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Literatura académica sobre el tema "Simulation of joint extremes"

Autor: Grafiati

Publicado: 25 de mayo de 2024

Última modificación: 19 de julio de 2025

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Artículos de revistas sobre el tema "Simulation of joint extremes"

Phalitnonkiat, Pakawat, Peter G. M. Hess, Mircea D. Grigoriu, et al. "Extremal dependence between temperature and ozone over the continental US." Atmospheric Chemistry and Physics 18, no. 16 (2018): 11927–48. http://dx.doi.org/10.5194/acp-18-11927-2018.

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Abstract. The co-occurrence of heat waves and pollution events and the resulting high mortality rates emphasize the importance of the co-occurrence of pollution and temperature extremes. Through the use of extreme value theory and other statistical methods, tropospheric surface ozone and temperature extremes and their joint occurrence are analyzed over the United States during the summer months (JJA) using measurements and simulations of the present and future climate and chemistry. Five simulations from the Chemistry-Climate Model Initiative (CCMI) reference experiment using specified dynamics (REFC1SD) were analyzed: the CESM1 CAM4-chem, CHASER, CMAM, MOCAGE and MRI-ESM1r1 simulations. In addition, a 25-year present-day simulation branched off the CCMI REFC2 simulation in the year 2000 and a 25-year future simulation branched off the CCMI REFC2 simulation in 2100 were analyzed using CESM1 CAM4-chem. The last two simulations differed in their concentration of carbon dioxide (representative of the years 2000 and 2100) but were otherwise identical. In general, regions with relatively high ozone extremes over the US do not occur in regions of relatively high temperature extremes. A new metric, the spectral density, is developed to measure the joint extremal dependence of ozone and temperature by evaluating the spectral dependence of their extremes. While in many areas of the country ozone and temperature are highly correlated overall, the correlation is significantly reduced when examined on the higher end of the distributions. Measures of spectral density are less than about 0.35 everywhere, suggesting that at most only about a third of the time do extreme temperatures coincide with extreme ozone. Two regions of the US have the strongest measured extreme dependence of ozone and temperature: the northeast and the southeast. The simulated future increase in temperature and ozone is primarily due to a shift in their distributions, not to an increase in their extremes. The locations where the right-hand side of the temperature distribution does increase (by up to 30 %) are consistent with locations where soil–moisture feedback may be expected. Future changes in the right-hand side of the ozone distribution range regionally between +20 % and −10 %. The location of future increases in the high-end tail of the ozone distribution are weakly related to those of temperature with a correlation of 0.3. However, the regions where the temperature extremes increase are not located where the extremes in ozone are large, suggesting a muted ozone response.

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Yao, L., W. Dongxiao, Z. Zhenwei, H. Weihong, and S. Hui. "A Monte Carlo simulation of multivariate general Pareto distribution and its application." Ocean Science Discussions 11, no. 6 (2014): 2733–53. http://dx.doi.org/10.5194/osd-11-2733-2014.

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Abstract. This paper presents a multivariate general Pareto distribution (MGPD) method and builds a method for solving MGPD through the use of a Monte Carlo simulation for marine environmental extreme-value parameters. The simulation method has proven to be feasible in the analysis of the joint probability of wave height and its concomitant wind from a hydrological station in the South China Sea (SCS). The MGPD is the natural distribution of the multivariate peaks-over-threshold (MPOT) sampling method, and is based on the extreme-value theory. The existing dependence functions can be used in the MGPD, so it may describe more variables which have different dependence relationships. The MGPD method improves the efficiency of the extremes in raw data. For the wave and the concomitant wind from a period of 23 years (1960–1982), the number of the wave and wind selected is averaged to 19 per year. For the joint conditional probability of the MGPD, the relative error is rather small in the Monte Carlo simulation method.

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Muheki, Derrick, Axel A. J. Deijns, Emanuele Bevacqua, Gabriele Messori, Jakob Zscheischler, and Wim Thiery. "The perfect storm? Co-occurring climate extremes in East Africa." Earth System Dynamics 15, no. 2 (2024): 429–66. http://dx.doi.org/10.5194/esd-15-429-2024.

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Abstract. Co-occurring extreme climate events exacerbate adverse impacts on humans, the economy, and the environment relative to extremes occurring in isolation. While changes in the frequency of individual extreme events have been researched extensively, changes in their interactions, dependence, and joint occurrence have received far less attention, particularly in the East African region. Here, we analyse the joint occurrence of pairs of the following extremes within the same location and calendar year over East Africa: river floods, droughts, heatwaves, crop failures, wildfires and tropical cyclones. We analyse their co-occurrence on a yearly timescale because some of the climate extremes we consider play out over timescales up to several months. We use bias-adjusted impact simulations under past and future climate conditions from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). We find an increase in the area affected by pairs of these extreme events, with the strongest increases for joint heatwaves and wildfires (+940 % by the end of the century under RCP6.0 relative to present day), followed by river floods and heatwaves (+900 %) and river floods and wildfires (+250 %). The projected increase in joint occurrences typically outweighs historical increases even under an aggressive mitigation scenario (RCP2.6). We illustrate that the changes in the joint occurrences are often driven by increases in the probability of one of the events within the pairs, for instance heatwaves. The most affected locations in the East Africa region by these co-occurring events are areas close to the River Nile and parts of the Congo basin. Our results overall highlight that co-occurring extremes will become the norm rather than the exception in East Africa, even under low-end warming scenarios.

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Tencer, Bárbara, Andrew Weaver, and Francis Zwiers. "Joint Occurrence of Daily Temperature and Precipitation Extreme Events over Canada." Journal of Applied Meteorology and Climatology 53, no. 9 (2014): 2148–62. http://dx.doi.org/10.1175/jamc-d-13-0361.1.

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AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.

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Sanga, Bharat, Reeta Wattal, and D. S. Nagesh. "An FEA based study of thermal behaviour of ultrasonically welded phosphor bronze sheets." Journal of Mechanical Engineering and Sciences 15, no. 2 (2021): 8057–71. http://dx.doi.org/10.15282/jmes.15.2.2021.10.0635.

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The ultrasonic joining of phosphor bronze sheets is analyzed using a 3-D finite element model for the study and prediction of the thermal profiles at the weld interface. The heat fluxes are calculated and assigned as boundary conditions during the thermal simulation. The forecast of temperature is done under various welding conditions. The maximum temperature obtained by transient simulation at the weld interface is 366.74℃. The continuous reduction in the temperature is observed towards the extremes of the weld metal. The sonotrode and the anvil achieve a lower temperature in comparison to the weld interface. The effect of clamping force and bonding ratio on the interface temperature is observed as positive. The model is validated with an error of 1.576% between the observed and predicted temperature results and a correlation co-efficient 0.96 is established between the simulated temperature results and the weld strength. Sufficiently strong joints were obtained at the optimum welding conditions with 74% joint efficiency. It is evident that the interface temperature has a strong linear relationship with joint strength and is a major deciding factor for achieving strong joints.

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Anderson, Dylan, Peter Ruggiero, Fernando J. Mendez, et al. "TIME-VARYING EMULATOR FOR SHORT- AND LONG-TERM ANALYSIS OF COASTAL FLOODING (TESLA-FLOOD)." Coastal Engineering Proceedings, no. 36 (December 30, 2018): 4. http://dx.doi.org/10.9753/icce.v36.currents.4.

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The ability to predict coastal flooding events and associated impacts has emerged as a primary societal need within the context of projected sea level rise (SLR) and climate change. The duration and extent of flooding is the result of nonlinear interactions between multiple environmental forcings (oceanographic, meteorological, hydrological) acting at varying spatial (local to global) and temporal scales (hours to centuries). Individual components contributing to total water levels (TWLs) include astronomical tides, monthly sea level anomalies, storm surges, and wave setup. Common practices often use the observational record of extreme water levels to estimate return levels of future extremes. However, such projections often do not account for the individual contribution of processes resulting in compound TWL events, nor do they account for time-dependent probabilities due to seasonal, interannual, and long-term oscillations within the climate system. More robust estimates of coastal flooding risk require the computation of joint probabilities and the simulation of hypothetical TWLs to better constrain the projection of extremes (Serafin [2014]).

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Brunner, Manuela I., and Eric Gilleland. "Stochastic simulation of streamflow and spatial extremes: a continuous, wavelet-based approach." Hydrology and Earth System Sciences 24, no. 8 (2020): 3967–82. http://dx.doi.org/10.5194/hess-24-3967-2020.

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Abstract. Stochastically generated streamflow time series are used for various water management and hazard estimation applications. They provide realizations of plausible but as yet unobserved streamflow time series with the same temporal and distributional characteristics as the observed data. However, the representation of non-stationarities and spatial dependence among sites remains a challenge in stochastic modeling. We investigate whether the use of frequency-domain instead of time-domain models allows for the joint simulation of realistic, continuous streamflow time series at daily resolution and spatial extremes at multiple sites. To do so, we propose the stochastic simulation approach called Phase Randomization Simulation using wavelets (PRSim.wave) which combines an empirical spatio-temporal model based on the wavelet transform and phase randomization with the flexible four-parameter kappa distribution. The approach consists of five steps: (1) derivation of random phases, (2) fitting of the kappa distribution, (3) wavelet transform, (4) inverse wavelet transform, and (5) transformation to kappa distribution. We apply and evaluate PRSim.wave on a large set of 671 catchments in the contiguous United States. We show that this approach allows for the generation of realistic time series at multiple sites exhibiting short- and long-range dependence, non-stationarities, and unobserved extreme events. Our evaluation results strongly suggest that the flexible, continuous simulation approach is potentially valuable for a diverse range of water management applications where the reproduction of spatial dependencies is of interest. Examples include the development of regional water management plans, the estimation of regional flood or drought risk, or the estimation of regional hydropower potential. Highlights. Stochastic simulation of continuous streamflow time series using an empirical, wavelet-based, spatio-temporal model in combination with the parametric kappa distribution. Generation of stochastic time series at multiple sites showing temporal short- and long-range dependence, non-stationarities, and spatial dependence in extreme events. Implementation of PRSim.wave in R package PRSim: Stochastic Simulation of Streamflow Time Series using Phase Randomization.

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Barbariol, Francesco, Alvise Benetazzo, Sandro Carniel, and Mauro Sclavo. "Space–Time Wave Extremes: The Role of Metocean Forcings." Journal of Physical Oceanography 45, no. 7 (2015): 1897–916. http://dx.doi.org/10.1175/jpo-d-14-0232.1.

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AbstractWave observations and modeling have recently demonstrated that wave extremes of short-crested seas are poorly predicted by statistics of time records. Indeed, the highest waves pertain to wave groups at focusing that have space–time dynamics. Therefore, the statistical prediction of extremes of short-crested sea states should rely on the multidimensional random wave fields’ assumption. To adapt wave extreme statistics to the space–time domain, theoretical models using parameters of the directional wave spectrum have been recently developed. In this paper, the influence of metocean forcings (wind conditions, ambient current, and bottom depth) on these parameters and hence on wave extremes is studied with a twofold strategy. First, parametric spectral formulations [Pierson–Moskowitz and Joint North Sea Wave Project (JONSWAP) frequency spectra with cos2 directional distribution function] are considered to represent the dependence of wave extremes upon wind speed, fetch, and space domain size. Afterward, arbitrary conditions are simulated by using the SWAN numerical model adapted to store the spectral parameters, and the effects on extremes of current- and depth-induced shoaling are investigated. Preliminarily, the space–time extremes prediction model adopted is assessed by means of numerical simulations of Gaussian random seas. Compared to the significant wave height of the sea state and for a given space domain size, results show that space–time extremes are enhanced by opposite currents, whereas they are weakened by increasing wind conditions (wind speed and fetch) and by depth-induced shoaling. In this respect, the remarkable contribution to wave extremes of the size of the space domain is substantiated.

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Vosniakos, G.-C., and A. Chronopoulos. "Industrial robot path planning in a constraint-based computer-aided design and kinematic analysis environment." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 223, no. 5 (2009): 523–33. http://dx.doi.org/10.1243/09544054jem1234.

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Paths of industrial robots are easier to plan by using constraints on accurate computer-aided design (CAD) models of both objects representing the real industrial robotic cell and virtual objects representing the auxiliary geometry that is necessary to define path points. The motion path normally needs to be split into segments possessing uniform characteristics, e.g. common active joints, at points usually corresponding to position or velocity extremes. Each segment corresponds either to point-to-point motion or to constrained motion. Point-to-point motion is implemented by interpolating between original and final position of each joint separately, positions being determined through inverse kinematics in the CAD environment and motion being imparted to each joint directly. Constrained motion may be defined using several alternatives materialized with stationary and moving virtual objects, real robot joints, virtual joints, contact constraints, and motion constraints. Motion duration is specified after the corresponding path geometry has been specified, by exploiting maximum active joints velocity as well as end-tool velocity as dictated by the process. Collisions are detected using available functionality and are alleviated interactively. A user-defined number of interpolated robot poses are generated per segment. These are all ‘sewn’ together at the motion synthesis stage and frame-based simulation is generated. A realistic robotic lathe loading/unloading example is used to verify the use of the above notions and tools.

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Bajda, Mirosław. "Predicting the working time of multi-ply conveyor belt splices in underground mines." Mining Science 31 (2024): 259–74. https://doi.org/10.37190/msc243115.

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Knowledge about the service life of the splices before they are made is extremely valuable information for the users of belt conveyors because having additional technical data about the conveyor and the place of its installation makes it possible to forecast the working time of the joint. The results of calculations of the service life of joints of multi-ply textile conveyor belts are presented. The calculations were made using a computer program specially created for this purpose, which predicts the service life of the joints before they are made. The program was created due to the implementation of research grant No. PBS3/A2/17/2015 financed by the National Center for Research and Development (NCBiR). The simulation results were compared with the data showing the working time of the joint in actual conditions of its operation in an underground mine. Comparing the simulation results of failure-free operation of joints with accurate data on the operation time of joints in the analyzed mines, it was noticed that the joints could work longer. Depending on the mine, it was from 3 to 8 months. The simulation did not consider sudden phenomena that could occur during the belt and joint operation. It was assumed that the belt operated smoothly, did not run off the conveyor, did not rub against the conveyor structure, etc. Each such phenomenon shortens its working time. The simulation results also showed that the joint made by hot vulcanization is characterized by a longer working time than the one made by cold gluing.

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Tesis sobre el tema "Simulation of joint extremes"

Legrand, Juliette. "Simulation and assessment of multivariate extreme models for environmental data." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASJ015.

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L'estimation précise des probabilités d'occurrence des événements extrêmes environnementaux est une préoccupation majeure dans l'évaluation des risques. Pour l'ingénierie côtière par exemple, le dimensionnement de structures implantées sur ou à proximité des côtes doit être tel qu'elles résistent aux événements les plus sévères qu'elles puissent rencontrer au cours de leur vie. Cette thèse porte sur la simulation d'événements extrêmes multivariés, motivée par des applications aux hauteurs significatives de vagues, et sur l'évaluation de modèles de prédiction d'occurrence d'événements extrêmes.Dans la première partie du manuscrit, nous proposons et étudions un simulateur stochastique qui génère conjointement, en fonction de certaines conditions d'état de mer au large, des extrêmes de hauteur significative de vagues (Hs) au large et à la côte. Pour cela, nous nous appuyons sur l'approche par dépassements de seuils bivariés et nous développons un algorithme de simulation non-paramétrique de lois de Pareto généralisées bivariées. À partir de ce simulateur d'événements cooccurrents, nous dérivons un modèle de simulation conditionnel. Les deux algorithmes de simulation sont mis en oeuvre sur des expériences numériques et appliqués aux extrêmes de Hs près des côtes bretonnes françaises. Un autre développement est traité quant à la modélisation des lois marginales des Hs. Afin de prendre en compte leur non-stationnaritée, nous adaptons une extension de la loi de Pareto généralisée, en considérant l'effet de la période et de la direction pic sur ses paramètres.La deuxième partie de cette thèse apporte un développement plus théorique. Pour évaluer différents modèles de prédiction d'extrêmes, nous étudions le cas spécifique des classifieurs binaires, qui constituent la forme la plus simple de prévision et de processus décisionnel : un événement extrême s'est produit ou ne s'est pas produit. Des fonctions de risque adaptées à la classification binaire d'événements extrêmes sont développées, ce qui nous permet de répondre à notre deuxième question. Leurs propriétés sont établies dans le cadre de la variation régulière multivariée et de la variation régulière cachée, permettant de considérer des formes plus fines d'indépendance asymptotique. Ces développements sont ensuite appliqués aux débits de rivière extrêmes Accurate estimation of the occurrence probabilities of extreme environmental events is a major issue for risk assessment. For example, in coastal engineering, the design of structures installed at or near the coasts must be such that they can withstand the most severe events they may encounter in their lifetime. This thesis focuses on the simulation of multivariate extremes, motivated by applications to significant wave height, and on the evaluation of models predicting the occurrences of extreme events.In the first part of the manuscript, we propose and study a stochastic simulator that, given offshore conditions, produces jointly offshore and coastal extreme significant wave heights (Hs). We rely on bivariate Peaks over Threshold and develop a non-parametric simulation scheme of bivariate generalised Pareto distributions. From such joint simulator, we derive a conditional simulation model. Both simulation algorithms are applied to numerical experiments and to extreme Hs near the French Brittanny coast. A further development is addressed regarding the marginal modelling of Hs. To take into account non-stationarities, we adapt the extended generalised Pareto model, letting the marginal parameters vary with the peak period and the peak direction.The second part of this thesis provides a more theoretical development. To evaluate different prediction models for extremes, we study the specific case of binary classifiers, which are the simplest type of forecasting and decision-making situation: an extreme event did or did not occur. Risk functions adapted to binary classifiers of extreme events are developed, answering our second question. Their properties are derived under the framework of multivariate regular variation and hidden regular variation, allowing to handle finer types of asymptotic independence. This framework is applied to extreme river discharges

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Li, Qinglan 1971. "Statistical downscaling and simulation of daily temperature extremes." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99521.

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There is now a broad scientific consensus that the global climate is changing in ways that could have a profound impact on human society and the natural environment over the coming decades. In particular, changes in the frequency and magnitude of extreme temperatures are likely to have more substantial impacts on the environment and human activities than changes in the mean temperature. The present study is therefore addressing three main objectives: (a) to propose a systematic data analysis method for characterizing the variability of daily extreme temperatures at different sites; (b) to develop new statistical downscaling models that could accurately describe the linkage between large-scale climate variables and the characteristics of temperature extremes at a local site; and (c) to develop a stochastic method for simulating accurately the extreme temperature processes. Firstly, a systematic data analysis procedure was proposed for analyzing the variability of daily maximum (Tmax) and minimum (Tmin) temperature characteristics. The suggested procedure consists of performing a detailed statistical analysis of twelve relevant temperature indices that are important for various practical application purposes: mean of diurnal temperature range, frost season length, growing season length, freeze and thaw cycle, 90th percentile of Tmax, 10th percentile of Tmin, means and standard deviations of Tmax, Tmin, and the daily mean temperature. The suggested method was applied to the analysis of daily Tmax and Tmin data for 20 stations in Quebec. The available records used are different from station to station, varying from 44 years to 107 years. In general, it was found that, depending on the temperature index considered as well as on the particular season of the year, there are some significant increasing or decreasing trends at some locations in Quebec. Results of this analysis would provide valuable information on the temporal and spatial variations of daily extreme temperature processes in the region. Furthermore, it can be observed that no systematic spatial variability of the increasing or decreasing trends of any of the twelve temperature indices considered could be identified for a given area in Quebec. Secondly, two new statistical downscaling models were proposed using the stepwise and robust regression methods in order to describe the linkage between largescale climate variables and the characteristics of Tmax and Tmin at a local site. The performance of these two models was tested using daily extreme temperature data available at Dorval Airport station in Quebec and the NCEP data for 25 different climate variables for the 1961-1990 period. It was found that the proposed stepwise and robust regression downscaling models can provide accurate estimates of fundamental statistical and physical properties of Tmax and Tmin. In addition, it has been observed that three climate variables, the mean sea level pressure, the 850hPa-geopotential height, and the near surface specific humidity, had the most significant effect on Tmax and Tmin at Dorval Airport. Furthermore, as compared with the popular SDSM model, the stepwise and robust regression models can provide more accurate estimates of the local Tmax and Tmin characteristics. In particular, the robust regression model was found to be the most accurate. Finally, a new stochastic simulation procedure was developed in this study for simulating the Tmax and Tmin temperature time series at a local site using the combination of the first-order autoregressive AR(1) model and the SVD technique. Results of the evaluation of the proposed AR(1)-SVD simulation method using daily extreme temperature data at Dorval Airport for the 1961-1990 period have indicated the feasibility of this method in describing accurately the observed basic statistical properties (mean, standard deviation, and first order autocorrelation) of the daily Tmax and Tmin time series at a local site.

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Oesting, Marco [Verfasser]. "Analysis and simulation of multivariate and spatial extremes / Marco Oesting." Siegen : Universitätsbibliothek der Universität Siegen, 2019. http://d-nb.info/1238353541/34.

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Casson, Edward Anthony. "Stochastic methodology for the extremes and directionality of meteorological processes." Thesis, Lancaster University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.287095.

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Wu, Elizabeth. "Spatio-Temporal Data Mining and Analysis of Precipitation Extremes." Thesis, The University of Sydney, 2008. https://hdl.handle.net/2123/28120.

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The work in this thesis aimed to discover new ways to analyse and mine information about precipitation extremes in South America from spatio-temporal data. This was done in two ways. First, analysis was performed through the use of statistical measures that provided insight into the behaviour of precipitation extremes between regions. Second, a new spatio-temporal outlier detection algorithm was introduced to discover moving outliers from the data.

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VanLandingham, Steve. "Applications of Joint Tactical Simulation modeling." Thesis, Monterey, California. Naval Postgraduate School, 1997. http://hdl.handle.net/10945/7975.

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Approved for public release; distribution is unlimited Advances in technology allow Computer Simulation Models (CSM) to be used as a powerful tool to aid military decision makers. This thesis explores the usefulness of one of these models, the Joint Tactical Simulation (JTS). First, this thesis outlines the information and tasks required to run JTS, which will give the reader a basic understanding of the program and how much effort it requires. Next, it describes the scenario presented in this thesis by detailing the methodology of terrain development, listing the assets required and the mission concept employed. It concludes by discussing some of the advantages and disadvantages of JTS followed by a reevaluation of the simulation and its possible uses. The concluding appendix is a tutorial that guides the reader through an amphibious assault modeled on the UNIX-based computer systems at the Naval Postgraduate School's (NPS) Secure Systems Technology Laboratory. It was designed to be accomplished in less than four hours and give the user an opportunity to run a simulation while conducting minimal interaction

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Revel, Aldric. "Nuclear forces at the extremes." Thesis, Normandie, 2018. http://www.theses.fr/2018NORMC227/document.

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L’émission de paires de neutrons par les noyaux riches en neutrons 18C et 20O (isotones N = 12) est étudié par réactions de knock-out d’un nucléon des faisceaux secondaires 19N et 21O, peuplant ainsi des états non liés jusqu’à 15 MeV au-dessus de leur seuil d’émission deux neutrons. L’analyse des corrélations des triples coïncidences fragment+n+n montre que la décroissance 19N(−1p)→18C → 16C+n+n est clairement dominée par l’émission directe de paires. Les corrélations n-n, les plus grandes jamais observées, suggèrent la prédominance d’un coeur de 14C entouré de quatre neutrons arrangés en paires très corrélées. De plus, une importante compétition du mode de décroissance séquentiel est observée dans la décroissance 21O(−1n) → 20O → 18O+n+n, interprétée par la déformation causée par le knock-out d’un neutron très lié ayant pour effet de casser le cœur de 16O et ainsi de réduire le nombre de paires.De plus, les états non liés du 26F et 28F sont étudiés. Les deux systèmes étant peuplés par knock-out d’un nucléon du 27F dans le cas du 26F et du 29Ne ou du 29F pour 28F. Cinq états ont été observés pour 26F avec en particulier l’état de plus basse énergie (0.39 MeV) identifié comme l’état 3+ résultant du couplage d5/2 ⊗ d3/2 . Pour 28F, cinq états ont aussi été observés et l’état fondamental (200 keV) a été identifié comme étant de parité négative, plaçant ainsi 28F dans l’îlot d’inversion The emission of neutron pairs from the neutron-rich N = 12 isotones 18C and 20O has been studied by high-energy nucleon knockout from 19N and 21O secondary beams, populating unbound states of the two isotones up to 15 MeV above their two-neutron emission thresholds. The analysis of triple fragment-n-n correlations shows that the decay 19N(−1p) → 18C → 16C+n+n is clearly dominated by direct pair emission. The two-neutron correlation strength, the largest ever observed, suggests the predominance of a 14C core surrounded by four neutrons arranged in strongly correlated pairs. On the other hand, a significant competition of a sequential branch is found in the decay 21O(−1n) → 20O → 18O+n+n, attributed to its formation through the knockout of a deeply-bound neutron that breaks the 16O core and reduces the number of pairs.Moreover, unbound states in 26F and 28F have been studied. The two systems were probed using single-nucleon knockout reaction from secondary beams of 27F respectively in the case of 26F, and 29Ne and 29F for 28F. Five possible states have been identified in 26F, with in particular the lowest energy one (0.39 MeV) being identified as the 3+ state resulting from the d5/2 ⊗ d3/2 coupling. In the case of 28F, five unbound state have also been observed and in particular its ground state (200 keV) has been identified as a negative parity state, meaning that 28F is located inside the island of inversion

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Nykänen, Robin. "Simulation of Bolted Joint with Frictional Contacts." Thesis, Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-74490.

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An easy and reliable way to join two or more components is to use a bolted joint. When torque is applied on the bolt head, a clamp force is achieved. However about 90% of this torque will be used just to overcome the friction in the interfaces. To be able to fasten these in an ecient and precise manner the friction in the bolt threads and underhead area is important to understand. This is currently investigated at Atlas Copco by using a friction test rig, FTR, which measures the clamp force, the total torque and the shank torque. To evaluate the test rig and also to be able to evaluate dierent friction models, a parameterised simulation model of a bolted joint is built. This is a 3D-model of the joint containing a bolt, a nut and a test specimen. The stiness and frictional behaviour of the FTR is used in the model to get a good comparison between these two. Dierent contact formulations and settings are tested to achieve a good model. Also, mesh size, step size and material models are evaluated to see the eect of these. The results show a good correlation between the FTR data and the simulation model. For the total torque to clamp force ratio a dierence of about 1% is achieved. The average dierence in shank torque and underhead torque is at 3.1% and -1.6% respectively. The pressure distribution for this model is shown to be unevenly distributed along the threads. This is minimized by softening the contact, but this instead increases the error between the FTR data and the simulation model. For the evaluation of friction models that are based on the contact pressure this needs to be investigated further to nd a good compromise between the contact pressure and the frictional behaviour.

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Sullivan, Mark James. "A methodology for evaluating a joint mobilizatoin plan using the Joint Theater Level Simulation (JTLS)." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1996. http://handle.dtic.mil/100.2/ADA321112.

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Boucher, Alexandre. "Conditional joint simulation of random fields on block-support /." St. Lucia, Qld, 2003. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe17169.pdf.

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Libros sobre el tema "Simulation of joint extremes"

Office, General Accounting. Joint simulation training. The Office, 1994.

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Office, General Accounting. Joint simulation training. The Office, 1994.

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United States. General Accounting Office. National Security and International Affairs Division, ed. Joint simulation training. The Office, 1994.

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Electronics Manufacturing Productivity Facility (U.S.), ed. Solder joint rework simulation analysis. The Facility, 1990.

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VanLandingham, Steve. Applications of Joint Tactical Simulation modeling. Naval Postgraduate School, 1997.

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United States. Joint Chiefs of Staff, ed. Joint modeling and simulation evolutionary overview. Joint Chief of Staff, 1994.

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Brown, SA, LN Gilbertson, and VD Good, eds. Wear of Articulating Surfaces: Understanding Joint Simulation. ASTM International, 2006. http://dx.doi.org/10.1520/stp1472-eb.

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Steenman, G. J. J. Modelling and simulation of a manipulator joint. National Aeronautical Laboratories, 1987.

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Sullivan, Mark James. A methodology for evaluating a joint mobilizatoin plan using the Joint Theater Level Simulation (JTLS). Naval Postgraduate School, 1996.

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E, Barr Ronald, Abraham Lawrence D, and United States. National Aeronautics and Space Administration., eds. A musculoskeletal model of the elbow joint complex. National Aeronautics and Space Administration, 1993.

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Capítulos de libros sobre el tema "Simulation of joint extremes"

Sharma, Ashish, and Fiona M. Johnson. "Latest Advances and Challenges in Extreme Flood 3D Simulation." In Arts, Research, Innovation and Society. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56114-6_3.

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AbstractThis chapter canvasses the latest developments in the modelling and communication of environmental extremes, with a focus on floods. Three scenarios are explored. The first refers to real-time prediction, including the current modelling basis that is adopted, and the visualisation/communication strategies in place. The second refers to an environmental extreme event that is conditional to a failure scenario, as is the case when an existing infrastructure (i.e. levee or spillway in an extreme flood) fails. The third, more complex scenario is the occurrence of a compound or joint extreme, possibly in the future, where extreme storms will intensify. A compound extreme here could represent a flood event that follows from an incident of rare storm conditions on a fire-damaged landscape. While the modelling challenges are significant, visualisation is even more challenging, as the scenario occurs under a hypothetical future. Demonstrating how coupled models can support the anticipation of extreme event scenarios, the chapter considers implications for risk assessment and communication that can support future preparedness and resilience. Surveying knowledge gaps that still need to be bridged, the authors formulate a list of key requirements in the fields of data availability, processing and representation.

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Schwitalla, Thomas, Volker Wulfmeyer, and Kirsten Warrach-Sagi. "Seasonal Simulation of Weather Extremes." In High Performance Computing in Science and Engineering ' 17. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-68394-2_26.

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Harr, Patrick A., Antoni Jordi, and Luke Madaus. "Analysis of the Future Change in Frequency of Tropical Cyclone-Related Impacts Due to Compound Extreme Events." In Hurricane Risk in a Changing Climate. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08568-0_5.

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AbstractTropical cyclone-related hazards are often comprised of compound, connected events that individually amplify the total impacts. Often, hazard risk assessments focus on one factor rather than the compound nature of multiple forcing mechanisms. It is possible that extreme event analysis in a univariate context may underestimate the probabilities and impacts of extreme events. In this study, a framework addresses multivariate analysis of risk due to compound hazards related to tropical cyclone characteristics. Combinations of observations and simulations are used to identify possible frequencies of annual chance extreme events forced via connected individual events. The framework emphasizes the statistical dependence of multiple physical variables that contribute to extreme compound events when individual events are not extreme.To make the analysis clear, specific locations are analyzed using both univariate and a joint analysis. The joint analysis is conducted using copula functions to remove the restriction that marginal distributions need come from the same family of probability functions. The primary results suggest that univariate and joint return periods for key tropical cyclone-related hazards could shorten in the future and univariate frequency analysis may underestimate the magnitude of the extreme events because the univariate analyses do not account for the dependence structure between the paired environmental factors.

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Schwitalla, Thomas, Volker Wulfmeyer, and Kirsten Warrach-Sagi. "Seasonal Simulation of Weather Extremes (WRFXXXL)." In High Performance Computing in Science and Engineering ' 18. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13325-2_24.

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Zhang, Yu, Xiaodong Wang, Zhixiang Min, et al. "Adaptive Regulation of Cascade Reservoirs System Under Non-stationary Runoff." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6138-0_88.

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AbstractUnder the influence of climate change and human activities, the spatial and temporal distribution of river runoff has changed. The statistical characteristics of runoff such as mean, variance and extreme values have changed significantly. Hydrological stationarity has been broken, deepening the uncertainty of water resources and their utilization. Hydrological stationarity is a fundamental assumption of traditional water resources planning and management. The occurrence of non-stationarity will undoubtedly have an impact on the operation and overall benefits of reservoirs, and may even threaten the safety of reservoirs and water resources. There is uncertainty as to whether reservoirs can operate safely and still achieve their design benefits under the new runoff conditions. Therefore, it is important to carry out adaptive regulation of reservoirs in response to non-stationary runoff. Based on the multi-objective theory of large system, a multi-objective joint scheduling model of the terrace reservoir group is constructed for adaptive regulation simulation. A set of combination schemes based on optimal scheduling, flood resource utilization, water saving is constructed. The adaptive regulation is validated using a real-world example of the Xiluodu cascade and Three Gorges cascade reservoirs system in Yangtze River, China. The adaptive regulation processes are analyzed by simulation and the adaptive regulation effects are evaluated. The results show that the non-stationary runoff in upper Yangtze River has had an impact on the comprehensive benefits of large hydropower projects. The use of non-engineering measures to improve flood resource utilization, adjust upstream water use behavior and optimize reservoir scheduling are effective means to reduce the negative impact of non-stationary runoff on cascade reservoirs system.

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Risser, Mark D., and Claudia Tebaldi. "Uncertainty and Extremes." In Uncertainty in Climate Change Research. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-85542-9_21.

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Abstract The impactful nature of extreme weather events calls for a robust quantification of their statistics, if risks are to be reliably characterized for both current and future hazards. In this chapter, using examples from recent events, we describe the rationale and some applications of the main statistical tools for such quantification, Extreme Value Analysis, EVA. We present the basic modeling of block maxima through Generalized Extreme Value distributions and that of threshold exceedances, through the Generalized Pareto distribution, and point at some effective extensions of the standard models that enable accounting for time-varying behavior and the joint modeling of phenomena over spatial domains. A section of this chapter is devoted to the description of how to characterize the uncertainty around the central estimates of various extreme metrics of interest, using both empirical (e.g., bootstrap) and formula-based approaches. The chapter concludes with a section that describes a particularly timely application of extreme event modeling: Extreme event attribution, by which the role of anthropogenic climate change in the behavior of a given class of observed events—usually having had large impacts—is quantified.

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Wang, Fengcai, and Hanyu Wang. "Biotribological Joint Simulation System." In Encyclopedia of Tribology. Springer US, 2013. http://dx.doi.org/10.1007/978-0-387-92897-5_1200.

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Falk, Michael. "Best Attainable Rate of Joint Convergence of Extremes." In Lecture Notes in Statistics. Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-3634-4_1.

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Klein, Gary, Paul J. Feltovich, Jeffrey M. Bradshaw, and David D. Woods. "Common Ground and Coordination in Joint Activity." In Organizational Simulation. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471739448.ch6.

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Hahn, Marjorie G., and Daniel C. Weiner. "On Joint Estimation of an Exponent of Regular Variation and an Asymmetry Parameter for Tail Distributions." In Sums, Trimmed Sums and Extremes. Birkhäuser Boston, 1991. http://dx.doi.org/10.1007/978-1-4684-6793-2_4.

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Actas de conferencias sobre el tema "Simulation of joint extremes"

Li, Jun, Dingcheng Li, Ping Li, and Gennady Samorodnitsky. "Generalized Pareto GAN: Generating Extremes of Distributions." In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650414.

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Pollinger, Theresa, Alexander Van Craen, Philipp Offenhäuser, and Dirk Pflüger. "Realizing Joint Extreme-Scale Simulations on Multiple Supercomputers—Two Superfacility Case Studies." In SC24: International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE, 2024. https://doi.org/10.1109/sc41406.2024.00104.

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Čakanišin, Adrián, and Mária Halenárová. "Monte Carlo as a Method for Examining of Business Changes in Tourism in Slovakia." In 25th International Joint Conference Central and Eastern Europe in the Changing Business Environment. Vydavateľstvo EKONÓM, 2025. https://doi.org/10.53465/ceecbe.2025.9788022552257.50-63.

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The business environment in tourism encompasses a set of factors influencing the establishment, development, and sustainability of businesses in this sector, including economic, legislative, and market conditions. The dynamics of this environment are crucial for the economic stability of the sector. The main objective of this paper is to model the development of business establishments and closures in the tourism sector based on historical data and the influence of selected factors. The data used for this study were obtained from the Statistical Office of the Slovak Republic upon request. To achieve this objective, correlation and regression analysis were employed to examine relationships between economic variables, while a Monte Carlo simulation was used to predict future business activity trends. The results indicated that there are only moderately statistically significant relationships between economic factors and business establishment or closure. Domestic tourists' expenditures showed a weak positive correlation with business formation, whereas expenditures on inbound tourism had the opposite effect. The Monte Carlo simulation suggested that, assuming historical trends continue, the number of newly established businesses will stabilize at around 7,500 per year, while the number of closed businesses will be approximately 6,000 per year. Extreme scenarios demonstrated that economic fluctuations could lead to significant deviations, with the pessimistic scenario predicting a higher number of business closures and the optimistic scenario indicating a more favorable sectoral development.

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Sando, Kosuke, Ryota Wada, Jeremy Rohmer, Sophie Lecacheux, and Philip Jonathan. "Estimating Joint Extremes of Significant Wave Height and Wind Speed for Tropical Cyclones." In ASME 2022 41st International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/omae2022-79888.

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Abstract We provide a computationally-efficient scheme for the estimation of joint extremes of significant wave height (Hs) and wind speed (U) for tropical cyclones. The method incorporates the simple spatial extremes method (STM-E) of Wada et al., 2019 (for spatial extremes of each of Hs and U) and the conditional extremes model of Heffernan and Tawn, 2004 (for conditional modeling of Hs given extreme U and U given extreme Hs). We demonstrate the methodology in application to data generated from hindcast simulations and track shifting of past tropical cyclones in the neighborhood of Réunion island in the Indian Ocean. Following the STM-E approach, spatio-temporal maxima (STM) and exposures (E) of both Hs and U are extracted for each tropical cyclone event. Marginal extreme value distributions are then estimated independently for the STM samples of Hs and U, providing a means for marginal extrapolation to long return periods. Exposure data are used to estimate densities for the spatial distribution of Hs and U. The conditional extremes model is then used to characterize the joint structure of STM for Hs and U, conditional on one of those variables being extreme. The estimated joint return values for Hs and U are validated by comparison with the original data.

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Jonathan, Philip, Kevin Ewans, and Jan Flynn. "On the Estimation of Ocean Engineering Design Contours." In ASME 2011 30th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2011. http://dx.doi.org/10.1115/omae2011-49886.

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Understanding extreme ocean environments and their interaction with fixed and floating structures is critical for offshore and coastal design. Design contours are useful to describe the joint behaviour of environmental, structural loading and response variables. We compare different forms of design contours, using theory and simulation, and present a new method for joint estimation of contours of constant exceedence probability for a general set of variables. The method is based on a conditional extremes model from the statistics literature, motivated by asymptotic considerations. We simulate under the conditional extremes model to estimate contours of constant exceedence probability. We also use the estimated conditional extremes model to estimate other forms of design contours, including those based on the First Order Reliability Method, without needing to specify the functional forms of conditional dependence between variables. We demonstrate the application of new method in estimation of contours of constant exceedence probability using measured and hindcast data from the Northern North Sea, the Gulf of Mexico and the North West Shelf of Australia, and quantify their uncertainties using a bootstrap analysis.

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Miao, Qingqing, Ankang Cheng, and Ying Min Low. "A Combination of Surrogate Model and Subset Simulation Method for Long-Term Extreme Response Analysis of Marine Risers." In ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/omae2023-101700.

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Abstract Evaluating the long-term extreme response of marine risers generally involves numerous time-consuming simulations of offshore structures in the time domain. Traditionally, the most rigorous reliability analysis method — Monte Carlo Simulation (MCS) is employed to account for both varying long-term environmental loads and short-term wave dynamics through extensive sampling. The number of simulations required by MCS is impractical when targeting long return periods to meet the industry standard. Subset Simulation (SS) as a variance reduction method has been widely applied to solve low failure probability problems. It significantly improves the efficiency of MCS while preserving accuracy. However, the computational time demanded by SS is still intolerable when simulating complex numerical models of offshore structures. Many recent studies have proposed the use of surrogate models, especially artificial neural networks (ANN) to predict the dynamic response of offshore structures for more efficient reliability analysis. This paper presents a method that combines artificial neural networks and subset simulation for long-term extreme response prediction. The ANN is well-constructed using designed training data sets of varying environmental conditions for accurate prediction. The efficiency and accuracy of the proposed method are verified through a case study to predict the extreme top riser stress of a floating production system. The structure is exposed to sea states characterized by a joint-probabilistic description of significant wave height (Hs), spectral period (Tp), and wave direction (θw). The proposed method has been shown to accurately estimate the long-term extremes with a remarkable reduction in computational time.

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Lopatoukhin, Leonid J., and Alexander V. Boukhanovsky. "Extreme and Freak Waves: Results of Measurements and Simulation." In ASME 2008 27th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/omae2008-57841.

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Main statistical characteristics of wave climate are considered in respect of offshore and ship design. Sophistication of ships and marine platforms and expansion of offshore activities to non-investigated regions means increasing of probability of being damaged by high waves. Hindcasting of wave fields, using the hydrodynamic models is main approach to wave climate investigation. Offshore wave measurements are used, mainly, for model verification. In compliance with existent regulatory documents and accepted practice applied statistical characteristics of wind waves are prescribed to operational and extreme. Operational statistics describe wind and wave conditions for the life span of a ship or an offshore structure. Extreme characteristics determine the so-called “structure survival regime”. There are a lot of approaches to calculations of extreme wave heights at a point (classical unconditional extremes). Their comparison shows the advantages and disadvantages of each of them. Freak (rogue) waves have some principal difference from extreme wave, mainly due to their form and asymmetry. In this sense freak wave is a multidimensional extreme. Contaminated distribution may be used for probability density approximation of joint extreme and freak wave. The example of recent freak wave event is the loss of ship “Aurelia” (Class of Russian Register of shipping) in February 2005 in the North Pacific. “Aurelia” sunk during passing of atmospheric front with veering wind, changing wind waves. Any wave has at least three dimensions: height, length, and crest length. The last parameter in mean is 3 times greater than wave length. Any information about three dimensional waves is of interest, as such measurements are unique. Some results of unique stereo wave measurements in the South Pacific where the wave as high as 24.9m was fixed (probably still almost the highest measured in the World Ocean), is presented and discussed.

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Leong, Darrell, Ying Min Low, and Youngkook Kim. "Long-Term Extreme Response Prediction of Mooring Lines Using Subset Simulation." In ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/omae2018-77064.

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Rigorous methods of probabilistic evaluations on long-term extremes are integral components in reliability research of offshore structures against overload events. Assessment across all conceivable sea states requires accounting for variabilities of long-term environmental loads and short-term stochastics, traditionally captured through extensive sampling or numerical expectation integration. The amount of environmental load variables render numerical integrations across high dimensions computationally prohibitive, while industry requirements of high return periods demand large Monte Carlo samples of timedomain dynamic analyses. Subset simulation offers a promising alternative to classic methods of statistical analysis, dividing ultra-low probability problems into subsets of intermediate probabilities. The methodology is uniquely advantageous for the assessment of heavy-tail overload events, which are unpredictably severe and occur at exceedingly rare frequencies. Subset simulation is experimented on a mooring case study situated in the hurricane-prone Gulf of Mexico, with the structure exposed to a joint-probabilistic description of wave, wind and current loads. The devised methodology is found to successfully evaluate hurricane-stimulated extreme events at ultra-low probabilities, beyond the feasible reach of Monte Carlo simulation at reasonable lead times.

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Vanem, Erik, Øystein Lande, and Elias Fekhari. "A Simulation Study on the Usefulness of the Bernstein Copula for Statistical Modeling of Metocean Variables." In ASME 2024 43rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/omae2024-121159.

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Abstract Probabilistic modelling of relevant environmental variables are crucial for the safe design and operation of marine structures. Using metocean data, a joint model of several variables can be estimated, including their dependence structure. Often, a conditional model is assumed for this, but recently the non-parametric Bernstein copula has been suggested as an alternative tool to model such dependencies. As a non-parametric technique, it is very flexible and often provides excellent goodness-of-fit to data with different dependencies. However, non-parametric techniques are prone to over-fitting and generalizability might be challenging. Moreover, care should be taken when using such models for extrapolation. In this paper, a simple simulation study will be presented that has investigated the usefulness of the Bernstein copula in modeling joint metocean variables. First, data have been generated from a known parametric joint distribution model. Then, a joint model based on the Bernstein copula is fitted to a subset of these data. Data simulated from the Bernstein-based models are then compared to data from the initial model. A particular focus will be put on how the model captures the dependencies in the extremes.

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Zhao, Yuliang, Sheng Dong, Zihao Yang, and Lance Manuel. "Estimating Design Loads for Floating Structures Using Environmental Contours." In ASME 2020 39th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/omae2020-18453.

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Abstract To ensure acceptable operation and/or survival of floating structures in extreme conditions, nonlinear time-domain simulations are often used to predict the structural response at the design stage. An environmental contour (EC) is commonly employed to identify critical sea states that serve as input for numerical simulations to assess the safety and performance of marine structures. In many studies, marginal and conditional distributions are defined to construct bivariate joint probability distributions for variables such as significant wave height and zero-crossing period; then, environmental contours can be constructed using the inverse first-order reliability method (IFORM). This study adopts alternative models to describe the generalized dependence structure between the environmental variables using copulas; the Nataf transformation is also discussed as a special case. Environmental contours are constructed, making use of measured wave data from moored buoys. Derived design loads are applied on a semi-submersible platform to assess possible differences. In addition, the long-term extremes of the tension of the mooring lines are estimated, considering uncertainties in the structural response using a 3D model (that includes response variability, ignored with the EC approach) to help establish more accurate design loads using Monte Carlo simulation. Results offer a clear indication of the extreme response of the floating structure based on the different models.

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Informes sobre el tema "Simulation of joint extremes"

Burchett, S. N., D. R. Frear, and M. M. Rashid. Computer simulation of solder joint failure. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/477670.

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Fikus, John. Global Information Enterprise Simulation (GIESIM) Joint Tactical Information Distribution Systems Simulation Experimentation. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada438999.

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Smith, Mark E. Distributed Test and Evaluation of Aerospace Systems: The Joint Advanced Distributed Simulation Joint Test Force Experience. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada378017.

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Shahani, Ashwin, and Sharon Glotzer. Probing the solidification of quasicrystals via joint experiment and simulation. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1856862.

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Sahu, Devaraj. A Study of the Defense Simulation Internet (DSI) for the Joint Advanced Distributed Simulation (JADS) Project. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada381147.

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Wilson, Jimmy H. USAF Concept of Operations for the Joint Simulation System (JSIMS), Version 1.0. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada358714.

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Baxley, Carl R. Mutual Security and Arms Reductions in Europe: A Joint Soviet-American Simulation Exercise. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada227289.

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Joyner, Tom, and Bob Maker. Joint Installed System Test Facility (JISTF) Infrared Sensor Simulation/Stimulation Enhancement: Dynamic Virtual Reality Simulation/Stimulation Technologies for Test, Evaluaiton, and Training. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada367704.

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Winters, Leslie S., and Andreas Tolk. The Integration of Modeling and Simulation with Joint Command and Control on the Global Information Grid. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada433871.

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Gagnon, Colleen M., and William K. Stevens. Use of Modeling and Simulation (M&S) in Support of Joint Command and Control Experimentation: Naval Simulation System (NSS) Support to Fleet Battle Experiments. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada461113.

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