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Готові списки джерел за темами / Availability Modeling

Добірка наукової літератури з теми "Availability Modeling"

Автор: Grafiati

Опубліковано: 7 липня 2024

Оновлено: 7 липня 2024

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Статті в журналах з теми "Availability Modeling":

1

Wood, A. "Availability modeling." IEEE Circuits and Devices Magazine 10, no. 3 (May 1994): 22–27. http://dx.doi.org/10.1109/101.283651.

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2

Ledoux, J. "Availability modeling of modular software." IEEE Transactions on Reliability 48, no. 2 (June 1999): 159–68. http://dx.doi.org/10.1109/24.784274.

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3

Sang-Chin Yang and J. A. Nachlas. "Bivariate reliability and availability modeling." IEEE Transactions on Reliability 50, no. 1 (March 2001): 26–35. http://dx.doi.org/10.1109/24.935013.

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4

Pérez-Miguel, Carlos, Alexander Mendiburu, and Jose Miguel-Alonso. "Modeling the availability of Cassandra." Journal of Parallel and Distributed Computing 86 (December 2015): 29–44. http://dx.doi.org/10.1016/j.jpdc.2015.08.001.

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5

Wurbs, Ralph A. "Texas Water Availability Modeling System." Journal of Water Resources Planning and Management 131, no. 4 (July 2005): 270–79. http://dx.doi.org/10.1061/(asce)0733-9496(2005)131:4(270).

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6

Kong, De Zhi, and Xiao Bing Li. "A Instantaneous Availability Modelling Method for Repairable System." Applied Mechanics and Materials 724 (January 2015): 334–39. http://dx.doi.org/10.4028/www.scientific.net/amm.724.334.

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A Instantaneous availability modelling method for repair system was introduced. The empirical modeling method was used to the reliability function, and the life distribution selection method was proposed. Then, under the assumption that the maintainability was decreasing with the calendar time, the Fourier function was chosen for the basic fitting functions. Under the original definition of availability for the system, the availability modeling method was proposed. Finally, a case example for the method was given, and the result showed that the method was convenient for availability evaluation.

7

Carmo, R. M. L. R., L. R. de Carvalho, E. de Souza e Suva, M. C. Diniz, and R. R. Muntz. "Performance/availability modeling with the TANGRAM-II modeling environment." Performance Evaluation 33, no. 1 (June 1998): 45–65. http://dx.doi.org/10.1016/s0166-5316(98)00011-x.

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8

Ahn, Yoonjung, and Christopher K. Uejio. "Modeling air conditioning ownership and availability." Urban Climate 46 (December 2022): 101322. http://dx.doi.org/10.1016/j.uclim.2022.101322.

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9

Laprie, J. C., and K. Kanoun. "X-ware reliability and availability modeling." IEEE Transactions on Software Engineering 18, no. 2 (1992): 130–47. http://dx.doi.org/10.1109/32.121755.

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10

Piiper, Johannes, and Peter Scheid. "Modeling oxygen availability to exercising muscle." Respiration Physiology 118, no. 2-3 (December 1999): 95–101. http://dx.doi.org/10.1016/s0034-5687(99)00082-1.

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Дисертації з теми "Availability Modeling":

1

Krishnamurthy, Ganesh. "Incorporating salinity considerations in water availability modeling." Texas A&M University, 2006. http://hdl.handle.net/1969.1/3833.

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This research focused on expanding the capabilities of the Water Rights Analysis Package (WRAP) for incorporating salinity considerations in assessments of water availability. A simulation modeling approach was used to address this issue and a generalized simulation model called WRAP-SALT was developed. The Brazos River Basin served as a case study to test the simulation approach adopted by the model. The simulation model adopts a generalized modeling approach applicable to any river basin system. The model tracks salinity throughout a river basin system over different periods of time for alternative scenarios of water use, reservoir system operating policies, and salt control mechanisms. The model was applied to the Brazos River Basin considering different management scenarios and the results obtained were analyzed. Reservoir reliabilities were assessed under user imposed salinity constraints. It was observed that the water supply reliabilities decreased significantly if salinity constraints were considered. Salt control dams proposed by the U.S. Army Corps of Engineers were also incorporated in the simulation of the river basin. It was observed that salinity in the main stem of the Brazos River was significantly reduced. However, no significant improvement was observed in water supply reliabilities.

2

Schuol, Jürgen. "GIS-based hydrological modeling of freshwater availability in Africa /." Zürich : ETH, 2008. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=17491.

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3

French, Timothy F. "Comparison of operational availability modeling by TIGER and SESAME." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA283943.

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Thesis (M.S. in Operations Research) Naval Postgraduate School, June 1994.
Thesis advisor(s): Alan W. McMasters, James D. Esary. "June 1994." Includes bibliographical references. Also available online.

4

Duan, Chunming. "Stochastic availability analysis and modeling of longwall mining operations." Diss., This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-07122007-103924/.

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5

Amich, Amine. "Efficient spectrum utilization using statistical modeling of channel availability." Thesis, University of Surrey, 2015. http://epubs.surrey.ac.uk/807095/.

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Cognitive radio systems have been suggested as a method to improve spectrum utilization by detecting and accessing vacant spectrum. In such a network, sub-bands of a spectrum are shared by licensed (primary) and unlicensed (secondary) users in that preferential order. It is generally recognized that the spectral occupancy by primary users exhibit dynamical spatial and temporal properties and hence the fundamental issue is to characterize the sub-band spectrum occupancy in terms of probabilities. Given statistical analysis of the frequency band of interest are available, it has been shown that adaptive searching for white spaces could improve by 70% when compared to random searching. In the open literature, there exist no accurate/efficient time-varying model representing the spectrum occupancy that the wireless researchers could employ for evaluating new algorithms and techniques designed for dynamic spectrum access (DSA). Therefore, the objective is to propose an accurate and efficient analytic model that can be used to enhance the sensing operations. Using real-time measurements conducted in different geographic locations, existing research has validated that subchannel availability is suitably modeled as independent but non identical (i.n.i.d.) Bernoulli variables characterized by pi , the probability of availability of the i-th subchannel. The magnitude of pi ’s could be extracted from sensed measurements or a geolocation database. Based on the i.n.i.d. paradigm, we develop a predictive model by probabilistically computing the distribution of the number of available subchannels over a wide-band at a given time. However, the combinatorial complexity behind the exact distribution computation alludes the need for accurate and efficient alternative approaches that can support frequency bands with a large number of non-overlapping subchannels. We propose 3 different techniques based on convolution, recursive, and hybrid convolution-recursive methods to resolve this complexity. We assess their efficiency by analyzing each algorithm’s time complexity and further compare their performance against existing models in the literature. Moreover, knowing the availability of the channel’s immediate neighbors can allow efficient power management as well as prioritize channels allocation to secondary users. Therefore, we categorize available channels into three different types based on the occupancy of its two adjacent channels then model their availability. Additionally, from a network performance analysis perspective, predicting the count of available channels has to be evaluated against the probability of detecting these channels within the same i.n.i.d. framework. Respectively, we propose a novel approach to calculate the probability of detecting multi-channels simultaneously. Finally, we validate the effectiveness of the proposed models using several real-time measurements and further present 2 associated applications where one features novel 2-Dimensional (time, freq) availability prediction.

6

Pinheiro, Everton Alves Rodrigues. "Hydrological modeling of soil-water availability in the Caatinga biome." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/11/11152/tde-10112016-170843/.

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Northeastern Brazil is hydrologically characterized by recurrent droughts leading to a highly vulnerable natural water resource system. The region contains the Caatinga biome, a sparsely studied ecosystem, covering an area of approximately 800,000 km2. Reduced wateravailability is projected to take place in large regions of the globe, including Northeastern Brazil. Given the strong interactions between climate and vegetation, research has addressed climate change effects on natural and agricultural ecosystems. In this context, soil hydraulic properties are essential to assess soil water flow, and thus the ability of soil to supply water to plants at potential rates under different ranges of pressure head. Based on that, the aims of this thesis are: to increase insight in water balance components for the Caatinga biome, under current and future climate scenarios; and to assess the ability of soils in supplying water to plants by the further development of an existing matric flux potential approach, followed by its application to a group of soils from two Brazilian climatic zones (semi-arid and subhumid). Both for current and future climate scenarios, hydrological simulations were performed with SWAP model parameterized for a preserved Caatinga basin of 12 km2. The validation of the simulations was performed using a dataset of daily soil-water content measurements taken at 0.2 m depth in the period from 2004 to 2012. The soil water supplying capacity was evaluated through a multilayer matric flux potential approach, coupling the soil hydraulic properties, root length density and plant transpiration. Regarding the current climate conditions, the Caatinga biome returns 75% of the annual precipitation to the atmosphere, whereas the partitioning of total evapotranspiration into its components (transpiration, evaporation and interception) on annual basis accounts for 41%, 40% and 19%, respectively. Evapotranspiration and air temperature are most sensitive to soil moisture during the periods June-September and December-January. Concerning the future climate, transpiration was enhanced by 36%, soil evaporation and interception losses reduced by 16% and 34%, respectively. The amount of precipitation returned to the atmosphere was on average 98%. For both climate scenarios, the soil-plant-atmosphere fluxes seem to be controlled by the surface soil layer (0-0.2 m) which provides, on average, 80% of the total transpiration, suggesting that the Caatinga biome may become completely soil-water pulse dominated under scenarios of reduced water availability. The matric flux potential analysis revealed that soils from the semiarid zone were able to deliver water to plants at potential rates under a wider range of bulk soil pressure head (-36 to -148 m), whereas the soils from the wetter zone showed more hydraulic restriction with limiting soil water potential above -1.5 m. For the analyzed soils, only a negligible increase in available water results from decreasing the root water potential below -150 m, therefore, in order to adapt to water-limited conditions, plant species may invest in other adaptive strategies, rather than spending energy in structures that allow a reduction of the lower suction limit in their tissues.
O Nordeste do Brasil é hidrologicamente caracterizado por secas recorrentes, tornando os recursos hídricos naturais altamente vulneráveis. Nesta região está o bioma Caatinga, ocupando uma área de aproximadamente 800.000 km2. Cenários de déficit hídrico são projetados para grandes regiões do globo, incluindo o Nordeste brasileiro. Devido às interações entre clima e vegetação, várias pesquisas têm abordado os efeitos das mudanças climáticas sobre os ecossistemas naturais e agrícolas. Neste contexto, as propriedades hidráulicas do solo são essenciais para avaliar o movimento de água, e assim a capacidade de fornecimento de água às plantas. Com base nesta contextualização, os objetivos desta tese são: simular os componentes do balanço hídrico do bioma Caatinga para cenários climáticos atuais e futuros; e avaliar a capacidade de alguns solos em fornecer água às plantas a partir de uma abordagem de potencial de fluxo matricial. Para os cenários climáticos atuais e futuros, simulações hidrológicas foram realizadas com o modelo SWAP, parametrizado para uma microbacia de 12 km2, inserida em área de Caatinga preservada. A validação das simulações foi processada a partir de medidas diárias do conteúdo de água do solo na profundidade de 0,2 m no período de 2004 a 2012. A capacidade do solo em fornecer água às plantas foi avaliada através da atualização de uma função de potencial de fluxo matricial, que acopla as propriedades hidráulicas do solo, densidade de comprimento radicular e transpiração das plantas, aplicada a um grupo de solos da zona climática semiárida e sub-úmida. Como resultados principais destacam-se: nas condições climáticas atuais, o bioma Caatinga retorna 75% da precipitação anual para a atmosfera como evapotranspiração, particionada entre seus componentes (transpiração, evaporação e intercepção) em 41%, 40% e 19%, respectivamente. Evapotranspiração e temperatura do ar foram sensíveis à umidade do solo durante os períodos de junho-setembro e dezembro-janeiro. Em relação ao cenário climático futuro, a taxa de transpiração foi acrescida em 36%. A evaporação do solo e a interceptação foram reduzidas em 16% e 34%, respectivamente. A quantidade de precipitação devolvida para a atmosfera foi em média 98%. Para ambos os cenários climáticos, é sugerido que os fluxos de água no sistema solo-planta-atmosfera são controlados pela camada superior do solo (0-0,2 m), fornecendo, em média, 80% do total transpirado, indicando que, caso os cenários de disponibilidade hídrica reduzida se confirmem, o bioma Caatinga pode se tornar completamente dependente dos pulsos de água no solo. A partir do potencial de fluxo matricial limitante revelou-se que os solos da região semiárida são capazes de manter o fluxo de água às plantas em taxas potenciais em condições de solo seco (potencial matricial limitante variando de -36 a -148 m), enquanto que, os solos da região mais úmida indicaram severa restrição hidráulica, com potencial matricial limitante maior do que -1,5 m. Ainda para os solos analisados, a atribuição de potencial na superfície da raiz inferior a -150 m não ocasionou aumento de disponibilidade hídrica, indicando que valores menores que -150 m não implicam em uma estratégia viável para suportar baixa disponibilidade hídrica.

7

Olmos, Alejo Hector Elias. "Improving capabilities for dealing with key complexities of water availability modeling." Texas A&M University, 2004. http://hdl.handle.net/1969.1/1463.

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Water availability has been of great concern in the State of Texas and many other places worldwide. During 1997-2003, pursuant to the 1997 Senate Bill 1, the Texas Commission on Environmental Quality (TCEQ), its partner agencies, and contractors developed a Water Availability Modeling (WAM) System based on the Water Rights Analysis Package (WRAP) model, developed at Texas A&M University. WAM has been widely applied in the State of Texas and because of its convenience, applications, and capabilities, it is planned to be implemented in other States and Countries. This thesis addresses different aspects of WAM, including conditional reliability modeling, firm yield analysis following classic and recently developed methodologies, evaluating the impact of different considerations on reliability analyses, simplification of complex WAM datasets and the display of WRAP results into ArcMap. Conditional reliability modeling evaluates short term diversion/storage reliabilities based on an initial storage level. WRAP-CON has been evaluated and improved, in addition a new modeling methodology has been developed, in which probabilities of occurrence for each hydrologic sequence is based on the relationship between storage and future flows. Recently developed WRAP capabilities have been evaluated, providing users new tools and increased flexibility. Some of these improvements are firm yield analysis, cycling and dual simulation. In addition to improved software, guidelines have also been developed, including a set to simplify extremely large WAM datasets, while maintaining the effect of all the other water rights in a basin.

8

Thorn, Dustin, and Matt Hubbard. "Investigating the relationship between customer wait time and operational availability through simulation modeling." Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/27914.

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Customer Wait Time (CWT) measures all supply chain processes, from the time a customer places an order until the item is delivered. The Marine Corps intermediate supply activity, the Supply Management Unit (SMU), has the primary task of reducing the amount of time it takes for the operating forces to receive supplies by stocking items close to the warfighter. Such forward positioning of repair parts shields the operating forces from delays found at the wholesale inventory level, thereby increasing the material readiness of the operating forces. Intuitively, decreasing CWT increases operational availability (Ao), but the degree and magnitude of this relationship has yet to be quantified. This lack of understanding pertaining to the relationship between Ao and CWT has led to arbitrary stock policies that do not account for the cost and benefit they provide. This project centers on monetizing the relationship between these variables through simulation modeling, and provides a tool whereby stock determination can be made based on desired end states.

9

Feng, Xin. "In vivo and modeling approaches to improve prediction of phosphorus availability in ruminants." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/52910.

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Improving prediction of P availability necessitates understanding of P digestion and absorption mechanism in ruminants. Greater knowledge of the interaction of P with other nutrients and the utilization of dietary P in the digestive tract will improve our ability to optimize P feeding and reduce P runoff in agricultural areas. In vivo experiments were performed and the data were used to reparamterize a model regarding P digestion and metabolism. The interaction of P and iron was investigated in lactating dairy cows by infusing 0, 200, 500, or 1250 mg/d Fe (equivalent to 0, 2, 5, or 12.5 mg Fe/L in drinking water) in the form of ferrous lactate solution into the abomasum of lactating cows. Phosphorus absorption was not negatively influenced by abomasally infused ferrous lactate, and the highest infusion (1250 mg Fe/d) approximates a drinking water iron content far above that found in most samples from the field. In the second study the effects of dietary P intake on intestinal P absorption was evaluated in eight growing Holstein steers fitted with permanent duodenal and ileal cannulas. Diets varying in P content (0.15%, 0.27%, 0.36% and 0.45%, DM basis) were fed , and increasing P intake increased the quantity of P absorbed from the small intestine linearly without affecting the absorption efficiency (mean = 59.6%). Only a small portion of P absorption occurred in large intestine and this was not affected by dietary P concentration. An absence of change of salivary P secretion at low dietary P suggested rumen function was prioritized during short-term P deficiency. Finally the data from these experiments along with four other studies were used to parameterize the P digestion and metabolism model of Hill et al. (2008) to provide a better understanding of the digestion and metabolism of P fractions in cattle. The data used were adequate to parameterize the digestive elements of the model with good precision, and the model structure appears to be appropriate with no significant mean or slope bias. The resulting model could be used to derive P bio-availabilities of commonly used feedstuffs in cattle production. Although the model explained the data used with no apparent bias, this does not guarantee that the model parameters are valid for all conditions. Additional data are needed to evaluate this model in a wider range of scenarios.
Ph. D.

10

McKim, Rebecca Lynn 1969. "Modeling changes in faunal use and availability on the Pajarito Plateau, New Mexico." Thesis, The University of Arizona, 1994. http://hdl.handle.net/10150/292002.

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This thesis tests the hypothesis that resource depletion accompanied aggregation on the Pajarito Plateau. It does so by examining changes in faunal resource availability and resource use during the Coalition and early Classic periods. The prehistoric deer population was estimated using precipitation data, following Young (1979). This estimation was used as a measure of potential resource availability for the periods concerned. Based upon the model, the mule deer population was expected to increase from the Coalition period to the early Classic period. Resource use was measured using faunal assemblages from 10 sites from the Pajarito Plateau. The sites examined in this thesis support various expectations which would suggest that resource depletion occurred on the Pajarito Plateau. It was found that changes in resource use could not be explained by environmental change alone. Thus, it appears that resource depletion on the Pajarito Plateau may have been due to human impact on the environment.

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Книги з теми "Availability Modeling":

1

), Travel Model Improvement Program (U S. Vehicle availability modeling. [Washington, D.C.?]: U.S. Dept of Transportation, Federal Highway Administration, Federak Transit Administration, Bureau of Transportation Statistics, Addistance Secretary for Transportation Policy, 2000.

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2

Schneeweiss, Winfrid G. Reliability modeling: (modeling in the fields of dependability, availability, maintainability, and safety engineering). Hagen: LiLoLe-Verlag, 2001.

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3

French, Timothy F. Comparison of operational availability modeling by TIGER and SESAME. Monterey, Calif: Naval Postgraduate School, 1994.

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4

Vergnaud, J. M. Assessing bioavailability of drug delivery systems: Mathematical modeling. Boca Raton, FL: Taylor & Francis/CRC Press, 2005.

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5

Wilson, Steven D. Hydrogeology and ground-water availability in southwest McLean and southeast Tazewell Counties: Aquifer modeling and final report. Champaign, IL: Illinois State Water Survey, 1998.

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6

United States. Environmental Protection Agency. Office of Transportation and Air Quality. EPA's approval of the MOVES2010a and EMFAC2007 emissions models for transportation conformity hot-spot analyses, and availability of modeling guidance: Questions and answers. 2nd ed. Washington, D.C.]: U.S. Environmental Protection Agency, Office of Transportation and Air Quality, 2010.

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7

Shooman, Martin L. Computer aided reliability, availability, and safety modeling for fault-tolerant computer systems with commentary on the HARP program: Final report research grant, NAG-1-1001. Farmingdale, NY: School of Electrical Engineering and Computer Science, Dept. of Computer Science, Long Island Center, 1991.

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8

Trivedi, Kishor S., and Andrea Bobbio. Reliability and Availability Engineering: Modeling, Analysis, and Applications. Cambridge University Press, 2017.

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9

Trivedi, Kishor S., and Andrea Bobbio. Reliability and Availability Engineering: Modeling, Analysis, and Applications. Cambridge University Press, 2017.

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10

Trivedi, Kishor S., and Andrea Bobbio. Reliability and Availability Engineering: Modeling, Analysis, and Applications. Cambridge University Press, 2017.

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Частини книг з теми "Availability Modeling":

1

Wang, Dazhi, and Kishor S. Trivedi. "Modeling User-Perceived Service Availability." In Service Availability, 107–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11560333_10.

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2

Toeroe, Maria, and Ferhat Khendek. "Overcoming Complexity: Formal Modeling Techniques at the Rescue." In Service Availability, 415–29. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119941378.ch16.

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3

Tokuno, Koichi, and Shigeru Yamada. "User-Perceived Software Service Availability Modeling with Reliability Growth." In Service Availability, 75–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-68129-8_8.

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4

Sahner, Robin, Kishor S. Trivedi, and Antonio Puliafito. "Reliability and Availability Modeling." In Performance and Reliability Analysis of Computer Systems, 155–202. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-2367-3_9.

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5

Van De Giesen, Nick, Luis J. Mata, Petra Döll, Arjen Hoekstra, Max Pfeffer, and Jorge A. Ramirez. "Modeling Water Availability: Scaling Issues." In Understanding the Earth System, 245–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56843-5_16.

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6

Höppner, Silke. "An Adaptive User-Interface-Agent Modeling Communication Availability." In User Modeling 2001, 127–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44566-8_13.

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7

Martins Maciel, Paulo Romero. "Modeling Availability Impact in Cloud Computing." In Springer Series in Reliability Engineering, 287–320. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30599-8_11.

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8

Petre, Luigia, Kaisa Sere, and Marina Waldén. "A Language for Modeling Network Availability." In Formal Methods and Software Engineering, 639–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11901433_35.

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9

Trivedi, Kishor S., Dong Seong Kim, and Xiaoyan Yin. "Multi-State Availability Modeling in Practice." In Springer Series in Reliability Engineering, 165–80. London: Springer London, 2011. http://dx.doi.org/10.1007/978-1-4471-2207-4_12.

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10

Tomek, Lorrie A., and Kishor S. Trivedi. "Fixed Point Iteration in Availability Modeling." In Fault-Tolerant Computing Systems, 229–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76930-6_20.

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Тези доповідей конференцій з теми "Availability Modeling":

1

Trivedi, Kishor S., Ranjith Vasireddy, David Trindade, Swami Nathan, and Rick Castro. "Modeling High Availability." In 2006 IEEE Pacific Rim International Symposium on Dependable Computing. IEEE, 2006. http://dx.doi.org/10.1109/prdc.2006.45.

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2

Milanovic, Nikola, Bratislav Milic, and Miroslaw Malek. "Modeling Business Process Availability." In 2008 IEEE Congress on Services Part 1 (SERVICES-1). IEEE, 2008. http://dx.doi.org/10.1109/services-1.2008.9.

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3

Bluvband, Zigmund, and Sergey Porotsky. "Availability growth modeling and assessment." In Integrity (RAMS). IEEE, 2011. http://dx.doi.org/10.1109/rams.2011.5754456.

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4

Dai, Bing Tian, and Hady W. Lauw. "Modeling Preferences with Availability Constraints." In 2013 IEEE International Conference on Data Mining (ICDM). IEEE, 2013. http://dx.doi.org/10.1109/icdm.2013.41.

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5

Wurbs, Ralph A. "Water Availability Modeling in Texas." In Joint Conference on Water Resource Engineering and Water Resources Planning and Management 2000. Reston, VA: American Society of Civil Engineers, 2000. http://dx.doi.org/10.1061/40517(2000)243.

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6

Yang, Song, Stojan Trajanovski, and Fernando A. Kuipers. "Availability-based path selection." In 2014 6th International Workshop on Reliable Networks Design and Modeling (RNDM). IEEE, 2014. http://dx.doi.org/10.1109/rndm.2014.7014929.

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7

Song, Tailiang, Xianzhen Bai, Qinqin Wang, and Liudong Xing. "Operational availability modeling and simulation evaluation." In 2012 Annual Reliability and Maintainability Symposium (RAMS). IEEE, 2012. http://dx.doi.org/10.1109/rams.2012.6175519.

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8

Brown, Justin, Randall Clendening, and Jerrell Stracener. "Availability Modeling for Complex System Design." In 2019 Annual Reliability and Maintainability Symposium (RAMS). IEEE, 2019. http://dx.doi.org/10.1109/rams.2019.8768915.

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9

Tu, Manghui, Dianxiang Xu, Zhonghang Xia, and Jicheng Fu. "Reach Availability Modeling of Replicated Services." In 2011 IEEE 35th Annual Computer Software and Applications Conference - COMPSAC 2011. IEEE, 2011. http://dx.doi.org/10.1109/compsac.2011.106.

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10

Meng Ji and Shao-hua Yu. "Availability modeling for reliable routing software." In DS-RT 2005 Proceedings. Ninth IEEE International Symposium on Distributed Simulation and Real-Time Applications. IEEE, 2005. http://dx.doi.org/10.1109/distra.2005.11.

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Звіти організацій з теми "Availability Modeling":

1

Tidwell, Vincent Carroll, Katie M. Zemlick, and Geoffrey Taylor Klise. Nationwide water availability data for energy-water modeling. Office of Scientific and Technical Information (OSTI), November 2013. http://dx.doi.org/10.2172/1121917.

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2

Witzke, Brian, J. Michael Gannon, and Richard Langel. Groundwater Availability Modeling, Silurian Aquifer, East-Central Iowa. Iowa City: Iowa Department of Natural Resources, November 2011. http://dx.doi.org/10.17077/rep.006546.

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3

Blakemore, Alex, and Gianfranco Ciardo. Integrated Environment for Performance, Reliability and Availability Modeling. Phase 1. Fort Belvoir, VA: Defense Technical Information Center, October 1995. http://dx.doi.org/10.21236/ada300206.

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4

Langel, Richard, and J. Michael Gannon. Groundwater Availability Modeling of the West Nishnabotna Aquifer in Iowa. Iowa City: Iowa Department of Natural Resources, September 2010. http://dx.doi.org/10.17077/rep.006482.

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5

Langel, Richard, Bill Bunker, Mary Howes, and J. Michael Gannon. Groundwater Availability Modeling of the Cambrian-Ordovician Aquifer in Iowa. Iowa City: Iowa Department of Natural Resources, July 2009. http://dx.doi.org/10.17077/rep.006477.

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6

McKay, Robert M., and J. Michael Gannon. Groundwater Availability Modeling of the Mississippian Aquifer North-Central Iowa. Iowa City: Iowa Department of Natural Resources, June 2013. http://dx.doi.org/10.17077/rep.006540.

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7

Rose, J., and K. Waren. Hydrogeology and groundwater availability at Big Sky, Montana. Montana Bureau of Mines and Geology, April 2022. http://dx.doi.org/10.59691/ommp9599.

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8

Witzke, Brian J., J. Michael Gannon, Bill Bunker, Mary Howes, Robert Rowden, and Raymond R. Anderson. Groundwater Availability Modeling of the Lower Dakota Aquifer in Northwest Iowa. Iowa City: Iowa Department of Natural Resources, October 2008. http://dx.doi.org/10.17077/rep.006479.

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9

Thorn, Dustin, and Matt Hubbard. Investigating the Relationship between Customer Wait Time and Operational Availability through Simulation Modeling. Fort Belvoir, VA: Defense Technical Information Center, December 2012. http://dx.doi.org/10.21236/ada576569.

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10

Gannon, J. Michael. Groundwater Availability Modeling, Des Moines River Aquifer, Palo Alto and Emmet Counties, Iowa. Iowa City: Iowa Department of Natural Resources, May 2011. http://dx.doi.org/10.17077/rep.006510.

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