936 resultados para Exit ramp
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To maintain a strict balance between demand and supply in the US power systems, the Independent System Operators (ISOs) schedule power plants and determine electricity prices using a market clearing model. This model determines for each time period and power plant, the times of startup, shutdown, the amount of power production, and the provisioning of spinning and non-spinning power generation reserves, etc. Such a deterministic optimization model takes as input the characteristics of all the generating units such as their power generation installed capacity, ramp rates, minimum up and down time requirements, and marginal costs for production, as well as the forecast of intermittent energy such as wind and solar, along with the minimum reserve requirement of the whole system. This reserve requirement is determined based on the likelihood of outages on the supply side and on the levels of error forecasts in demand and intermittent generation. With increased installed capacity of intermittent renewable energy, determining the appropriate level of reserve requirements has become harder. Stochastic market clearing models have been proposed as an alternative to deterministic market clearing models. Rather than using a fixed reserve targets as an input, stochastic market clearing models take different scenarios of wind power into consideration and determine reserves schedule as output. Using a scaled version of the power generation system of PJM, a regional transmission organization (RTO) that coordinates the movement of wholesale electricity in all or parts of 13 states and the District of Columbia, and wind scenarios generated from BPA (Bonneville Power Administration) data, this paper explores a comparison of the performance between a stochastic and deterministic model in market clearing. The two models are compared in their ability to contribute to the affordability, reliability and sustainability of the electricity system, measured in terms of total operational costs, load shedding and air emissions. The process of building the models and running for tests indicate that a fair comparison is difficult to obtain due to the multi-dimensional performance metrics considered here, and the difficulty in setting up the parameters of the models in a way that does not advantage or disadvantage one modeling framework. Along these lines, this study explores the effect that model assumptions such as reserve requirements, value of lost load (VOLL) and wind spillage costs have on the comparison of the performance of stochastic vs deterministic market clearing models.
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© 2015 Elsevier Inc.Links between emission trading programs are not immutable, as highlighted by New Jersey's exit from the Regional Greenhouse Gas Initiative in 2011. This raises the question of what to do with existing permits that are banked for future use-choices that have consequences for market behavior in advance of, or upon speculation about, delinking. We consider two delinking policies. One differentiates banked permits by origin, the other treats banked permits the same. We describe the price behavior and relative cost-effectiveness of each policy. Treating permits differently generally leads to higher costs, and may lead to price divergence, even with only speculation about delinking.
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INTRODUCTION: Adherence to glaucoma medications is essential for successful treatment of the disease but is complex and difficult for many of our patients. Health coaching has been used successfully in the treatment of other chronic diseases. This pilot study explores the use of health coaching for glaucoma care. METHODS: A mixed methods study design was used to assess the health coaching intervention for glaucoma patients. The health coaching intervention consisted of four to six health coaching sessions with a certified health coach via telephone. Quantitative measures included demographic and health information, adherence to glaucoma medications (using the visual analog adherence scale and medication event monitoring system), and an exit survey rating the experience. Qualitative measures included a precoaching health questionnaire, notes made by the coach during the intervention, and an exit interview with the subjects at the end of the study. RESULTS: Four glaucoma patients participated in the study; all derived benefits from the health coaching. Study subjects demonstrated increased glaucoma drop adherence in response to the coaching intervention, in both visual analog scale and medication event monitoring system. Study subjects' qualitative feedback reflected a perceived improvement in both eye and general health self-care. The subjects stated that they would recommend health coaching to friends or family members. CONCLUSION: Health coaching was helpful to the glaucoma patients in this study; it has the potential to improve glaucoma care and overall health.
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The purpose of this paper is to demonstrate the potential of the EXODUS evacuation model in building environments. The latest PC/workstation version of EXODUS is described and is also applied to a large hypothetical supermarket/restaurant complex measuring 50 m x 40 m. A range of scenarios is presented where population characteristics (such as size, individual travel speeds, and individual response times), and enclosure configuration characteristics (such as number of exits, size of exits, and opening times of exits) are varied. The results demonstrate a wide range of occupant behavior including overtaking, queuing, redirection, and conflict avoidance. Evacuation performance is measured by a number of model predicted parameters including individual exit flow rates, overall evacuation flow rates, total evacuation time, average evacuation time per occupant, average travel distance, and average wait time. The simulations highlight the profound impact that variations in individual travel speeds and occupant response times have in determining the overall evacuation performance.
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The purpose of this paper is to demonstrate the potential of the EXODUS evacuation model in building environments. The latest PC/workstation version of EXODUS is described and is also applied to a large hypothetical supermarket/restaurant complex measuring 50 m x 40 m. A range of scenarios is presented where population characteristics (such as size, individual travel speeds, and individual response times), and enclosure configuration characteristics (such as number of exits, size of exits, and opening times of exits) are varied. The results demonstrate a wide range of occupant behavior including overtaking, queuing, redirection, and conflict avoidance. Evacuation performance is measured by a number of model predicted parameters including individual exit flow rates, overall evacuation flow rates, total evacuation time, average evacuation time per occupant, average travel distance, and average wait time. The simulations highlight the profound impact that variations in individual travel speeds and occupant response times have in determining the overall evacuation performance. 1. Jin, T., and Yamada T., "Experimental Study of Human Behavior in Smoke Filled Corridors," Proceedings of The Second International Symposium on Fire Safety Science, 1988, pp. 511-519. 2. Galea, E.R., and Galparsoro, J.M.P., "EXODUS: An Evacuation Model for Mass Transport Vehicles," UK CAA Paper 93006 ISBN 086039 543X, CAA London, 1993. 3. Galea, E.R., and Galparsoro, J.M.P., "A Computer Based Simulation Model for the Prediction of Evacuation from Mass Transport Vehicles," Fire Safety Journal, Vol. 22, 1994, pp. 341-366. 4. Galea, E.R., Owen, M., and Lawrence, P., "Computer Modeling of Human Be havior in Aircraft Fire Accidents," to appear in the Proceedings of Combus tion Toxicology Symposium, CAMI, Oklahoma City, OK, 1995. 5. Kisko, T.M. and Francis, R.L., "EVACNET+: A Computer Program to Determine Optimal Building Evacuation Plans," Fire Safety Journal, Vol. 9, 1985, pp. 211-220. 6. Levin, B., "EXITT, A Simulation Model of Occupant Decisions and Actions in Residential Fires," Proceedings of The Second International Symposium on Fire Safety Science, 1988, pp. 561-570. 7. Fahy, R.F., "EXIT89: An Evacuation Model for High-Rise Buildings," Pro ceedings of The Third International Sym posium on Fire Safety Science, 1991, pp. 815-823. 8. Thompson, P.A., and Marchant, E.W., "A Computer Model for the Evacuation of Large Building Populations," Fire Safety Journal, Vol. 24, 1995, pp. 131-148. 9. Still, K., "New Computer System Can Predict Human Behavior Response to Building Fires," FIRE 84, 1993, pp. 40-41. 10. Ketchell, N., Cole, S.S., Webber, D.M., et.al., "The Egress Code for Human Move ment and Behavior in Emergency Evacu ations," Engineering for Crowd Safety (Smith, R.A., and Dickie, J.F., Eds.), Elsevier, 1993, pp. 361-370. 11. Takahashi, K., Tanaka, T. and Kose, S., "An Evacuation Model for Use in Fire Safety Design of Buildings," Proceedings of The Second International Symposium on Fire Safety Science, 1988, pp. 551- 560. 12. G2 Reference Manual, Version 3.0, Gensym Corporation, Cambridge, MA. 13. XVT Reference Manual, Version 3.0 XVT Software Inc., Boulder, CO. 14. Galea, E.R., "On the Field Modeling Approach to the Simulation of Enclosure Fires, Journal of Fire Protection Engineering, Vol. 1, No. 1, 1989, pp. 11-22. 15. Purser, D.A., "Toxicity Assessment of Combustion Products," SFPE Handbook of Fire Protection Engineering, National Fire Protection Association, Quincy, MA, pp. 1-200 - 1-245, 1988. 16. Hankin, B.D., and Wright, R.A., "Pas senger Flows in Subways," Operational Research Quarterly, Vol. 9, 1958, pp. 81-88. 17. HMSO, The Building Regulations 1991 - Approved Document B, section B 1 (1992 edition), HMSO publications, London, pp. 9-40. 18. Polus A., Schofer, J.L., and Ushpiz, A., "Pedestrian Flow and Level of Service," Journal of Transportation Engineering, Vol. 109, 1983, pp. 46-47. 19. Muir, H., Marrison, C., and Evans, A., "Aircraft Evacuations: the Effect of Passenger Motivation and Cabin Con figuration Adjacent to the Exit," CAA Paper 89019, ISBN 0 86039 406 9, 1989. 20. Muir, H., Private communication to appear as a CAA report, 1996.
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In this paper, the buildingEXODUS (V1.1) evacuation model is described and discussed and attempts at qualitative and quantitative model validation are presented. The data set used for the validation is the Tsukuba pavilion evacuation data. This data set is of particular interest as the evacuation was influenced by external conditions, namely inclement weather. As part of the validation exercise, the sensitivity of the buildingEXODUS predictions to a range of variables and conditions is examined, including; exit flow capacity, occupant response times and the impact of external conditions on the developing evacuation. The buildingEXODUS evacuation model was found to be able to produce good qualitative and quantitative agreement with the experimental data.
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In this paper, the buildingEXODUS (V1.1) evacuation model is described and discussed and attempts at qualitative and quantitative model validation are presented. The data sets used for validation are the Stapelfeldt and Milburn House evacuation data. As part of the validation exercise, the sensitivity of the buildingEXODUS predictions to a range of variables is examined, including: occupant drive, occupant location, exit flow capacity, exit size, occupant response times and geometry definition. An important consideration that has been highlighted by this work is that any validation exercise must be scrutinised to identify both the results generated and the considerations and assumptions on which they are based. During the course of the validation exercise, both data sets were found to be less than ideal for the purpose of validating complex evacuation models. However, the buildingEXODUS evacuation model was found to be able to produce reasonable qualitative and quantitative agreement with the experimental data.
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In this article, the buildingEXODUS (V1.1) evacuation model is described and discussed and attempts at qualitative and quantitative model validation are presented. The data set used for the validation is the Tsukuba pavilion evacuation data. This data set is of particular interest as the evacuation was influenced by external conditions, namely inclement weather. As part of the validation exercise, the sensitivity of the buildingEXODUS predictions to a range of variables and conditions is examined, including: exit flow capacity, occupant response times, and the impact of external conditions on the developing evacuation. The buildingEXODUS evacuation model was found to produce good qualitative and quantitative agreement with the experimental data.
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Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However such models have a heavy dependency on real evacuation data in order to (a) identify the key processes and factors associated with evacuation, (b) quantify variables and parameters associated with the identified factors/processes and finally (c) validate the models. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise from three major data sources in order to address these issues. This paper describes the extraction and application of data from one of these sources - aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (aircraft accident statistics and knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK comprises four component sub-databases. These consist of the ACCIDENT (crash details), FLIGHT ATTENDANT (observations and actions of the flight attendants), FATALS (details concerning passenger fatalities) and PAX (observations and accounts from individual passengers) databases. AASK currently contains information from 25 survivable aviation accidents covering the period 4 April 1977 to 6 August 1995, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. In addition to aiding the development of aircraft evacuation models, AASK is also being used to challenge some of the myths which proliferate in the aviation safety industry such as, passenger exit selection during evacuation, nature and frequency of seat jumping, speed of passenger response and group dynamics. AASK can also be used to aid in the development of a more comprehensive approach to conducting post accident interviews, and will eventually be used to store the data directly.
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Given the importance of occupant behaviour on evacuation efficiency, a new behavioural feature has been implemented into buildingEXODUS. This feature concerns the response of occupants to exit selection and re-direction. This behaviour is not simply pre-determined by the user as part of the initialisation process, but involves the occupant taking decisions based on their previous experiences and the information available to them. This information concerns the occupants prior knowledge of the enclosure and line-of-sight information concerning queues at neighbouring exits. This new feature is demonstrated and reviewed through several examples.
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Given the importance of occupant behavior on evacuation efficiency, a new behavioral feature has been developed and implemented into buildingEXODUS. This feature concerns the response of occupants to exit selection and re-direction. This behavior is not simply pre-determined by the user as part of the initialization process, but involves the occupant taking decisions based on their previous experiences and the information available to them. This information concerns the occupants prior knowledge of the enclosure and line-of-sight information concerning queues at neighboring exits. This new feature is demonstrated and reviewed through several examples.
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When evacuating through fire environments, the presence of smoke may not only have a physiological impact on the evacuees but may also lead occupants to adapt their evacuation strategy through the adoption of another exit. This paper attempts to introduce this type of adaptive behaviour within the buildingEXODUS evacuation model through enabling occupants to make decisions concerning the selection of the most viable available exit during an evacuation involving fire. The development of this adaptive behaviour requires the introduction of several new capabilities namely, the representation of the occupants’ familiarity with the structure, the behaviour of an occupant that is engulfed in smoke and the behaviour of an occupant that is faced with a smoke barrier. The appropriateness of the redirection decision is dependent upon behavioural data gathered from real fire incidents (in the UK and USA) that is used to construct the redirection probabilities. The implementation is shown to provide a more complex and arguably more realistic representation of this behaviour than that provided previously.
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On the 19 June 2001, a Thames passenger/tour boat underwent several evacuation trials. This work was conducted in order to collect data for the validation of marine-based computer models. The trials involved 111 participants who were distributed throughout the vessel. The boat had two decks and two points of exit from the lower deck placed on either side of the craft, forward and aft. The boat had a twin set of staircases towards the rear of the craft, just forward of the rear exits. maritimeEXODUS was used to simulate the full-scale evacuation trials conducted. The simulation times generated were compared against the original results and categorised according to the exit point availability. The predictions closely approximate the original results, differing by an average of 6.6% across the comparisons, with numerous qualitative similarities between the predictions and experimental results. The maritimeEXODUS evacuation model was then used to examine the evacuation procedure currently employed on the vessel. This was found to have potential to produce long evacuation times. maritimeEXODUS was used to suggest modifications to the mustering procedures. These theoretical results suggest that it is possible to significantly reduce evacuation times.
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The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes recent developments with the database leading to the development of AASK v3.0. These include significantly increasing the number of passenger accounts in the database, the introduction of cabin crew accounts, the introduction of fatality information, improved functionality through the seat plan viewer utility and improved ease of access to the database via the internet. In addition, the paper demonstrates the use of the database by investigating a number of important issues associated with aircraft evacuation. These include issues associated with social bonding and evacuation, the relationship between the number of crew and evacuation efficiency, frequency of exit/slide failures in accidents and exploring possible relationships between seating location and chances of survival. Finally, the passenger behavioural trends described in analysis undertaken with the earlier database are confirmed with the wider data set.
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Very Large Transport Aircraft (VLTA) pose considerable challenges to designers, operators and certification authorities. Questions concerning seating arrangement, nature and design of recreational space, the number, design and location of internal staircases, the number of cabin crew required and the nature of the cabin crew emergency procedures are just some of the issues that need to be addressed. Other more radical concepts such as blended wing body (BWB) design, involving one or two decks with possibly four or more aisles offer even greater challenges. Can the largest exits currently available cope with passenger flow arising from four or five aisles? Do we need to consider new concepts in exit design? Should the main aisles be made wider to accommodate more passengers? In this paper we demonstrate how computer based evacuation models can be used to investigate these issues through examination of staircase evacuation procedures for VLTA and aisle/exit configuration for BWB cabin layouts.