Готові списки джерел за темами / Propagation uncertainties

Добірка наукової літератури з теми "Propagation uncertainties"

Автор: Grafiati

Опубліковано: 7 липня 2024

Оновлено: 7 липня 2024

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Статті в журналах з теми "Propagation uncertainties":

Demeyer, Séverine, Samuel K. Kristoffersen, Alexis Le Pichon, Franck Larsonnier, and Nicolas Fischer. "Contribution to Uncertainty Propagation Associated with On-Site Calibration of Infrasound Monitoring Systems." Remote Sensing 15, no. 7 (March 31, 2023): 1892. http://dx.doi.org/10.3390/rs15071892.

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To improve the confidence and quality of measurements produced by regional and international infrasound monitoring networks, this work investigates a methodology for propagating uncertainty associated with on-site measurement systems. We focus on the propagation of sensor calibration uncertainties. The proposed approach is applied to synthetic infrasound signals with known back azimuth and trace velocity, recorded at the array elements. Relevant input uncertainties are investigated for propagation targeting the incoming signals (noise), instrumentation (microbarometers, calibration system, wind noise reduction system), and the time-delay-of-arrival (TDOA) model (frequency band). Uncertainty propagation is performed using the Monte Carlo method to obtain the corresponding uncertainties of the relevant output quantities of interest, namely back azimuth and trace velocity. The results indicate that, at high frequencies, large sensor uncertainties are acceptable. However, at low frequencies (<0.1 Hz), even a 2∘ sensor phase uncertainty can lead to errors in the back azimuth of up to 5∘ and errors in the trace velocity of 20 m/s.

Dachs, Edgar. "Uncertainties in the activities of garnets and their propagation into geothermobarometry." European Journal of Mineralogy 6, no. 2 (March 31, 1994): 291–96. http://dx.doi.org/10.1127/ejm/6/2/0291.

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Matzke, Manfred. "Propagation of uncertainties in unfolding procedures." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 476, no. 1-2 (January 2002): 230–41. http://dx.doi.org/10.1016/s0168-9002(01)01438-3.

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Dong, W. M., W. L. Chiang, and F. S. Wong. "Propagation of uncertainties in deterministic systems." Computers & Structures 26, no. 3 (January 1987): 415–23. http://dx.doi.org/10.1016/0045-7949(87)90041-1.

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Frosio, Thomas, Thomas Bonaccorsi, and Patrick Blaise. "Manufacturing Data Uncertainties Propagation Method in Burn-Up Problems." Science and Technology of Nuclear Installations 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/7275346.

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A nuclear data-based uncertainty propagation methodology is extended to enable propagation of manufacturing/technological data (TD) uncertainties in a burn-up calculation problem, taking into account correlation terms between Boltzmann and Bateman terms. The methodology is applied to reactivity and power distributions in a Material Testing Reactor benchmark. Due to the inherent statistical behavior of manufacturing tolerances, Monte Carlo sampling method is used for determining output perturbations on integral quantities. A global sensitivity analysis (GSA) is performed for each manufacturing parameter and allows identifying and ranking the influential parameters whose tolerances need to be better controlled. We show that the overall impact of some TD uncertainties, such as uranium enrichment, or fuel plate thickness, on the reactivity is negligible because the different core areas induce compensating effects on the global quantity. However, local quantities, such as power distributions, are strongly impacted by TD uncertainty propagations. For isotopic concentrations, no clear trends appear on the results.

Wiwatanadate, Phongtape, and H. Gregg Claycamp. "Exact propagation of uncertainties in multiplicative models." Human and Ecological Risk Assessment: An International Journal 6, no. 2 (April 2000): 355–68. http://dx.doi.org/10.1080/10807030009380068.

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TANSEL, BERRIN. "PROPAGATION OF PARAMETER UNCERTAINTIES TO SYSTEM DEPENDABILITY." Civil Engineering and Environmental Systems 16, no. 1 (March 1999): 19–35. http://dx.doi.org/10.1080/02630259908970249.

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Butler, T., C. Dawson, and T. Wildey. "Propagation of Uncertainties Using Improved Surrogate Models." SIAM/ASA Journal on Uncertainty Quantification 1, no. 1 (January 2013): 164–91. http://dx.doi.org/10.1137/120888399.

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Hauptmanns, Ulrich. "Analytical propagation of uncertainties through fault trees." Reliability Engineering & System Safety 76, no. 3 (June 2002): 327–29. http://dx.doi.org/10.1016/s0951-8320(02)00016-9.

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van der Drift, J. H. M., and C. J. M. Heemskerk. "Propagation of Spatial Uncertainties Between Assembly Primitives." IFAC Proceedings Volumes 23, no. 3 (September 1990): 677–81. http://dx.doi.org/10.1016/s1474-6670(17)52638-5.

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Дисертації з теми "Propagation uncertainties":

Stanton, Richard. "Robust acoustic beamforming in the presence of channel propagation uncertainties." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/43535.

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Beamforming is a popular multichannel signal processing technique used in conjunction with microphone arrays to spatially filter a sound field. Conventional optimal beamformers assume that the propagation channels between each source and microphone pair are a deterministic function of the source and microphone geometry. However in real acoustic environments, there are several mechanisms that give rise to unpredictable variations in the phase and amplitudes of the propagation channels. In the presence of these uncertainties the performance of beamformers degrade. Robust beamformers are designed to reduce this performance degradation. However, robust beamformers rely on tuning parameters that are not closely related to the array geometry. By modeling the uncertainty in the acoustic channels explicitly we can derive more accurate expressions for the source-microphone channel variability. As such we are able to derive beamformers that are well suited to the application of acoustics in realistic environments. Through experiments we validate the acoustic channel models and through simulations we show the performance gains of the associated robust beamformer. Furthermore, by modeling the speech short time Fourier transform coefficients we are able to design a beamformer framework in the power domain. By utilising spectral subtraction we are able to see performance benefits over ideal conventional beamformers. Including the channel uncertainties models into the weights design improves robustness.

Bertin, Michaël. "Propagation des incertitudes dans un modèle réduit de propagation des infrasons." Thesis, Cachan, Ecole normale supérieure, 2014. http://www.theses.fr/2014DENS0020/document.

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La perturbation d’un système peut donner lieu à de la propagation d’onde. Une façon classique d’appréhender ce phénomène est de rechercher les modes propres de vibration du milieu. Mathématiquement, trouver ces modes consiste à rechercher les valeurs et fonctions propres de l’opérateur de propagation. Cependant, d’un point de vue numérique, l’opération peut s’avérer coûteuse car les matrices peuvent avoir de très grandes tailles. En outre, dans la plupart des applications, des incertitudes sont inévitablement associées à notre modèle. La question se pose alors de savoir s’il faut attribuer d’importantes ressources de calcul pour une simulation dont la précision du résultat n’est pas assurée. Nous proposons dans cette thèse une démarche qui permet à la fois de mieux comprendre l’influence des incertitudes sur la propagation et de réduire considérablement les coûts de calcul pour la propagation des infrasons dans l’atmosphère. L’idée principale est que tous les modes n’ont pas la même importance et souvent, seule une poignée d’entre eux suffit à décrire le phénomène sans perte notable de précision. Ces modes s’avèrent être ceux qui sont les plus sensibles aux perturbations atmosphériques. Plus précisément, l’analyse de sensibilité permet d’identifier les structures de l’atmosphère les plus influentes, les groupes de modes qui leur sont associés et les parties du signal infrasonore qui leur correspondent. Ces groupes de modes peuvent être spécifiquement ciblés dans un calcul de spectre au moyen de techniques de projection sur des sous-espace de Krylov, ce qui implique un gain important en coût de calcul. Cette méthode de réduction de modèle peut être appliquée dans un cadre statistique et l’estimation de l’espérance et de la variance du résultat s’effectue là aussi sans perte notable de précision et avec un coût réduit
The perturbation of a system can give rise to wave propagation. A classical approach to understand this phenomenon is to look for natural modes of vibration of the medium. Mathematically, finding these modes requires to seek the eigenvalues and eigenfunctions of the propagation operator. However, from a numerical point of view, the operation can be costly because the matrices can be of very large size. Furthermore, in most applications, uncertainties are inevitably associated with our model. The question then arises as to whether we should allocate significant computational resources for simulation while the accuracy of the result is not guaranteed. We propose in this thesis an approach that allows both a better understanding of the influence of uncertainties on the propagation and a significant decrease of computational costs for infrasound propagation in the atmosphere. The main idea is that all modes do not have the same importance and only a few of them is often sufficient to account for the phenomenon without a significant loss of accuracy. These modes appear to be those which are most sensitive to atmospheric disturbances. Specifically, a sensitivity analysis is used to identify the most influential structures of the atmosphere, the associated groups of modes and their associated parts of the infrasound signal. These groups of modes can be specifically targeted in a spectrum calculation with the projection of the operator onto Krylov subspaces, that allows a significant decrease of the computational cost. This method of model reduction can be applied in a statistical framework as well and estimations of the expectation and the variance of the results are carried out without a significant loss of accuracy and still with a low cost

Moreno, de Castro María [Verfasser]. "Propagation of uncertainties in mesocosm experiments on ocean acidification / María Moreno de Castro." Kiel : Universitätsbibliothek Kiel, 2016. http://d-nb.info/1102933058/34.

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Davis, Daniel E. "A Technique for Evaluating the Uncertainties in Path Loss Predictions Caused by Sparsely Sampled Terrain Data." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23314.

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Radio propagation models provide an estimate of the power loss in a communication link caused by the surface of the ground, atmospheric refraction, foliage, and other environmental factors. Many of the models rely on digital topographic databases to provide information about the terrain, and generally the databases are sparsely sampled relative to the electromagnetic wavelengths used for communication systems. This work primarily develops a technique to evaluate the effects of that sparsity on the uncertainty of propagation models.

That is accomplished by accurately solving the electromagnetic fields over many randomly rough surfaces which pass through the sparse topographic data points, many possible communication links, all of which fit the underlying data, are represented. The power variation
caused by the different surface realizations is that due to the sparse sampling. Additionally, to verify that this solution technique is a good model, experimental propagation measurements were taken, and compared to the computations.

Master of Science

Lu, Yen-Sen [Verfasser]. "Propagation of land surface model uncertainties in simulated terrestrial system states / Yen-Sen Lu." Bonn : Universitäts- und Landesbibliothek Bonn, 2018. http://d-nb.info/1161462252/34.

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Geraci, Gianluca. "Schemes and Strategies to Propagate and Analyze Uncertainties in Computational Fluid Dynamics Applications." Phd thesis, Université Sciences et Technologies - Bordeaux I, 2013. http://tel.archives-ouvertes.fr/tel-00954413.

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In this manuscript, three main contributions are illustrated concerning the propagation and the analysis of uncertainty for computational fluid dynamics (CFD) applications. First, two novel numerical schemes are proposed : one based on a collocation approach, and the other one based on a finite volume like representation in the stochastic space. In both the approaches, the key element is the introduction of anon-linear multiresolution representation in the stochastic space. The aim is twofold : reducing the dimensionality of the discrete solution and applying a time-dependent refinement/coarsening procedure in the combined physical/stochastic space. Finally, an innovative strategy, based on variance-based analysis, is proposed for handling problems with a moderate large number of uncertainties in the context of the robust design optimization. Aiming to make more robust this novel optimization strategies, the common ANOVA-like approach is also extended to high-order central moments (up to fourth order). The new approach is more robust, with respect to the original variance-based one, since the analysis relies on new sensitivity indexes associated to a more complete statistic description.

Saussus, Denis. "Probabilistic distributions of ultimate axial pile resistance derived from propagation of epistemic and aleatory material and model uncertainties." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/32819.

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Chiang, Keng-Yen. "Thermal hydraulic limits analysis for the MIT Research Reactor low enrichment uranium core conversion using statistical propagation of parametric uncertainties." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/77069.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references.
The MIT Research Reactor (MITR) is evaluating the conversion from highly enriched uranium (HEU) to low enrichment uranium (LEU) fuel. In addition to the fuel element re-design from 15 to 18 plates per element, a reactor power upgraded from 6 MW to 7 MW is proposed in order to maintain the same reactor performance of the HEU core. Previous approaches in analyzing the impact of engineering uncertainties on thermal hydraulic limits via the use of engineering hot channel factors (EHCFs) were unable to explicitly quantify the uncertainty and confidence level in reactor parameters. The objective of this study is to develop a methodology for MITR thermal hydraulic limits analysis by statistically combining engineering uncertainties in order to eliminate unnecessary conservatism inherent in traditional analyses. This methodology was employed to analyze the Limiting Safety System Settings (LSSS) for the MITR LEU core, based on the criterion of onset of nucleate boiling (ONB). Key parameters, such as coolant channel tolerances and heat transfer coefficients, were considered as normal distributions using Oracle Crystal Ball for the LSSS evaluation. The LSSS power is determined with 99.7% confidence level. The LSSS power calculated using this new methodology is 9.1 MW, based on core outlet coolant temperature of 60 'C, and primary coolant flow rate of 1800 gpm, compared to 8.3 MW obtained from the analytical method using the EHCFs with same operating conditions. The same methodology was also used to calculate the safety limit (SL) to ensure that adequate safety margin exists between LSSS and SL. The criterion used to calculate SL is the onset of flow instability. The calculated SL is 10.6 MW, which is 1.5 MW higher than LSSS, permitting sufficient margin between LSSS and SL.
by Keng-Yen Chiang.
S.M.

Leissing, Thomas. "Nonlinear acoustic wave propagation in complex media : application to propagation over urban environments." Phd thesis, Université Paris-Est, 2009. http://tel.archives-ouvertes.fr/tel-00584398.

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Dans cette recherche, un modèle de propagation d'ondes de choc sur grandes distances sur un environnement urbain est construit et validé. L'approche consiste à utiliser l'Equation Parabolique Nonlinéaire (NPE) comme base. Ce modèle est ensuite étendu afin de prendre en compte d'autres effets relatifs à la propagation du son en milieu extérieur (surfaces non planes, couches poreuses, etc.). La NPE est résolue en utilisant la méthode des différences finies et donne des résultats en accord avec d'autres méthodes numériques. Ce modèle déterministe est ensuite utilisé comme base pour la construction d'un modèle stochastique de propagation sur environnements urbains. La Théorie de l'Information et le Principe du Maximum d'Entropie permettent la construction d'un modèle probabiliste d'incertitudes intégrant la variabilité du système dans la NPE. Des résultats de référence sont obtenus grâce à une méthode exacte et permettent ainsi de valider les développements théoriques et l'approche utilisée

Dumont, Nicolas. "Méthodes numériques et modèle réduit de chimie tabulée pour la propagation d'incertitudes de cinétique chimique." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC037.

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La simulation numérique joue aujourd'hui un rôle majeur dans le domaine de la combustion, que ce soit au niveau de la recherche en offrant la possibilité de mieux comprendre les phénomènes ayant lieu au sein des écoulements réactifs ou au niveau du développement de nouveaux systèmes industriels par une diminution des coûts liés à la conception de ces systèmes. A l'heure actuelle, la simulation aux grandes échelles est l'outil le mieux adapté à la simulation numérique d'écoulements réactifs turbulents. Cette simulation aux grandes échelles d'écoulements réactifs n'est en pratique possible que grâce à une modélisation des différents phénomènes:- la turbulence est modélisée pour les plus petites structures permettant de n'avoir à résoudre que les plus grandes structures de l'écoulement et ainsi réduire le coût de calcul- la chimie des différentes espèces réactives est modélisée à l'aide de méthodes de réduction permettant de considérablement réduire le coût de calculLa maturité de la simulation aux grandes échelles d'écoulements réactifs en fait aujourd'hui un outil fiable, prédictif et prometteur. Il fait désormais sens de s'intéresser à l'impact des paramètres impliqués dans les différents modèles sur le résultat de la simulation. Cette étude de l'impact des paramètres de modélisation peut être vue sous l'angle de la propagation d'incertitudes, et peut donner des informations intéressantes à la fois d'un côté pratique pour la conception robuste de systèmes mais également d'un côté théorique afin d'améliorer les modèles utilisées et d'orienter les mesures expérimentales à réaliser afin d'améliorer la fiabilité de ces modèles.Le contexte de cette thèse est le développement de méthodes efficaces permettant la propagation d'incertitudes présentes dans les paramètres de cinétique chimique des mécanismes réactionnels au sein de simulation aux grandes échelles, ces méthodes devant être non intrusive afin de profiter de l'existence des différents codes de calcul qui sont des outils nécessitant de lourds moyens pour leur développement. Une telle propagation d'incertitude à l'aide d'une méthode de force brute souffre du "fléau de la dimension" du fait du grand nombre de paramètres de cinétique chimique, impliquant une impossibilité pratique avec les moyens de calculs actuels et justifiant le développement de méthodes efficaces.L'objectif de la thèse est donc le développement d'un modèle réduit utilisable pour la propagation d'incertitudes dans la simulation aux grandes échelles. La prise en main et l'implémentation de différents outils issus de la propagation d'incertitudes a été un travail préliminaire indispensable dans cette thèse afin d'amener ces connaissances et compétences au sein du laboratoire EM2C.La méthode développée dans cette thèse pour la propagation d'incertitudes des paramètres de cinétique chimique se restreint aux cas d'une modélisation de la chimie dans laquelle l'avancement du processus de combustion est résumé par l'évolution d'une variable d'avancement donnée par une équation de transport, l'accès aux autres informations se faisant grâce à l'utilisation d'une table. Au travers de l'étude de l'évolution d'un réacteur adiabatique à pression constante contenant un mélange homogène d'air et de dihydrogène, il est montré qu'une grande partie des incertitudes d'un tel système peuvent être expliquées grâce aux incertitudes de la variable d'avancement. Cela permet de définir une table chimique utilisable pour la propagation d'incertitudes des paramètres de cinétique chimique dans les simulations aux grandes échelles. L'introduction des incertitudes se fait alors uniquement par la modélisation du terme source présent dans l'équation de transport de la variable d'avancement, lequel peut être paramétré à l'aide de quelques paramètres incertains évitant ainsi le "fléau de la dimension"
Numerical simulation plays a key role in the field of combustion today, either in the research area by permitting a better understanding of phenomenons taking place inside reactive flows or in the development of industrial application by reducing designing cost of systems. Large Eddy Simulation is at the time the most suited tool for the simulation of reactive flows. Large Eddy Simulation of reactive flows is in practice only possible thanks to a modeling of different phenomenons:- turbulence is modeled for small structures allowing to resolve only big structures which results in lower computational cost- chemistry is modeled using reduction methods which allows to drastically reduce computational costThe maturity of Large Eddy Simulation of reactive flows makes it today a reliable, predictive and promising tool. It now makes sense to focus on the impact of the parameters involved in the different models on the simulation results. This study of the impact of the modeling parameters can be seen from the perspective of uncertainties propagation, and can give interesting informations both from a practical side for the robust design of systems but also on the theoretical side in order to improve the models used and guide the experimental measurements to be made for the reliability improvement of these models.The context of this thesis is the development of efficient methods allowing the propagation of uncertainties present in the chemical kinetic parameters of the reaction mechanisms within Large Eddy Simulation, these methods having to be non-intrusive in order to take advantage of the existence of the different computation codes which are tools requiring heavy means for their development. Such a propagation of uncertainties using a brute-force method suffers from the "curse of dimensionality" because of the large number of chemical kinetic parameters, implying a practical impossibility with the current means of computation which justifies the development of efficient methods.The objective of the thesis is the development of a reduced model that can be used for uncertainties propagation in Large Eddy simulations. The handling and implementation of various tools resulting from the uncertainties propagation framework has been an essential preliminary work in this thesis in order to bring this knowledge and skills into the EM2C laboratory.The method developed in this thesis for the propagation of chemical kinetic parameters uncertainties is limited to chemistry models in which the advancement of the combustion process is summarized by the evolution of a progress variable given by a transport equation, the access to other informations being made through the use of a table. Through the study of the evolution of a constant pressure adiabatic reactor containing a homogeneous mixture of air and dihydrogen, it is shown that a large part of the uncertainties of such a system can be explained by the uncertainties of the progress variable. This makes it possible to define a chemical table that can be used to propagate uncertainties of chemical kinetic parameters in Large Eddy Simulations. The introduction of the uncertainties is then done only by the modeling of the source term present in the transport equation of the progress variable, which can be parameterized with the help of few uncertain parameters thus avoiding the "curse of dimensionality"

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Книги з теми "Propagation uncertainties":

Center, Langley Research, ed. Propagation of experimental uncertainties from the tunnel to the body coordinate system in 3-D LDV flow field studies. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1994.

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National Aeronautics and Space Administration (NASA) Staff. Propagation of Experimental Uncertainties from the Tunnel to the Body Coordinate System in 3-D LDV Flow Field Studies. Independently Published, 2018.

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A Review of techniques for propagating data and parameter uncertainties in high-level radioactive waste repository performance assessment models. Division of High-Level Waste Management, Office of Nuclear Material Safety and Safeguards, U.S. Nuclear Regulatory Commission, 1990.

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Частини книг з теми "Propagation uncertainties":

Gupta, S. V. "Propagation of Uncertainty." In Measurement Uncertainties, 109–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20989-5_5.

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Pinto, Paolo Emilio. "Modeling and Propagation of Uncertainties." In SYNER-G: Typology Definition and Fragility Functions for Physical Elements at Seismic Risk, 29–45. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7872-6_2.

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Grabe, Michael. "Error Propagation, Two Variables." In Measurement Uncertainties in Science and Technology, 81–96. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04888-8_6.

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Grabe, Michael. "Error Propagation, m Variables." In Measurement Uncertainties in Science and Technology, 97–104. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04888-8_7.

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Chikhaoui, Khaoula, Noureddine Bouhaddi, Najib Kacem, Mohamed Guedri, and Mohamed Soula. "Uncertainties Propagation through Robust Reduced Model." In Design and Modeling of Mechanical Systems - II, 537–44. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17527-0_53.

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Crowder, Stephen, Collin Delker, Eric Forrest, and Nevin Martin. "Analytical Methods for the Propagation of Uncertainties." In Introduction to Statistics in Metrology, 131–51. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53329-8_7.

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Litvinenko, Alexander, Dmitry Logashenko, Raul Tempone, Gabriel Wittum, and David Keyes. "Propagation of Uncertainties in Density-Driven Flow." In Lecture Notes in Computational Science and Engineering, 101–26. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81362-8_5.

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Li, Wenye. "Clustering with Uncertainties: An Affinity Propagation-Based Approach." In Neural Information Processing, 437–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34500-5_52.

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Crowder, Stephen, Collin Delker, Eric Forrest, and Nevin Martin. "Monte Carlo Methods for the Propagation of Uncertainties." In Introduction to Statistics in Metrology, 153–80. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53329-8_8.

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Bouchon, Bernadette, and Sylvie Desprès. "Propagation of uncertainties and inaccuracies in knowledge-based system." In Uncertainty in Knowledge-Based Systems, 58–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/3-540-18579-8_4.

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Тези доповідей конференцій з теми "Propagation uncertainties":

Novák, Drahomír. "FReET: Software for Uncertainties Propagation." In 5th International Conference on Statistics: Theory and Applications (ICSTA 2023). Avestia Publishing, 2023. http://dx.doi.org/10.11159/icsta23.150.

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Taillet, Richard. "Cosmic Ray propagation uncertainties and Dark Matter." In Identification of Dark Matter 2010. Trieste, Italy: Sissa Medialab, 2011. http://dx.doi.org/10.22323/1.110.0015.

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Mao, Wengang, Jingxia Yue, Da Wu, Luis De Gracia, and Naoki Osawa. "Uncertainties of Crack Propagation Analysis in Ship Structures." In ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/omae2016-54226.

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Fatigue cracks can be observed quite frequently on today’s ocean crossing vessels. To ensure the safety of ship structures sailing in the sea, it is important to know the residual fatigue life of these damaged ship structures. In this case, the fracture mechanics theory is often employed to estimate how fast these cracks can propagate along ship structures. However, large uncertainties are always associated with the crack prediction and residual fatigue life analysis. In this study, two uncertainties sources will be investigated, i.e. the reliability of encountered wave environments connected with shipload determinations and different fracture estimation methods for crack propagation analysis. Firstly, different available codes based on fracture mechanic theory are used to compute the stress intensity factor related parameters for crack propagation analysis. The analysis is carried out for both 2D and 3D cases of some typical ship structural details. The comparison is presented to illustrate the uncertainties of crack propagation analysis related with different codes. Furthermore, it is assumed that the structural details will undertake dynamic loading from a containership operated in the North Atlantic. A statistical wave model is used to generate wave environments along recorded ship routes for different years. The uncertainties of crack growth analysis related with encountered weather environments is also investigated in the study. The comparison of these two uncertainties indicated the requirement of further development for the fracture mechanics theory and associated numerical codes, as well as the reliable life-cycle encountered weather environments.

Bell, Kristine L., and Robert E. Zarnich. "MAP-PF multitarget tracking with propagation modeling uncertainties." In 2013 Asilomar Conference on Signals, Systems and Computers. IEEE, 2013. http://dx.doi.org/10.1109/acssc.2013.6810602.

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Garg, Diksha, Mary Hall Reno, and NuSpaceSim Collaboration. "Neutrino propagation through Earth: modeling uncertainties using nuPyProp." In 38th International Cosmic Ray Conference. Trieste, Italy: Sissa Medialab, 2023. http://dx.doi.org/10.22323/1.444.1115.

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Arz, Uwe, Jens Leinhos, and Dirk Schubert. "Uncertainties in Coplanar Waveguide Capacitance Measurements." In 2006 IEEE Workshop on Signal Propagation on Interconnects. IEEE, 2006. http://dx.doi.org/10.1109/spi.2006.289162.

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Diamant, Roee, and Lutz Lampe. "Underwater localization with time-synchronization and propagation speed uncertainties." In 2011 8th Workshop on Positioning, Navigation and Communication (WPNC). IEEE, 2011. http://dx.doi.org/10.1109/wpnc.2011.5961023.

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Taylor, Craig, William Graf, Yajie Jerry Lee, Charles Huyck, and Zhenghui Hu. "Propagation of Uncertainties through Robust Simulation and Future Research." In 5th Asian-Pacific Symposium on Structural Reliability and its Applications. Singapore: Research Publishing Services, 2012. http://dx.doi.org/10.3850/978-981-07-2219-7_p255.

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Pourgol-Mohammad, Mohammad. "Uncertainty Propagation in Complex Codes Calculations." In 2013 21st International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/icone21-16570.

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The uncertainty propagation is an important segment of quantitative uncertainty analysis for complex computational codes (e.g., RELAP5 thermal-hydraulics) computations. Different sampling techniques, dependencies between uncertainty sources, and accurate inference on results are among the issues to be considered. The dynamic behavior of the system codes executed in each time step, results in transformation of accumulated errors and uncertainties to next time step. Depending on facility type, availability of data, scenario specification, computing machine and the software used, propagation of uncertainty results in considerably different results. This paper discusses the practical considerations of uncertainty propagation for code computations. The study evaluates the implications of the complexity on propagation of the uncertainties through inputs, sub-models and models. The study weighs different techniques of propagation, their statistics with considering their advantages and limitation at dealing with the problem. The considered methods are response surface, Monte Carlo (including simple, Latin Hypercube, and importance sampling) and boot-strap techniques. As a case study, the paper will discuss uncertainty propagation of the Integrated Methodology on Thermal-Hydraulics Uncertainty Analysis (IMTHUA). The methodology comprehensively covers various aspects of complex code uncertainty assessment for important accident transients. It explicitly examines the TH code structural uncertainties by treating internal sub-model uncertainties and by propagating such model uncertainties along with parameters in the code calculations. The two-step specification of IMTHUA (input phase following with the output updating) makes it special case to make sure that the figure of merit statistical coverage is achieved at the end with target confidence level. Tolerance limit statistics provide confidence a level on the level of coverage depending on the sample size, number of output measures, and one-sided or two-sided type of statistics. This information should be transferred to the second phase in the form of a probability distribution for each of the output measures. The research question is how to use data to develop such distributions from the corresponding tolerance limit statistics. Two approaches of using extreme values method and Bayesian updating are selected to estimate the parametric distribution parameters and compare the coverage in respect to the selected coverage criteria. The analysis is demonstrated on the large break loss of coolant accident for the LOFT test facility.

Fei, Zhouxiang, Yi Huang, and Jiafeng Zhou. "Crosstalk variations caused by uncertainties in three-conductor transmission lines." In 2015 Loughborough Antennas & Propagation Conference (LAPC). IEEE, 2015. http://dx.doi.org/10.1109/lapc.2015.7366057.

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Звіти організацій з теми "Propagation uncertainties":

Masri, Sami F. Analytical and Experimental Studies of the Quantification and Propagation of Uncertainties in Nonlinear System Modeling and Simulation. Fort Belvoir, VA: Defense Technical Information Center, March 2007. http://dx.doi.org/10.21236/ada473592.

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Dunn, Floyd E., Lin-wen Hu, and Erik Wilson. The STAT7 Code for Statistical Propagation of Uncertainties In Steady-State Thermal Hydraulics Analysis of Plate-Fueled Reactors. Office of Scientific and Technical Information (OSTI), December 2016. http://dx.doi.org/10.2172/1349053.

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Pham, Son, Lin-wen Hu, and Erik Wilson. The STAT7 Code for Statistical Propagation of Uncertainties In Steady-State Thermal Hydraulics Analysis of Plate-Fueled Reactors. Office of Scientific and Technical Information (OSTI), July 2020. http://dx.doi.org/10.2172/1825880.

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Yang, Se, Dhongik Yoon, Lin-wen Hu, and Erik Wilson. The STAT7 Code for Statistical Propagation of Uncertainties in Steady State Thermal Hydraulics Analysis of Plate Fueled Reactors. Office of Scientific and Technical Information (OSTI), January 2023. http://dx.doi.org/10.2172/1923025.

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Wendelberger, James G. Non-Destructive Assay (NDA) Uncertainties Impact on Physical Inventory Difference (ID) and Material Balance Determination: Sources of Error, Precision/Accuracy, and ID/Propagation of Error (POV). Office of Scientific and Technical Information (OSTI), October 2016. http://dx.doi.org/10.2172/1304800.

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Zimmerman, D., K. Wahl, A. Gutjahr, and P. Davis. A review of techniques for propagating data and parameter uncertainties in high-level radioactive waste repository performance assessment models. Office of Scientific and Technical Information (OSTI), March 1990. http://dx.doi.org/10.2172/6961264.

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Bray, Jonathan, Ross Boulanger, Misko Cubrinovski, Kohji Tokimatsu, Steven Kramer, Thomas O'Rourke, Ellen Rathje, Russell Green, Peter Robertson, and Christine Beyzaei. U.S.—New Zealand— Japan International Workshop, Liquefaction-Induced Ground Movement Effects, University of California, Berkeley, California, 2-4 November 2016. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, March 2017. http://dx.doi.org/10.55461/gzzx9906.

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There is much to learn from the recent New Zealand and Japan earthquakes. These earthquakes produced differing levels of liquefaction-induced ground movements that damaged buildings, bridges, and buried utilities. Along with the often spectacular observations of infrastructure damage, there were many cases where well-built facilities located in areas of liquefaction-induced ground failure were not damaged. Researchers are working on characterizing and learning from these observations of both poor and good performance. The “Liquefaction-Induced Ground Movements Effects” workshop provided an opportunity to take advantage of recent research investments following these earthquake events to develop a path forward for an integrated understanding of how infrastructure performs with various levels of liquefaction. Fifty-five researchers in the field, two-thirds from the U.S. and one-third from New Zealand and Japan, convened in Berkeley, California, in November 2016. The objective of the workshop was to identify research thrusts offering the greatest potential for advancing our capabilities for understanding, evaluating, and mitigating the effects of liquefaction-induced ground movements on structures and lifelines. The workshop also advanced the development of younger researchers by identifying promising research opportunities and approaches, and promoting future collaborations among participants. During the workshop, participants identified five cross-cutting research priorities that need to be addressed to advance our scientific understanding of and engineering procedures for soil liquefaction effects during earthquakes. Accordingly, this report was organized to address five research themes: (1) case history data; (2) integrated site characterization; (3) numerical analysis; (4) challenging soils; and (5) effects and mitigation of liquefaction in the built environment and communities. These research themes provide an integrated approach toward transformative advances in addressing liquefaction hazards worldwide. The archival documentation of liquefaction case history datasets in electronic data repositories for use by the broader research community is critical to accelerating advances in liquefaction research. Many of the available liquefaction case history datasets are not fully documented, published, or shared. Developing and sharing well-documented liquefaction datasets reflect significant research efforts. Therefore, datasets should be published with a permanent DOI, with appropriate citation language for proper acknowledgment in publications that use the data. Integrated site characterization procedures that incorporate qualitative geologic information about the soil deposits at a site and the quantitative information from in situ and laboratory engineering tests of these soils are essential for quantifying and minimizing the uncertainties associated site characterization. Such information is vitally important to help identify potential failure modes and guide in situ testing. At the site scale, one potential way to do this is to use proxies for depositional environments. At the fabric and microstructure scale, the use of multiple in situ tests that induce different levels of strain should be used to characterize soil properties. The development of new in situ testing tools and methods that are more sensitive to soil fabric and microstructure should be continued. The development of robust, validated analytical procedures for evaluating the effects of liquefaction on civil infrastructure persists as a critical research topic. Robust validated analytical procedures would translate into more reliable evaluations of critical civil infrastructure iv performance, support the development of mechanics-based, practice-oriented engineering models, help eliminate suspected biases in our current engineering practices, and facilitate greater integration with structural, hydraulic, and wind engineering analysis capabilities for addressing multi-hazard problems. Effective collaboration across countries and disciplines is essential for developing analytical procedures that are robust across the full spectrum of geologic, infrastructure, and natural hazard loading conditions encountered in practice There are soils that are challenging to characterize, to model, and to evaluate, because their responses differ significantly from those of clean sands: they cannot be sampled and tested effectively using existing procedures, their properties cannot be estimated confidently using existing in situ testing methods, or constitutive models to describe their responses have not yet been developed or validated. Challenging soils include but are not limited to: interbedded soil deposits, intermediate (silty) soils, mine tailings, gravelly soils, crushable soils, aged soils, and cemented soils. New field and laboratory test procedures are required to characterize the responses of these materials to earthquake loadings, physical experiments are required to explore mechanisms, and new soil constitutive models tailored to describe the behavior of such soils are required. Well-documented case histories involving challenging soils where both the poor and good performance of engineered systems are documented are also of high priority. Characterizing and mitigating the effects of liquefaction on the built environment requires understanding its components and interactions as a system, including residential housing, commercial and industrial buildings, public buildings and facilities, and spatially distributed infrastructure, such as electric power, gas and liquid fuel, telecommunication, transportation, water supply, wastewater conveyance/treatment, and flood protection systems. Research to improve the characterization and mitigation of liquefaction effects on the built environment is essential for achieving resiliency. For example, the complex mechanisms of ground deformation caused by liquefaction and building response need to be clarified and the potential bias and dispersion in practice-oriented procedures for quantifying building response to liquefaction need to be quantified. Component-focused and system-performance research on lifeline response to liquefaction is required. Research on component behavior can be advanced by numerical simulations in combination with centrifuge and large-scale soil–structure interaction testing. System response requires advanced network analysis that accounts for the propagation of uncertainty in assessing the effects of liquefaction on large, geographically distributed systems. Lastly, research on liquefaction mitigation strategies, including aspects of ground improvement, structural modification, system health monitoring, and rapid recovery planning, is needed to identify the most effective, cost-efficient, and sustainable measures to improve the response and resiliency of the built environment.