailed technical papers in the subject session.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Perkins, Casey J.; Brigantic, Robert T.; Keating, Douglas H.
There is a need to develop and demonstrate technical approaches for verifying potential future agreements to limit and reduce total warhead stockpiles. To facilitate this aim, warhead monitoring systems employ both concepts of operations (CONOPS) and technologies. A systems evaluation approach can be used to assess the relative performance of CONOPS and technologies in their ability to achieve monitoring system objectives which include: 1) confidence that a treaty accountable item (TAI) initialized by the monitoring system is as declared; 2) confidence that there is no undetected diversion from the monitoring system; and 3) confidence that a TAI is dismantled asmore » declared. Although there are many quantitative methods that can be used to assess system performance for the above objectives, this paper focuses on a simulation perspective primarily for the ability to support analysis of the probabilities that are used to define operating characteristics of CONOPS and technologies. This paper describes a discrete event simulation (DES) model, comprised of three major sub-models: including TAI lifecycle flow, monitoring activities, and declaration behavior. The DES model seeks to capture all processes and decision points associated with the progressions of virtual TAIs, with notional characteristics, through the monitoring system from initialization through dismantlement. The simulation updates TAI progression (i.e., whether the generated test objects are accepted and rejected at the appropriate points) all the way through dismantlement. Evaluation of TAI lifecycles primarily serves to assess how the order, frequency, and combination of functions in the CONOPS affect system performance as a whole. It is important, however, to note that discrete event simulation is also capable (at a basic level) of addressing vulnerabilities in the CONOPS and interdependencies between individual functions as well. This approach is beneficial because it does not rely on complex mathematical models, but instead attempts to recreate the real world system as a decision and event driven simulation. Finally, because the simulation addresses warhead confirmation, chain of custody, and warhead dismantlement in a modular fashion, a discrete-event model could be easily adapted to multiple CONOPS for the exploration of a large number of “what if” scenarios.« less
Integration of simulations and visualizations into classroom contexts through role playing
NASA Astrophysics Data System (ADS)
Moysey, S. M.
2016-12-01
While simulations create a novel way to engage students, the idea of numerical modeling may be overwhelming to a wide swath of students - particularly non-geoscience majors or those students early in their earth science education. Yet even for these students, simulations and visualizations remain a powerful way to explore concepts and take ownership over their learning. One approach to bring these tools into the classroom is to introduce them as a component of a larger role-playing activity. I present two specific examples of how I have done this within a general education course broadly focused on water resources sustainability. In the first example, we have created an online multi-player watershed management game where players make management decisions for their individual farms, which in turn set the parameters for a watershed-scale groundwater model that continuously runs in the background. Through the simulation students were able to influence the behavior of the environment and see feedbacks on their individual land within the game. Though the original intent was to focus student learning on the hydrologic aspects of the watershed behavior, I have found that the value of the simulation is actually in allowing students to become immersed in a way that enables deep conversations about topics ranging from environmental policy to social justice. The second example presents an overview of a role playing activity focused on a multi-party negotiation of water rights in the Klamath watershed. In this case each student takes on a different role in the negotiation (e.g., farmer, energy producer, government, environmental advocate, etc.) and is presented with a rich set of data tying environmental and economic factors to the operation of reservoirs. In this case the simulation model is very simple, i.e., a mass balance calculator that students use to predict the consequences of their management decisions. The simplicity of the simulator, however, allows for reinforcement of the fundamental concept of mass balance which is a key scientific theme throughout the course. It also allows students to focus on analysis of data that enables them to tie hydrologic behaviors to societal consequences that guide their decision making.
RESTSIM: A Simulation Model That Highlights Decision Making under Conditions of Uncertainty.
ERIC Educational Resources Information Center
Zinkhan, George M.; Taylor, James R.
1983-01-01
Describes RESTSIM, an interactive computer simulation program for graduate and upper-level undergraduate management, marketing, and retailing courses, which introduces naive users to simulation as a decision support technique, and provides a vehicle for studying various statistical procedures for evaluating simulation output. (MBR)
Bus operators' responses to job strain: An experimental test of the job demand-control model.
Cendales-Ayala, Boris; Useche, Sergio Alejandro; Gómez-Ortiz, Viviola; Bocarejo, Juan Pablo
2017-10-01
The research aim was to test the Job Demand-Control (JDC) Model demands × Control interaction (or buffering) hypothesis in a simulated bus driving experiment. The buffering hypothesis was tested using a 2 (low and high demands) × 2 (low and high decision latitude) design with repeated measures on the second factor. A sample of 80 bus operators were randomly assigned to the low (n = 40) and high demands (n = 40) conditions. Demands were manipulated by increasing or reducing the number of stops to pick up passengers, and decision latitude by imposing or removing restrictions on the Rapid Transit Bus (BRT) operators' pace of work. Outcome variables include physiological markers (heart rate [HR], heart rate variability [HRV], breathing rate [BR], electromyography [EMG], and skin conductance [SC]), objective driving performance and self-report measurements of psychological wellbeing (psychological distress, interest/enjoyment [I/E], perceived competence, effort/importance [E/I], and pressure/tension [P/T]). It was found that job decision latitude moderates the effect of job demands on both physiological arousal (BR: F(1, 74) = 4.680, p = .034, SC: F(1, 75) = 6.769, p = .011, and EMG: F(1, 75) = 6.550, p = .013) and psychological well-being (P/T: F(1, 75) = 4.289, p = .042 and I/E: F(1, 74) = 4.548, p = .036). Consistently with the JDC model buffering hypothesis, the experimental findings suggest that increasing job decision latitude can moderate the negative effect of job demands on different psychophysiological outcomes. This finding is useful for designing organizational and clinical interventions in an occupational group at high risk of work stress-related disease. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shott, G.; Yucel, V.; Desotell, L.
2006-07-01
The long-term safety of U.S. Department of Energy (DOE) low-level radioactive disposal facilities is assessed by conducting a performance assessment -- a systematic analysis that compares estimated risks to the public and the environment with performance objectives contained in DOE Manual 435.1-1, Radioactive Waste Management Manual. Before site operations, facilities design features such as final inventory, waste form characteristics, and closure cover design may be uncertain. Site operators need a modeling tool that can be used throughout the operational life of the disposal site to guide decisions regarding the acceptance of problematic waste streams, new disposal cell design, environmental monitoringmore » program design, and final site closure. In response to these needs the National Nuclear Security Administration Nevada Site Office (NNSA/NSO) has developed a decision support system for the Area 5 Radioactive Waste Management Site in Frenchman Flat on the Nevada Test Site. The core of the system is a probabilistic inventory and performance assessment model implemented in the GoldSim{sup R} simulation platform. The modeling platform supports multiple graphic capabilities that allow clear documentation of the model data sources, conceptual model, mathematical implementation, and results. The combined models have the capability to estimate disposal site inventory, contaminant concentrations in environmental media, and radiological doses to members of the public engaged in various activities at multiple locations. The model allows rapid assessment and documentation of the consequences of waste management decisions using the most current site characterization information, radionuclide inventory, and conceptual model. The model is routinely used to provide annual updates of site performance, evaluate the consequences of disposal of new waste streams, develop waste concentration limits, optimize the design of new disposal cells, and assess the adequacy of environmental monitoring programs. (authors)« less
Warfighter decision making performance analysis as an investment priority driver
NASA Astrophysics Data System (ADS)
Thornley, David J.; Dean, David F.; Kirk, James C.
2010-04-01
Estimating the relative value of alternative tactics, techniques and procedures (TTP) and information systems requires measures of the costs and benefits of each, and methods for combining and comparing those measures. The NATO Code of Best Practice for Command and Control Assessment explains that decision making quality would ideally be best assessed on outcomes. Lessons learned in practice can be assessed statistically to support this, but experimentation with alternate measures in live conflict is undesirable. To this end, the development of practical experimentation to parameterize effective constructive simulation and analytic modelling for system utility prediction is desirable. The Land Battlespace Systems Department of Dstl has modeled human development of situational awareness to support constructive simulation by empirically discovering how evidence is weighed according to circumstance, personality, training and briefing. The human decision maker (DM) provides the backbone of the information processing activity associated with military engagements because of inherent uncertainty associated with combat operations. To develop methods for representing the process in order to assess equipment and non-technological interventions such as training and TTPs we are developing componentized or modularized timed analytic stochastic model components and instruments as part of a framework to support quantitative assessment of intelligence production and consumption methods in a human decision maker-centric mission space. In this paper, we formulate an abstraction of the human intelligence fusion process from the Defence Science and Technology Laboratory's (Dstl's) INCIDER model to include in our framework, and synthesize relevant cost and benefit characteristics.
A virtual reality system for the training of volunteers involved in health emergency situations.
De Leo, Gianluca; Ponder, Michal; Molet, Tom; Fato, Marco; Thalmann, Daniel; Magnenat-Thalmann, Nadia; Bermano, Francesco; Beltrame, Francesco
2003-06-01
In order to guarantee an effective and punctual medical intervention to injured people involved in health emergency situations, where usually both professional and non-professional health operators are involved, a fast and accurate treatment has to be carried out. In case of catastrophic or very critical situations, non-professional operators who did not receive proper training (volunteers are among them) could be affected by psychological inhibitions. Their performances could slow down in such way that would affect the quality of the treatment and increase both direct and indirect costs. Our virtual reality system that is currently in use at the health care emergency center of San Martino Hospital in Genoa, Italy, has been designed and developed to check health emergency operators' capabilities to adopt correct decision-making procedures, to make optimal use of new technological equipment and to overcome psychological barriers. Our system is composed of (1) a high-end simulation PC, whose main functions are execution of the main software module, rendering of 3D scenes in stereo mode, rendering of sound, and control of data transmission from/to VR devices; (2) a low-end control PC, which controls the VR simulation running on the simulation PC, manages medical emergency simulation scenarios, introduces unexpected events to the simulation and controls the simulation difficulty level; (3) a magnetic-based motion tracking device used for head and hand tracking; (4) a wireless pair of shutter glasses together with a cathode ray tube wall projector; and (5) a high-end surround sound system. The expected benefits have been verified through the design and implementation of controlled clinical trials.
McKendrick, Ryan; Shaw, Tyler; de Visser, Ewart; Saqer, Haneen; Kidwell, Brian; Parasuraman, Raja
2014-05-01
Assess team performance within a net-worked supervisory control setting while manipulating automated decision aids and monitoring team communication and working memory ability. Networked systems such as multi-unmanned air vehicle (UAV) supervision have complex properties that make prediction of human-system performance difficult. Automated decision aid can provide valuable information to operators, individual abilities can limit or facilitate team performance, and team communication patterns can alter how effectively individuals work together. We hypothesized that reliable automation, higher working memory capacity, and increased communication rates of task-relevant information would offset performance decrements attributed to high task load. Two-person teams performed a simulated air defense task with two levels of task load and three levels of automated aid reliability. Teams communicated and received decision aid messages via chat window text messages. Task Load x Automation effects were significant across all performance measures. Reliable automation limited the decline in team performance with increasing task load. Average team spatial working memory was a stronger predictor than other measures of team working memory. Frequency of team rapport and enemy location communications positively related to team performance, and word count was negatively related to team performance. Reliable decision aiding mitigated team performance decline during increased task load during multi-UAV supervisory control. Team spatial working memory, communication of spatial information, and team rapport predicted team success. An automated decision aid can improve team performance under high task load. Assessment of spatial working memory and the communication of task-relevant information can help in operator and team selection in supervisory control systems.
Dynamic situation assessment and prediction (DSAP)
NASA Astrophysics Data System (ADS)
Sisti, Alex F.
2003-09-01
The face of war has changed. We no longer have the luxury of planning campaigns against a known enemy operating under a well-understood doctrine, using conventional weapons and rules of engagement; all in a well-charted region. Instead, today's Air Force faces new, unforeseen enemies, asymmetric combat situations and unconventional warfare (Chem/Bio, co-location of military assets near civilian facilities, etc.). At the same time, the emergence of new Air Force doctrinal notions (e.g., Global Strike Task Force, Effects-Based Operations, the desire to minimize or eliminate any collateral damage, etc.)- while propounding the benefits that can be expected with the adoption of such concepts - also impose many new technical and operational challenges. Furthermore, future mission/battle commanders will need to assimilate a tremendous glut of available information, and still be expected to make quick-response decisions - and to quantify the effects of those decisions - all in the face of uncertainty. All these factors translate to the need for dramatic improvements in the way we plan, rehearse, execute and dynamically assess the status of military campaigns. This paper addresses these crucial and revolutionary requirements through the pursuit of a new simulation paradigm that allows a user to perform real-time dynamic situation assessment and prediction.
Modeling and Simulation at NASA
NASA Technical Reports Server (NTRS)
Steele, Martin J.
2009-01-01
This slide presentation is composed of two topics. The first reviews the use of modeling and simulation (M&S) particularly as it relates to the Constellation program and discrete event simulation (DES). DES is defined as a process and system analysis, through time-based and resource constrained probabilistic simulation models, that provide insight into operation system performance. The DES shows that the cycles for a launch from manufacturing and assembly to launch and recovery is about 45 days and that approximately 4 launches per year are practicable. The second topic reviews a NASA Standard for Modeling and Simulation. The Columbia Accident Investigation Board made some recommendations related to models and simulations. Some of the ideas inherent in the new standard are the documentation of M&S activities, an assessment of the credibility, and reporting to decision makers, which should include the analysis of the results, a statement as to the uncertainty in the results,and the credibility of the results. There is also discussion about verification and validation (V&V) of models. There is also discussion about the different types of models and simulation.
NASA-STD-7009 Guidance Document for Human Health and Performance Models and Simulations
NASA Technical Reports Server (NTRS)
Walton, Marlei; Mulugeta, Lealem; Nelson, Emily S.; Myers, Jerry G.
2014-01-01
Rigorous verification, validation, and credibility (VVC) processes are imperative to ensure that models and simulations (MS) are sufficiently reliable to address issues within their intended scope. The NASA standard for MS, NASA-STD-7009 (7009) [1] was a resultant outcome of the Columbia Accident Investigation Board (CAIB) to ensure MS are developed, applied, and interpreted appropriately for making decisions that may impact crew or mission safety. Because the 7009 focus is engineering systems, a NASA-STD-7009 Guidance Document is being developed to augment the 7009 and provide information, tools, and techniques applicable to the probabilistic and deterministic biological MS more prevalent in human health and performance (HHP) and space biomedical research and operations.
Evaluation of center-cut separations applying simulated moving bed chromatography with 8 zones.
Santos da Silva, Francisco Vitor; Seidel-Morgenstern, Andreas
2016-07-22
Different multi-column options to perform continuous chromatographic separations of ternary mixtures have been proposed in order to overcome limitations of batch chromatography. One attractive option is given by simulated moving bed chromatography (SMB) with 8 zones, a process that offers uninterrupted production, and, potentially, improved economy. As in other established ternary separation processes, the separation sequence is crucial for the performance of the process. This problem is addressed here by computing and comparing optimal performances of the two possibilities assuming linear adsorption isotherms. The conclusions are presented in a decision tree which can be used to guide the selection of system configuration and operation. Copyright © 2016 Elsevier B.V. All rights reserved.
Real time flight simulation methodology
NASA Technical Reports Server (NTRS)
Parrish, E. A.; Cook, G.; Mcvey, E. S.
1976-01-01
An example sensitivity study is presented to demonstrate how a digital autopilot designer could make a decision on minimum sampling rate for computer specification. It consists of comparing the simulated step response of an existing analog autopilot and its associated aircraft dynamics to the digital version operating at various sampling frequencies and specifying a sampling frequency that results in an acceptable change in relative stability. In general, the zero order hold introduces phase lag which will increase overshoot and settling time. It should be noted that this solution is for substituting a digital autopilot for a continuous autopilot. A complete redesign could result in results which more closely resemble the continuous results or which conform better to original design goals.
NASA Technical Reports Server (NTRS)
Lozito, Sandy; Mackintosh, Margaret-Anne; DiMeo, Karen; Kopardekar, Parimal
2002-01-01
A simulation was conducted to examine the effect of shared air/ground authority when each is equipped with enhanced traffic- and conflict-alerting systems. The potential benefits of an advanced air traffic management (ATM) concept referred to as "free flight" include improved safety through enhanced conflict detection and resolution capabilities, increased flight-operations management, and better decision-making tools for air traffic controllers and flight crews. One element of the free-flight concept suggests shifting aircraft separation responsibility from air traffic controllers to flight crews, thereby creating an environment with "shared-separation" authority. During FY00. NASA, the Federal Aviation Administration (FAA), and the Volpe National Transportation Systems Center completed the first integrated, high-fidelity, real-time, human-in-the-loop simulation.
NASA Astrophysics Data System (ADS)
Subagadis, Yohannes Hagos; Schütze, Niels; Grundmann, Jens
2014-05-01
An amplified interconnectedness between a hydro-environmental and socio-economic system brings about profound challenges of water management decision making. In this contribution, we present a fuzzy stochastic approach to solve a set of decision making problems, which involve hydrologically, environmentally, and socio-economically motivated criteria subjected to uncertainty and ambiguity. The proposed methodological framework combines objective and subjective criteria in a decision making procedure for obtaining an acceptable ranking in water resources management alternatives under different type of uncertainty (subjective/objective) and heterogeneous information (quantitative/qualitative) simultaneously. The first step of the proposed approach involves evaluating the performance of alternatives with respect to different types of criteria. The ratings of alternatives with respect to objective and subjective criteria are evaluated by simulation-based optimization and fuzzy linguistic quantifiers, respectively. Subjective and objective uncertainties related to the input information are handled through linking fuzziness and randomness together. Fuzzy decision making helps entail the linguistic uncertainty and a Monte Carlo simulation process is used to map stochastic uncertainty. With this framework, the overall performance of each alternative is calculated using an Order Weighted Averaging (OWA) aggregation operator accounting for decision makers' experience and opinions. Finally, ranking is achieved by conducting pair-wise comparison of management alternatives. This has been done on the basis of the risk defined by the probability of obtaining an acceptable ranking and mean difference in total performance for the pair of management alternatives. The proposed methodology is tested in a real-world hydrosystem, to find effective and robust intervention strategies for the management of a coastal aquifer system affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. The results show that the approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.
SIMRAND I- SIMULATION OF RESEARCH AND DEVELOPMENT PROJECTS
NASA Technical Reports Server (NTRS)
Miles, R. F.
1994-01-01
The Simulation of Research and Development Projects program (SIMRAND) aids in the optimal allocation of R&D resources needed to achieve project goals. SIMRAND models the system subsets or project tasks as various network paths to a final goal. Each path is described in terms of task variables such as cost per hour, cost per unit, availability of resources, etc. Uncertainty is incorporated by treating task variables as probabilistic random variables. SIMRAND calculates the measure of preference for each alternative network. The networks yielding the highest utility function (or certainty equivalence) are then ranked as the optimal network paths. SIMRAND has been used in several economic potential studies at NASA's Jet Propulsion Laboratory involving solar dish power systems and photovoltaic array construction. However, any project having tasks which can be reduced to equations and related by measures of preference can be modeled. SIMRAND analysis consists of three phases: reduction, simulation, and evaluation. In the reduction phase, analytical techniques from probability theory and simulation techniques are used to reduce the complexity of the alternative networks. In the simulation phase, a Monte Carlo simulation is used to derive statistics on the variables of interest for each alternative network path. In the evaluation phase, the simulation statistics are compared and the networks are ranked in preference by a selected decision rule. The user must supply project subsystems in terms of equations based on variables (for example, parallel and series assembly line tasks in terms of number of items, cost factors, time limits, etc). The associated cumulative distribution functions and utility functions for each variable must also be provided (allowable upper and lower limits, group decision factors, etc). SIMRAND is written in Microsoft FORTRAN 77 for batch execution and has been implemented on an IBM PC series computer operating under DOS.
Jun, Gyuchan T; Morris, Zoe; Eldabi, Tillal; Harper, Paul; Naseer, Aisha; Patel, Brijesh; Clarkson, John P
2011-05-19
There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection.
Policy Tree Optimization for Adaptive Management of Water Resources Systems
NASA Astrophysics Data System (ADS)
Herman, J. D.; Giuliani, M.
2016-12-01
Water resources systems must cope with irreducible uncertainty in supply and demand, requiring policy alternatives capable of adapting to a range of possible future scenarios. Recent studies have developed adaptive policies based on "signposts" or "tipping points", which are threshold values of indicator variables that signal a change in policy. However, there remains a need for a general method to optimize the choice of indicators and their threshold values in a way that is easily interpretable for decision makers. Here we propose a conceptual framework and computational algorithm to design adaptive policies as a tree structure (i.e., a hierarchical set of logical rules) using a simulation-optimization approach based on genetic programming. We demonstrate the approach using Folsom Reservoir, California as a case study, in which operating policies must balance the risk of both floods and droughts. Given a set of feature variables, such as reservoir level, inflow observations and forecasts, and time of year, the resulting policy defines the conditions under which flood control and water supply hedging operations should be triggered. Importantly, the tree-based rule sets are easy to interpret for decision making, and can be compared to historical operating policies to understand the adaptations needed under possible climate change scenarios. Several remaining challenges are discussed, including the empirical convergence properties of the method, and extensions to irreversible decisions such as infrastructure. Policy tree optimization, and corresponding open-source software, provide a generalizable, interpretable approach to designing adaptive policies under uncertainty for water resources systems.
TAMU: A New Space Mission Operations Paradigm
NASA Technical Reports Server (NTRS)
Meshkat, Leila; Ruszkowski, James; Haensly, Jean; Pennington, Granvil A.; Hogle, Charles
2011-01-01
The Transferable, Adaptable, Modular and Upgradeable (TAMU) Flight Production Process (FPP) is a model-centric System of System (SoS) framework which cuts across multiple organizations and their associated facilities, that are, in the most general case, in geographically diverse locations, to develop the architecture and associated workflow processes for a broad range of mission operations. Further, TAMU FPP envisions the simulation, automatic execution and re-planning of orchestrated workflow processes as they become operational. This paper provides the vision for the TAMU FPP paradigm. This includes a complete, coherent technique, process and tool set that result in an infrastructure that can be used for full lifecycle design and decision making during any flight production process. A flight production process is the process of developing all products that are necessary for flight.
Spot and Runway Departure Advisor (SARDA)
NASA Technical Reports Server (NTRS)
Jung, Yoon
2016-01-01
Spot and Runway Departure Advisor (SARDA) is a decision support tool to assist airline ramp controllers and ATC tower controllers to manage traffic on the airport surface to significantly improve efficiency and predictability in surface operations. The core function of the tool is the runway scheduler which generates an optimal solution for runway sequence and schedule of departure aircraft, which would minimize system delay and maximize runway throughput. The presentation also discusses the latest status of NASA's current surface research through a collaboration with an airline partner, where a tool is developed for airline ramp operators to assist departure pushback operations. The presentation describes the concept of the SARDA tool and results from human-in-the-loop simulations conducted in 2012 for Dallas-Ft. Worth International Airport and 2014 for Charlotte airport ramp tower.
Harte, Philip T.
2012-01-01
The U.S. Geological Survey and the New Hampshire Department of Environmental Services entered into a cooperative agreement to assist in the evaluation of remedy simulations of the MSGD aquifer that are being performed by various parties to track the remedial progress of the PCE plume. This report summarizes findings from this evaluation. Topics covered include description of groundwater flow and transport models used in the study of the Savage Superfund site (section 2), evaluation of models and their results (section 3), testing of several new simulations (section 4), an assessment of the representation of models to simulate field conditions (section 5), and an assessment of models as a tool in remedial operational decision making (section 6).
NASA Astrophysics Data System (ADS)
Matrosov, E.; Padula, S.; Huskova, I.; Harou, J. J.
2012-12-01
Population growth and the threat of drier or changed climates are likely to increase water scarcity world-wide. A combination of demand management (water conservation) and new supply infrastructure is often needed to meet future projected demands. In this case system planners must decide what to implement, when and at what capacity. Choices can range from infrastructure to policies or a mix of the two, culminating in a complex planning problem. Decision making under uncertainty frameworks can be used to help planners with this planning problem. This presentation introduces, applies and compares four decision making under uncertainty frameworks. The application is to the Thames basin water resource system which includes the city of London. The approaches covered here include least-economic cost capacity expansion optimization (EO), Robust Decision Making (RDM), Info-Gap Decision Theory (Info-gap) and many-objective evolutionary optimization (MOEO). EO searches for the least-economic cost program, i.e. the timing, sizing, and choice of supply-demand management actions/upgrades which meet projected water demands. Instead of striving for optimality, the RDM and Info-gap approaches help build plans that are robust to 'deep' uncertainty in future conditions. The MOEO framework considers multiple performance criteria and uses water systems simulators as a function evaluator for the evolutionary algorithm. Visualizations show Pareto approximate tradeoffs between multiple objectives. In this presentation we detail the application of each framework to the Thames basin (including London) water resource planning problem. Supply and demand options are proposed by the major water companies in the basin. We apply the EO method using a 29 year time horizon and an annual time step considering capital, operating (fixed and variable), social and environmental costs. The method considers all plausible combinations of supply and conservation schemes and capacities proposed by water companies and generates the least-economic cost annual plan. The RDM application uses stochastic simulation under a weekly time-step and regret analysis to choose a candidate strategy. We then use a statistical cluster algorithm to identify future states of the world under which the strategy is vulnerable. The method explicitly considers the effects of uncertainty in supply, demands and energy price on multiple performance criteria. The Info-gap approach produces robustness and opportuneness plots that show the performance of different plans under the most dire and favorable sets of future conditions. The same simulator, supply and demand options and uncertainties are considered as in the RDM application. The MOEO application considers many more combinations of supply and demand options while still employing a simulator that enables a more realistic representation of the physical system and operating rules. A computer cluster is employed to ease the computational burden. Visualization software allows decision makers to interactively view tradeoffs in many dimensions. Benefits and limitations of each framework are discussed and recommendations for future planning in the basin are provided.
Human System Simulation in Support of Human Performance Technical Basis at NPPs
DOE Office of Scientific and Technical Information (OSTI.GOV)
David Gertman; Katya Le Blanc; alan mecham
2010-06-01
This paper focuses on strategies and progress toward establishing the Idaho National Laboratory’s (INL’s) Human Systems Simulator Laboratory at the Center for Advanced Energy Studies (CAES), a consortium of Idaho State Universities. The INL is one of the National Laboratories of the US Department of Energy. One of the first planned applications for the Human Systems Simulator Laboratory is implementation of a dynamic nuclear power plant simulation (NPP) where studies of operator workload, situation awareness, performance and preference will be carried out in simulated control rooms including nuclear power plant control rooms. Simulation offers a means by which to reviewmore » operational concepts, improve design practices and provide a technical basis for licensing decisions. In preparation for the next generation power plant and current government and industry efforts in support of light water reactor sustainability, human operators will be attached to a suite of physiological measurement instruments and, in combination with traditional Human Factors Measurement techniques, carry out control room tasks in simulated advanced digital and hybrid analog/digital control rooms. The current focus of the Human Systems Simulator Laboratory is building core competence in quantitative and qualitative measurements of situation awareness and workload. Of particular interest is whether introduction of digital systems including automated procedures has the potential to reduce workload and enhance safety while improving situation awareness or whether workload is merely shifted and situation awareness is modified in yet to be determined ways. Data analysis is carried out by engineers and scientists and includes measures of the physical and neurological correlates of human performance. The current approach supports a user-centered design philosophy (see ISO 13407 “Human Centered Design Process for Interactive Systems, 1999) wherein the context for task performance along with the requirements of the end-user are taken into account during the design process and the validity of design is determined through testing of real end users« less
Cohen-Hatton, Sabrina R; Honey, R C
2015-12-01
Decisions made by operational commanders at emergency incidents have been characterized as involving a period of information gathering followed by courses of action that are often generated without explicit plan formulation. We examined the efficacy of goal-oriented training in engendering explicit planning that would enable better communication at emergency incidents. While standard training mirrored current operational guidance, goal-oriented training incorporated "decision controls" that highlighted the importance of evaluating goals, anticipated consequences, and risk/benefit analyses once a potential course of action has been identified. In Experiment 1, 3 scenarios (a house fire, road traffic collision, and skip fire) were presented in a virtual environment, and in Experiment 2 they were recreated on the fireground. In Experiment 3, the house fire was recreated as a "live burn," and incident commanders and their crews responded to this scenario as an emergency incident. In all experiments, groups given standard training showed the reported tendency to move directly from information gathering to action, whereas those given goal-oriented training were more likely to develop explicit plans and show anticipatory situational awareness. These results indicate that training can be readily modified to promote explicit plan formulation that could facilitate plan sharing between incident commanders and their teams. (c) 2015 APA, all rights reserved).
NASA Technical Reports Server (NTRS)
Corker, Kevin M.; Pisanich, Gregory M.; Lebacqz, Victor (Technical Monitor)
1996-01-01
The Man-Machine Interaction Design and Analysis System (MIDAS) has been under development for the past ten years through a joint US Army and NASA cooperative agreement. MIDAS represents multiple human operators and selected perceptual, cognitive, and physical functions of those operators as they interact with simulated systems. MIDAS has been used as an integrated predictive framework for the investigation of human/machine systems, particularly in situations with high demands on the operators. Specific examples include: nuclear power plant crew simulation, military helicopter flight crew response, and police force emergency dispatch. In recent applications to airborne systems development, MIDAS has demonstrated an ability to predict flight crew decision-making and procedural behavior when interacting with automated flight management systems and Air Traffic Control. In this paper we describe two enhancements to MIDAS. The first involves the addition of working memory in the form of an articulatory buffer for verbal communication protocols and a visuo-spatial buffer for communications via digital datalink. The second enhancement is a representation of multiple operators working as a team. This enhanced model was used to predict the performance of human flight crews and their level of compliance with commercial aviation communication procedures. We show how the data produced by MIDAS compares with flight crew performance data from full mission simulations. Finally, we discuss the use of these features to study communications issues connected with aircraft-based separation assurance.
1990-04-01
DECISION AIDS HAVE CREATED A VAST NEW POTENTIAL FOR SUPPORT OF STRATEGIC AND TACTICAL OPERATIONS. THE NON-MONOTONIC PROBABILIST (NMP), DEVELOPED BY...QUALITY OF THE NEW DESIGN WILL BE EVALUATED BY CREATING A VIDEO TAPE USING A VIDEO ANIMATION SYSTEM, AND A SOFTWARE SIMULATION OF THE NEW DESIGN. THE...FAULT TOLERANT, SECURE SHIPBOARD COMMUNICATIONS. THE LAN WILL UTILIZE PHOENIX DIGITAL’S FAULT TOLERANT, " SELF - HEALING " SMALL BUSINESS INNOVATION RESEARCH
Performance assessment in complex individual and team tasks
NASA Technical Reports Server (NTRS)
Eddy, Douglas R.
1992-01-01
Described here is an eclectic, performance based approach to assessing cognitive performance from multiple perspectives. The experience gained from assessing the effects of antihistamines and scenario difficulty on C (exp 2) decision making performance in Airborne Warning and Control Systems (AWACS) weapons director (WD) teams can serve as a model for realistic simulations in space operations. Emphasis is placed on the flexibility of measurement, hierarchical organization of measurement levels, data collection from multiple perspectives, and the difficulty of managing large amounts of data.
Journal of Air Transportation, Volume 10, No. 3
NASA Technical Reports Server (NTRS)
Bowen, Brent D. (Editor); Kabashkin, Igor (Editor)
2005-01-01
The following topics are discussed: The Effects of Safety Information on Aeronautical Decision Making; Design, Development, and Validation of an Interactive Multimedia Training Simulator for Responding to Air Transportation Bomb Threats; Discovering the Regulatory Considerations of the Federal Aviation Administration: Interviewing the Aviation Rulemaking Advisory Committee; How to Control Airline Routes from the Supply Side: The Case of TAP; An Attempt to Measure the Traffic Impact of Airline Alliances; and Study Results on Knowledge Requirements for Entry-level Airport Operations and Management Personnel.
Visual cues to geographical orientation during low-level flight
NASA Technical Reports Server (NTRS)
Battiste, Vernol; Delzell, Suzanne
1991-01-01
A field study of an operational Emergency Medical Service (EMS) unit was conducted to investigate the relationships among geographical orientation, pilot decision making, and workload in EMS flights. The map data collected during this study were compared to protocols gathered in the laboratory, where pilots viewed a simulated flight over different types of unfamiliar terrain and verbally identified the features utilized to maintain geographical orientation. The EMS pilot's questionnaire data were compared with data from non-EMS helicopter pilots with comparable flight experience.
An Amphibious Ship-To-Shore Simulation for Use on an IBM PC (Personal Computer)
1984-09-01
CA : «< <- j Special ■ *- amphibious ship- an IBM Personal ion of the phy- he logic used analysis, and a DD | JAM 11 1473 COITION...research, for instance, wiL1 be geared toward a technically oriented person who is familiar with computers, programming and the associated logic. A...problem, often vaguely stated by the decision aaker , into precise and operational terms [Ref. Hz p.51]. The analysis begins with specification of the
An Integrated Tool Suite for En Route Radar Controllers in NextGen
NASA Technical Reports Server (NTRS)
Mercer, Joey; Prevot, Thomas; Brasil, Connie; Mainini, Matthew; Kupfer, Michael; Smtih, Nancy
2010-01-01
This paper describes recent human-in-the-loop research in the Airspace Operations Laboratory at the NASA Ames Research Center focusing on en route air traffic management with advanced trajectory planning tools and increased levels of human-automation cooperation. The decision support tools were exercised in a simulation of seven contiguous high-altitude sectors. Preliminary data suggests the controllers were able to manage higher amounts of traffic as compared to today, while maintaining acceptable levels of workload.
NASA Technical Reports Server (NTRS)
Wing, David J.; Adams, Richard J.; Barmore, Bryan E.; Moses, Donald
2001-01-01
This paper presents initial findings of a research study designed to provide insight into the issue of intent information exchange in constrained en-route air-traffic operations and its effect on pilot decision making and flight performance. The piloted simulation was conducted in the Air Traffic Operations Laboratory at the NASA Langley Research Center. Two operational modes for autonomous operations were compared under conditions of low and high operational complexity. The tactical mode was characterized primarily by the use of state information for conflict detection and resolution and an open-loop means for the pilot to meet operational constraints. The strategic mode involved the combined use of state and intent information, provided the pilot an additional level of alerting, and allowed a closed-loop approach to meeting operational constraints. Operational constraints included separation assurance, schedule adherence, airspace hazard avoidance, flight efficiency, and passenger comfort. Potential operational benefits of both modes are illustrated through several scenario case studies. Subjective pilot ratings and comments comparing the tactical and strategic modes are presented.
NASA Technical Reports Server (NTRS)
Wing, David J.; Adams, Richard J.; Barmore, Bryan E.; Moses, Donald
2002-01-01
This paper presents initial findings of a research study designed to provide insight into the issue of intent information exchange in constrained en-route air-traffic operations and its effect on pilot decision making and flight performance. The piloted simulation was conducted in the Air Traffic Operations Laboratory at the NASA Langley Research Center. Two operational modes for autonomous operations were compared under conditions of low and high operational complexity. The tactical mode was characterized primarily by the use of state information for conflict detection and resolution and an open-loop means for the pilot to meet operational constraints. The strategic mode involved the combined use of state and intent information, provided the pilot an additional level of alerting, and allowed a closed-loop approach to meeting operational constraints. Operational constraints included separation assurance, schedule adherence, airspace hazard avoidance, flight efficiency, and passenger comfort. Potential operational benefits of both modes are illustrated through several scenario case studies. Subjective pilot ratings and comments comparing the tactical and strategic modes are presented.
NASA Astrophysics Data System (ADS)
Arthur, Jarvis J., III; Prinzel, Lawrence J., III; Williams, Steven P.; Bailey, Randall E.; Shelton, Kevin J.; Norman, R. Mike
2011-06-01
NASA is researching innovative technologies for the Next Generation Air Transportation System (NextGen) to provide a "Better-Than-Visual" (BTV) capability as adjunct to "Equivalent Visual Operations" (EVO); that is, airport throughputs equivalent to that normally achieved during Visual Flight Rules (VFR) operations rates with equivalent and better safety in all weather and visibility conditions including Instrument Meteorological Conditions (IMC). These new technologies build on proven flight deck systems and leverage synthetic and enhanced vision systems. Two piloted simulation studies were conducted to access the use of a Head-Worn Display (HWD) with head tracking for synthetic and enhanced vision systems concepts. The first experiment evaluated the use a HWD for equivalent visual operations to San Francisco International Airport (airport identifier: KSFO) compared to a visual concept and a head-down display concept. A second experiment evaluated symbology variations under different visibility conditions using a HWD during taxi operations at Chicago O'Hare airport (airport identifier: KORD). Two experiments were conducted, one in a simulated San Francisco airport (KSFO) approach operation and the other, in simulated Chicago O'Hare surface operations, evaluating enhanced/synthetic vision and head-worn display technologies for NextGen operations. While flying a closely-spaced parallel approach to KSFO, pilots rated the HWD, under low-visibility conditions, equivalent to the out-the-window condition, under unlimited visibility, in terms of situational awareness (SA) and mental workload compared to a head-down enhanced vision system. There were no differences between the 3 display concepts in terms of traffic spacing and distance and the pilot decision-making to land or go-around. For the KORD experiment, the visibility condition was not a factor in pilot's rating of clutter effects from symbology. Several concepts for enhanced implementations of an unlimited field-of-regard BTV concept for low-visibility surface operations were determined to be equivalent in pilot ratings of efficacy and usability.
NASA Technical Reports Server (NTRS)
Arthur, Jarvis J., III; Prinzell, Lawrence J.; Williams, Steven P.; Bailey, Randall E.; Shelton, Kevin J.; Norman, R. Mike
2011-01-01
NASA is researching innovative technologies for the Next Generation Air Transportation System (NextGen) to provide a "Better-Than-Visual" (BTV) capability as adjunct to "Equivalent Visual Operations" (EVO); that is, airport throughputs equivalent to that normally achieved during Visual Flight Rules (VFR) operations rates with equivalent and better safety in all weather and visibility conditions including Instrument Meteorological Conditions (IMC). These new technologies build on proven flight deck systems and leverage synthetic and enhanced vision systems. Two piloted simulation studies were conducted to access the use of a Head-Worn Display (HWD) with head tracking for synthetic and enhanced vision systems concepts. The first experiment evaluated the use a HWD for equivalent visual operations to San Francisco International Airport (airport identifier: KSFO) compared to a visual concept and a head-down display concept. A second experiment evaluated symbology variations under different visibility conditions using a HWD during taxi operations at Chicago O'Hare airport (airport identifier: KORD). Two experiments were conducted, one in a simulated San Francisco airport (KSFO) approach operation and the other, in simulated Chicago O'Hare surface operations, evaluating enhanced/synthetic vision and head-worn display technologies for NextGen operations. While flying a closely-spaced parallel approach to KSFO, pilots rated the HWD, under low-visibility conditions, equivalent to the out-the-window condition, under unlimited visibility, in terms of situational awareness (SA) and mental workload compared to a head-down enhanced vision system. There were no differences between the 3 display concepts in terms of traffic spacing and distance and the pilot decision-making to land or go-around. For the KORD experiment, the visibility condition was not a factor in pilot's rating of clutter effects from symbology. Several concepts for enhanced implementations of an unlimited field-of-regard BTV concept for low-visibility surface operations were determined to be equivalent in pilot ratings of efficacy and usability.
Jena, Manas Kumar; Samantaray, Subhransu Ranjan
2016-01-01
This paper presents a data-mining-based intelligent differential relaying scheme for transmission lines, including flexible ac transmission system device, such as unified power flow controller (UPFC) and wind farms. Initially, the current and voltage signals are processed through extended Kalman filter phasor measurement unit for phasor estimation, and 21 potential features are computed at both ends of the line. Once the features are extracted at both ends, the corresponding differential features are derived. These differential features are fed to a data-mining model known as decision tree (DT) to provide the final relaying decision. The proposed technique has been extensively tested for single-circuit transmission line, including UPFC and wind farms with in-feed, double-circuit line with UPFC on one line and wind farm as one of the substations with wide variations in operating parameters. The test results obtained from simulation as well as in real-time digital simulator testing indicate that the DT-based intelligent differential relaying scheme is highly reliable and accurate with a response time of 2.25 cycles from the fault inception.
NASA Astrophysics Data System (ADS)
Shibuo, Yoshihiro; Ikoma, Eiji; Lawford, Peter; Oyanagi, Misa; Kanauchi, Shizu; Koudelova, Petra; Kitsuregawa, Masaru; Koike, Toshio
2014-05-01
While availability of hydrological- and hydrometeorological data shows growing tendency and advanced modeling techniques are emerging, such newly available data and advanced models may not always be applied in the field of decision-making. In this study we present an integrated system of ensemble streamflow forecast (ESP) and virtual dam simulator, which is designed to support river and dam manager's decision making. The system consists of three main functions: real time hydrological model, ESP model, and dam simulator model. In the real time model, the system simulates current condition of river basins, such as soil moisture and river discharges, using LSM coupled distributed hydrological model. The ESP model takes initial condition from the real time model's output and generates ESP, based on numerical weather prediction. The dam simulator model provides virtual dam operation and users can experience impact of dam control on remaining reservoir volume and downstream flood under the anticipated flood forecast. Thus the river and dam managers shall be able to evaluate benefit of priori dam release and flood risk reduction at the same time, on real time basis. Furthermore the system has been developed under the concept of data and models integration, and it is coupled with Data Integration and Analysis System (DIAS) - a Japanese national project for integrating and analyzing massive amount of observational and model data. Therefore it has advantage in direct use of miscellaneous data from point/radar-derived observation, numerical weather prediction output, to satellite imagery stored in data archive. Output of the system is accessible over the web interface, making information available with relative ease, e.g. from ordinary PC to mobile devices. We have been applying the system to the Upper Tone region, located northwest from Tokyo metropolitan area, and we show application example of the system in recent flood events caused by typhoons.
NASA Astrophysics Data System (ADS)
Wang, H.; Asefa, T.
2017-12-01
A real-time decision support tool (DST) for water supply system would consider system uncertainties, e.g., uncertain streamflow and demand, as well as operational constraints and infrastructure outage (e.g., pump station shutdown, an offline reservoir due to maintenance). Such DST is often used by water managers for resource allocation and delivery for customers. Although most seasonal DST used by water managers recognize those system uncertainties and operational constraints, most use only historical information or assume deterministic outlook of water supply systems. This study presents a seasonal DST that incorporates rainfall/streamflow uncertainties, seasonal demand outlook and system operational constraints. Large scale climate-information is captured through a rainfall simulator driven by a Bayesian non-homogeneous Markov Chain Monte Carlo model that allows non-stationary transition probabilities contingent on Nino 3.4 index. An ad-hoc seasonal demand forecasting model considers weather conditions explicitly and socio-economic factors implicitly. Latin Hypercube sampling is employed to effectively sample probability density functions of flow and demand. Seasonal system operation is modelled as a mixed-integer optimization problem that aims at minimizing operational costs. It embeds the flexibility of modifying operational rules at different components, e.g., surface water treatment plants, desalination facilities, and groundwater pumping stations. The proposed framework is illustrated at a wholesale water supplier in Southeastern United States, Tampa Bay Water. The use of the tool is demonstrated in proving operational guidance in a typical drawdown and refill cycle of a regional reservoir. The DST provided: 1) probabilistic outlook of reservoir storage and chance of a successful refill by the end of rainy season; 2) operational expectations for large infrastructures (e.g., high service pumps and booster stations) throughout the season. Other potential use of such DST is also discussed.
Trending in Probability of Collision Measurements
NASA Technical Reports Server (NTRS)
Vallejo, J. J.; Hejduk, M. D.; Stamey, J. D.
2015-01-01
A simple model is proposed to predict the behavior of Probabilities of Collision (P(sub c)) for conjunction events. The model attempts to predict the location and magnitude of the peak P(sub c) value for an event by assuming the progression of P(sub c) values can be modeled to first order by a downward-opening parabola. To incorporate prior information from a large database of past conjunctions, the Bayes paradigm is utilized; and the operating characteristics of the model are established through a large simulation study. Though the model is simple, it performs well in predicting the temporal location of the peak (P(sub c)) and thus shows promise as a decision aid in operational conjunction assessment risk analysis.
Artificial Intelligent Platform as Decision Tool for Asset Management, Operations and Maintenance.
2018-01-04
An Artificial Intelligence (AI) system has been developed and implemented for water, wastewater and reuse plants to improve management of sensors, short and long term maintenance plans, asset and investment management plans. It is based on an integrated approach to capture data from different computer systems and files. It adds a layer of intelligence to the data. It serves as a repository of key current and future operations and maintenance conditions that a plant needs have knowledge of. With this information, it is able to simulate the configuration of processes and assets for those conditions to improve or optimize operations, maintenance and asset management, using the IViewOps (Intelligent View of Operations) model. Based on the optimization through model runs, it is able to create output files that can feed data to other systems and inform the staff regarding optimal solutions to the conditions experienced or anticipated in the future.
Ruohonen, Toni; Ennejmy, Mohammed
2013-01-01
Making reliable and justified operational and strategic decisions is a really challenging task in the health care domain. So far, the decisions have been made based on the experience of managers and staff, or they are evaluated with traditional methods, using inadequate data. As a result of this kind of decision-making process, attempts to improve operations usually have failed or led to only local improvements. Health care organizations have a lot of operational data, in addition to clinical data, which is the key element for making reliable and justified decisions. However, it is progressively problematic to access it and make usage of it. In this paper we discuss about the possibilities how to exploit operational data in the most efficient way in the decision-making process. We'll share our future visions and propose a conceptual framework for automating the decision-making process.
How to guide - transit operations decision support systems (TODSS).
DOT National Transportation Integrated Search
2014-12-01
Transit Operations Decision Support Systems (TODSS) are decision support systems designed to support dispatchers in real-time bus operations management in response to incidents, special events, and other changing conditions in order to restore servic...
Soft Decision Analyzer and Method
NASA Technical Reports Server (NTRS)
Zucha, Joan P. (Inventor); Schlesinger, Adam M. (Inventor); Lansdowne, Chatwin (Inventor); Steele, Glen F. (Inventor)
2015-01-01
A soft decision analyzer system is operable to interconnect soft decision communication equipment and analyze the operation thereof to detect symbol wise alignment between a test data stream and a reference data stream in a variety of operating conditions.
Soft Decision Analyzer and Method
NASA Technical Reports Server (NTRS)
Zucha, Joan P. (Inventor); Schlesinger, Adam M. (Inventor); Lansdowne, Chatwin (Inventor); Steele, Glen F. (Inventor)
2016-01-01
A soft decision analyzer system is operable to interconnect soft decision communication equipment and analyze the operation thereof to detect symbol wise alignment between a test data stream and a reference data stream in a variety of operating conditions.
Multi-shock Shield Performance at 16.5 MJ for Catalogued Debris
NASA Technical Reports Server (NTRS)
Miller, J. E.; Christiansen, E. L.; Davis, B. A.
2014-01-01
While orbital debris of ten centimeters or more are tracked and catalogued, the difficulty of finding and accurately accounting for forces acting on the objects near the ten centimeter threshold results in both uncertainty of their presence and location. These challenges result in difficult decisions for operators balancing potential costly operational approaches with system loss risk. In this paper, numerical simulations and an experiment using the multi-shock shield system is described for a cylindrical projectile composed of Nylon, aluminum and void that is approximately 8 cm in diameter and 10 cm in length weighing 670 g impacting the multi-shock shield normal to the surface with approximately 16.5 MJ of kinetic energy. The multi-shock shield system has been optimized to facilitate the fragmentation, spread and deceleration of the projectile remnants using hydrodynamic simulations of the impact event. The characteristics and function of each of the layers of the multi-shock system will be discussed along with considerations for deployment and improvement.
Water Resources Planning under Uncertainty: A "Real Options" Approach
NASA Astrophysics Data System (ADS)
Jeuland, M. A.; Whittington, D.
2011-12-01
This research develops a real options approach for planning new water resources developments, in infrastructure construction and system operation, under uncertainty. The approach treats the planning problem as a series of staged decisions - the selection of new projects; their scale, timing and sequencing; and finally their operating rules - each of which is characterized by varying levels of irreversibility. The performance of different configurations of the system is then assessed along the various dimensions of the decision space, using simulation methods. The methodology is then made operational using an existing hydrological simulation model that can be used to study the example of hydropower development options in the Blue Nile in Ethiopia. The model includes physical linkages between climate change and system hydrology, and allows users to test the sensitivity of the basin-wide economic consequences of dams, which consist of energy generation, changes in irrigation crop-water demand, the value of flood control, and other basin-wide impacts, to climate change or changes in runoff, as well as to other uncertainties. The analysis shows that, from an economic perspective, there is no single optimal system configuration across a range of future climate conditions deemed plausible for this basin. For example, small infrastructures perform best in scenarios with reduced runoff into the river, whereas large ones are best when runoff increases. The real options framework therefore becomes useful for helping to identify configurations that are both more robust to poor outcomes and still contain sufficient flexibility to capture high upside benefits should favorable future conditions arise. The framework could readily be extended to explore a range of features that could be usefully built into water resources projects more generally, to improve the long-term economic performance of such investments.
NASA Technical Reports Server (NTRS)
Trimble, Jay
2017-01-01
For NASA's Resource Prospector (RP) Lunar Rover Mission, we are moving away from a control center concept, to a fully distributed operation utilizing control nodes, with decision support from anywhere via mobile devices. This operations concept will utilize distributed information systems, notifications, mobile data access, and optimized mobile data display for off-console decision support. We see this concept of operations as a step in the evolution of mission operations from a central control center concept to a mission operations anywhere concept. The RP example is part of a trend, in which mission expertise for design, development and operations is distributed across countries and across the globe. Future spacecraft operations will be most cost efficient and flexible by following this distributed expertise, enabling operations from anywhere. For the RP mission we arrived at the decision to utilize a fully distributed operations team, where everyone operates from their home institution, based on evaluating the following factors: the requirement for physical proximity for near-real time command and control decisions; the cost of distributed control nodes vs. a centralized control center; the impact on training and mission preparation of flying the team to a central location. Physical proximity for operational decisions is seldom required, though certain categories of decisions, such as launch abort, or close coordination for mission or safety-critical near-real-time command and control decisions may benefit from co-location. The cost of facilities and operational infrastructure has not been found to be a driving factor for location in our studies. Mission training and preparation benefit from having all operators train and operate from home institutions.
GROTTO visualization for decision support
NASA Astrophysics Data System (ADS)
Lanzagorta, Marco O.; Kuo, Eddy; Uhlmann, Jeffrey K.
1998-08-01
In this paper we describe the GROTTO visualization projects being carried out at the Naval Research Laboratory. GROTTO is a CAVE-like system, that is, a surround-screen, surround- sound, immersive virtual reality device. We have explored the GROTTO visualization in a variety of scientific areas including oceanography, meteorology, chemistry, biochemistry, computational fluid dynamics and space sciences. Research has emphasized the applications of GROTTO visualization for military, land and sea-based command and control. Examples include the visualization of ocean current models for the simulation and stud of mine drifting and, inside our computational steering project, the effects of electro-magnetic radiation on missile defense satellites. We discuss plans to apply this technology to decision support applications involving the deployment of autonomous vehicles into contaminated battlefield environments, fire fighter control and hostage rescue operations.
Exploration Criteria for Low Permeability Geothermal Resources
DOE Office of Scientific and Technical Information (OSTI.GOV)
Norton, D
1977-03-01
The decision to drill deep holes in a prospective geothermal system implies that geothermal energy resources exist at depth. The drill hole location and budget result from hypothesis regarding the location and depth of the resource within the overall system. Although operational decisions normally dictate the practicality of drilling, the characteristics, we must first understand how unique various surface or shallow subsurface data are in assessing the nature of the resource. The following progress report summarizes the results of numerical simulations of heat and mass transport around igneous plutons and the synthesis of geologic data. To date, the results ofmore » the study describe the transient nature of thermal resources and the ambiguities which must be accounted for in using current technology to assess the nation's geothermal resources. [DJE-2005]« less
Toward sensor-based context aware systems.
Sakurai, Yoshitaka; Takada, Kouhei; Anisetti, Marco; Bellandi, Valerio; Ceravolo, Paolo; Damiani, Ernesto; Tsuruta, Setsuo
2012-01-01
This paper proposes a methodology for sensor data interpretation that can combine sensor outputs with contexts represented as sets of annotated business rules. Sensor readings are interpreted to generate events labeled with the appropriate type and level of uncertainty. Then, the appropriate context is selected. Reconciliation of different uncertainty types is achieved by a simple technique that moves uncertainty from events to business rules by generating combs of standard Boolean predicates. Finally, context rules are evaluated together with the events to take a decision. The feasibility of our idea is demonstrated via a case study where a context-reasoning engine has been connected to simulated heartbeat sensors using prerecorded experimental data. We use sensor outputs to identify the proper context of operation of a system and trigger decision-making based on context information.
Decision Making Training in the Mission Operations Directorate
NASA Technical Reports Server (NTRS)
O'Keefe, William S.
2013-01-01
At JSC, we train our new flight controllers on a set of team skills that we call Space Flight Resource Management (SFRM). SFRM is akin to Crew Resource Management for the airlines and trains flight controllers to work as an effective team to reduce errors and improve safety. We have developed this training over the years with the assistance of Ames Research Center, Wyle Labs and University of Central Florida. One of the skills we teach is decision making/ problem solving (DM/PS). We teach DM/PS first in several classroom sessions, reinforce it in several part task training environments, and finally practice it in full-mission, full-team simulations. What I am proposing to talk about is this training flow: its content and how we teach it.
Fuzzy methods in decision making process - A particular approach in manufacturing systems
NASA Astrophysics Data System (ADS)
Coroiu, A. M.
2015-11-01
We are living in a competitive environment, so we can see and understand that the most of manufacturing firms do the best in order to accomplish meeting demand, increasing quality, decreasing costs, and delivery rate. In present a stake point of interest is represented by the development of fuzzy technology. A particular approach for this is represented through the development of methodologies to enhance the ability to managed complicated optimization and decision making aspects involving non-probabilistic uncertainty with the reason to understand, development, and practice the fuzzy technologies to be used in fields such as economic, engineering, management, and societal problems. Fuzzy analysis represents a method for solving problems which are related to uncertainty and vagueness; it is used in multiple areas, such as engineering and has applications in decision making problems, planning and production. As a definition for decision making process we can use the next one: result of mental processes based upon cognitive process with a main role in the selection of a course of action among several alternatives. Every process of decision making can be represented as a result of a final choice and the output can be represented as an action or as an opinion of choice. Different types of uncertainty can be discovered in a wide variety of optimization and decision making problems related to planning and operation of power systems and subsystems. The mixture of the uncertainty factor in the construction of different models serves for increasing their adequacy and, as a result, the reliability and factual efficiency of decisions based on their analysis. Another definition of decision making process which came to illustrate and sustain the necessity of using fuzzy method: the decision making is an approach of choosing a strategy among many different projects in order to achieve some purposes and is formulated as three different models: high risk decision, usual risk decision and low risk decision - some specific formulas of fuzzy logic. The fuzzy set concepts has some certain parameterization features which are certain extensions of crisp and fuzzy relations respectively and have a rich potential for application to the decision making problems. The proposed approach from this paper presents advantages of fuzzy approach, in comparison with other paradigm and presents a particular way in which fuzzy logic can emerge in decision making process and planning process with implication, as a simulation, in manufacturing - involved in measuring performance of advanced manufacturing systems. Finally, an example is presented to illustrate our simulation.
Aircraft accident investigation: the decision-making in initial action scenario.
Barreto, Marcia M; Ribeiro, Selma L O
2012-01-01
In the complex aeronautical environment, the efforts in terms of operational safety involve the adoption of proactive and reactive measures. The process of investigation begins right after the occurrence of the aeronautical accident, through the initial action. Thus, it is in the crisis scenario, that the person responsible for the initial action makes decisions and gathers the necessary information for the subsequent phases of the investigation process. Within this scenario, which is a natural environment, researches have shown the fragility of rational models of decision making. The theoretical perspective of naturalistic decision making constitutes a breakthrough in the understanding of decision problems demanded by real world. The proposal of this study was to verify if the initial action, after the occurrence of an accident, and the decision-making strategies, used by the investigators responsible for this activity, are characteristic of the naturalistic decision making theoretical approach. To attend the proposed objective a descriptive research was undertaken with a sample of professionals that work in this activity. The data collected through individual interviews were analyzed and the results demonstrated that the initial action environment, which includes restricted time, dynamic conditions, the presence of multiple actors, stress and insufficient information is characteristic of the naturalistic decision making. They also demonstrated that, when the investigators make their decisions, they use their experience and the mental simulation, intuition, improvisation, metaphors and analogues cases, as strategies, all of them related to the naturalistic approach of decision making, in order to satisfy the needs of the situation and reach the objectives of the initial action in the accident scenario.
Maintenance and operations decision support tool : Clarus regional demonstrations.
DOT National Transportation Integrated Search
2011-01-01
Weather affects almost all maintenance activity decisions. The Federal Highway Administration (FHWA) tested a new decision support system for maintenance in Iowa, Indiana, and Illinois called the Maintenance and Operations Decision Support System (MO...
NASA Astrophysics Data System (ADS)
Curtis, Christopher; Lenzo, Matthew; McClure, Matthew; Preiss, Bruce
2010-04-01
In order to anticipate the constantly changing landscape of global warfare, the United States Air Force must acquire new capabilities in the field of Intelligence, Surveillance, and Reconnaissance (ISR). To meet this challenge, the Air Force Research Laboratory (AFRL) is developing a unifying construct of "Layered Sensing" which will provide military decision-makers at all levels with the timely, actionable, and trusted information necessary for complete battlespace awareness. Layered Sensing is characterized by the appropriate combination of sensors and platforms (including those for persistent sensing), infrastructure, and exploitation capabilities to enable this synergistic awareness. To achieve the Layered Sensing vision, AFRL is pursuing a Modeling & Simulation (M&S) strategy through the Layered Sensing Operations Center (LSOC). An experimental ISR system-of-systems test-bed, the LSOC integrates DoD standard simulation tools with commercial, off-the-shelf video game technology for rapid scenario development and visualization. These tools will help facilitate sensor management performance characterization, system development, and operator behavioral analysis. Flexible and cost-effective, the LSOC will implement a non-proprietary, open-architecture framework with well-defined interfaces. This framework will incentivize the transition of current ISR performance models to service-oriented software design for maximum re-use and consistency. This paper will present the LSOC's development and implementation thus far as well as a summary of lessons learned and future plans for the LSOC.
NASA Astrophysics Data System (ADS)
Buffa, F.; Pinna, A.; Sanna, G.
2016-06-01
The Sardinia Radio Telescope (SRT) is a 64 m diameter antenna, whose primary mirror is equipped with an active surface capable to correct its deformations by means of a thick network of actuators. Close range photogrammetry (CRP) was used to measure the self-load deformations of the SRT primary reflector from its optimal shape, which are requested to be minimized for the radio telescope to operate at full efficiency. In the attempt to achieve such performance, we conceived a near real-time CRP system which requires the cameras to be installed in fixed positions and at the same time to avoid any interference with the antenna operativeness. The design of such system is not a trivial task, and to assist our decision we therefore developed a simulation pipeline to realistically reproduce and evaluate photogrammetric surveys of large structures. The described simulation environment consists of (i) a detailed description of the SRT model, included the measurement points and the camera parameters, (ii) a tool capable of generating realistic images accordingly to the above model, and (iii) a self-calibrating bundle adjustment to evaluate the performance in terms of RMSE of the camera configurations.
NASA Technical Reports Server (NTRS)
Jackson, E. Bruce; Raney, David L.; Glaab, Louis J.; Derry, Stephen D.
2002-01-01
An assessment of a proposed configuration of a high-speed civil transport was conducted by using NASA and industry research pilots. The assessment was conducted to evaluate operational aspects of the configuration from a pilot's perspective, with the primary goal being to identify potential deficiencies in the configuration. The configuration was evaluated within and at the limits of the design operating envelope to determine the suitability of the configuration to maneuver in a typical mission as well as in emergency or envelope-limit conditions. The Cooper-Harper rating scale was used to evaluate the flying qualities of the configuration. A summary flying qualities metric was also calculated. The assessment was performed in the Langley six-degree-of-freedom Visual Motion Simulator. The effect of a restricted cockpit field-of-view due to obstruction by the vehicle nose was not included in this study. Tasks include landings, takeoffs, climbs, descents, overspeeds, coordinated turns, and recoveries from envelope limit excursions. Emergencies included engine failures, loss of stability augmentation, engine inlet unstarts, and emergency descents. Minimum control speeds and takeoff decision, rotation, and safety speeds were also determined.
Operating Comfort Prediction Model of Human-Machine Interface Layout for Cabin Based on GEP.
Deng, Li; Wang, Guohua; Chen, Bo
2015-01-01
In view of the evaluation and decision-making problem of human-machine interface layout design for cabin, the operating comfort prediction model is proposed based on GEP (Gene Expression Programming), using operating comfort to evaluate layout scheme. Through joint angles to describe operating posture of upper limb, the joint angles are taken as independent variables to establish the comfort model of operating posture. Factor analysis is adopted to decrease the variable dimension; the model's input variables are reduced from 16 joint angles to 4 comfort impact factors, and the output variable is operating comfort score. The Chinese virtual human body model is built by CATIA software, which will be used to simulate and evaluate the operators' operating comfort. With 22 groups of evaluation data as training sample and validation sample, GEP algorithm is used to obtain the best fitting function between the joint angles and the operating comfort; then, operating comfort can be predicted quantitatively. The operating comfort prediction result of human-machine interface layout of driller control room shows that operating comfort prediction model based on GEP is fast and efficient, it has good prediction effect, and it can improve the design efficiency.
Operating Comfort Prediction Model of Human-Machine Interface Layout for Cabin Based on GEP
Wang, Guohua; Chen, Bo
2015-01-01
In view of the evaluation and decision-making problem of human-machine interface layout design for cabin, the operating comfort prediction model is proposed based on GEP (Gene Expression Programming), using operating comfort to evaluate layout scheme. Through joint angles to describe operating posture of upper limb, the joint angles are taken as independent variables to establish the comfort model of operating posture. Factor analysis is adopted to decrease the variable dimension; the model's input variables are reduced from 16 joint angles to 4 comfort impact factors, and the output variable is operating comfort score. The Chinese virtual human body model is built by CATIA software, which will be used to simulate and evaluate the operators' operating comfort. With 22 groups of evaluation data as training sample and validation sample, GEP algorithm is used to obtain the best fitting function between the joint angles and the operating comfort; then, operating comfort can be predicted quantitatively. The operating comfort prediction result of human-machine interface layout of driller control room shows that operating comfort prediction model based on GEP is fast and efficient, it has good prediction effect, and it can improve the design efficiency. PMID:26448740
NASA Astrophysics Data System (ADS)
Leavesley, G.; Markstrom, S.; Frevert, D.; Fulp, T.; Zagona, E.; Viger, R.
2004-12-01
Increasing demands for limited fresh-water supplies, and increasing complexity of water-management issues, present the water-resource manager with the difficult task of achieving an equitable balance of water allocation among a diverse group of water users. The Watershed and River System Management Program (WARSMP) is a cooperative effort between the U.S. Geological Survey (USGS) and the Bureau of Reclamation (BOR) to develop and deploy a database-centered, decision-support system (DSS) to address these multi-objective, resource-management problems. The decision-support system couples the USGS Modular Modeling System (MMS) with the BOR RiverWare tools using a shared relational database. MMS is an integrated system of computer software that provides a research and operational framework to support the development and integration of a wide variety of hydrologic and ecosystem models, and their application to water- and ecosystem-resource management. RiverWare is an object-oriented reservoir and river-system modeling framework developed to provide tools for evaluating and applying water-allocation and management strategies. The modeling capabilities of MMS and Riverware include simulating watershed runoff, reservoir inflows, and the impacts of resource-management decisions on municipal, agricultural, and industrial water users, environmental concerns, power generation, and recreational interests. Forecasts of future climatic conditions are a key component in the application of MMS models to resource-management decisions. Forecast methods applied in MMS include a modified version of the National Weather Service's Extended Streamflow Prediction Program (ESP) and statistical downscaling from atmospheric models. The WARSMP DSS is currently operational in the Gunnison River Basin, Colorado; Yakima River Basin, Washington; Rio Grande Basin in Colorado and New Mexico; and Truckee River Basin in California and Nevada.
Trabelsi, O; Villalobos, J L López; Ginel, A; Cortes, E Barrot; Doblaré, M
2014-05-01
Swallowing depends on physiological variables that have a decisive influence on the swallowing capacity and on the tracheal stress distribution. Prosthetic implantation modifies these values and the overall performance of the trachea. The objective of this work was to develop a decision support system based on experimental, numerical and statistical approaches, with clinical verification, to help the thoracic surgeon in deciding the position and appropriate dimensions of a Dumon prosthesis for a specific patient in an optimal time and with sufficient robustness. A code for mesh adaptation to any tracheal geometry was implemented and used to develop a robust experimental design, based on the Taguchi's method and the analysis of variance. This design was able to establish the main swallowing influencing factors. The equations to fit the stress and the vertical displacement distributions were obtained. The resulting fitted values were compared to those calculated directly by the finite element method (FEM). Finally, a checking and clinical validation of the statistical study were made, by studying two cases of real patients. The vertical displacements and principal stress distribution obtained for the specific tracheal model were in agreement with those calculated by FE simulations with a maximum absolute error of 1.2 mm and 0.17 MPa, respectively. It was concluded that the resulting decision support tool provides a fast, accurate and simple tool for the thoracic surgeon to predict the stress state of the trachea and the reduction in the ability to swallow after implantation. Thus, it will help them in taking decisions during pre-operative planning of tracheal interventions.
NASA Technical Reports Server (NTRS)
Bienert, Nancy; Mercer, Joey; Homola, Jeffrey; Morey, Susan; Prevot, Thomas
2014-01-01
This paper presents a case study of how factors such as wind prediction errors and metering delays can influence controller performance and workload in Human-In-The-Loop simulations. Retired air traffic controllers worked two arrival sectors adjacent to the terminal area. The main tasks were to provide safe air traffic operations and deliver the aircraft to the metering fix within +/- 25 seconds of the scheduled arrival time with the help of provided decision support tools. Analyses explore the potential impact of metering delays and system uncertainties on controller workload and performance. The results suggest that trajectory prediction uncertainties impact safety performance, while metering fix accuracy and workload appear subject to the scenario difficulty.
Mass balances for a biological life support system simulation model
NASA Technical Reports Server (NTRS)
Volk, Tyler; Rummel, John D.
1987-01-01
Design decisions to aid the development of future space based biological life support systems (BLSS) can be made with simulation models. The biochemistry stoichiometry was developed for: (1) protein, carbohydrate, fat, fiber, and lignin production in the edible and inedible parts of plants; (2) food consumption and production of organic solids in urine, feces, and wash water by the humans; and (3) operation of the waste processor. Flux values for all components are derived for a steady state system with wheat as the sole food source. The large scale dynamics of a materially closed (BLSS) computer model is described in a companion paper. An extension of this methodology can explore multifood systems and more complex biochemical dynamics while maintaining whole system closure as a focus.
A simulation exercise to teach principles of bovine reproductive management.
Perry, G A; Smith, M F
2004-05-01
Students in Reproductive Management (a senior-level course with approximately 20 to 50 students per semester) at the University of Missouri-Columbia are required to participate in a simulation exercise that is designed to improve reproductive efficiency in a beef herd. During a simulated 5-yr period, students must 1) improve reproductive efficiency in a beef cow-herd through implementation of reproductive management principles; 2) determine the economic impact of reproductive management decisions in a beef herd; and 3) evaluate the constraints of different geographical locations on approaches to reproductive management. Groups of three to four students are provided with the reproductive and economic records of a farm/ranch located in different parts of North America. Students create reproductive management plans consisting of 1) detailed discussion of farm/ranch environment (climate, terrain, forage and grain availability, and stocking rate; season for breeding and calving; and justification for choice of breed); 2) assessment of current level of reproductive performance; 3) identification and economic justification of specific (measurable) objectives; 4) discussion of alternatives for accomplishing specific objectives; 5) prediction of reproductive performance (pregnancy rate, quantity of calf weaned per cow exposed, and cost per quantity of calf weaned) in response to implementation of specific management practices; and 6) an annual and 5-yr reproductive and economic summary. Students obtain livestock marketing information for their assigned location via the Internet. Spreadsheets were developed to calculate the reproductive efficiency of postpartum cows and replacement heifers based on management decisions made by the groups and to calculate a yearly economic summary for each of the 5 yr. Management decisions are justified in a written report, and oral presentations are given to the class when the project is completed. Greater than 85% of students indicated that the exercise increased their understanding of how management decisions affect reproductive efficiency and profitability in a beef operation and also provided added confidence for students that applied for beef management positions.
A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning
NASA Astrophysics Data System (ADS)
Basdekas, L.; Stewart, N.; Triana, E.
2013-12-01
Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU evaluate tradeoffs in a continually changing world.
NASA Astrophysics Data System (ADS)
Hassanzadeh, Elmira; Elshorbagy, Amin; Wheater, Howard; Gober, Patricia
2015-04-01
Climate uncertainty can affect water resources availability and management decisions. Sustainable water resources management therefore requires evaluation of policy and management decisions under a wide range of possible future water supply conditions. This study proposes a risk-based framework to integrate water supply uncertainty into a forward-looking decision making context. To apply this framework, a stochastic reconstruction scheme is used to generate a large ensemble of flow series. For the Rocky Mountain basins considered here, two key characteristics of the annual hydrograph are its annual flow volume and the timing of the seasonal flood peak. These are perturbed to represent natural randomness and potential changes due to future climate. 30-year series of perturbed flows are used as input to the SWAMP model - an integrated water resources model that simulates regional water supply-demand system and estimates economic productivity of water and other sustainability indicators, including system vulnerability and resilience. The simulation results are used to construct 2D-maps of net revenue of a particular water sector; e.g., hydropower, or for all sectors combined. Each map cell represents a risk scenario of net revenue based on a particular annual flow volume, timing of the peak flow, and 200 stochastic realizations of flow series. This framework is demonstrated for a water resources system in the Saskatchewan River Basin (SaskRB) in Saskatchewan, Canada. Critical historical drought sequences, derived from tree-ring reconstructions of several hundred years of annual river flows, are used to evaluate the system's performance (net revenue risk) under extremely low flow conditions and also to locate them on the previously produced 2D risk maps. This simulation and analysis framework is repeated under various reservoir operation strategies (e.g., maximizing flood protection or maximizing water supply security); development proposals, such as irrigation expansion; and change in energy prices. Such risk-based analysis demonstrates relative reduction/increase of risk associated with management and policy decisions and allow decision makers to explore the relative importance of policy versus natural water supply change in a water resources system.
NASA Astrophysics Data System (ADS)
Aktan, A. Emin
2003-08-01
Although the interconnected systems nature of the infrastructures, and the complexity of interactions between their engineered, socio-technical and natural constituents have been recognized for some time, the principles of effectively operating, protecting and preserving such systems by taking full advantage of "modeling, simulations, optimization, control and decision making" tools developed by the systems engineering and operations research community have not been adequately studied or discussed by many engineers including the writer. Differential and linear equation systems, numerical and finite element modeling techniques, statistical and probabilistic representations are universal, however, different disciplines have developed their distinct approaches to conceptualizing, idealizing and modeling the systems they commonly deal with. The challenge is in adapting and integrating deterministic and stochastic, geometric and numerical, physics-based and "soft (data-or-knowledge based)", macroscopic or microscopic models developed by various disciplines for simulating infrastructure systems. There is a lot to be learned by studying how different disciplines have studied, improved and optimized the systems relating to various processes and products in their domains. Operations research has become a fifty-year old discipline addressing complex systems problems. Its mathematical tools range from linear programming to decision processes and game theory. These tools are used extensively in management and finance, as well as by industrial engineers for optimizing and quality control. Progressive civil engineering academic programs have adopted "systems engineering" as a focal area. However, most of the civil engineering systems programs remain focused on constructing and analyzing highly idealized, often generic models relating to the planning or operation of transportation, water or waste systems, maintenance management, waste management or general infrastructure hazards risk management. We further note that in the last decade there have been efforts for "agent-based" modeling of synthetic infrastructure systems by taking advantage of supercomputers at various DOE Laboratories. However, whether there is any similitude between such synthetic and actual systems needs investigating further.
Cutrì, Elena; Meoli, Alessio; Dubini, Gabriele; Migliavacca, Francesco; Hsia, Tain-Yen; Pennati, Giancarlo
2017-09-01
Hypoplastic left heart syndrome is a complex congenital heart disease characterised by the underdevelopment of the left ventricle normally treated with a three-stage surgical repair. In this study, a multiscale closed-loop cardio-circulatory model is created to reproduce the pre-operative condition of a patient suffering from such pathology and virtual surgery is performed. Firstly, cardio-circulatory parameters are estimated using a fully closed-loop cardio-circulatory lumped parameter model. Secondly, a 3D standalone FEA model is build up to obtain active and passive ventricular characteristics and unloaded reference state. Lastly, the 3D model of the single ventricle is coupled to the lumped parameter model of the circulation obtaining a multiscale closed-loop pre-operative model. Lacking any information on the fibre orientation, two cases were simulated: (i) fibre distributed as in the physiological right ventricle and (ii) fibre as in the physiological left ventricle. Once the pre-operative condition is satisfactorily simulated for the two cases, virtual surgery is performed. The post-operative results in the two cases highlighted similar hemodynamic behaviour but different local mechanics. This finding suggests that the knowledge of the patient-specific fibre arrangement is important to correctly estimate the single ventricle's working condition and consequently can be valuable to support clinical decision. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.
Subjective scaling of mental workload in a multi-task environment
NASA Technical Reports Server (NTRS)
Daryanian, B.
1982-01-01
Those factors in a multi-task environment that contribute to the operators' "sense" of mental workload were identified. The subjective judgment as conscious experience of mental effort was decided to be the appropriate method of measurement. Thurstone's law of comparative judgment was employed in order to construct interval scales of subjective mental workload from paired comparisons data. An experimental paradigm (Simulated Multi-Task Decision-Making Environment) was employed to represent the ideal experimentally controlled environment in which human operators were asked to "attend" to different cases of Tulga's decision making tasks. Through various statistical analyses it was found that, in general, a lower number of tasks-to-be-processed per unit time (a condition associated with longer interarrival times), results in a lower mental workload, a higher consistency of judgments within a subject, a higher degree of agreement among the subjects, and larger distances between the cases on the Thurstone scale of subjective mental workload. The effects of various control variables and their interactions, and the different characteristics of the subjects on the variation of subjective mental workload are demonstrated.
NASA Technical Reports Server (NTRS)
Kyle, R. G.
1972-01-01
Information transfer between the operator and computer-generated display systems is an area where the human factors engineer discovers little useful design data relating human performance to system effectiveness. This study utilized a computer-driven, cathode-ray-tube graphic display to quantify human response speed in a sequential information processing task. The performance criteria was response time to sixteen cell elements of a square matrix display. A stimulus signal instruction specified selected cell locations by both row and column identification. An equal probable number code, from one to four, was assigned at random to the sixteen cells of the matrix and correspondingly required one of four, matched keyed-response alternatives. The display format corresponded to a sequence of diagnostic system maintenance events, that enable the operator to verify prime system status, engage backup redundancy for failed subsystem components, and exercise alternate decision-making judgements. The experimental task bypassed the skilled decision-making element and computer processing time, in order to determine a lower bound on the basic response speed for given stimulus/response hardware arrangement.
Reach a nonlinear consensus for MAS via doubly stochastic quadratic operators
NASA Astrophysics Data System (ADS)
Abdulghafor, Rawad; Turaev, Sherzod; Zeki, Akram; Al-Shaikhli, Imad
2018-06-01
This technical note addresses the new nonlinear protocol class of doubly stochastic quadratic operators (DSQOs) for coordination of consensus problem in multi-agent systems (MAS). We derive the conditions for ensuring that every agent reaches consensus on a desired rate of the group's decision where the group decision value in its agent's initial statuses varies. Besides that, we investigate a nonlinear protocol sub-class of extreme DSQO (EDSQO) to reach a consensus for MAS to a common value with nonlinear low-complexity rules and fast time convergence if the interactions for each agent are not selfish. In addition, to extend the results to reach a consensus and to avoid the selfish case we specify a general class of DSQO for reaching a consensus under any given case of initial states. The case that MAS reach a consensus by DSQO is if each member of the agent group has positive interactions of DSQO (PDSQO) with the others. The convergence of both EDSQO and PDSQO classes is found to be directed towards the centre point. Finally, experimental simulations are given to support the analysis from theoretical aspect.
RPA Field Simulations:Dilemma Training for Legal and Ethical Decision Making
2015-11-07
Simulation Two phases in RPA Field Simulation – classroom phase and field phase Purpose: link theoretical understanding/ moral reasoning with...rapid, informed decision-making/ moral behavior IRREGULAR WARFARE U.S. dominates conventional warfare, but irregular warfare falls under Things...aspects: Mental simulation of action Modify Implement Will it work? MORAL REASONING/BEHAVIOR Military-Leader Responsibility requires
Simulations and the Curriculum.
ERIC Educational Resources Information Center
Ediger, Marlow
Microcomputers can be used with simulation software to provide students both with experience in the "real world" of decision making and feedback on the decisions made. Such software allows individual students to choose the roles they wish to play from a menu of diverse roles and provides alternatives for them to consider for each decision to be…
Energy requirements in pressure irrigation systems
NASA Astrophysics Data System (ADS)
Sánchez, R.; Rodríguez-Sinobas, L.; Juana, L.; Laguna, F. V.; Castañón, G.; Gil, M.; Benítez, J.
2012-04-01
Modernization of irrigation schemes, generally understood as transformation of surface irrigation systems into pressure -sprinkler and trickle- irrigation systems, aims at, among others, improving irrigation efficiency and reduction of operation and maintenance efforts made by the irrigators. However, pressure irrigation systems, in contrast, carry a serious energy cost. Energy requirements depend on decisions taken on management strategies during the operation phase, which are conditioned by previous decisions taken on the design project of the different elements which compose the irrigation system. Most of the countries where irrigation activity is significant bear in mind that modernization irrigation must play a key role in the agricultural infrastructure policies. The objective of this study is to characterize and estimate the mean and variation of the energy consumed by common types of irrigation systems and their management possibilities. The work includes all processes involved from the diversion of water into irrigation specific infrastructure to water discharge by the emitters installed on the crop fields. Simulation taking into account all elements comprising the irrigation system has been used to estimate the energy requirements of typical irrigation systems of several crop production systems. It has been applied to extensive and intensive crop systems, such us extensive winter crops, summer crops and olive trees, fruit trees and vineyards and intensive horticulture in greenhouses. The simulation of various types of irrigation systems and management strategies, in the framework imposed by particular cropping systems, would help to develop criteria for improving the energy balance in relation to the irrigation water supply productivity.
Measuring Command Post Operations in a Decisive Action Training Environment
2017-05-01
Research Report 2001 Measuring Command Post Operations in a Decisive Action Training Environment Michelle N...September 2014 - September 2015 4. TITLE AND SUBTITLE Measuring Command Post Operations in a Decisive Action Training Environment 5a...Readiness Training Center Warrior Leadership Council, we explored whether a guide on Command Post (CP) Operations could improve performance during
Heim, Joseph A; Huang, Hao; Zabinsky, Zelda B; Dickerson, Jane; Wellner, Monica; Astion, Michael; Cruz, Doris; Vincent, Jeanne; Jack, Rhona
2015-08-01
Design and implement a concurrent campaign of influenza immunization and tuberculosis (TB) screening for health care workers (HCWs) that can reduce the number of clinic visits for each HCW. A discrete-event simulation model was developed to support issues of resource allocation decisions in planning and operations phases. The campaign was compressed to100 days in 2010 and further compressed to 75 days in 2012 and 2013. With more than 5000 HCW arrivals in 2011, 2012 and 2013, the 14-day goal of TB results was achieved for each year and reduced to about 4 days in 2012 and 2013. Implementing a concurrent campaign allows less number of visiting clinics and the compressing of campaign length allows earlier immunization. The support of simulation modelling can provide useful evaluations of different configurations. © 2015 John Wiley & Sons, Ltd.
A generic discrete-event simulation model for outpatient clinics in a large public hospital.
Weerawat, Waressara; Pichitlamken, Juta; Subsombat, Peerapong
2013-01-01
The orthopedic outpatient department (OPD) ward in a large Thai public hospital is modeled using Discrete-Event Stochastic (DES) simulation. Key Performance Indicators (KPIs) are used to measure effects across various clinical operations during different shifts throughout the day. By considering various KPIs such as wait times to see doctors, percentage of patients who can see a doctor within a target time frame, and the time that the last patient completes their doctor consultation, bottlenecks are identified and resource-critical clinics can be prioritized. The simulation model quantifies the chronic, high patient congestion that is prevalent amongst Thai public hospitals with very high patient-to-doctor ratios. Our model can be applied across five different OPD wards by modifying the model parameters. Throughout this work, we show how DES models can be used as decision-support tools for hospital management.
Simulating cyber warfare and cyber defenses: information value considerations
NASA Astrophysics Data System (ADS)
Stytz, Martin R.; Banks, Sheila B.
2011-06-01
Simulating cyber warfare is critical to the preparation of decision-makers for the challenges posed by cyber attacks. Simulation is the only means we have to prepare decision-makers for the inevitable cyber attacks upon the information they will need for decision-making and to develop cyber warfare strategies and tactics. Currently, there is no theory regarding the strategies that should be used to achieve objectives in offensive or defensive cyber warfare, and cyber warfare occurs too rarely to use real-world experience to develop effective strategies. To simulate cyber warfare by affecting the information used for decision-making, we modify the information content of the rings that are compromised during in a decision-making context. The number of rings affected and value of the information that is altered (i.e., the closeness of the ring to the center) is determined by the expertise of the decision-maker and the learning outcome(s) for the simulation exercise. We determine which information rings are compromised using the probability that the simulated cyber defenses that protect each ring can be compromised. These probabilities are based upon prior cyber attack activity in the simulation exercise as well as similar real-world cyber attacks. To determine which information in a compromised "ring" to alter, the simulation environment maintains a record of the cyber attacks that have succeeded in the simulation environment as well as the decision-making context. These two pieces of information are used to compute an estimate of the likelihood that the cyber attack can alter, destroy, or falsify each piece of information in a compromised ring. The unpredictability of information alteration in our approach adds greater realism to the cyber event. This paper suggests a new technique that can be used for cyber warfare simulation, the ring approach for modeling context-dependent information value, and our means for considering information value when assigning cyber resources to information protection tasks. The first section of the paper introduces the cyber warfare simulation challenge and the reasons for its importance. The second section contains background information related to our research. The third section contains a discussion of the information ring technique and its use for simulating cyber attacks. The fourth section contains a summary and suggestions for research.
NASA Astrophysics Data System (ADS)
Coughlin, J.; Mital, R.; Nittur, S.; SanNicolas, B.; Wolf, C.; Jusufi, R.
2016-09-01
Operational analytics when combined with Big Data technologies and predictive techniques have been shown to be valuable in detecting mission critical sensor anomalies that might be missed by conventional analytical techniques. Our approach helps analysts and leaders make informed and rapid decisions by analyzing large volumes of complex data in near real-time and presenting it in a manner that facilitates decision making. It provides cost savings by being able to alert and predict when sensor degradations pass a critical threshold and impact mission operations. Operational analytics, which uses Big Data tools and technologies, can process very large data sets containing a variety of data types to uncover hidden patterns, unknown correlations, and other relevant information. When combined with predictive techniques, it provides a mechanism to monitor and visualize these data sets and provide insight into degradations encountered in large sensor systems such as the space surveillance network. In this study, data from a notional sensor is simulated and we use big data technologies, predictive algorithms and operational analytics to process the data and predict sensor degradations. This study uses data products that would commonly be analyzed at a site. This study builds on a big data architecture that has previously been proven valuable in detecting anomalies. This paper outlines our methodology of implementing an operational analytic solution through data discovery, learning and training of data modeling and predictive techniques, and deployment. Through this methodology, we implement a functional architecture focused on exploring available big data sets and determine practical analytic, visualization, and predictive technologies.
ERIC Educational Resources Information Center
West, G. Page, III; Wilson, E. Vance
1995-01-01
Examines simulation in entrepreneurial research, reviews cognitive structures and theories, and presents a computerized simulation of strategic decision-making in situational stereotype conditions for entrepreneurial companies. The study suggests repeated exposure to a pattern recognition issue in entrepreneurship may lead to a broader…
Historical Development of Simulation Models of Recreation Use
Jan W. van Wagtendonk; David N. Cole
2005-01-01
The potential utility of modeling as a park and wilderness management tool has been recognized for decades. Romesburg (1974) explored how mathematical decision modeling could be used to improve decisions about regulation of wilderness use. Cesario (1975) described a computer simulation modeling approach that utilized GPSS (General Purpose Systems Simulator), a...
NASA Technical Reports Server (NTRS)
Johnson, Lee F.; Maneta, Marco P.; Kimball, John S.
2016-01-01
Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in a typical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight 'app' that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.
NASA Astrophysics Data System (ADS)
Maneta, M. P.; Johnson, L.; Kimball, J. S.
2016-12-01
Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in atypical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight `app` that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.
Cohen-Hatton, Sabrina R; Butler, Philip C; Honey, Robert C
2015-08-01
The aim of this study was to better understand the nature of decision making at operational incidents in order to inform operational guidance and training. Normative models of decision making have been adopted in the guidance and training for emergency services. In these models, it is assumed that decision makers assess the current situation, formulate plans, and then execute the plans. However, our understanding of how decision making unfolds at operational incidents remains limited. Incident commanders, attending 33 incidents across six U.K. Fire and Rescue Services, were fitted with helmet-mounted cameras, and the resulting video footage was later independently coded and used to prompt participants to provide a running commentary concerning their decisions. The analysis revealed that assessment of the operational situation was most often followed by plan execution rather than plan formulation, and there was little evidence of prospection about the potential consequences of actions. This pattern of results was consistent across different types of incident, characterized by level of risk and time pressure, but was affected by the operational experience of the participants. Decision making did not follow the sequence of phases assumed by normative models and conveyed in current operational guidance but instead was influenced by both reflective and reflexive processes. These results have clear implications for understanding operational decision making as it occurs in situ and suggest a need for future guidance and training to acknowledge the role of reflexive processes. © 2015, Human Factors and Ergonomics Society.
Application of Domain Knowledge to Software Quality Assurance
NASA Technical Reports Server (NTRS)
Wild, Christian W.
1997-01-01
This work focused on capturing, using, and evolving a qualitative decision support structure across the life cycle of a project. The particular application of this study was towards business process reengineering and the representation of the business process in a set of Business Rules (BR). In this work, we defined a decision model which captured the qualitative decision deliberation process. It represented arguments both for and against proposed alternatives to a problem. It was felt that the subjective nature of many critical business policy decisions required a qualitative modeling approach similar to that of Lee and Mylopoulos. While previous work was limited almost exclusively to the decision capture phase, which occurs early in the project life cycle, we investigated the use of such a model during the later stages as well. One of our significant developments was the use of the decision model during the operational phase of a project. By operational phase, we mean the phase in which the system or set of policies which were earlier decided are deployed and put into practice. By making the decision model available to operational decision makers, they would have access to the arguments pro and con for a variety of actions and can thus make a more informed decision which balances the often conflicting criteria by which the value of action is measured. We also developed the concept of a 'monitored decision' in which metrics of performance were identified during the decision making process and used to evaluate the quality of that decision. It is important to monitor those decision which seem at highest risk of not meeting their stated objectives. Operational decisions are also potentially high risk decisions. Finally, we investigated the use of performance metrics for monitored decisions and audit logs of operational decisions in order to feed an evolutionary phase of the the life cycle. During evolution, decisions are revisisted, assumptions verified or refuted, and possible reassessments resulting in new policy are made. In this regard we implemented a machine learning algorithm which automatically defined business rules based on expert assessment of the quality of operational decisions as recorded during deployment.
Integrating macro and micro scale approaches in the agent-based modeling of residential dynamics
NASA Astrophysics Data System (ADS)
Saeedi, Sara
2018-06-01
With the advancement of computational modeling and simulation (M&S) methods as well as data collection technologies, urban dynamics modeling substantially improved over the last several decades. The complex urban dynamics processes are most effectively modeled not at the macro-scale, but following a bottom-up approach, by simulating the decisions of individual entities, or residents. Agent-based modeling (ABM) provides the key to a dynamic M&S framework that is able to integrate socioeconomic with environmental models, and to operate at both micro and macro geographical scales. In this study, a multi-agent system is proposed to simulate residential dynamics by considering spatiotemporal land use changes. In the proposed ABM, macro-scale land use change prediction is modeled by Artificial Neural Network (ANN) and deployed as the agent environment and micro-scale residential dynamics behaviors autonomously implemented by household agents. These two levels of simulation interacted and jointly promoted urbanization process in an urban area of Tehran city in Iran. The model simulates the behavior of individual households in finding ideal locations to dwell. The household agents are divided into three main groups based on their income rank and they are further classified into different categories based on a number of attributes. These attributes determine the households' preferences for finding new dwellings and change with time. The ABM environment is represented by a land-use map in which the properties of the land parcels change dynamically over the simulation time. The outputs of this model are a set of maps showing the pattern of different groups of households in the city. These patterns can be used by city planners to find optimum locations for building new residential units or adding new services to the city. The simulation results show that combining macro- and micro-level simulation can give full play to the potential of the ABM to understand the driving mechanism of urbanization and provide decision-making support for urban management.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-08-16
... Garrison, Hawai`i, (USAG-HI) announce the decision to construct and operate a new Infantry Platoon Battle... decision allows the Army to construct and operate an IPBC that will meet Army training requirements and... with alternatives to construct and operate the IPBC. In the Final EIS published in the Federal Register...
Janice K. Wiedenbeck; Philip A. Araman
1995-01-01
We've been telling the wood industry about our process simulation modeling research and development work for several years. We've demonstrated our crosscut-first and rip-first rough mill simulation and animation models. Weâve advised companies on how they could use simulation modeling to help make critically important, pending decisions related to mill layout...
ERIC Educational Resources Information Center
Neely, Pat; Tucker, Jan
2013-01-01
Purpose: Simulations are designed as activities which imitate real world scenarios and are often used to teach and enhance skill building. The purpose of this case study is to examine the decision making process and outcomes of a faculty committee tasked with examining simulations in the marketplace to determine if the simulations could be used as…
Principal Candidates Create Decision-Making Simulations to Prepare for the JOB
ERIC Educational Resources Information Center
Staub, Nancy A.; Bravender, Marlena
2014-01-01
Online simulations offer opportunities for trial and error decision-making. What better tool for a principal than to make decisions when the consequences will not have real-world ramifications. In this study, two groups of graduate students in a principal preparation program taking the same course in the same semester use online simulations…
Decisions and Macroeconomics: Development and Implementation of a Simulation Game
ERIC Educational Resources Information Center
Woltjer, Geert B.
2005-01-01
For many students macroeconomics is very abstract; it is difficult for them to imagine that the theories are fundamentally about the coordination of human decisions. The author developed a simulation game called Steer the Economy that creates the possibility for students to make the decisions of the firms that are implicit in macroeconomic models.…
Simulation software: engineer processes before reengineering.
Lepley, C J
2001-01-01
People make decisions all the time using intuition. But what happens when you are asked: "Are you sure your predictions are accurate? How much will a mistake cost? What are the risks associated with this change?" Once a new process is engineered, it is difficult to analyze what would have been different if other options had been chosen. Simulating a process can help senior clinical officers solve complex patient flow problems and avoid wasted efforts. Simulation software can give you the data you need to make decisions. The author introduces concepts, methodologies, and applications of computer aided simulation to illustrate their use in making decisions to improve workflow design.
Constrained optimization via simulation models for new product innovation
NASA Astrophysics Data System (ADS)
Pujowidianto, Nugroho A.
2017-11-01
We consider the problem of constrained optimization where the decision makers aim to optimize the primary performance measure while constraining the secondary performance measures. This paper provides a brief overview of stochastically constrained optimization via discrete event simulation. Most review papers tend to be methodology-based. This review attempts to be problem-based as decision makers may have already decided on the problem formulation. We consider constrained optimization models as there are usually constraints on secondary performance measures as trade-off in new product development. It starts by laying out different possible methods and the reasons using constrained optimization via simulation models. It is then followed by the review of different simulation optimization approach to address constrained optimization depending on the number of decision variables, the type of constraints, and the risk preferences of the decision makers in handling uncertainties.
Maxson, Pamela M; Dozois, Eric J; Holubar, Stefan D; Wrobleski, Diane M; Dube, Joyce A Overman; Klipfel, Janee M; Arnold, Jacqueline J
2011-01-01
To determine whether interdisciplinary simulation team training can positively affect registered nurse and/or physician perceptions of collaboration in clinical decision making. Between March 1 and April 21, 2009, a convenience sample of volunteer nurses and physicians was recruited to undergo simulation training consisting of a team response to 3 clinical scenarios. Participants completed the Collaboration and Satisfaction About Care Decisions (CSACD) survey before training and at 2 weeks and 2 months after training. Differences in CSACD summary scores between the time points were assessed with paired t tests. Twenty-eight health care professionals (19 nurses, 9 physicians) underwent simulation training. Nurses were of similar age to physicians (27.3 vs 34.5 years; p = .82), were more likely to be women (95.0% vs 12.5%; p < .001), and were less likely to have undergone prior simulation training (0% vs 37.5%; p = .02). The pretest showed that physicians were more likely to perceive that open communication exists between nurses and physicians (p = .04) and that both medical and nursing concerns influence the decision-making process (p = .02). Pretest CSACD analysis revealed that most participants were dissatisfied with the decision-making process. The CSACD summary score showed significant improvement from baseline to 2 weeks (4.2 to 5.1; p < .002), a trend that persisted at 2 months (p < .002). Team training using high-fidelity simulation scenarios promoted collaboration between nurses and physicians and enhanced the patient care decision-making process.
Terminal weather information management
NASA Technical Reports Server (NTRS)
Lee, Alfred T.
1990-01-01
Since the mid-1960's, microburst/windshear events have caused at least 30 aircraft accidents and incidents and have killed more than 600 people in the United States alone. This study evaluated alternative means of alerting an airline crew to the presence of microburst/windshear events in the terminal area. Of particular interest was the relative effectiveness of conventional and data link ground-to-air transmissions of ground-based radar and low-level windshear sensing information on microburst/windshear avoidance. The Advanced Concepts Flight Simulator located at Ames Research Center was employed in a line oriented simulation of a scheduled round-trip airline flight from Salt Lake City to Denver Stapleton Airport. Actual weather en route and in the terminal area was simulated using recorded data. The microburst/windshear incident of July 11, 1988 was re-created for the Denver area operations. Six experienced airline crews currently flying scheduled routes were employed as test subjects for each of three groups: (1) A baseline group which received alerts via conventional air traffic control (ATC) tower transmissions; (2) An experimental group which received alerts/events displayed visually and aurally in the cockpit six miles (approx. 2 min.) from the microburst event; and (3) An additional experimental group received displayed alerts/events 23 linear miles (approx. 7 min.) from the microburst event. Analyses of crew communications and decision times showed a marked improvement in both situation awareness and decision-making with visually displayed ground-based radar information. Substantial reductions in the variability of decision times among crews in the visual display groups were also found. These findings suggest that crew performance will be enhanced and individual differences among crews due to differences in training and prior experience are significantly reduced by providing real-time, graphic display of terminal weather hazards.
Evidence-based Sensor Tasking for Space Domain Awareness
NASA Astrophysics Data System (ADS)
Jaunzemis, A.; Holzinger, M.; Jah, M.
2016-09-01
Space Domain Awareness (SDA) is the actionable knowledge required to predict, avoid, deter, operate through, recover from, and/or attribute cause to the loss and/or degradation of space capabilities and services. A main purpose for SDA is to provide decision-making processes with a quantifiable and timely body of evidence of behavior(s) attributable to specific space threats and/or hazards. To fulfill the promise of SDA, it is necessary for decision makers and analysts to pose specific hypotheses that may be supported or refuted by evidence, some of which may only be collected using sensor networks. While Bayesian inference may support some of these decision making needs, it does not adequately capture ambiguity in supporting evidence; i.e., it struggles to rigorously quantify 'known unknowns' for decision makers. Over the past 40 years, evidential reasoning approaches such as Dempster Shafer theory have been developed to address problems with ambiguous bodies of evidence. This paper applies mathematical theories of evidence using Dempster Shafer expert systems to address the following critical issues: 1) How decision makers can pose critical decision criteria as rigorous, testable hypotheses, 2) How to interrogate these hypotheses to reduce ambiguity, and 3) How to task a network of sensors to gather evidence for multiple competing hypotheses. This theory is tested using a simulated sensor tasking scenario balancing search versus track responsibilities.
A Global System for Transportation Simulation and Visualization in Emergency Evacuation Scenarios
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Wei; Liu, Cheng; Thomas, Neil
2015-01-01
Simulation-based studies are frequently used for evacuation planning and decision making processes. Given the transportation systems complexity and data availability, most evacuation simulation models focus on certain geographic areas. With routine improvement of OpenStreetMap road networks and LandScanTM global population distribution data, we present WWEE, a uniform system for world-wide emergency evacuation simulations. WWEE uses unified data structure for simulation inputs. It also integrates a super-node trip distribution model as the default simulation parameter to improve the system computational performance. Two levels of visualization tools are implemented for evacuation performance analysis, including link-based macroscopic visualization and vehicle-based microscopic visualization. Formore » left-hand and right-hand traffic patterns in different countries, the authors propose a mirror technique to experiment with both scenarios without significantly changing traffic simulation models. Ten cities in US, Europe, Middle East, and Asia are modeled for demonstration. With default traffic simulation models for fast and easy-to-use evacuation estimation and visualization, WWEE also retains the capability of interactive operation for users to adopt customized traffic simulation models. For the first time, WWEE provides a unified platform for global evacuation researchers to estimate and visualize their strategies performance of transportation systems under evacuation scenarios.« less
Design and Evaluation of Simulations for the Development of Complex Decision-Making Skills.
ERIC Educational Resources Information Center
Hartley, Roger; Varley, Glen
2002-01-01
Command and Control Training Using Simulation (CACTUS) is a computer digital mapping system used by police to manage large-scale public events. Audio and video records of adaptive training scenarios using CACTUS show how the simulation develops decision-making skills for strategic and tactical event management. (SK)
NASA Astrophysics Data System (ADS)
Al Hadhrami, Tawfik; Nightingale, James M.; Wang, Qi; Grecos, Christos
2014-05-01
In emergency situations, the ability to remotely monitor unfolding events using high-quality video feeds will significantly improve the incident commander's understanding of the situation and thereby aids effective decision making. This paper presents a novel, adaptive video monitoring system for emergency situations where the normal communications network infrastructure has been severely impaired or is no longer operational. The proposed scheme, operating over a rapidly deployable wireless mesh network, supports real-time video feeds between first responders, forward operating bases and primary command and control centers. Video feeds captured on portable devices carried by first responders and by static visual sensors are encoded in H.264/SVC, the scalable extension to H.264/AVC, allowing efficient, standard-based temporal, spatial, and quality scalability of the video. A three-tier video delivery system is proposed, which balances the need to avoid overuse of mesh nodes with the operational requirements of the emergency management team. In the first tier, the video feeds are delivered at a low spatial and temporal resolution employing only the base layer of the H.264/SVC video stream. Routing in this mode is designed to employ all nodes across the entire mesh network. In the second tier, whenever operational considerations require that commanders or operators focus on a particular video feed, a `fidelity control' mechanism at the monitoring station sends control messages to the routing and scheduling agents in the mesh network, which increase the quality of the received picture using SNR scalability while conserving bandwidth by maintaining a low frame rate. In this mode, routing decisions are based on reliable packet delivery with the most reliable routes being used to deliver the base and lower enhancement layers; as fidelity is increased and more scalable layers are transmitted they will be assigned to routes in descending order of reliability. The third tier of video delivery transmits a high-quality video stream including all available scalable layers using the most reliable routes through the mesh network ensuring the highest possible video quality. The proposed scheme is implemented in a proven simulator, and the performance of the proposed system is numerically evaluated through extensive simulations. We further present an in-depth analysis of the proposed solutions and potential approaches towards supporting high-quality visual communications in such a demanding context.
NASA Astrophysics Data System (ADS)
Sindiy, Oleg V.
This dissertation presents a model-based system-of-systems engineering (SoSE) approach as a design philosophy for architecting in system-of-systems (SoS) problems. SoS refers to a special class of systems in which numerous systems with operational and managerial independence interact to generate new capabilities that satisfy societal needs. Design decisions are more complicated in a SoS setting. A revised Process Model for SoSE is presented to support three phases in SoS architecting: defining the scope of the design problem, abstracting key descriptors and their interrelations in a conceptual model, and implementing computer-based simulations for architectural analyses. The Process Model enables improved decision support considering multiple SoS features and develops computational models capable of highlighting configurations of organizational, policy, financial, operational, and/or technical features. Further, processes for verification and validation of SoS models and simulations are also important due to potential impact on critical decision-making and, thus, are addressed. Two research questions frame the research efforts described in this dissertation. The first concerns how the four key sources of SoS complexity---heterogeneity of systems, connectivity structure, multi-layer interactions, and the evolutionary nature---influence the formulation of SoS models and simulations, trade space, and solution performance and structure evaluation metrics. The second question pertains to the implementation of SoSE architecting processes to inform decision-making for a subset of SoS problems concerning the design of information exchange services in space-based operations domain. These questions motivate and guide the dissertation's contributions. A formal methodology for drawing relationships within a multi-dimensional trade space, forming simulation case studies from applications of candidate architecture solutions to a campaign of notional mission use cases, and executing multi-purpose analysis studies is presented. These efforts are coupled to the generation of aggregate and time-dependent solution performance metrics via the hierarchical decomposition of objectives and the analytical recomposition of multi-attribute qualitative program drivers from quantifiable measures. This methodology was also applied to generate problem-specific solution structure evaluation metrics that facilitate the comparison of alternate solutions at a high level of aggregation, at lower levels of abstraction, and to relate options for design variables with associated performance values. For proof-of-capability demonstration, the selected application problem concerns the design of command, control, communication, and information (C3I) architecture services for a notional campaign of crewed and robotic lunar surface missions. The impetus for the work was the demonstration of using model-based SoSE for design of sustainable interoperability capabilities between all data and communication assets in extended lunar campaigns. A comprehensive Lunar C3I simulation tool was developed by a team of researchers at Purdue University in support of NASA's Constellation Program; the author of this dissertation was a key contributor to the creation of this tool and made modifications and extensions to key components relevant to the methodological concepts presented in this dissertation. The dissertation concludes with a presentation of example results based on the interrogation of the constructed Lunar C3I computational model. The results are based on a family of studies, structured around a trade-tree of architecture options, which were conducted to test the hypothesis that the SoSE approach is efficacious in the information-exchange architecture design in space exploration domain. Included in the family of proof-of-capability studies is a simulation of the Apollo 17 mission, which allows not only for partial verification and validation of the model, but also provides insights for prioritizing future model design iterations to make it more realistic representation of the "real world." A caveat within the results presented is that they serve within the capacity of a proof-of-capability demonstration, and as such, they are a product of models and analyses that need further development before the tool's results can be employed for decision-making. Additional discussion is provided for how to further develop and validate the Lunar C3I tool and also to make it extensible to other SoS design problems of similar nature in space exploration and other problem application domains.
Incorporation of RAM techniques into simulation modeling
NASA Astrophysics Data System (ADS)
Nelson, S. C., Jr.; Haire, M. J.; Schryver, J. C.
1995-01-01
This work concludes that reliability, availability, and maintainability (RAM) analytical techniques can be incorporated into computer network simulation modeling to yield an important new analytical tool. This paper describes the incorporation of failure and repair information into network simulation to build a stochastic computer model to represent the RAM Performance of two vehicles being developed for the US Army: The Advanced Field Artillery System (AFAS) and the Future Armored Resupply Vehicle (FARV). The AFAS is the US Army's next generation self-propelled cannon artillery system. The FARV is a resupply vehicle for the AFAS. Both vehicles utilize automation technologies to improve the operational performance of the vehicles and reduce manpower. The network simulation model used in this work is task based. The model programmed in this application requirements a typical battle mission and the failures and repairs that occur during that battle. Each task that the FARV performs--upload, travel to the AFAS, refuel, perform tactical/survivability moves, return to logistic resupply, etc.--is modeled. Such a model reproduces a model reproduces operational phenomena (e.g., failures and repairs) that are likely to occur in actual performance. Simulation tasks are modeled as discrete chronological steps; after the completion of each task decisions are programmed that determine the next path to be followed. The result is a complex logic diagram or network. The network simulation model is developed within a hierarchy of vehicle systems, subsystems, and equipment and includes failure management subnetworks. RAM information and other performance measures are collected which have impact on design requirements. Design changes are evaluated through 'what if' questions, sensitivity studies, and battle scenario changes.
Two-Graph Building Interior Representation for Emergency Response Applications
NASA Astrophysics Data System (ADS)
Boguslawski, P.; Mahdjoubi, L.; Zverovich, V.; Fadli, F.
2016-06-01
Nowadays, in a rapidly developing urban environment with bigger and higher public buildings, disasters causing emergency situations and casualties are unavoidable. Preparedness and quick response are crucial issues saving human lives. Available information about an emergency scene, such as a building structure, helps for decision making and organizing rescue operations. Models supporting decision-making should be available in real, or near-real, time. Thus, good quality models that allow implementation of automated methods are highly desirable. This paper presents details of the recently developed method for automated generation of variable density navigable networks in a 3D indoor environment, including a full 3D topological model, which may be used not only for standard navigation but also for finding safe routes and simulating hazard and phenomena associated with disasters such as fire spread and heat transfer.
Implementation Of Fuzzy Automated Brake Controller Using TSK Algorithm
NASA Astrophysics Data System (ADS)
Mittal, Ruchi; Kaur, Magandeep
2010-11-01
In this paper an application of Fuzzy Logic for Automatic Braking system is proposed. Anti-blocking system (ABS) brake controllers pose unique challenges to the designer: a) For optimal performance, the controller must operate at an unstable equilibrium point, b) Depending on road conditions, the maximum braking torque may vary over a wide range, c) The tire slippage measurement signal, crucial for controller performance, is both highly uncertain and noisy. A digital controller design was chosen which combines a fuzzy logic element and a decision logic network. The controller identifies the current road condition and generates a command braking pressure signal Depending upon the speed and distance of train. This paper describes design criteria, and the decision and rule structure of the control system. The simulation results present the system's performance depending upon the varying speed and distance of the train.
Optimal use of human and machine resources for Space Station assembly operations
NASA Technical Reports Server (NTRS)
Parrish, Joseph C.
1988-01-01
This paper investigates the issues involved in determining the best mix of human and machine resources for assembly of the Space Station. It presents the current Station assembly sequence, along with descriptions of the available assembly resources. A number of methodologies for optimizing the human/machine tradeoff problem have been developed, but the Space Station assembly offers some unique issues that have not yet been addressed. These include a strong constraint on available EVA time for early flights and a phased deployment of assembly resources over time. A methodology for incorporating the previously developed decision methods to the special case of the Space Station is presented. This methodology emphasizes an application of multiple qualitative and quantitative techniques, including simulation and decision analysis, for producing an objective, robust solution to the tradeoff problem.
Data mining for multiagent rules, strategies, and fuzzy decision tree structure
NASA Astrophysics Data System (ADS)
Smith, James F., III; Rhyne, Robert D., II; Fisher, Kristin
2002-03-01
A fuzzy logic based resource manager (RM) has been developed that automatically allocates electronic attack resources in real-time over many dissimilar platforms. Two different data mining algorithms have been developed to determine rules, strategies, and fuzzy decision tree structure. The first data mining algorithm uses a genetic algorithm as a data mining function and is called from an electronic game. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge. It calls a data mining function, a genetic algorithm, for data mining of the database as required and allows easy evaluation of the information mined in the second step. The criterion for re- optimization is discussed as well as experimental results. Then a second data mining algorithm that uses a genetic program as a data mining function is introduced to automatically discover fuzzy decision tree structures. Finally, a fuzzy decision tree generated through this process is discussed.
Yin, Kedong; Yang, Benshuo; Li, Xuemei
2018-01-24
In this paper, we investigate multiple attribute group decision making (MAGDM) problems where decision makers represent their evaluation of alternatives by trapezoidal fuzzy two-dimensional uncertain linguistic variable. To begin with, we introduce the definition, properties, expectation, operational laws of trapezoidal fuzzy two-dimensional linguistic information. Then, to improve the accuracy of decision making in some case where there are a sort of interrelationship among the attributes, we analyze partition Bonferroni mean (PBM) operator in trapezoidal fuzzy two-dimensional variable environment and develop two operators: trapezoidal fuzzy two-dimensional linguistic partitioned Bonferroni mean (TF2DLPBM) aggregation operator and trapezoidal fuzzy two-dimensional linguistic weighted partitioned Bonferroni mean (TF2DLWPBM) aggregation operator. Furthermore, we develop a novel method to solve MAGDM problems based on TF2DLWPBM aggregation operator. Finally, a practical example is presented to illustrate the effectiveness of this method and analyses the impact of different parameters on the results of decision-making.
Yin, Kedong; Yang, Benshuo
2018-01-01
In this paper, we investigate multiple attribute group decision making (MAGDM) problems where decision makers represent their evaluation of alternatives by trapezoidal fuzzy two-dimensional uncertain linguistic variable. To begin with, we introduce the definition, properties, expectation, operational laws of trapezoidal fuzzy two-dimensional linguistic information. Then, to improve the accuracy of decision making in some case where there are a sort of interrelationship among the attributes, we analyze partition Bonferroni mean (PBM) operator in trapezoidal fuzzy two-dimensional variable environment and develop two operators: trapezoidal fuzzy two-dimensional linguistic partitioned Bonferroni mean (TF2DLPBM) aggregation operator and trapezoidal fuzzy two-dimensional linguistic weighted partitioned Bonferroni mean (TF2DLWPBM) aggregation operator. Furthermore, we develop a novel method to solve MAGDM problems based on TF2DLWPBM aggregation operator. Finally, a practical example is presented to illustrate the effectiveness of this method and analyses the impact of different parameters on the results of decision-making. PMID:29364849
The influence of learning and updating speed on the growth of commercial websites
NASA Astrophysics Data System (ADS)
Wan, Xiaoji; Deng, Guishi; Bai, Yang; Xue, Shaowei
2012-08-01
In this paper, we study the competition model of commercial websites with learning and updating speed, and further analyze the influence of learning and updating speed on the growth of commercial websites from a nonlinear dynamics perspective. Using the center manifold theory and the normal form method, we give the explicit formulas determining the stability and periodic fluctuation of commercial sites. Numerical simulations reveal that sites periodically fluctuate as the speed of learning and updating crosses one threshold. The study provides reference and evidence for website operators to make decisions.
Group-sequential three-arm noninferiority clinical trial designs
Ochiai, Toshimitsu; Hamasaki, Toshimitsu; Evans, Scott R.; Asakura, Koko; Ohno, Yuko
2016-01-01
We discuss group-sequential three-arm noninferiority clinical trial designs that include active and placebo controls for evaluating both assay sensitivity and noninferiority. We extend two existing approaches, the fixed margin and fraction approaches, into a group-sequential setting with two decision-making frameworks. We investigate the operating characteristics including power, Type I error rate, maximum and expected sample sizes, as design factors vary. In addition, we discuss sample size recalculation and its’ impact on the power and Type I error rate via a simulation study. PMID:26892481
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sanfilippo, Antonio P.; Riensche, Roderick M.; Haack, Jereme N.
“Gamification”, the application of gameplay to real-world problems, enables the development of human computation systems that support decision-making through the integration of social and machine intelligence. One of gamification’s major benefits includes the creation of a problem solving environment where the influence of cognitive and cultural biases on human judgment can be curtailed through collaborative and competitive reasoning. By reducing biases on human judgment, gamification allows human computation systems to exploit human creativity relatively unhindered by human error. Operationally, gamification uses simulation to harvest human behavioral data that provide valuable insights for the solution of real-world problems.
Optimal strategies for electric energy contract decision making
NASA Astrophysics Data System (ADS)
Song, Haili
2000-10-01
The power industry restructuring in various countries in recent years has created an environment where trading of electric energy is conducted in a market environment. In such an environment, electric power companies compete for the market share through spot and bilateral markets. Being profit driven, electric power companies need to make decisions on spot market bidding, contract evaluation, and risk management. New methods and software tools are required to meet these upcoming needs. In this research, bidding strategy and contract pricing are studied from a market participant's viewpoint; new methods are developed to guide a market participant in spot and bilateral market operation. A supplier's spot market bidding decision is studied. Stochastic optimization is formulated to calculate a supplier's optimal bids in a single time period. This decision making problem is also formulated as a Markov Decision Process. All the competitors are represented by their bidding parameters with corresponding probabilities. A systematic method is developed to calculate transition probabilities and rewards. The optimal strategy is calculated to maximize the expected reward over a planning horizon. Besides the spot market, a power producer can also trade in the bilateral markets. Bidding strategies in a bilateral market are studied with game theory techniques. Necessary and sufficient conditions of Nash Equilibrium (NE) bidding strategy are derived based on the generators' cost and the loads' willingness to pay. The study shows that in any NE, market efficiency is achieved. Furthermore, all Nash equilibria are revenue equivalent for the generators. The pricing of "Flexible" contracts, which allow delivery flexibility over a period of time with a fixed total amount of electricity to be delivered, is analyzed based on the no-arbitrage pricing principle. The proposed algorithm calculates the price based on the optimality condition of the stochastic optimization formulation. Simulation examples illustrate the tradeoffs between prices and scheduling flexibility. Spot bidding and contract pricing are not independent decision processes. The interaction between spot bidding and contract evaluation is demonstrated with game theory equilibrium model and market simulation results. It leads to the conclusion that a market participant's contract decision making needs to be further investigated as an integrated optimization formulation.
NASA Astrophysics Data System (ADS)
Şahin, Rıdvan; Zhang, Hong-yu
2018-03-01
Induced Choquet integral is a powerful tool to deal with imprecise or uncertain nature. This study proposes a combination process of the induced Choquet integral and neutrosophic information. We first give the operational properties of simplified neutrosophic numbers (SNNs). Then, we develop some new information aggregation operators, including an induced simplified neutrosophic correlated averaging (I-SNCA) operator and an induced simplified neutrosophic correlated geometric (I-SNCG) operator. These operators not only consider the importance of elements or their ordered positions, but also take into account the interactions phenomena among decision criteria or their ordered positions under multiple decision-makers. Moreover, we present a detailed analysis of I-SNCA and I-SNCG operators, including the properties of idempotency, commutativity and monotonicity, and study the relationships among the proposed operators and existing simplified neutrosophic aggregation operators. In order to handle the multi-criteria group decision-making (MCGDM) situations where the weights of criteria and decision-makers usually correlative and the criterion values are considered as SNNs, an approach is established based on I-SNCA operator. Finally, a numerical example is presented to demonstrate the proposed approach and to verify its effectiveness and practicality.
Toolbox for Urban Mobility Simulation: High Resolution Population Dynamics for Global Cities
NASA Astrophysics Data System (ADS)
Bhaduri, B. L.; Lu, W.; Liu, C.; Thakur, G.; Karthik, R.
2015-12-01
In this rapidly urbanizing world, unprecedented rate of population growth is not only mirrored by increasing demand for energy, food, water, and other natural resources, but has detrimental impacts on environmental and human security. Transportation simulations are frequently used for mobility assessment in urban planning, traffic operation, and emergency management. Previous research, involving purely analytical techniques to simulations capturing behavior, has investigated questions and scenarios regarding the relationships among energy, emissions, air quality, and transportation. Primary limitations of past attempts have been availability of input data, useful "energy and behavior focused" models, validation data, and adequate computational capability that allows adequate understanding of the interdependencies of our transportation system. With increasing availability and quality of traditional and crowdsourced data, we have utilized the OpenStreetMap roads network, and has integrated high resolution population data with traffic simulation to create a Toolbox for Urban Mobility Simulations (TUMS) at global scale. TUMS consists of three major components: data processing, traffic simulation models, and Internet-based visualizations. It integrates OpenStreetMap, LandScanTM population, and other open data (Census Transportation Planning Products, National household Travel Survey, etc.) to generate both normal traffic operation and emergency evacuation scenarios. TUMS integrates TRANSIMS and MITSIM as traffic simulation engines, which are open-source and widely-accepted for scalable traffic simulations. Consistent data and simulation platform allows quick adaption to various geographic areas that has been demonstrated for multiple cities across the world. We are combining the strengths of geospatial data sciences, high performance simulations, transportation planning, and emissions, vehicle and energy technology development to design and develop a simulation framework to assist decision makers at all levels - local, state, regional, and federal. Using Cleveland, Tennessee as an example, in this presentation, we illustrate how emerging cities could easily assess future land use scenario driven impacts on energy and environment utilizing such a capability.
NASA Astrophysics Data System (ADS)
Macian-Sorribes, Hector; Pulido-Velazquez, Manuel
2016-04-01
This contribution presents a methodology for defining optimal seasonal operating rules in multireservoir systems coupling expert criteria and stochastic optimization. Both sources of information are combined using fuzzy logic. The structure of the operating rules is defined based on expert criteria, via a joint expert-technician framework consisting in a series of meetings, workshops and surveys carried out between reservoir managers and modelers. As a result, the decision-making process used by managers can be assessed and expressed using fuzzy logic: fuzzy rule-based systems are employed to represent the operating rules and fuzzy regression procedures are used for forecasting future inflows. Once done that, a stochastic optimization algorithm can be used to define optimal decisions and transform them into fuzzy rules. Finally, the optimal fuzzy rules and the inflow prediction scheme are combined into a Decision Support System for making seasonal forecasts and simulate the effect of different alternatives in response to the initial system state and the foreseen inflows. The approach presented has been applied to the Jucar River Basin (Spain). Reservoir managers explained how the system is operated, taking into account the reservoirs' states at the beginning of the irrigation season and the inflows previewed during that season. According to the information given by them, the Jucar River Basin operating policies were expressed via two fuzzy rule-based (FRB) systems that estimate the amount of water to be allocated to the users and how the reservoir storages should be balanced to guarantee those deliveries. A stochastic optimization model using Stochastic Dual Dynamic Programming (SDDP) was developed to define optimal decisions, which are transformed into optimal operating rules embedding them into the two FRBs previously created. As a benchmark, historical records are used to develop alternative operating rules. A fuzzy linear regression procedure was employed to foresee future inflows depending on present and past hydrological and meteorological variables actually used by the reservoir managers to define likely inflow scenarios. A Decision Support System (DSS) was created coupling the FRB systems and the inflow prediction scheme in order to give the user a set of possible optimal releases in response to the reservoir states at the beginning of the irrigation season and the fuzzy inflow projections made using hydrological and meteorological information. The results show that the optimal DSS created using the FRB operating policies are able to increase the amount of water allocated to the users in 20 to 50 Mm3 per irrigation season with respect to the current policies. Consequently, the mechanism used to define optimal operating rules and transform them into a DSS is able to increase the water deliveries in the Jucar River Basin, combining expert criteria and optimization algorithms in an efficient way. This study has been partially supported by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) and FEDER funds. It also has received funding from the European Union's Horizon 2020 research and innovation programme under the IMPREX project (grant agreement no: 641.811).
Exploring the Learning from an Enterprise Simulation.
ERIC Educational Resources Information Center
Sawyer, John E.; Gopinath, C.
1999-01-01
A computer simulation used in teams by 151 business students tested their ability to translate strategy into decisions. Over eight weeks, the experiential learning activity encouraged strategic decision making and group behavior consistent with long-term strategy. (SK)
NASA Astrophysics Data System (ADS)
Trindade, B. C.; Reed, P. M.
2017-12-01
The growing access and reduced cost for computing power in recent years has promoted rapid development and application of multi-objective water supply portfolio planning. As this trend continues there is a pressing need for flexible risk-based simulation frameworks and improved algorithm benchmarking for emerging classes of water supply planning and management problems. This work contributes the Water Utilities Management and Planning (WUMP) model: a generalizable and open source simulation framework designed to capture how water utilities can minimize operational and financial risks by regionally coordinating planning and management choices, i.e. making more efficient and coordinated use of restrictions, water transfers and financial hedging combined with possible construction of new infrastructure. We introduce the WUMP simulation framework as part of a new multi-objective benchmark problem for planning and management of regionally integrated water utility companies. In this problem, a group of fictitious water utilities seek to balance the use of the mentioned reliability driven actions (e.g., restrictions, water transfers and infrastructure pathways) and their inherent financial risks. Several traits of this problem make it ideal for a benchmark problem, namely the presence of (1) strong non-linearities and discontinuities in the Pareto front caused by the step-wise nature of the decision making formulation and by the abrupt addition of storage through infrastructure construction, (2) noise due to the stochastic nature of the streamflows and water demands, and (3) non-separability resulting from the cooperative formulation of the problem, in which decisions made by stakeholder may substantially impact others. Both the open source WUMP simulation framework and its demonstration in a challenging benchmarking example hold value for promoting broader advances in urban water supply portfolio planning for regions confronting change.
Systematic review of skills transfer after surgical simulation-based training.
Dawe, S R; Pena, G N; Windsor, J A; Broeders, J A J L; Cregan, P C; Hewett, P J; Maddern, G J
2014-08-01
Simulation-based training assumes that skills are directly transferable to the patient-based setting, but few studies have correlated simulated performance with surgical performance. A systematic search strategy was undertaken to find studies published since the last systematic review, published in 2007. Inclusion of articles was determined using a predetermined protocol, independent assessment by two reviewers and a final consensus decision. Studies that reported on the use of surgical simulation-based training and assessed the transferability of the acquired skills to a patient-based setting were included. Twenty-seven randomized clinical trials and seven non-randomized comparative studies were included. Fourteen studies investigated laparoscopic procedures, 13 endoscopic procedures and seven other procedures. These studies provided strong evidence that participants who reached proficiency in simulation-based training performed better in the patient-based setting than their counterparts who did not have simulation-based training. Simulation-based training was equally as effective as patient-based training for colonoscopy, laparoscopic camera navigation and endoscopic sinus surgery in the patient-based setting. These studies strengthen the evidence that simulation-based training, as part of a structured programme and incorporating predetermined proficiency levels, results in skills transfer to the operative setting. © 2014 BJS Society Ltd. Published by John Wiley & Sons Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Flory, John Andrew; Padilla, Denise D.; Gauthier, John H.
Upcoming weapon programs require an aggressive increase in Application Specific Integrated Circuit (ASIC) production at Sandia National Laboratories (SNL). SNL has developed unique modeling and optimization tools that have been instrumental in improving ASIC production productivity and efficiency, identifying optimal operational and tactical execution plans under resource constraints, and providing confidence in successful mission execution. With ten products and unprecedented levels of demand, a single set of shared resources, highly variable processes, and the need for external supplier task synchronization, scheduling is an integral part of successful manufacturing. The scheduler uses an iterative multi-objective genetic algorithm and a multi-dimensional performancemore » evaluator. Schedule feasibility is assessed using a discrete event simulation (DES) that incorporates operational uncertainty, variability, and resource availability. The tools provide rapid scenario assessments and responses to variances in the operational environment, and have been used to inform major equipment investments and workforce planning decisions in multiple SNL facilities.« less
Secure Remote Access Issues in a Control Center Environment
NASA Technical Reports Server (NTRS)
Pitts, Lee; McNair, Ann R. (Technical Monitor)
2002-01-01
The ISS finally reached an operational state and exists for local and remote users. Onboard payload systems are managed by the Huntsville Operations Support Center (HOSC). Users access HOSC systems by internet protocols in support of daily operations, preflight simulation, and test. In support of this diverse user community, a modem security architecture has been implemented. The architecture has evolved over time from an isolated but open system to a system which supports local and remote access to the ISS over broad geographic regions. This has been accomplished through the use of an evolved security strategy, PKI, and custom design. Through this paper, descriptions of the migration process and the lessons learned are presented. This will include product decision criteria, rationale, and the use of commodity products in the end architecture. This paper will also stress the need for interoperability of various products and the effects of seemingly insignificant details.
Secure Payload Access to the International Space Station
NASA Technical Reports Server (NTRS)
Pitts, R. Lee; Reid, Chris
2002-01-01
The ISS finally reached an operational state and exists for local and remote users. Onboard payload systems are managed by the Huntsville Operations Support Center (HOSC). Users access HOSC systems by internet protocols in support of daily operations, preflight simulation, and test. In support of this diverse user community, a modem security architecture has been implemented. The architecture has evolved over time from an isolated but open system to a system which supports local and remote access to the ISS over broad geographic regions. This has been accomplished through the use of an evolved security strategy, PKI, and custom design. Through this paper, descriptions of the migration process and the lessons learned are presented. This will include product decision criteria, rationale, and the use of commodity products in the end architecture. This paper will also stress the need for interoperability of various products and the effects of seemingly insignificant details.
Modeling and Simulation of Bus Dispatching Policy for Timed Transfers on Signalized Networks
NASA Astrophysics Data System (ADS)
Cho, Hsun-Jung; Lin, Guey-Shii
2007-12-01
The major work of this study is to formulate the system cost functions and to integrate the bus dispatching policy with signal control. The integrated model mainly includes the flow dispersion model for links, signal control model for nodes, and dispatching control model for transfer terminals. All such models are inter-related for transfer operations in one-center transit network. The integrated model that combines dispatching policies with flexible signal control modes can be applied to assess the effectiveness of transfer operations. It is found that, if bus arrival information is reliable, an early dispatching decision made at the mean bus arrival times is preferable. The costs for coordinated operations with slack times are relatively low at the optimal common headway when applying adaptive route control. Based on such findings, a threshold function of bus headway for justifying an adaptive signal route control under various time values of auto drivers is developed.
How can surgeons facilitate resident intraoperative decision-making?
Hill, Katherine A; Dasari, Mohini; Littleton, Eliza B; Hamad, Giselle G
2017-10-01
Cognitive skills such as decision-making are critical to developing operative autonomy. We explored resident decision-making using a recollection of specific examples, from the attending surgeon and resident, after laparoscopic cholecystectomy. In a separate semi-structured interview, the attending and resident both answered five questions, regarding the resident's operative roles and decisions, ways the attending helped, times when the attending operated, and the effect of the relationship between attending and resident. Themes were extracted using inductive methods. Thirty interviews were completed after 15 cases. Facilitators of decision-making included dialogue, safe struggle, and appreciation for retraction. Aberrant case characteristics, anatomic uncertainties, and time pressures provided barriers. Attending-resident mismatches included descriptions of transitioning control to the attending. Reciprocal dialogue, including concept-driven feedback, is helpful during intraoperative teaching. Unanticipated findings impede resident decision-making, and we describe differences in understanding transfers of operative control. Given these factors, we suggest that pre-operative discussions may be beneficial. Copyright © 2017 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Liu, Peide; Qin, Xiyou
2017-11-01
Linguistic intuitionistic fuzzy number (LIFN) is a special intuitionistic fuzzy number which can more easily describe the vagueness existing in the real decision-making. Maclaurin symmetric mean (MSM) operator has the characteristic of considering the interrelationships among any number of input parameters. In this paper, we extended the MSM operator to the LIFNs and some extended MSM operators for LIFNs were proposed, some new decision-making methods were developed. Firstly, we introduced the definition, score function, properties and operational rules of the LIFNs. Then, we proposed some linguistic intuitionistic fuzzy MSM operators, such as linguistic intuitionistic fuzzy Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy Maclaurin symmetric mean (WLIFMSM) operator, linguistic intuitionistic fuzzy dual Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy dual Maclaurin symmetric mean (WLIFDMSM) operator. In the meantime, we studied some important properties of these operators, and developed some methods based on WLIFMSM operator and WLIFDMSM operator for multi-attribute decision-making. Finally, we use an example to demonstrate the effectiveness of the proposed methods.
Bruen, Catherine; Kreiter, Clarence; Wade, Vincent; Pawlikowska, Teresa
2017-01-01
Experience with simulated patients supports undergraduate learning of medical consultation skills. Adaptive simulations are being introduced into this environment. The authors investigate whether it can underpin valid and reliable assessment by conducting a generalizability analysis using IT data analytics from the interaction of medical students (in psychiatry) with adaptive simulations to explore the feasibility of adaptive simulations for supporting automated learning and assessment. The generalizability (G) study was focused on two clinically relevant variables: clinical decision points and communication skills. While the G study on the communication skills score yielded low levels of true score variance, the results produced by the decision points, indicating clinical decision-making and confirming user knowledge of the process of the Calgary-Cambridge model of consultation, produced reliability levels similar to what might be expected with rater-based scoring. The findings indicate that adaptive simulations have potential as a teaching and assessment tool for medical consultations.
Maxson, Pamela M.; Dozois, Eric J.; Holubar, Stefan D.; Wrobleski, Diane M.; Dube, Joyce A. Overman; Klipfel, Janee M.; Arnold, Jacqueline J.
2011-01-01
OBJECTIVE: To determine whether interdisciplinary simulation team training can positively affect registered nurse and/or physician perceptions of collaboration in clinical decision making. PARTICIPANTS AND METHODS: Between March 1 and April 21, 2009, a convenience sample of volunteer nurses and physicians was recruited to undergo simulation training consisting of a team response to 3 clinical scenarios. Participants completed the Collaboration and Satisfaction About Care Decisions (CSACD) survey before training and at 2 weeks and 2 months after training. Differences in CSACD summary scores between the time points were assessed with paired t tests. RESULTS: Twenty-eight health care professionals (19 nurses, 9 physicians) underwent simulation training. Nurses were of similar age to physicians (27.3 vs 34.5 years; p=.82), were more likely to be women (95.0% vs 12.5%; p<.001), and were less likely to have undergone prior simulation training (0% vs 37.5%; p=.02). The pretest showed that physicians were more likely to perceive that open communication exists between nurses and physicians (p=.04) and that both medical and nursing concerns influence the decision-making process (p=.02). Pretest CSACD analysis revealed that most participants were dissatisfied with the decision-making process. The CSACD summary score showed significant improvement from baseline to 2 weeks (4.2 to 5.1; p<.002), a trend that persisted at 2 months (p<.002). CONCLUSION: Team training using high-fidelity simulation scenarios promoted collaboration between nurses and physicians and enhanced the patient care decision-making process. PMID:21193653
Soós, Reka; Whiteman, Andrew D; Wilson, David C; Briciu, Cosmin; Nürnberger, Sofia; Oelz, Barbara; Gunsilius, Ellen; Schwehn, Ekkehard
2017-08-01
This is the second of two papers reporting the results of a major study considering 'operator models' for municipal solid waste management (MSWM) in emerging and developing countries. Part A documents the evidence base, while Part B presents a four-step decision support system for selecting an appropriate operator model in a particular local situation. Step 1 focuses on understanding local problems and framework conditions; Step 2 on formulating and prioritising local objectives; and Step 3 on assessing capacities and conditions, and thus identifying strengths and weaknesses, which underpin selection of the operator model. Step 4A addresses three generic questions, including public versus private operation, inter-municipal co-operation and integration of services. For steps 1-4A, checklists have been developed as decision support tools. Step 4B helps choose locally appropriate models from an evidence-based set of 42 common operator models ( coms); decision support tools here are a detailed catalogue of the coms, setting out advantages and disadvantages of each, and a decision-making flowchart. The decision-making process is iterative, repeating steps 2-4 as required. The advantages of a more formal process include avoiding pre-selection of a particular com known to and favoured by one decision maker, and also its assistance in identifying the possible weaknesses and aspects to consider in the selection and design of operator models. To make the best of whichever operator models are selected, key issues which need to be addressed include the capacity of the public authority as 'client', management in general and financial management in particular.
Human and Robotic Mission to Small Bodies: Mapping, Planning and Exploration
NASA Technical Reports Server (NTRS)
Neffian, Ara V.; Bellerose, Julie; Beyer, Ross A.; Archinal, Brent; Edwards, Laurence; Lee, Pascal; Colaprete, Anthony; Fong, Terry
2013-01-01
This study investigates the requirements, performs a gap analysis and makes a set of recommendations for mapping products and exploration tools required to support operations and scientific discovery for near- term and future NASA missions to small bodies. The mapping products and their requirements are based on the analysis of current mission scenarios (rendezvous, docking, and sample return) and recommendations made by the NEA Users Team (NUT) in the framework of human exploration. The mapping products that sat- isfy operational, scienti c, and public outreach goals include topography, images, albedo, gravity, mass, density, subsurface radar, mineralogical and thermal maps. The gap analysis points to a need for incremental generation of mapping products from low (flyby) to high-resolution data needed for anchoring and docking, real-time spatial data processing for hazard avoidance and astronaut or robot localization in low gravity, high dynamic environments, and motivates a standard for coordinate reference systems capable of describing irregular body shapes. Another aspect investigated in this study is the set of requirements and the gap analysis for exploration tools that support visualization and simulation of operational conditions including soil interactions, environment dynamics, and communications coverage. Building robust, usable data sets and visualisation/simulation tools is the best way for mission designers and simulators to make correct decisions for future missions. In the near term, it is the most useful way to begin building capabilities for small body exploration without needing to commit to specific mission architectures.
Jahn, Beate; Theurl, Engelbert; Siebert, Uwe; Pfeiffer, Karl-Peter
2010-01-01
In most decision-analytic models in health care, it is assumed that there is treatment without delay and availability of all required resources. Therefore, waiting times caused by limited resources and their impact on treatment effects and costs often remain unconsidered. Queuing theory enables mathematical analysis and the derivation of several performance measures of queuing systems. Nevertheless, an analytical approach with closed formulas is not always possible. Therefore, simulation techniques are used to evaluate systems that include queuing or waiting, for example, discrete event simulation. To include queuing in decision-analytic models requires a basic knowledge of queuing theory and of the underlying interrelationships. This tutorial introduces queuing theory. Analysts and decision-makers get an understanding of queue characteristics, modeling features, and its strength. Conceptual issues are covered, but the emphasis is on practical issues like modeling the arrival of patients. The treatment of coronary artery disease with percutaneous coronary intervention including stent placement serves as an illustrative queuing example. Discrete event simulation is applied to explicitly model resource capacities, to incorporate waiting lines and queues in the decision-analytic modeling example.
Deduction of reservoir operating rules for application in global hydrological models
NASA Astrophysics Data System (ADS)
Coerver, Hubertus M.; Rutten, Martine M.; van de Giesen, Nick C.
2018-01-01
A big challenge in constructing global hydrological models is the inclusion of anthropogenic impacts on the water cycle, such as caused by dams. Dam operators make decisions based on experience and often uncertain information. In this study information generally available to dam operators, like inflow into the reservoir and storage levels, was used to derive fuzzy rules describing the way a reservoir is operated. Using an artificial neural network capable of mimicking fuzzy logic, called the ANFIS adaptive-network-based fuzzy inference system, fuzzy rules linking inflow and storage with reservoir release were determined for 11 reservoirs in central Asia, the US and Vietnam. By varying the input variables of the neural network, different configurations of fuzzy rules were created and tested. It was found that the release from relatively large reservoirs was significantly dependent on information concerning recent storage levels, while release from smaller reservoirs was more dependent on reservoir inflows. Subsequently, the derived rules were used to simulate reservoir release with an average Nash-Sutcliffe coefficient of 0.81.
NASA Astrophysics Data System (ADS)
Jeuland, Marc; Whittington, Dale
2014-03-01
This article presents a methodology for planning new water resources infrastructure investments and operating strategies in a world of climate change uncertainty. It combines a real options (e.g., options to defer, expand, contract, abandon, switch use, or otherwise alter a capital investment) approach with principles drawn from robust decision-making (RDM). RDM comprises a class of methods that are used to identify investment strategies that perform relatively well, compared to the alternatives, across a wide range of plausible future scenarios. Our proposed framework relies on a simulation model that includes linkages between climate change and system hydrology, combined with sensitivity analyses that explore how economic outcomes of investments in new dams vary with forecasts of changing runoff and other uncertainties. To demonstrate the framework, we consider the case of new multipurpose dams along the Blue Nile in Ethiopia. We model flexibility in design and operating decisions—the selection, sizing, and sequencing of new dams, and reservoir operating rules. Results show that there is no single investment plan that performs best across a range of plausible future runoff conditions. The decision-analytic framework is then used to identify dam configurations that are both robust to poor outcomes and sufficiently flexible to capture high upside benefits if favorable future climate and hydrological conditions should arise. The approach could be extended to explore design and operating features of development and adaptation projects other than dams.
Evaluation of the Terminal Precision Scheduling and Spacing System for Near-Term NAS Application
NASA Technical Reports Server (NTRS)
Thipphavong, Jane; Martin, Lynne Hazel; Swenson, Harry N.; Lin, Paul; Nguyen, Jimmy
2012-01-01
NASA has developed a capability for terminal area precision scheduling and spacing (TAPSS) to provide higher capacity and more efficiently manage arrivals during peak demand periods. This advanced technology is NASA's vision for the NextGen terminal metering capability. A set of human-in-the-loop experiments was conducted to evaluate the performance of the TAPSS system for near-term implementation. The experiments evaluated the TAPSS system under the current terminal routing infrastructure to validate operational feasibility. A second goal of the study was to measure the benefit of the Center and TRACON advisory tools to help prioritize the requirements for controller radar display enhancements. Simulation results indicate that using the TAPSS system provides benefits under current operations, supporting a 10% increase in airport throughput. Enhancements to Center decision support tools had limited impact on improving the efficiency of terminal operations, but did provide more fuel-efficient advisories to achieve scheduling conformance within 20 seconds. The TRACON controller decision support tools were found to provide the most benefit, by improving the precision in schedule conformance to within 20 seconds, reducing the number of arrivals having lateral path deviations by 50% and lowering subjective controller workload. Overall, the TAPSS system was found to successfully develop an achievable terminal arrival metering plan that was sustainable under heavy traffic demand levels and reduce the complexity of terminal operations when coupled with the use of the terminal controller advisory tools.
DOT National Transportation Integrated Search
2009-10-01
Transit Operations Decision Support Systems (TODSS) are systems designed to support dispatchers and others in real-time operations : management in response to incidents, special events, and other changing conditions in order to improve operating spee...
Smink, Douglas S; Peyre, Sarah E; Soybel, David I; Tavakkolizadeh, Ali; Vernon, Ashley H; Anastakis, Dimitri J
2012-04-01
Experts become automated when performing surgery, making it difficult to teach complex procedures to trainees. Cognitive task analysis (CTA) enables experts to articulate operative steps and cognitive decisions in complex procedures such as laparoscopic appendectomy, which can then be used to identify central teaching points. Three local surgeon experts in laparoscopic appendectomy were interviewed using critical decision method-based CTA methodology. Interview transcripts were analyzed, and a cognitive demands table (CDT) was created for each expert. The individual CDTs were reviewed by each expert for completeness and then combined into a master CDT. Percentage agreement on operative steps and decision points was calculated for each expert. The experts then participated in a consensus meeting to review the master CDT. Each surgeon expert was asked to identify in the master CDT the most important teaching objectives for junior-level and senior-level residents. The experts' responses for junior-level and senior-level residents were compared using a χ(2) test. The surgeon experts identified 24 operative steps and 27 decision points. Eighteen of the 24 operative steps (75%) were identified by all 3 surgeon experts. The percentage of operative steps identified was high for each surgeon expert (96% for surgeon 1, 79% for surgeon 2, and 83% for surgeon 3). Of the 27 decision points, only 5 (19%) were identified by all 3 surgeon experts. The percentage of decision points identified varied by surgeon expert (78% for surgeon 1, 59% for surgeon 2, and 48% for surgeon 3). When asked to identify key teaching points, the surgeon experts were more likely to identify operative steps for junior residents (9 operative steps and 6 decision points) and decision points for senior residents (4 operative steps and 13 decision points) (P < .01). CTA can deconstruct the essential operative steps and decision points associated with performing a laparoscopic appendectomy. These results provide a framework to identify key teaching principles to guide intraoperative instruction. These learning objectives could be used to guide resident level-appropriate teaching of an essential general surgery procedure. Copyright © 2012 Elsevier Inc. All rights reserved.
Kyle, Richard R; Via, Darin K; Lowy, R Joel; Madsen, James M; Marty, Aileen M; Mongan, Paul D
2004-03-01
To reinforce concepts presented in the lectures; understand the complexity and speed of casualty and information generation during a Weapons of Mass Destruction and Terrorism (WMD/T) event; experience the novelty of combined weapons' effects; recognize the time course of the various chemical, biological, and radiation agents; and make challenging decisions with incomplete and conflicting information. Two environments simulated simultaneously: one a major trauma center emergency room (ER) with two patient simulators and several human actors; the other an Emergency Operations Command Center (EOC). Students for this course included: clinicians, scientists, military and intelligence officers, lawyers, administrators, and logistic personnel whose jobs involve planning and executing emergency response plans to WMD/T. SIMULATION SCRIPT: A WMD/T attack in Washington, D.C., has occurred. Clinical students performed in their real life roles in the simulated ER, while nonclinical students did the same in the simulated EOC. Six ER casualties with combined WMD/T injuries were presented and treated over 40 minutes. In the EOC, each person was given his or her role title with identification tag. The EOC scenario took cues from the action in the ER via two television (TV) news feeds and telephone calls from other Emergency Operations Assets. PERFORMANCE EXPECTATIONS: Students were expected to actively engage in their roles. Student performances were self-evaluated during the debriefing. DEBRIEFING: The two groups were reunited and debriefed utilizing disaster crisis resource management tools. ASSESSMENT OF EFFECTIVENESS: Students answered an 18-point questionnaire to help evaluate the usefulness and acceptance of multimodality patient simulation. Large-scale multimodality patient simulation can be used to train both clinicians and nonclinicians for future events of WMD/T. Students accepted the simulation experience and thought that scenario was appropriately realistic, complex, and overwhelming. Difficulties include the extensive man-hours involved in designing and presenting the live simulations. EOC-only sessions could be staged with only a few video cassette recorders, TVs, telephones, and callers.
The Roles of Decision Makers in Special Operations
2016-12-01
question and hypotheses. 9 II. CASE STUDIES A. OPERATION THUNDERBOLT (THE RAID ON ENTEBBE) The Israeli Special Forces’ hostage rescue operation...Operations Warfare, 338. 28 Herzog, “The War Against Terrorism: Entebbe,” 338. 29 Chaitanya Arun Sathe, “A Case Study on Crisis Management with a...Assessment of the Roles of Decision Makers This assessment is based on this case study , and the decision makers’ roles in the three phases of a
Quantum decision-maker theory and simulation
NASA Astrophysics Data System (ADS)
Zak, Michail; Meyers, Ronald E.; Deacon, Keith S.
2000-07-01
A quantum device simulating the human decision making process is introduced. It consists of quantum recurrent nets generating stochastic processes which represent the motor dynamics, and of classical neural nets describing the evolution of probabilities of these processes which represent the mental dynamics. The autonomy of the decision making process is achieved by a feedback from the mental to motor dynamics which changes the stochastic matrix based upon the probability distribution. This feedback replaces unavailable external information by an internal knowledge- base stored in the mental model in the form of probability distributions. As a result, the coupled motor-mental dynamics is described by a nonlinear version of Markov chains which can decrease entropy without an external source of information. Applications to common sense based decisions as well as to evolutionary games are discussed. An example exhibiting self-organization is computed using quantum computer simulation. Force on force and mutual aircraft engagements using the quantum decision maker dynamics are considered.
NASA Astrophysics Data System (ADS)
Delaney, C.; Mendoza, J.; Whitin, B.; Hartman, R. K.
2017-12-01
Ensemble Forecast Operations (EFO) is a risk based approach of reservoir flood operations that incorporates ensemble streamflow predictions (ESPs) made by NOAA's California-Nevada River Forecast Center (CNRFC). With the EFO approach, each member of an ESP is individually modeled to forecast system conditions and calculate risk of reaching critical operational thresholds. Reservoir release decisions are computed which seek to manage forecasted risk to established risk tolerance levels. A water management model was developed for Lake Mendocino, a 111,000 acre-foot reservoir located near Ukiah, California, to evaluate the viability of the EFO alternative to improve water supply reliability but not increase downstream flood risk. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United States Army Corps of Engineers and is operated for water supply by the Sonoma County Water Agency. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has suffered from water supply reliability issues since 2007. The EFO alternative was simulated using a 26-year (1985-2010) ESP hindcast generated by the CNRFC, which approximates flow forecasts for 61 ensemble members for a 15-day horizon. Model simulation results of the EFO alternative demonstrate a 36% increase in median end of water year (September 30) storage levels over existing operations. Additionally, model results show no increase in occurrence of flows above flood stage for points downstream of Lake Mendocino. This investigation demonstrates that the EFO alternative may be a viable approach for managing Lake Mendocino for multiple purposes (water supply, flood mitigation, ecosystems) and warrants further investigation through additional modeling and analysis.
NASA Technical Reports Server (NTRS)
Kramer, Lynda J.; Bailey, Randall E.; Ellis, Kyle K. E.; Williams, Steven P.; Arthur, Jarvis J., III; Prinzel, Lawrence J., III; Shelton, Kevin J.
2013-01-01
Synthetic Vision Systems and Enhanced Flight Vision System (SVS/EFVS) technologies have the potential to provide additional margins of safety for aircrew performance and enable operational improvements for low visibility operations in the terminal area environment with equivalent efficiency as visual operations. To meet this potential, research is needed for effective technology development and implementation of regulatory standards and design guidance to support introduction and use of SVS/EFVS advanced cockpit vision technologies in Next Generation Air Transportation System (NextGen) operations. A fixed-base pilot-in-the-loop simulation test was conducted at NASA Langley Research Center that evaluated the use of SVS/EFVS in NextGen low visibility approach and landing operations. Twelve crews flew approach and landing operations in a simulated NextGen Chicago O'Hare environment. Various scenarios tested the potential for using EFVS to conduct approach, landing, and roll-out operations in visibility as low as 1000 feet runway visual range (RVR). Also, SVS was tested to evaluate the potential for lowering decision heights (DH) on certain instrument approach procedures below what can be flown today. Expanding the portion of the visual segment in which EFVS can be used in lieu of natural vision from 100 feet above the touchdown zone elevation to touchdown and rollout in visibilities as low as 1000 feet RVR appears to be viable as touchdown performance was acceptable without any apparent workload penalties. A lower DH of 150 feet and/or possibly reduced visibility minima using SVS appears to be viable when implemented on a Head-Up Display, but the landing data suggests further study for head-down implementations.
A trainable decisions-in decision-out (DEI-DEO) fusion system
NASA Astrophysics Data System (ADS)
Dasarathy, Belur V.
1998-03-01
Most of the decision fusion systems proposed hitherto in the literature for multiple data source (sensor) environments operate on the basis of pre-defined fusion logic, be they crisp (deterministic), probabilistic, or fuzzy in nature, with no specific learning phase. The fusion systems that are trainable, i.e., ones that have a learning phase, mostly operate in the features-in-decision-out mode, which essentially reduces the fusion process functionally to a pattern classification task in the joint feature space. In this study, a trainable decisions-in-decision-out fusion system is described which estimates a fuzzy membership distribution spread across the different decision choices based on the performance of the different decision processors (sensors) corresponding to each training sample (object) which is associated with a specific ground truth (true decision). Based on a multi-decision space histogram analysis of the performance of the different processors over the entire training data set, a look-up table associating each cell of the histogram with a specific true decision is generated which forms the basis for the operational phase. In the operational phase, for each set of decision inputs, a pointer to the look-up table learnt previously is generated from which a fused decision is derived. This methodology, although primarily designed for fusing crisp decisions from the multiple decision sources, can be adapted for fusion of fuzzy decisions as well if such are the inputs from these sources. Examples, which illustrate the benefits and limitations of the crisp and fuzzy versions of the trainable fusion systems, are also included.
DOT National Transportation Integrated Search
2000-07-14
This is a draft document for the Surface Transportation Weather Decision Support Requirements (STWDSR) project. The STWDSR project is being conducted for the FHWAs Office of Transportation Operations (HOTO) Road Weather Management Program by Mitre...
ERIC Educational Resources Information Center
Hunsaker, L. Phillip
2007-01-01
Purpose: The purpose of this paper is to describe two social simulations created to assess leadership potential and train leaders to make effective decisions in turbulent environments. One is set in the novel environment of a lunar moon colony and the other is a military combat command. The research generated from these simulations for assessing…
Combined monitoring, decision and control model for the human operator in a command and control desk
NASA Technical Reports Server (NTRS)
Muralidharan, R.; Baron, S.
1978-01-01
A report is given on the ongoing efforts to mode the human operator in the context of the task during the enroute/return phases in the ground based control of multiple flights of remotely piloted vehicles (RPV). The approach employed here uses models that have their analytical bases in control theory and in statistical estimation and decision theory. In particular, it draws heavily on the modes and the concepts of the optimal control model (OCM) of the human operator. The OCM is being extended into a combined monitoring, decision, and control model (DEMON) of the human operator by infusing decision theoretic notions that make it suitable for application to problems in which human control actions are infrequent and in which monitoring and decision-making are the operator's main activities. Some results obtained with a specialized version of DEMON for the RPV control problem are included.
Analysis of UAS DAA Alerting in Fast-Time Simulations without DAA Mitigation
NASA Technical Reports Server (NTRS)
Thipphavong, David P.; Santiago, Confesor; Isaacson, Douglas R.; Lee, Seung Man; Park, Chunki; Refai, Mohamad Said; Snow, James
2015-01-01
Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of performance standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements for DAA alerting system performance. A recent study conducted using NASA's ACES (Airspace Concept Evaluation System) simulation capability begins to address questions surrounding the development of draft MOPS for DAA alerting systems. ACES simulations were conducted to study the performance of alerting systems proposed by the SC-228 DAA Alerting sub-group. Analysis included but was not limited to: 1) correct alert (and timeliness), 2) false alert (and severity and duration), 3) missed alert, and 4) probability of an alert type at the time of loss of well clear. The performance of DAA alerting systems when using intent vs. dead-reckoning for UAS ownship trajectories was also compared. The results will be used by SC-228 to inform decisions about the surveillance standards of UAS DAA systems and future requirements development and validation efforts.
Analysis of UAS DAA Surveillance in Fast-Time Simulations without DAA Mitigation
NASA Technical Reports Server (NTRS)
Thipphavong, David P.; Santiago, Confesor; Isaacson, David R.; Lee, Seung Man; Refai, Mohamad Said; Snow, James William
2015-01-01
Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of performance standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements for DAA surveillance system performance. A recent study conducted using NASA's ACES (Airspace Concept Evaluation System) simulation capability begins to address questions surrounding the development of draft MOPS for DAA surveillance systems. ACES simulations were conducted to study the performance of sensor systems proposed by the SC-228 DAA Surveillance sub-group. Analysis included but was not limited to: 1) number of intruders (both IFR and VFR) detected by all sensors as a function of UAS flight time, 2) number of intruders (both IFR and VFR) detected by radar alone as a function of UAS flight time, and 3) number of VFR intruders detected by all sensors as a function of UAS flight time. The results will be used by SC-228 to inform decisions about the surveillance standards of UAS DAA systems and future requirements development and validation efforts.
NASA Astrophysics Data System (ADS)
Imbrogno, Stano; Rinaldi, Sergio; Raso, Antonio; Bordin, Alberto; Bruschi, Stefania; Umbrello, Domenico
2018-05-01
The Additive Manufacturing techniques are gaining more and more interest in various industrial fields due to the possibility of drastically reduce the material waste during the production processes, revolutionizing the standard scheme and strategies of the manufacturing processes. However, the metal parts shape produced, frequently do not satisfy the tolerances as well as the surface quality requirements. During the design phase, the finite element simulation results a fundamental tool to help the engineers in the correct decision of the most suitable process parameters, especially in manufacturing processes, in order to produce products of high quality. The aim of this work is to develop a 3D finite element model of semi-finishing turning operation of Ti6Al4V, produced via Direct Metal Laser Sintering (DMLS). A customized user sub-routine was built-up in order to model the mechanical behavior of the material under machining operations to predict the main fundamental variables as cutting forces and temperature. Moreover, the machining induced alterations are also studied by the finite element model developed.
Interdisciplinary collaboration to maintain a culture of safety in a labor and delivery setting.
Burke, Carol; Grobman, William; Miller, Deborah
2013-01-01
A culture of safety is a growing movement in obstetrical healthcare quality and management. Patient-centered and safe care is a primary priority for all healthcare workers, with communication and teamwork central to achieving optimal maternal health outcomes. A mandatory educational program was developed and implemented by physicians and nurses to sustain awareness and compliance to current protocols within a large university-based hospital. A didactic portion reviewing shoulder dystocia, operative vaginal delivery, obstetric hemorrhage, and fetal monitoring escalation was combined with a simulation session. The simulation was a fetal bradycardia activating the decision to perform an operative vaginal delivery complicated by a shoulder dystocia. More than 370 members of the healthcare team participated including obstetricians, midwives, the anesthesia team, and nurses. Success of the program was measured by an evaluation tool and comparing results from a prior safety questionnaire. Ninety-seven percent rated the program as excellent, and the response to a question on perception of overall grade on patient safety measured by the Agency for Healthcare Research and Quality safety survey demonstrated a significant improvement in the score (P = .003) following the program.
DeHart, Mark D.; Baker, Benjamin A.; Ortensi, Javier
2017-07-27
The Transient Test Reactor (TREAT) at Idaho National Laboratory will resume operations in late 2017 after a 23 year hiatus while maintained in a cold standby state. Over that time period, computational power and simulation capabilities have increased substantially and now allow for new multiphysics modeling possibilities that were not practical or feasible for most of TREAT's operational history. Hence the return of TREAT to operational service provides a unique opportunity to apply state-of-the-art software and associated methods in the modeling and simulation of general three-dimensional steady state and kinetic behavior for reactor operation, and for coupling of the coremore » power transient model to experiment simulations. However, measurements taken in previous operations were intended to predict power deposition in experimental samples, with little consideration of three-dimensional core power distributions. Hence, interpretation of data for the purpose of validation of modern methods can be challenging. For the research discussed herein, efforts are described for the process of proper interpretation of data from the most recent calibration experiments performed in the core, the M8 calibration series (M8-CAL). These measurements were taken between 1990 and 1993 using a set of fission wires and test fuel pins to estimate the power deposition that would be produced in fast reactor test fuel pins during the M8 experiment series. Because of the decision to place TREAT into a standby state in 1994, the M8 series of transients were never performed. However, potentially valuable information relevant for validation is available in the M8-CAL measurement data, if properly interpreted. This article describes the current state of the process of recovery of useful data from M8-CAL measurements and quantification of biases and uncertainties to potentially apply to the validation of multiphysics methods.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
DeHart, Mark D.; Baker, Benjamin A.; Ortensi, Javier
The Transient Test Reactor (TREAT) at Idaho National Laboratory will resume operations in late 2017 after a 23 year hiatus while maintained in a cold standby state. Over that time period, computational power and simulation capabilities have increased substantially and now allow for new multiphysics modeling possibilities that were not practical or feasible for most of TREAT's operational history. Hence the return of TREAT to operational service provides a unique opportunity to apply state-of-the-art software and associated methods in the modeling and simulation of general three-dimensional steady state and kinetic behavior for reactor operation, and for coupling of the coremore » power transient model to experiment simulations. However, measurements taken in previous operations were intended to predict power deposition in experimental samples, with little consideration of three-dimensional core power distributions. Hence, interpretation of data for the purpose of validation of modern methods can be challenging. For the research discussed herein, efforts are described for the process of proper interpretation of data from the most recent calibration experiments performed in the core, the M8 calibration series (M8-CAL). These measurements were taken between 1990 and 1993 using a set of fission wires and test fuel pins to estimate the power deposition that would be produced in fast reactor test fuel pins during the M8 experiment series. Because of the decision to place TREAT into a standby state in 1994, the M8 series of transients were never performed. However, potentially valuable information relevant for validation is available in the M8-CAL measurement data, if properly interpreted. This article describes the current state of the process of recovery of useful data from M8-CAL measurements and quantification of biases and uncertainties to potentially apply to the validation of multiphysics methods.« less
Intelligent reservoir operation system based on evolving artificial neural networks
NASA Astrophysics Data System (ADS)
Chaves, Paulo; Chang, Fi-John
2008-06-01
We propose a novel intelligent reservoir operation system based on an evolving artificial neural network (ANN). Evolving means the parameters of the ANN model are identified by the GA evolutionary optimization technique. Accordingly, the ANN model should represent the operational strategies of reservoir operation. The main advantages of the Evolving ANN Intelligent System (ENNIS) are as follows: (i) only a small number of parameters to be optimized even for long optimization horizons, (ii) easy to handle multiple decision variables, and (iii) the straightforward combination of the operation model with other prediction models. The developed intelligent system was applied to the operation of the Shihmen Reservoir in North Taiwan, to investigate its applicability and practicability. The proposed method is first built to a simple formulation for the operation of the Shihmen Reservoir, with single objective and single decision. Its results were compared to those obtained by dynamic programming. The constructed network proved to be a good operational strategy. The method was then built and applied to the reservoir with multiple (five) decision variables. The results demonstrated that the developed evolving neural networks improved the operation performance of the reservoir when compared to its current operational strategy. The system was capable of successfully simultaneously handling various decision variables and provided reasonable and suitable decisions.
A simulation-optimization-based decision support tool for mitigating traffic congestion.
DOT National Transportation Integrated Search
2009-12-01
"Traffic congestion has grown considerably in the United States over the past twenty years. In this paper, we develop : a robust decision support tool based on simulation optimization to evaluate and recommend congestion-mitigation : strategies to tr...
Bradley, Beverly D; Jung, Tiffany; Tandon-Verma, Ananya; Khoury, Bassem; Chan, Timothy C Y; Cheng, Yu-Ling
2017-04-18
Operations research (OR) is a discipline that uses advanced analytical methods (e.g. simulation, optimisation, decision analysis) to better understand complex systems and aid in decision-making. Herein, we present a scoping review of the use of OR to analyse issues in global health, with an emphasis on health equity and research impact. A systematic search of five databases was designed to identify relevant published literature. A global overview of 1099 studies highlights the geographic distribution of OR and common OR methods used. From this collection of literature, a narrative description of the use of OR across four main application areas of global health - health systems and operations, clinical medicine, public health and health innovation - is also presented. The theme of health equity is then explored in detail through a subset of 44 studies. Health equity is a critical element of global health that cuts across all four application areas, and is an issue particularly amenable to analysis through OR. Finally, we present seven select cases of OR analyses that have been implemented or have influenced decision-making in global health policy or practice. Based on these cases, we identify three key drivers for success in bridging the gap between OR and global health policy, namely international collaboration with stakeholders, use of contextually appropriate data, and varied communication outlets for research findings. Such cases, however, represent a very small proportion of the literature found. Poor availability of representative and quality data, and a lack of collaboration between those who develop OR models and stakeholders in the contexts where OR analyses are intended to serve, were found to be common challenges for effective OR modelling in global health.
Leitner, Stephan; Brauneis, Alexander; Rausch, Alexandra
2015-01-01
In this paper, we investigate the impact of inaccurate forecasting on the coordination of distributed investment decisions. In particular, by setting up a computational multi-agent model of a stylized firm, we investigate the case of investment opportunities that are mutually carried out by organizational departments. The forecasts of concern pertain to the initial amount of money necessary to launch and operate an investment opportunity, to the expected intertemporal distribution of cash flows, and the departments' efficiency in operating the investment opportunity at hand. We propose a budget allocation mechanism for coordinating such distributed decisions The paper provides guidance on how to set framework conditions, in terms of the number of investment opportunities considered in one round of funding and the number of departments operating one investment opportunity, so that the coordination mechanism is highly robust to forecasting errors. Furthermore, we show that-in some setups-a certain extent of misforecasting is desirable from the firm's point of view as it supports the achievement of the corporate objective of value maximization. We then address the question of how to improve forecasting quality in the best possible way, and provide policy advice on how to sequence activities for improving forecasting quality so that the robustness of the coordination mechanism to errors increases in the best possible way. At the same time, we show that wrong decisions regarding the sequencing can lead to a decrease in robustness. Finally, we conduct a comprehensive sensitivity analysis and prove that-in particular for relatively good forecasters-most of our results are robust to changes in setting the parameters of our multi-agent simulation model.
Francis, Tittu; Washington, Travis; Srivastava, Karan; Moutzouros, Vasilios; Makhni, Eric C; Hakeos, William
2017-11-01
Tension band wiring (TBW) and locked plating are common treatment options for Mayo IIA olecranon fractures. Clinical trials have shown excellent functional outcomes with both techniques. Although TBW implants are significantly less expensive than a locked olecranon plate, TBW often requires an additional operation for implant removal. To choose the most cost-effective treatment strategy, surgeons must understand how implant costs and return to the operating room influence the most cost-effective strategy. This cost-effective analysis study explored the optimal treatment strategies by using decision analysis tools. An expected-value decision tree was constructed to estimate costs based on the 2 implant choices. Values for critical variables, such as implant removal rate, were obtained from the literature. A Monte Carlo simulation consisting of 100,000 trials was used to incorporate variability in medical costs and implant removal rates. Sensitivity analysis and strategy tables were used to show how different variables influence the most cost-effective strategy. TBW was the most cost-effective strategy, with a cost savings of approximately $1300. TBW was also the dominant strategy by being the most cost-effective solution in 63% of the Monte Carlo trials. Sensitivity analysis identified implant costs for plate fixation and surgical costs for implant removal as the most sensitive parameters influencing the cost-effective strategy. Strategy tables showed the most cost-effective solution as 2 parameters vary simultaneously. TBW is the most cost-effective strategy in treating Mayo IIA olecranon fractures despite a higher rate of return to the operating room. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.
Remote Sensing and Modeling for Improving Operational Aquatic Plant Management
NASA Technical Reports Server (NTRS)
Bubenheim, Dave
2016-01-01
The California Sacramento-San Joaquin River Delta is the hub for California’s water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, water quality changes, and expansion of invasive aquatic plants threatens ecosystems, impedes ecosystem restoration, and is economically, environmentally, and sociologically detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California and local governments to develop science-based, adaptive-management strategies for the Sacramento-San Joaquin Delta. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and waterway managers make science-informed decisions regarding management and outcomes. The team provides a comprehensive understanding of agricultural and urban land use in the Delta and the major water sheds (San Joaquin/Sacramento) supplying the Delta and interaction with drought and climate impacts on the environment, water quality, and weed growth. The team recommends conservation and modified land-use practices and aids local Delta stakeholders in developing management strategies. New remote sensing tools have been developed to enhance ability to assess conditions, inform decision support tools, and monitor management practices. Science gaps in understanding how native and invasive plants respond to altered environmental conditions are being filled and provide critical biological response parameters for Delta-SWAT simulation modeling. Operational agencies such as the California Department of Boating and Waterways provide testing and act as initial adopter of decision support tools. Methods developed by the project can become routine land and water management tools in complex river delta systems.
NASA Astrophysics Data System (ADS)
Pentz, Alan Carter
With today's uncertain funding climate (including sequestration and continuing budget resolutions), decision makers face severe budgetary challenges to maintain dominance through all aspects of the Department of Defense (DoD). To meet war-fighting capabilities, the DoD continues to extend aircraft programs beyond their design service lives by up to ten years, and occasionally much more. The budget requires a new approach to traditional extension strategies (i.e., reuse, reset, and reclamation) for structural hardware. While extending service life without careful controls can present a safety concern, future operations planning does not consider how much risk is present when operating within sound structural principles. Traditional structural hardware extension methods drive increased costs. Decision makers often overlook the inherent damage tolerance and fatigue capability of structural components and rely on simple time- and flight-based cycle accumulation when determining aircraft retirement lives. This study demonstrates that decision makers should consider risk in addition to the current extension strategies. Through an evaluation of eight military aircraft programs and the application and simulation of F-18 turbine engine usage data, this dissertation shows that insight into actual aircraft mission data, consideration of fatigue capability, and service extension length are key factors to consider. Aircraft structural components, as well as many critical safety components and system designs, have a predefined level of conservatism and inherent damage tolerance. The methods applied in this study would apply to extensions of other critical structures such as bridges. Understanding how much damage tolerance is built into the design compared to the original design usage requirements presents the opportunity to manage systems based on risk. The study presents the sensitivity of these factors and recommends avenues for further research.
Leitner, Stephan; Brauneis, Alexander; Rausch, Alexandra
2015-01-01
In this paper, we investigate the impact of inaccurate forecasting on the coordination of distributed investment decisions. In particular, by setting up a computational multi-agent model of a stylized firm, we investigate the case of investment opportunities that are mutually carried out by organizational departments. The forecasts of concern pertain to the initial amount of money necessary to launch and operate an investment opportunity, to the expected intertemporal distribution of cash flows, and the departments’ efficiency in operating the investment opportunity at hand. We propose a budget allocation mechanism for coordinating such distributed decisions The paper provides guidance on how to set framework conditions, in terms of the number of investment opportunities considered in one round of funding and the number of departments operating one investment opportunity, so that the coordination mechanism is highly robust to forecasting errors. Furthermore, we show that—in some setups—a certain extent of misforecasting is desirable from the firm’s point of view as it supports the achievement of the corporate objective of value maximization. We then address the question of how to improve forecasting quality in the best possible way, and provide policy advice on how to sequence activities for improving forecasting quality so that the robustness of the coordination mechanism to errors increases in the best possible way. At the same time, we show that wrong decisions regarding the sequencing can lead to a decrease in robustness. Finally, we conduct a comprehensive sensitivity analysis and prove that—in particular for relatively good forecasters—most of our results are robust to changes in setting the parameters of our multi-agent simulation model. PMID:25803736
Energy-Efficient Channel Handoff for Sensor Network-Assisted Cognitive Radio Network
Usman, Muhammad; Sajjad Khan, Muhammad; Vu-Van, Hiep; Insoo, Koo
2015-01-01
The visiting and less-privileged status of the secondary users (SUs) in a cognitive radio network obligates them to release the occupied channel instantly when it is reclaimed by the primary user. The SU has a choice to make: either wait for the channel to become free, thus conserving energy at the expense of delayed transmission and delivery, or find and switch to a vacant channel, thereby avoiding delay in transmission at the expense of increased energy consumption. An energy-efficient decision that considers the tradeoff between energy consumption and continuous transmission needs to be taken as to whether to switch the channels. In this work, we consider a sensor network-assisted cognitive radio network and propose a backup channel, which is sensed by the SU in parallel with the operating channel that is being sensed by the sensor nodes. Imperfect channel sensing and residual energy of the SU are considered in order to develop an energy-efficient handoff strategy using the partially observable Markov decision process (POMDP), which considers beliefs about the operating and backup channels and the remaining energy of the SU in order to take an optimal channel handoff decision on the question “Should we switch the channel?” The objective is to dynamically decide in each time slot whether the SU should switch the channel or not in order to maximize throughput by utilizing energy efficiently. Extensive simulations were performed to show the effectiveness of the proposed channel handoff strategy, which was demonstrated in the form of throughput with respect to various parameters, i.e., detection probability, the channel idle probabilities of the operating and backup channels, and the maximum energy of the SU. PMID:26213936
NASA Astrophysics Data System (ADS)
Barros, Ana; Ager, Alan; Preisler, Haiganoush; Day, Michelle; Spies, Tom; Bolte, John
2015-04-01
Agent-based models (ABM) allow users to examine the long-term effects of agent decisions in complex systems where multiple agents and processes interact. This framework has potential application to study the dynamics of coupled natural and human systems where multiple stimuli determine trajectories over both space and time. We used Envision, a landscape based ABM, to analyze long-term wildfire dynamics in a heterogeneous, multi-owner landscape in Oregon, USA. Landscape dynamics are affected by land management policies, actors decisions, and autonomous processes such as vegetation succession, wildfire, or at a broader scale, climate change. Key questions include: 1) How are landscape dynamics influenced by policies and institutions, and 2) How do land management policies and actor decisions interact to produce intended and unintended consequences with respect to wildfire on fire-prone landscapes. Applying Envision to address these questions required the development of a wildfire module that could accurately simulate wildfires on the heterogeneous landscapes within the study area in terms of replicating historical fire size distribution, spatial distribution and fire intensity. In this paper we describe the development and testing of a mechanistic fire simulation system within Envision and application of the model on a 3.2 million fire prone landscape in central Oregon USA. The core fire spread equations use the Minimum Travel Time algorithm developed by M Finney. The model operates on a daily time step and uses a fire prediction system based on the relationship between energy release component and historical fires. Specifically, daily wildfire probabilities and sizes are generated from statistical analyses of historical fires in relation to daily ERC values. The MTT was coupled with the vegetation dynamics module in Envision to allow communication between the respective subsystem and effectively model fire effects and vegetation dynamics after a wildfire. Canopy and surface fuels are modeled in a state and transition framework that accounts for succession, fire effects, and fuels management. Fire effects are modeled using simulated fire intensity (flame length) to calculate expected vegetation impacts for each vegetation state. This talk will describe the mechanics of the simulation system along with initial results of Envision simulations for the Central Oregon study area that explore the dynamics of wildfire, fuel management, and succession over time.
ERIC Educational Resources Information Center
Alasia, Alessandro; Weersink, Alfons; Bollman, Ray D.; Cranfield, John
2009-01-01
Understanding the factors affecting off-farm labour decisions of census-farm operators has significant implications for rural development and farm income support policy. We examine the off-farm labour decisions of Canadian farm operators using micro-level data from the 2001 Census of Agriculture combined with community level data from the 2001…
Federal Register 2010, 2011, 2012, 2013, 2014
2012-06-12
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Proper Edging and Trimming Will Help Improve Lumber Value
Philip A. Araman
1991-01-01
Decisions on where to edge and trim waning edged boards, or to trim other boards, can have a major effect on the performance of a sawmill. Optimum decisions are difficult for a number of reasons, including: complexity of grading rules; operator skills; operator fatigue or lack of interest at times; and, the inability of operators to include lumber prices in decisions....
Perrin, B M; Barnett, B J; Walrath, L; Grossman, J D
2001-01-01
Findings that decision makers can come to different conclusions depending on the order in which they receive information have been termed the "information order bias." When trained, experienced individuals exhibit similar behaviors; however, it has been argued that this result is not a bias, but rather, a pattern-matching process. This study provides a critical examination of this claim. It also assesses both experts' susceptibility to an outcome framing bias and the effects of varying task loads on judgment. Using a simulation of state-of-the-art ship defensive systems operated by experienced, active-duty U.S. Navy officers, we found no evidence of a framing bias, while task load had a minor, but systematic effect. The order in which information was received had a significant impact, with the effect being consistent with a judgment bias. Nonetheless, we note that pattern-matching processes, similar to those that produce inferential and reconstructive effects on memory, could also explain our results. Actual or potential applications of this research include decision support system interfaces or training programs that might be developed to reduce judgment bias.
NASA Astrophysics Data System (ADS)
Lammers, Craig; McGraw, Robert M.; Steinman, Jeffrey S.
2005-05-01
Technological advances and emerging threats reduce the time between target detection and action to an order of a few minutes. To effectively assist with the decision-making process, C4I decision support tools must quickly and dynamically predict and assess alternative Courses Of Action (COAs) to assist Commanders in anticipating potential outcomes. These capabilities can be provided through the faster-than-real-time predictive simulation of plans that are continuously re-calibrating with the real-time picture. This capability allows decision-makers to assess the effects of re-tasking opportunities, providing the decision-maker with tremendous freedom to make time-critical, mid-course decisions. This paper presents an overview and demonstrates the use of a software infrastructure that supports DSAP capabilities. These DSAP capabilities are demonstrated through the use of a Multi-Replication Framework that supports (1) predictivie simulations using JSAF (Joint Semi-Automated Forces); (2) real-time simulation, also using JSAF, as a state estimation mechanism; and, (3) real-time C4I data updates through TBMCS (Theater Battle Management Core Systems). This infrastructure allows multiple replications of a simulation to be executed simultaneously over a grid faster-than-real-time, calibrated with live data feeds. A cost evaluator mechanism analyzes potential outcomes and prunes simulations that diverge from the real-time picture. In particular, this paper primarily serves to walk a user through the process for using the Multi-Replication Framework providing an enhanced decision aid.
Some Results of Weak Anticipative Concept Applied in Simulation Based Decision Support in Enterprise
NASA Astrophysics Data System (ADS)
Kljajić, Miroljub; Kofjač, Davorin; Kljajić Borštnar, Mirjana; Škraba, Andrej
2010-11-01
The simulation models are used as for decision support and learning in enterprises and in schools. Tree cases of successful applications demonstrate usefulness of weak anticipative information. Job shop scheduling production with makespan criterion presents a real case customized flexible furniture production optimization. The genetic algorithm for job shop scheduling optimization is presented. Simulation based inventory control for products with stochastic lead time and demand describes inventory optimization for products with stochastic lead time and demand. Dynamic programming and fuzzy control algorithms reduce the total cost without producing stock-outs in most cases. Values of decision making information based on simulation were discussed too. All two cases will be discussed from optimization, modeling and learning point of view.
Criteria for assessing problem solving and decision making in complex environments
NASA Technical Reports Server (NTRS)
Orasanu, Judith
1993-01-01
Training crews to cope with unanticipated problems in high-risk, high-stress environments requires models of effective problem solving and decision making. Existing decision theories use the criteria of logical consistency and mathematical optimality to evaluate decision quality. While these approaches are useful under some circumstances, the assumptions underlying these models frequently are not met in dynamic time-pressured operational environments. Also, applying formal decision models is both labor and time intensive, a luxury often lacking in operational environments. Alternate approaches and criteria are needed. Given that operational problem solving and decision making are embedded in ongoing tasks, evaluation criteria must address the relation between those activities and satisfaction of broader task goals. Effectiveness and efficiency become relevant for judging reasoning performance in operational environments. New questions must be addressed: What is the relation between the quality of decisions and overall performance by crews engaged in critical high risk tasks? Are different strategies most effective for different types of decisions? How can various decision types be characterized? A preliminary model of decision types found in air transport environments will be described along with a preliminary performance model based on an analysis of 30 flight crews. The performance analysis examined behaviors that distinguish more and less effective crews (based on performance errors). Implications for training and system design will be discussed.
Rollins, Brent L; Gunturi, Rahul; Sullivan, Donald
2014-04-17
To implement a pharmacy business management simulation exercise as a practical application of business management material and principles and assess students' perceived value. As part of a pharmacy management and administration course, students made various calculations and management decisions in the global categories of hours of operation, inventory, pricing, and personnel. The students entered the data into simulation software and a realistic community pharmacy marketplace was modeled. Course topics included accounting, economics, finance, human resources, management, marketing, and leadership. An 18-item posttest survey was administered. Students' slightly to moderately agreed the pharmacy simulation program enhanced their knowledge and understanding, particularly of inventory management, cash flow statements, balance sheets, and income statements. Overall attitudes toward the pharmacy simulation program were also slightly positive and students also slightly agreed the pharmacy simulation program enhanced their learning of pharmacy business management. Inventory management was the only area in which students felt they had at least "some" exposure to the assessed business management topics during IPPEs/internship, while all other areas of experience ranged from "not at all" to "a little." The pharmacy simulation program is an effective active-learning exercise and enhanced students' knowledge and understanding of the business management topics covered.
Rollins, Brent L.; Gunturi, Rahul; Sullivan, Donald
2014-01-01
Objective. To implement a pharmacy business management simulation exercise as a practical application of business management material and principles and assess students’ perceived value. Design. As part of a pharmacy management and administration course, students made various calculations and management decisions in the global categories of hours of operation, inventory, pricing, and personnel. The students entered the data into simulation software and a realistic community pharmacy marketplace was modeled. Course topics included accounting, economics, finance, human resources, management, marketing, and leadership. Assessment. An 18-item posttest survey was administered. Students’ slightly to moderately agreed the pharmacy simulation program enhanced their knowledge and understanding, particularly of inventory management, cash flow statements, balance sheets, and income statements. Overall attitudes toward the pharmacy simulation program were also slightly positive and students also slightly agreed the pharmacy simulation program enhanced their learning of pharmacy business management. Inventory management was the only area in which students felt they had at least “some” exposure to the assessed business management topics during IPPEs/internship, while all other areas of experience ranged from “not at all” to “a little.” Conclusion. The pharmacy simulation program is an effective active-learning exercise and enhanced students’ knowledge and understanding of the business management topics covered. PMID:24761023
Statistical and Probabilistic Extensions to Ground Operations' Discrete Event Simulation Modeling
NASA Technical Reports Server (NTRS)
Trocine, Linda; Cummings, Nicholas H.; Bazzana, Ashley M.; Rychlik, Nathan; LeCroy, Kenneth L.; Cates, Grant R.
2010-01-01
NASA's human exploration initiatives will invest in technologies, public/private partnerships, and infrastructure, paving the way for the expansion of human civilization into the solar system and beyond. As it is has been for the past half century, the Kennedy Space Center will be the embarkation point for humankind's journey into the cosmos. Functioning as a next generation space launch complex, Kennedy's launch pads, integration facilities, processing areas, launch and recovery ranges will bustle with the activities of the world's space transportation providers. In developing this complex, KSC teams work through the potential operational scenarios: conducting trade studies, planning and budgeting for expensive and limited resources, and simulating alternative operational schemes. Numerous tools, among them discrete event simulation (DES), were matured during the Constellation Program to conduct such analyses with the purpose of optimizing the launch complex for maximum efficiency, safety, and flexibility while minimizing life cycle costs. Discrete event simulation is a computer-based modeling technique for complex and dynamic systems where the state of the system changes at discrete points in time and whose inputs may include random variables. DES is used to assess timelines and throughput, and to support operability studies and contingency analyses. It is applicable to any space launch campaign and informs decision-makers of the effects of varying numbers of expensive resources and the impact of off nominal scenarios on measures of performance. In order to develop representative DES models, methods were adopted, exploited, or created to extend traditional uses of DES. The Delphi method was adopted and utilized for task duration estimation. DES software was exploited for probabilistic event variation. A roll-up process was used, which was developed to reuse models and model elements in other less - detailed models. The DES team continues to innovate and expand DES capabilities to address KSC's planning needs.
Data Management for Mars Exploration Rovers
NASA Technical Reports Server (NTRS)
Snyder, Joseph F.; Smyth, David E.
2004-01-01
Data Management for the Mars Exploration Rovers (MER) project is a comprehensive system addressing the needs of development, test, and operations phases of the mission. During development of flight software, including the science software, the data management system can be simulated using any POSIX file system. During testing, the on-board file system can be bit compared with files on the ground to verify proper behavior and end-to-end data flows. During mission operations, end-to-end accountability of data products is supported, from science observation concept to data products within the permanent ground repository. Automated and human-in-the-loop ground tools allow decisions regarding retransmitting, re-prioritizing, and deleting data products to be made using higher level information than is available to a protocol-stack approach such as the CCSDS File Delivery Protocol (CFDP).
Integrating Systems Health Management with Adaptive Controls for a Utility-Scale Wind Turbine
NASA Technical Reports Server (NTRS)
Frost, Susan A.; Goebel, Kai; Trinh, Khanh V.; Balas, Mark J.; Frost, Alan M.
2011-01-01
Increasing turbine up-time and reducing maintenance costs are key technology drivers for wind turbine operators. Components within wind turbines are subject to considerable stresses due to unpredictable environmental conditions resulting from rapidly changing local dynamics. Systems health management has the aim to assess the state-of-health of components within a wind turbine, to estimate remaining life, and to aid in autonomous decision-making to minimize damage. Advanced adaptive controls can provide the mechanism to enable optimized operations that also provide the enabling technology for Systems Health Management goals. The work reported herein explores the integration of condition monitoring of wind turbine blades with contingency management and adaptive controls. Results are demonstrated using a high fidelity simulator of a utility-scale wind turbine.
NASA Technical Reports Server (NTRS)
Lietzke, K. R.
1975-01-01
An economic model and simulation are developed to estimate the potential social benefit arising from the use of alternative measurement systems in rangeland management. In order to estimate these benefits, it was necessary to model three separate systems: the range environment, the rangeland manager, and the information system which links the two. The rancher's decision-making behavior is modeled according to sound economic principles. Results indicate substantial potential benefits, particularly when used in assisting management of government-operated ranges; possible annual benefits in this area range from $20 to $46 million, depending upon the system capabilities assumed. Possible annual benefit in privately-managed stocker operations range from $2.8 to $49.5 million, depending upon where actual rancher capabilities lie and what system capabilities are assumed.
NASA Technical Reports Server (NTRS)
Sultan, Labib; Janabi, Talib
1992-01-01
This paper analyses the internal operation of fuzzy logic controllers as referenced to the human cognitive tasks of control and decision making. Two goals are targeted. The first goal focuses on the cognitive interpretation of the mechanisms employed in the current design of fuzzy logic controllers. This analysis helps to create a ground to explore the potential of enhancing the functional intelligence of fuzzy controllers. The second goal is to outline the features of a new class of fuzzy controllers, the Clearness Transformation Fuzzy Logic Controller (CT-FLC), whereby some new concepts are advanced to qualify fuzzy controllers as 'cognitive devices' rather than 'expert system devices'. The operation of the CT-FLC, as a fuzzy pattern processing controller, is explored, simulated, and evaluated.
NASA Technical Reports Server (NTRS)
Mercer, Joey S.; Bienert, Nancy; Gomez, Ashley; Hunt, Sarah; Kraut, Joshua; Martin, Lynne; Morey, Susan; Green, Steven M.; Prevot, Thomas; Wu, Minghong G.
2013-01-01
A Human-In-The-Loop air traffic control simulation investigated the impact of uncertainties in trajectory predictions on NextGen Trajectory-Based Operations concepts, seeking to understand when the automation would become unacceptable to controllers or when performance targets could no longer be met. Retired air traffic controllers staffed two en route transition sectors, delivering arrival traffic to the northwest corner-post of Atlanta approach control under time-based metering operations. Using trajectory-based decision-support tools, the participants worked the traffic under varying levels of wind forecast error and aircraft performance model error, impacting the ground automations ability to make accurate predictions. Results suggest that the controllers were able to maintain high levels of performance, despite even the highest levels of trajectory prediction errors.
CET exSim: mineral exploration experience via simulation
NASA Astrophysics Data System (ADS)
Wong, Jason C.; Holden, Eun-Jung; Kovesi, Peter; McCuaig, T. Campbell; Hronsky, Jon
2013-08-01
Undercover mineral exploration is a challenging task as it requires understanding of subsurface geology by relying heavily on remotely sensed (i.e. geophysical) data. Cost-effective exploration is essential in order to increase the chance of success using finite budgets. This requires effective decision-making in both the process of selecting the optimum data collection methods and in the process of achieving accuracy during subsequent interpretation. Traditionally, developing the skills, behaviour and practices of exploration decision-making requires many years of experience through working on exploration projects under various geological settings, commodities and levels of available resources. This implies long periods of sub-optimal exploration decision-making, before the necessary experience has been successfully obtained. To address this critical industry issue, our ongoing research focuses on the development of the unique and novel e-learning environment, exSim, which simulates exploration scenarios where users can test their strategies and learn the consequences of their choices. This simulator provides an engaging platform for self-learning and experimentation in exploration decision strategies, providing a means to build experience more effectively. The exSim environment also provides a unique platform on which numerous scenarios and situations (e.g. deposit styles) can be simulated, potentially allowing the user to become virtually familiarised with a broader scope of exploration practices. Harnessing the power of computer simulation, visualisation and an intuitive graphical user interface, the simulator provides a way to assess the user's exploration decisions and subsequent interpretations. In this paper, we present the prototype functionalities in exSim including: simulation of geophysical surveys, follow-up drill testing and interpretation assistive tools.
NASA Astrophysics Data System (ADS)
Squibb, Gael F.
1984-10-01
The operation teams for the Infrared Astronomical Satellite (IRAS) included scientists from the IRAS International Science Team. The scientific decisions on an hour-to-hour basis, as well as the long-term strategic decisions, were made by science team members. The IRAS scientists were involved in the analysis of the instrument performance, the analysis of the quality of the data, the decision to reacquire data that was contaminated by radiation effects, the strategy for acquiring the survey data, and the process for using the telescope for additional observations, as well as the processing decisions required to ensure the publication of the final scientific products by end of flight operations plus one year. Early in the project, two science team members were selected to be responsible for the scientific operational decisions. One, located at the operations control center in England, was responsible for the scientific aspects of the satellite operations; the other, located at the scientific processing center in Pasadena, was responsible for the scientific aspects of the processing. These science team members were then responsible for approving the design and test of the tools to support their responsibilities and then, after launch, for using these tools in making their decisions. The ability of the project to generate the final science data products one year after the end of flight operations is due in a large measure to the active participation of the science team members in the operations. This paper presents a summary of the operational experiences gained from this scientific involvement.