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Raïssi, Tarek, and Denis Efimov. "Some recent results on the design and implementation of interval observers for uncertain systems." at - Automatisierungstechnik 66, no. 3 (March 26, 2018): 213–24. http://dx.doi.org/10.1515/auto-2017-0081.
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Abstract Based on the theory of positive systems, the goal of interval observers is to compute sets of admissible values of the state vector at each instant of time for systems subject to bounded uncertainties (noises, disturbances and parameters). The size of the estimated sets, which should be minimised, has to be proportional to the model uncertainties. An interval estimation can be seen as a conventional point estimation (the centre of the interval) with an estimation error given by the interval radius. The reliable uncertainties propagation performed in this context can be useful in several fields such as robust control, diagnosis and fault-tolerant control. This paper presents some recent results on interval observers for several dynamical systems classes such as continuous-time and switched systems.
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Martins, L. L., J. P. Gomes, and A. S. Ribeiro. "Metrological quality of the excitation force in forced vibration test of concrete dams." Journal of Physics: Conference Series 2647, no. 21 (June 1, 2024): 212001. http://dx.doi.org/10.1088/1742-6596/2647/21/212001.
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Abstract This paper describes the study of the metrological quality of the excitation force in the context of force vibration test of concrete dams. For this purpose, a measurement uncertainty evaluation was performed, based on available probabilistic information about the input quantities – rotation frequency, mass, radial position, dimension, diameter and density of the generator’s rod – which support the determination of the excitation force in an eccentric masses vibration generator, used by LNEC in concrete dam’s field observation. The uncertainty propagation from the input quantities to the output quantity was performed by a Monte Carlo method, considering the mathematical model used for the determination of the excitation force. Two experimental cases were studied: (A) the use of five weights in the generator in the frequency range of 1 Hz up to 6 Hz; and (B) the use of a single weight in the generator in the frequency interval comprised between 5 Hz and 15 Hz. In the first case, the excitation force estimates and expanded measurement uncertainties (considering a 95 % confidence interval) varied between 3.55 kN ± 0.14 kN and 127.68 kN ± 0.91 kN, being rotation frequency the major contribution for the obtained dispersion of force values. In the second case, the excitation force estimates and expanded measurement uncertainties varied between 16.71 kN ± 0.25 kN and 150.4 kN ± 1.8 kN, being the generator’s rod diameter the main contribution for the output measurement uncertainty. The obtained knowledge is essential to assure confidence and rigorous knowledge about the applied excitation force, namely, in extreme situations near dynamical structural safety limits of the observed concrete dam and of the testing equipment.
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Mezić, Igor, and Thordur Runolfsson. "Uncertainty propagation in dynamical systems." Automatica 44, no. 12 (December 2008): 3003–13. http://dx.doi.org/10.1016/j.automatica.2008.04.020.
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Banks, H. T., and Shuhua Hu. "Propagation of Uncertainty in Dynamical Systems." Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 2012 (May 5, 2012): 134–39. http://dx.doi.org/10.5687/sss.2012.134.
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Piqueira, José R. C., and Felipe Barbosa Cesar. "Dynamical Models for Computer Viruses Propagation." Mathematical Problems in Engineering 2008 (2008): 1–11. http://dx.doi.org/10.1155/2008/940526.
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Nowadays, digital computer systems and networks are the main engineering tools, being used in planning, design, operation, and control of all sizes of building, transportation, machinery, business, and life maintaining devices. Consequently, computer viruses became one of the most important sources of uncertainty, contributing to decrease the reliability of vital activities. A lot of antivirus programs have been developed, but they are limited to detecting and removing infections, based on previous knowledge of the virus code. In spite of having good adaptation capability, these programs work just as vaccines against diseases and are not able to prevent new infections based on the network state. Here, a trial on modeling computer viruses propagation dynamics relates it to other notable events occurring in the network permitting to establish preventive policies in the network management. Data from three different viruses are collected in the Internet and two different identification techniques, autoregressive and Fourier analyses, are applied showing that it is possible to forecast the dynamics of a new virus propagation by using the data collected from other viruses that formerly infected the network.
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DeMars, Kyle J., Robert H. Bishop, and Moriba K. Jah. "Entropy-Based Approach for Uncertainty Propagation of Nonlinear Dynamical Systems." Journal of Guidance, Control, and Dynamics 36, no. 4 (July 2013): 1047–57. http://dx.doi.org/10.2514/1.58987.
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Park, Inkwan, Kohei Fujimoto, and Daniel J. Scheeres. "Effect of Dynamical Accuracy for Uncertainty Propagation of Perturbed Keplerian Motion." Journal of Guidance, Control, and Dynamics 38, no. 12 (December 2015): 2287–300. http://dx.doi.org/10.2514/1.g000956.
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Xu, Tianlai, Zhe Zhang, and Hongwei Han. "Adaptive Gaussian Mixture Model for Uncertainty Propagation Using Virtual Sample Generation." Applied Sciences 13, no. 5 (February 27, 2023): 3069. http://dx.doi.org/10.3390/app13053069.
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Orbit uncertainty propagation plays an important role in the analysis of a space mission. The accuracy and computation expense are two critical essences of uncertainty propagation. Repeated evaluations of the objective model are required to improve the preciseness of prediction, especially for long-term propagation. To balance the computational complexity and accuracy, an adaptive Gaussian mixture model using virtual sample generation (AGMM-VSG) is proposed. First, an unscented transformation and Cubature rule (UT-CR) based splitting method is employed to adaptive update the weights of Gaussian components for nonlinear dynamics. The Gaussian mixture model (GMM) approximation is applied to better approximate the original probability density function. Second, instead of the pure expensive evaluations by conventional GMM methods, virtual samples are generated using a new active-sampling-based Kriging (AS-KRG) method to improve the propagation efficiency. Three cases of uncertain orbital dynamical systems are used to verify the accuracy and efficiency of the proposed manuscript. The likelihood agreement measure (LAM) criterion and the number of expense evaluations prove the performance.
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Baili, H., and G. A. Fleury. "Indirect Measurement Within Dynamical Context: Probabilistic Approach to Deal With Uncertainty." IEEE Transactions on Instrumentation and Measurement 53, no. 6 (December 2004): 1449–54. http://dx.doi.org/10.1109/tim.2004.831138.
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Kuehn, Christian. "Uncertainty transformation via Hopf bifurcation in fast–slow systems." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 473, no. 2200 (April 2017): 20160346. http://dx.doi.org/10.1098/rspa.2016.0346.
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Propagation of uncertainty in dynamical systems is a significant challenge. Here we focus on random multiscale ordinary differential equation models. In particular, we study Hopf bifurcation in the fast subsystem for random initial conditions. We show that a random initial condition distribution can be transformed during the passage near a delayed/dynamic Hopf bifurcation: (i) to certain classes of symmetric copies, (ii) to an almost deterministic output, (iii) to a mixture distribution with differing moments and (iv) to a very restricted class of general distributions. We prove under which conditions the cases (i)–(iv) occur in certain classes vector fields.
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Alwan, Aravind, and Narayana R. Aluru. "Analysis of the Effect of Spatial Uncertainties on the Dynamic Behavior of Electrostatic Microactuators." Communications in Computational Physics 20, no. 2 (July 21, 2016): 279–300. http://dx.doi.org/10.4208/cicp.220115.071215a.
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AbstractThis paper examines the effect of spatial roughness on the dynamical behaviour of electrostatic microactuators. We develop a comprehensive physical model that comprises a nonlinear electrostatic actuation force aswell as a squeeze-film damping term to accurately simulate the dynamical behavior of a cantilever beam actuator. Spatial roughness is modeled as a nonstationary stochastic process whose parameters can be estimated from profilometric measurements. We propagate the stochastic model through the physical system and examine the resulting uncertainty in the dynamical behavior that manifests as a variation in the quality factor of the device. We identify two distinct, yet coupled, modes of uncertainty propagation in the system, that result from the roughness causing variation in the electrostatic actuation force and the damping pressure, respectively. By artificially turning off each of these modes of propagation in sequence, we demonstrate that the variation in the damping pressure has a greater effect on the damping ratio than that arising from the electrostatic force. Comparison with similar simulations performed using a simplified mass-spring-damper model show that the coupling between these two mechanisms can be captured only when the physical model includes the primary nonlinear interactions along with a proper treatment of spatial variations. We also highlight the difference between nonstationary and stationary covariance formulations by showing that the stationary model is unable to properly capture the full range of variation as compared to its nonstationary counterpart.
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Schoetter, Robert, Julia Hidalgo, Renaud Jougla, Valéry Masson, Mario Rega, and Julien Pergaud. "A Statistical–Dynamical Downscaling for the Urban Heat Island and Building Energy Consumption—Analysis of Its Uncertainties." Journal of Applied Meteorology and Climatology 59, no. 5 (May 2020): 859–83. http://dx.doi.org/10.1175/jamc-d-19-0182.1.
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AbstractHigh-resolution maps of the urban heat island (UHI) and building energy consumption are relevant for urban planning in the context of climate change mitigation and adaptation. A statistical–dynamical downscaling for these parameters is proposed in the present study. It combines a statistical local weather type approach with dynamical simulations using the mesoscale atmospheric model Meso-NH coupled to the urban canopy model Town Energy Balance. The downscaling is subject to uncertainties related to the weather type approach (statistical uncertainty) and to the numerical models (dynamical uncertainty). These uncertainties are quantified for two French cities (Toulouse and Dijon) for which long-term dense high-quality observations are available. The seasonal average nocturnal UHI intensity is simulated with less than 0.2 K bias for Dijon, but it is overestimated by up to 0.8 K for Toulouse. The sensitivity of the UHI intensity to weather type is, on average, captured by Meso-NH. The statistical uncertainty is as large as the dynamical uncertainty if only one day is simulated for each weather type. It can be considerably reduced if 3–6 days are taken instead. The UHI reduces the building energy consumption by 10% in the center of Toulouse; it should therefore be taken into account in the production of building energy consumption maps.
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Butkewitsch, Sergio. "Dynamical Modelling, Stochastic Simulation and Optimization in the Context of Damage Tolerant Design." Shock and Vibration 13, no. 4-5 (2006): 445–58. http://dx.doi.org/10.1155/2006/431319.
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This paper addresses the situation in which some form of damage is induced by cyclic mechanical stresses yielded by the vibratory motion of a system whose dynamical behaviour is, in turn, affected by the evolution of the damage. It is assumed that both phenomena, vibration and damage propagation, can be modeled by means of time depended equations of motion whose coupled solution is sought. A brief discussion about the damage tolerant design philosophy for aircraft structures is presented at the introduction, emphasizing the importance of the accurate definition of inspection intervals and, for this sake, the need of a representative damage propagation model accounting for the actual loading environment in which a structure may operate. For the purpose of illustration, the finite element model of a cantilever beam is formulated, providing that the stiffness matrix can be updated as long as a crack of an assumed initial length spreads in a given location of the beam according to a proper propagation model. This way, it is possible to track how the mechanical vibration, through its varying amplitude stress field, activates and develops the fatigue failure mechanism. Conversely, it is also possible to address how the effect of the fatigue induced stiffness degradation influences the motion of the beam, closing the loop for the analysis of a coupled vibration-degradation dynamical phenomenon. In the possession of this working model, stochastic simulation of the beam behaviour is developed, aiming at the identification of the most influential parameters and at the characterization of the probability distributions of the relevant responses of interest. The knowledge of the parameters and responses allows for the formulation of optimization problems aiming at the improvement of the beam robustness with respect to the fatigue induced stiffness degradation. The overall results are presented and analyzed, conducting to the conclusions and outline of future investigation.
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LANDOLFI, G., G. RUGGERI, and G. SOLIANI. "A NOTE ON THE LOSS OF COHERENCE IN WAVE PACKETS SQUEEZED SYSTEMS." International Journal of Quantum Information 02, no. 04 (December 2004): 529–40. http://dx.doi.org/10.1142/s0219749904000900.
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Time-dependent dynamical systems with a particular emphasis on models attaining the minimum value of uncertainty formula are considered. The role of the Bogolubov coefficients, in general and in the context of the loss of minimum uncertainty, is analyzed. Different fluctuation values on squeezed states are performed. The decoherence energy is parametrized by an angle ϕ and turns out to vanish whenever ϕ=π. An application to the Paul trap theory is discussed.
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DA SILVA, GEOVANNA LUIZ PEREIRA, MÁRCIO JOSÉ MENON, and REGINA FONSECA ÁVILA. "PROTON PROFILE FUNCTION AT 52.8 GeV." International Journal of Modern Physics E 16, no. 09 (October 2007): 2923–26. http://dx.doi.org/10.1142/s0218301307008732.
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We present the results of a novel model-independent fit to elastic proton-proton differential cross section data at [Formula: see text]. Taking into account the error propagation from the fit parameters, we determine the scattering amplitude in the impact parameter space (the proton profile function) and its statistical uncertainty region. We show that both the real and imaginary parts of the profile are consistent with two dynamical contributions, one from a central dense region, up to roughly 1 fm and another from a peripheral evanescent region from 1 to 3 fm.
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Brahma, A., D. C. Wynn, and O. Isaksson. "Use of Margin to Absorb Variation in Design Specifications: An Analysis Using the Margin Value Method." Proceedings of the Design Society 2 (May 2022): 323–32. http://dx.doi.org/10.1017/pds.2022.34.
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AbstractPredicting the impact of changes in a design can be challenging, especially for complex designs. Margins are often built into the designs which can absorb the knock-on effect of such changes, erroneously allocating which can however, lead to propagation. A method for localising and sizing margins in an incremental design context is the Margin Value Method. This paper adapts MVM in the context of uncertainty in input specifications. It discusses possible ways to allocate them in a design such that undesirable effects of margins are minimised while preventing change propagation.
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Ruiz-Medina, M. D., V. V. Anh, R. M. Espejo, and M. P. Frías. "Heterogeneous Spatial Dynamical Regression in a Hilbert-Valued Context." Stochastic Analysis and Applications 31, no. 3 (May 2013): 509–27. http://dx.doi.org/10.1080/07362994.2013.777281.
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Carobbi, Carlo. "An informed type A evaluation of standard uncertainty valid for any sample size greater than or equal to 1." ACTA IMEKO 11, no. 2 (May 4, 2022): 1. http://dx.doi.org/10.21014/acta_imeko.v11i2.1170.
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An informed type A evaluation of standard uncertainty is here derived based on Bayesian analysis. The result is mathematically simple, easily interpretable, applicable both in the theoretical framework of the Guide to the Expression of Uncertainty in Measurement (propagation of standard uncertainties) and in that of the Supplement 1 of the Guide (propagation of distributions), valid for any size greater than or equal to 1 of the sample of present observations. The evaluation consistently addresses prior information in the form of the sample variance of a series of recorded experimental observations and in the form of an educated guess based on expert’s experience. It turns out that distinction between type A and type B evaluation is, in this context, contrived.
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Sonnenborg, T. O., D. Seifert, and J. C. Refsgaard. "Climate model uncertainty vs. conceptual geological uncertainty in hydrological modeling." Hydrology and Earth System Sciences Discussions 12, no. 4 (April 29, 2015): 4353–85. http://dx.doi.org/10.5194/hessd-12-4353-2015.
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Abstract. Projections of climate change impact are associated with a cascade of uncertainties including CO2 emission scenario, climate model, downscaling and impact model. The relative importance of the individual uncertainty sources is expected to depend on several factors including the quantity that is projected. In the present study the impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Each projection of future climate is a result of a GCM-RCM model combination (from the ENSEMBLES project) forced by the same CO2 scenario (A1B). The changes from the reference period (1991–2010) to the future period (2081–2100) in projected hydrological variables are evaluated and the effects of geological model and climate model uncertainties are quantified. The results show that uncertainty propagation is context dependent. While the geological conceptualization is the dominating uncertainty source for projection of travel time and capture zones, the uncertainty on the climate models is more important for groundwater hydraulic heads and stream flow.
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Alves, Josivan Leite, and Marly Monteiro de Carvalho. "Knowledge management and project uncertainty in ppen innovation context." Brazilian Journal of Operations & Production Management 20, no. 1 (November 17, 2022): 1530. http://dx.doi.org/10.14488/bjopm.1530.2023.
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Goal: We aims to map the literature that correlates uncertainty management and Open Innovation at project level, identifying the main contributions of knowledge management. Design/Methodology/Approach: We applied the Systematic Literature Review - SLR approach associated with Bibliometric analysis. To sample compose we use the Scopus and Web of Science databases. We also use the Bibliometrix R package to managed the sample process compose and bibliometric analysis and content analysis to identify the main topics. Results: The contributions mainly discuss the performance of OI projects to generate competitive advantage for organizations. The sample are categorized in technical, market, organizational and resource uncertainties. There is a greater focus on market and organizational uncertainties justified by the propagation of uncertainty. Limitations of the investigation: Even with transparency in the analysis and sample composition, the discussions may be subject to subjective interpretations by the authors. Practical Implications: This study has managerial implications. Our study helps managers identify core KM mechanisms in OI projects that enable sharing, integration, and knowledge flow between the network partners. Our findings show that the main challenge lies in organizational culture and the change of mindset, which influences the opening to new partnerships, knowledge sharing, and internal and external partners' trust to leverage innovation. For that, managers have to be aware of the KM barriers such as lack of trust or information asymmetry. Originality/ Value: We correlate uncertainties management in the OI projects, considering the influence of KM. We present conceptual maps. We identified emerging topics and we suggest a theoretical model of the research.
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Kubíček, Petr, Čeněk Šašinka, and Zdeněk Stachoň. "Selected Cognitive Issues of Positional Uncertainty in Geographical Data." Geografie 119, no. 1 (2014): 67–90. http://dx.doi.org/10.37040/geografie2014119010067.
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In accordance with the development of theoretical aspects of cartographic visualization and methods of uncertainty propagation in models, the generally accepted opinion argues that uncertainty has to be presented to users in an unambiguous and understandable way. Studies published in psychological literature prove that users react to presented information differently depending on the presentation method, the specific task and its context. The presented paper describes the process of test development for selected methods of cartographic visualization of positional uncertainty, the utilization of multivariate testing software tool for test processing, and its consequent evaluation. Results of testing are further discussed in comparison with similar studies which have been published.
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Sonnenborg, T. O., D. Seifert, and J. C. Refsgaard. "Climate model uncertainty versus conceptual geological uncertainty in hydrological modeling." Hydrology and Earth System Sciences 19, no. 9 (September 16, 2015): 3891–901. http://dx.doi.org/10.5194/hess-19-3891-2015.
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Abstract. Projections of climate change impact are associated with a cascade of uncertainties including in CO2 emission scenarios, climate models, downscaling and impact models. The relative importance of the individual uncertainty sources is expected to depend on several factors including the quantity that is projected. In the present study the impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Each projection of future climate is a result of a GCM–RCM model combination (from the ENSEMBLES project) forced by the same CO2 scenario (A1B). The changes from the reference period (1991–2010) to the future period (2081–2100) in projected hydrological variables are evaluated and the effects of geological model and climate model uncertainties are quantified. The results show that uncertainty propagation is context-dependent. While the geological conceptualization is the dominating uncertainty source for projection of travel time and capture zones, the uncertainty due to the climate models is more important for groundwater hydraulic heads and stream flow.
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de Rocquigny, E. "An applied framework for uncertainty treatment and key challenges in hydrological and hydraulic modelingThis article is one of a selection of papers published in this Special Issue on Hydrotechnical Engineering." Canadian Journal of Civil Engineering 37, no. 7 (July 2010): 941–54. http://dx.doi.org/10.1139/l10-042.
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Within the larger domain of risk or environmental assessment, uncertainty treatment is gaining growing interest in the fields of hydrological and hydraulic modeling. A generic approach to quantitative uncertainty is suggested, putting together the applicable decision-making framework and associated probabilistic formulations involving uncertainty modeling (possibly through an inverse approach), uncertainty propagation, and the ranking of importance or sensitivity analysis. Accordingly, a number of generic statistical, physical, and numerical methods could be more largely disseminated in the water domain. Two axes of particular potential interest are outlined: the tricky choice of differentiating according to the epistemological nature of the uncertainty, with considerable impact on the formulation of the risk criterion and the associated level of complexity; the challenges posed by uncertainty modeling in the context of data scarcity, and the corresponding calibration and inverse probabilistic techniques, bound to be developed to best value hydro-monitoring and data acquisition systems under uncertainty.
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Eriksson, Olivia, Alexandra Jauhiainen, Sara Maad Sasane, Andrei Kramer, Anu G. Nair, Carolina Sartorius, and Jeanette Hellgren Kotaleski. "Uncertainty quantification, propagation and characterization by Bayesian analysis combined with global sensitivity analysis applied to dynamical intracellular pathway models." Bioinformatics 35, no. 2 (July 13, 2018): 284–92. http://dx.doi.org/10.1093/bioinformatics/bty607.
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Gerber, Edwin P., and Elisa Manzini. "The Dynamics and Variability Model Intercomparison Project (DynVarMIP) for CMIP6: assessing the stratosphere–troposphere system." Geoscientific Model Development 9, no. 9 (September 23, 2016): 3413–25. http://dx.doi.org/10.5194/gmd-9-3413-2016.
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Abstract. Diagnostics of atmospheric momentum and energy transport are needed to investigate the origin of circulation biases in climate models and to understand the atmospheric response to natural and anthropogenic forcing. Model biases in atmospheric dynamics are one of the factors that increase uncertainty in projections of regional climate, precipitation and extreme events. Here we define requirements for diagnosing the atmospheric circulation and variability across temporal scales and for evaluating the transport of mass, momentum and energy by dynamical processes in the context of the Coupled Model Intercomparison Project Phase 6 (CMIP6). These diagnostics target the assessments of both resolved and parameterized dynamical processes in climate models, a novelty for CMIP, and are particularly vital for assessing the impact of the stratosphere on surface climate change.
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MEHDIPOUR, S. HAMID, KOUROSH NOZARI, and S. DAVOOD SADATIAN. "FRACTIONAL ANALYSIS OF WAVE PACKET PROPAGATION AND SOME ASPECTS OF VSL WITH GUP." Fractals 16, no. 01 (March 2008): 33–42. http://dx.doi.org/10.1142/s0218348x0800379x.
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In this paper, we consider the problem of wave packet broadening in the framework of the Generalized Uncertainty Principle (GUP) of quantum gravity. Then we find a fractal Klein-Gordon equation to further analyze the wave packet broadening in a foamy spacetime. We derive a Modified Dispersion Relation (MDR) in the context of GUP which shows an extra broadening due to gravitational induced uncertainty. As a result of these dispersion relations, a generalized Klein-Gordon equation can be obtained. We solve this generalized equation under certain conditions to find both analytical and numerical results. We show that GUP can lead to a variation of the fundamental constants such as speed of light. With this novel properties, we find a time-dependent equation of state for perfect fluid in de Sitter universe and we interpret its physical implications.
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Verley, Gatien. "Dynamical equivalence classes for Markov jump processes." Journal of Statistical Mechanics: Theory and Experiment 2022, no. 2 (February 1, 2022): 023211. http://dx.doi.org/10.1088/1742-5468/ac4981.
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Abstract Two different Markov jump processes driven out of equilibrium by constant thermodynamic forces may have identical current fluctuations in the stationary state. The concept of dynamical equivalence classes emerges from this statement as proposed by Andrieux for discrete-time Markov chains on simple graphs. We define dynamical equivalence classes in the context of continuous-time Markov chains on multigraphs using the symmetric part of the rate matrices that define the dynamics. The freedom on the skew-symmetric part is at the core of the freedom inside a dynamical equivalence class. It arises from different splittings of the thermodynamic forces onto the system’s transitions.
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Zhang, Jian-Chen, Jing Zheng, and Tong-Jie Zhang. "Model-independent Reconstruction of the Cosmological Scale Factor as a Function of Lookback Time." Astrophysical Journal 928, no. 1 (March 1, 2022): 4. http://dx.doi.org/10.3847/1538-4357/ac549c.
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Abstract We present a model-independent method of reconstructing scale factor against lookback time from the Observational Hubble parameter Data (OHD). The reconstruction method is independent of dynamical models and is only based on the Friedmann–Robertson–Walker metric. We also calculate the propagation of error in the reconstruction process. The reconstruction data errors mainly come from trapezoidal rule approximation and the uncertainty from OHD. Furthermore, the model discrimination ability of original OHD and reconstructed a–t data is discussed under a dimensionless standard method. The a–t data can present the differences between cosmology models more clearly than H–z data by comparing their coefficients of variations. Finally, we add 50 simulated H(z) data to estimate the influence of future observation. More Hubble measurements in the future will help constrain cosmological parameters more accurately.
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Bernardini, A. E., and J. F. G. Santos. "CνB Damping of Primordial Gravitational Waves and the Fine-Tuning of the CγB Temperature Anisotropy." Advances in High Energy Physics 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/807857.
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Damping of primordial gravitational waves due to the anisotropic stress contribution owing to the cosmological neutrino background (CνB) is investigated in the context of a radiation-to-matter dominated universe. Besides its inherent effects on the gravitational wave propagation, the inclusion of the CνB anisotropic stress into the dynamical equations also affects the tensor mode contribution to the anisotropy of the cosmological microwave background (CγB) temperature. The mutual effects on the gravitational waves and on the CγB are obtained through a unified prescription for a radiation-to-matter dominated scenario. The results are confronted with some preliminary results for the radiation dominated scenario. Both scenarios are supported by a simplified analytical framework, in terms of a scale independent dynamical variable,kη, that relates cosmological scales,k, and the conformal time,η. The background relativistic (hot dark) matter essentially works as an effective dispersive medium for the gravitational waves such that the damping effect is intensified for the universe evolving to the matter dominated era. Changes on the temperature variance owing to the inclusion of neutrino collision terms into the dynamical equations result in spectral features that ratify that the multipole expansion coefficientsClT’s die out forl~100.
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De Bastiani, Marco, Alex Aimetta, Roberto Bonifetto, and Sandra Dulla. "Application of the Polynomial Chaos Expansion to the Uncertainty Propagation in Fault Transients in Nuclear Fusion Reactors: DTT TF Fast Current Discharge." Applied Sciences 14, no. 3 (January 26, 2024): 1068. http://dx.doi.org/10.3390/app14031068.
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Nuclear fusion reactors are composed of several complex components whose behavior may be not certain a priori. This uncertainty may have a significant impact on the evolution of fault transients in the machine, causing unexpected damage to its components. For this reason, a suitable method for the uncertainty propagation during those transients is required. The Monte Carlo method would be the reference option, but it is, in most of the cases, not applicable due to the large number of required, repeated simulations. In this context, the Polynomial Chaos Expansion has been considered as a valuable alternative. It allows us to create a surrogate model of the original one in terms of orthogonal polynomials. Then, the uncertainty quantification is performed repeatedly, relying on this much simpler and faster model. Using the fast current discharge in the Divertor Tokamak Test Toroidal Field (DTT TF) coils as a reference scenario, the following method has been applied: the uncertainty on the parameters of the Fast Discharge Unit (FDU) varistor disks is propagated to the simulated electrical and electromagnetic relevant effects. Eventually, two worst-case scenarios are analyzed from a thermal–hydraulic point of view with the 4C code, simulating a fast current discharge as a consequence of a coil quench. It has been demonstrated that the uncertainty on the inputs (varistor parameters) strongly propagates, leading to a wide range of possible scenarios in the case of accidental transients. This result underlines the necessity of taking into account and propagating all possible uncertainties in the design of a fusion reactor according to the Best Estimate Plus Uncertainty approach. The uncertainty propagation from input data to electrical, electromagnetic, and thermal hydraulic results, using surrogate models, is the first of its kind in the field of the modeling of superconducting magnets for nuclear fusion applications.
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Machado, M. R., and J. M. C. Dos Santos. "Reliability Analysis of Damaged Beam Spectral Element with Parameter Uncertainties." Shock and Vibration 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/574846.
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The paper examines the influence of uncertainty parameters on the wave propagation responses at high frequencies for a damaged beam structure in the structural reliability context. The reliability analyses were performed using the perturbation method, First-Order Reliability Method (FORM), and response surface method (RSM) which were compared with Monte Carlo simulation (MCS) under the spectral element method environment. The simulated results were performed to investigate the effects of material property and geometric uncertainties on the response at high frequency modes, such as the computational efficiency of reliability methods. For the first time, the spectral element method is used in the context of reliability analysis at medium and high frequency bands applied to damage detection. It has shown the effects of parameters uncertainty on the dynamic beam response due on an impulsive load and the robustness of each method. Numerical examples in a bending vibrating beam with random parameters are performed to verify the computational efficiency of the present study.
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Masoudian, Sahar, Jason Sharples, Zlatko Jovanoski, Isaac Towers, and Simon Watt. "Incorporating Stochastic Wind Vectors in Wildfire Spread Prediction." Atmosphere 14, no. 11 (October 27, 2023): 1609. http://dx.doi.org/10.3390/atmos14111609.
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The stochastic nature of environmental factors that govern the behavior of fire, such as wind and fuel, exposes wildfire modeling to a degree of uncertainty. In order to produce more realistic wildfire predictions, it is, therefore, necessary to incorporate these uncertainties within wildfire models in a way that reflects the influence of environmental stochasticity on wildfire propagation. Otherwise, the risks of the potential danger of a given wildfire may be under-represented. Specifically, environmental stochasticity in the form of wind variability results in considerable uncertainty in the output of fire spread models. Here, we consider two stochastic wind models and their implementation in the spark fire simulator framework to capture the environmental uncertainty related to wind variability. The results are compared with the output from purely deterministic wildfire spread models and are discussed in the context of the potential ramifications for wildfire risk management.
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Burrello, Stefano, Maria Colonna, Francesco Matera, and Rui Wang. "Dilute nuclear matter with light clusters and in-medium effects: Towards a unified dynamical framework." EPJ Web of Conferences 311 (2024): 00005. http://dx.doi.org/10.1051/epjconf/202431100005.
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Understanding the dynamics of dilute nuclear matter is of crucial importance in several contexts, ranging from nuclear fragmentation to supernova collapse and gravitational-wave signal emission. However, within a unified dynamical framework, describing the concurrent appearance of light clusters, emerging from few-nucleon correlations, and heavier fragments formed due to large-scale correlations related to liquid-gas phase instabilities, remains a significant challenge. Within a linearized Vlasov dynamics, we show that light clusters, and in-medium effects in their propagation, have a strong influence on the growth and characteristics of the unstable modes that prelude the fragmentation of the system. These findings might pave the way for novel avenues in the study of dilute composite matter, envisioning intriguing consequences for heavy-ion collisions and in the broader astrophysical context.
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Millán, Luis F., Gloria L. Manney, Harald Boenisch, Michaela I. Hegglin, Peter Hoor, Daniel Kunkel, Thierry Leblanc, et al. "Multi-parameter dynamical diagnostics for upper tropospheric and lower stratospheric studies." Atmospheric Measurement Techniques 16, no. 11 (June 15, 2023): 2957–88. http://dx.doi.org/10.5194/amt-16-2957-2023.
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Abstract. Ozone trend estimates have shown large uncertainties in the upper troposphere–lower stratosphere (UTLS) region despite multi-decadal observations available from ground-based, balloon, aircraft, and satellite platforms. These uncertainties arise from large natural variability driven by dynamics (reflected in tropopause and jet variations) as well as the strength in constituent transport and mixing. Additionally, despite all the community efforts there is still a lack of representative high-quality global UTLS measurements to capture this variability. The Stratosphere-troposphere Processes And their Role in Climate (SPARC) Observed Composition Trends and Variability in the UTLS (OCTAV-UTLS) activity aims to reduce uncertainties in UTLS composition trend estimates by accounting for this dynamically induced variability. In this paper, we describe the production of dynamical diagnostics using meteorological information from reanalysis fields that facilitate mapping observations from several platforms into numerous geophysically based coordinates (including tropopause and upper tropospheric jet relative coordinates). Suitable coordinates should increase the homogeneity of the air masses analyzed together, thus reducing the uncertainty caused by spatiotemporal sampling biases in the quantification of UTLS composition trends. This approach thus provides a framework for comparing measurements with diverse sampling patterns and leverages the meteorological context to derive maximum information on UTLS composition and trends and its relationships to dynamical variability. The dynamical diagnostics presented here are the first comprehensive set describing the meteorological context for multi-decadal observations by ozonesondes, lidar, aircraft, and satellite measurements in order to study the impact of dynamical processes on observed UTLS trends by different sensors on different platforms. Examples using these diagnostics to map multi-platform datasets into different geophysically based coordinate systems are provided. The diagnostics presented can also be applied to analysis of greenhouse gases other than ozone that are relevant to surface climate and UTLS chemistry.
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Vaidogas, Egidijus R. "ACTIONS IMPOSED ON STRUCTURES DURING MAN‐MADE ACCIDENTS: PREDICTION VIA SIMULATION‐BASED UNCERTAINTY PROPAGATION." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 11, no. 3 (September 30, 2005): 225–42. http://dx.doi.org/10.3846/13923730.2005.9636354.
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Prediction of mechanical, thermal, and chemical actions induced during man‐made accidents (accidental actions) is of crucial importance to assessing potential damage to structures exposed to these actions. A logical result of such a prediction may be expressed in the form of probabilistic models describing likelihood of occurrence and characteristics of accidental actions. For many types of accidental actions the models are to be selected under the conditions of incomplete knowledge about and/or scarce statistical information on intensities and likelihood of imposition of the actions. This paper proposes a simulation‐based procedure intended for a selection of the probabilistic models under these conditions. The proposed procedure is formulated in the context of the classical Bayesian approach to risk assessment. The main idea of it is that statistical samples necessary for fitting the probabilistic action models can be acquired from a stochastic simulation of accident sequences leading to an imposition of accidental actions. Formally, the stochastic simulation of accidents serves the purpose of propagating uncertainties related to the physical phenomena capable of inducing accidental actions. These uncertainties are quantified in line with the classical Bayesian approach. The simulation‐based procedure can be used for damage assessment and risk studies within the methodological framework provided by the above‐mentioned approach.
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Gibson, Peter B., Duane E. Waliser, Huikyo Lee, Baijun Tian, and Elias Massoud. "Climate Model Evaluation in the Presence of Observational Uncertainty: Precipitation Indices over the Contiguous United States." Journal of Hydrometeorology 20, no. 7 (July 1, 2019): 1339–57. http://dx.doi.org/10.1175/jhm-d-18-0230.1.
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Abstract Climate model evaluation is complicated by the presence of observational uncertainty. In this study we analyze daily precipitation indices and compare multiple gridded observational and reanalysis products with regional climate models (RCMs) from the North American component of the Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) multimodel ensemble. In the context of model evaluation, observational product differences across the contiguous United States (CONUS) are also deemed nontrivial for some indices, especially for annual counts of consecutive wet days and for heavy precipitation indices. Multidimensional scaling (MDS) is used to directly include this observational spread into the model evaluation procedure, enabling visualization and interpretation of model differences relative to a “cloud” of observational uncertainty. Applying MDS to the evaluation of NA-CORDEX RCMs reveals situations of added value from dynamical downscaling, situations of degraded performance from dynamical downscaling, and the sensitivity of model performance to model resolution. On precipitation days, higher-resolution RCMs typically simulate higher mean and extreme precipitation rates than their lower-resolution pairs, sometimes improving model fidelity with observations. These results document the model spread and biases in daily precipitation extremes across the full NA-CORDEX model ensemble. The often-large divergence between in situ observations, satellite data, and reanalysis, shown here for CONUS, is especially relevant for data-sparse regions of the globe where satellite and reanalysis products are extensively relied upon. This highlights the need to carefully consider multiple observational products when evaluating climate models.
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KHINE, YU YU, DENNIS B. CREAMER, and STEVEN FINETTE. "ACOUSTIC PROPAGATION IN AN UNCERTAIN WAVEGUIDE ENVIRONMENT USING STOCHASTIC BASIS EXPANSIONS." Journal of Computational Acoustics 18, no. 04 (December 2010): 397–441. http://dx.doi.org/10.1142/s0218396x10004255.
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A generalization of acoustic propagation in an uncertain ocean waveguide environment is described using a probabilistic formulation in terms of stochastic basis expansions. The problem is studied in the context of wave propagation in random media, where environmental uncertainty and its interaction with the acoustic field are described by stochastic, rather than deterministic parameters and fields. This representation, constructed explicitly in terms of Karhunen-Loève (KL) and polynomial chaos (PC) expansions, leads to coupled differential equations for the expansion coefficients from which the stochastic acoustic field can be obtained as a random process. The equations are solved in the narrow-angle parabolic approximation using a split-step method to compute moments of the random acoustic field at any point in the waveguide. Results are compared with Monte-Carlo computations of the acoustic field in the same environment to study the convergence of the truncated stochastic basis expansion representing the acoustic field. The rate of convergence of the truncated chaos expansion was found to be dependent on the particular moment computed. For the first and second moments corresponding to the mean field and the field intensity, convergence was achieved rapidly, only requiring low order expansions. Another second moment, the acoustic spatial coherence, converged more slowly due to the relative phase information that, in this formulation, is described by polynomial approximation. While stochastic basis expansions show promise for the development of compact representations of the acoustic field in the presence of environmental uncertainty, accelerated convergence schemes will be needed to allow for practical applications.
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Asif Zahoor Raja, Muhammad, Adeeba Haider, Kottakkaran Sooppy Nisar, and Muhammad Shoaib. "Intelligent computing knacks for infected media and time delay impacts on dynamical behaviors and control measures of rumor-spreading model." AIMS Biophysics 11, no. 1 (2024): 1–17. http://dx.doi.org/10.3934/biophy.2024001.
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<abstract> <p>Artificial neural networks (ANNs) have transformed machine learning and computational intelligence by providing unprecedented powers in modeling complicated data and addressing a wide range of challenges. In the field of ANNs, back propagation is a key approach for training neural networks. However, obtaining optimum network efficiency while tackling over fitting and controlling uncertainty is a difficult task. The present study employs the Bayesian Regularization Method with Neural Network Backpropagation (BRM-NNB) technique to investigate the rumors spreading delay model. With their rapid spread, rumors have the potential to cause fear and even financial loss. Thus, we must take decisive actions to stop the rumor from spreading. Nowadays, rumors can spread through instant messaging, emails, or publishing, thanks to the development of the internet. In this research, an XY-SIR rumors spreading delay model (XY-SIR-RS-DM) is investigated in relation to the novel spreading pattern. Media networks can be categorized into susceptible and infected media, while friendship networks can be categorized into three groups: spreaders (S, I, and R), who actively disseminate rumors, those who are ignorant and those who have no desire to do so. To estimate the solution of the suggested model, the Bayesian regularization method with neural network back propagation (BRM-NNB) is used. The data set is generated by applying the explicit Runge-Kutta method. The computing BRM-NNB strategy is implemented for three different performances, where the training, testing, and verification data are reported as 80%, 15%, and 5%, respectively, with 10 hidden neurons. To verify the validity of the developed artificial intelligence (AI) approach represented by the BRM-NNB, outcome comparisons are presented. The result is compatible with obtaining a minimal absolute error that is nearly equal to zero, thereby proving the efficacy of the proposed method.</p> </abstract>
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Cleuren, Bart, and Ralf Eichhorn. "Energetics of a microscopic Feynman ratchet." Journal of Statistical Mechanics: Theory and Experiment 2023, no. 4 (April 1, 2023): 043202. http://dx.doi.org/10.1088/1742-5468/acc64e.
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Abstract A general formalism is derived describing both dynamical and energetic properties of a microscopic Feynman ratchet. Work and heat flows are given as a series expansion in the thermodynamic forces, obtaining analytical expressions for the (non)linear response coefficients. Our results extend previously obtained expressions in the context of a chiral heat pump.
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Manke, Thomas, Lloyd Demetrius, and Martin Vingron. "An entropic characterization of protein interaction networks and cellular robustness." Journal of The Royal Society Interface 3, no. 11 (July 11, 2006): 843–50. http://dx.doi.org/10.1098/rsif.2006.0140.
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The structure of molecular networks is believed to determine important aspects of their cellular function, such as the organismal resilience against random perturbations. Ultimately, however, cellular behaviour is determined by the dynamical processes, which are constrained by network topology. The present work is based on a fundamental relation from dynamical systems theory, which states that the macroscopic resilience of a steady state is correlated with the uncertainty in the underlying microscopic processes, a property that can be measured by entropy. Here, we use recent network data from large-scale protein interaction screens to characterize the diversity of possible pathways in terms of network entropy. This measure has its origin in statistical mechanics and amounts to a global characterization of both structural and dynamical resilience in terms of microscopic elements. We demonstrate how this approach can be used to rank network elements according to their contribution to network entropy and also investigate how this suggested ranking reflects on the functional data provided by gene knockouts and RNAi experiments in yeast and Caenorhabditis elegans . Our analysis shows that knockouts of proteins with large contribution to network entropy are preferentially lethal. This observation is robust with respect to several possible errors and biases in the experimental data. It underscores the significance of entropy as a fundamental invariant of the dynamical system, and as a measure of structural and dynamical properties of networks. Our analytical approach goes beyond the phenomenological studies of cellular robustness based on local network observables, such as connectivity. One of its principal achievements is to provide a rationale to study proxies of cellular resilience and rank proteins according to their importance within the global network context.
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Lehtonen, Aleksi, and Juha Heikkinen. "Uncertainty of upland soil carbon sink estimate for Finland." Canadian Journal of Forest Research 46, no. 3 (March 2016): 310–22. http://dx.doi.org/10.1139/cjfr-2015-0171.
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Changes in the soil carbon stock of Finnish upland soils were quantified using forest inventory data, forest statistics, biomass models, litter turnover rates, and the Yasso07 soil model. Uncertainty in the estimated stock changes was assessed by combining model and sampling errors associated with the various data sources into variance–covariance matrices that allowed computationally efficient error propagation in the context of Yasso07 simulations. In sensitivity analysis, we found that the uncertainty increased drastically as a result of adding random year-to-year variation to the litter input. Such variation is smoothed out when using periodic inventory data with constant biomass models and turnover rates. Model errors (biomass, litter, understorey vegetation) and the systematic error of total drain had a marginal effect on the uncertainty regarding soil carbon stock change. Most of the uncertainty appears to be related to uncaptured annual variation in litter amounts. This is due to fact that variation in the slopes of litter input trends dictates the uncertainty of soil carbon stock change. If we assume that there is annual variation only in foliage and fine root litter rates and that this variation is less than 10% from year to year, then we can claim that Finnish upland forest soils have accumulated carbon during the first Kyoto period (2008–2012).
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Guillaume, Bruno, Bernard Porterie, Antonio Batista, Phil Cottle, and Armand Albergel. "Improving the uncertainty assessment of economic losses from large destructive wildfires." International Journal of Wildland Fire 28, no. 6 (2019): 420. http://dx.doi.org/10.1071/wf18104.
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Currently, as fire risk is considered a high-frequency and low-severity risk, actuarial and underwriting pricing and risk management methods have stuck to methods based purely on historical loss data. In the global context of both increasing fire severity with climate change and increasing wildland–urban interface area, the use of environmental-based dynamical modelling tools offers a good alternative to better evaluate fire risk. A new method is presented here that combines the raster-based fire spread model SWIFFT and a stochastic approach for generating the spatial and temporal distribution of ignition points. Monte Carlo simulations are conducted, and the uncertainties of hazard and losses are evaluated. Adapted and applied to the landscape conditions of a Brazilian plantation, it is shown to be well suited for a precise reconstruction of the fire burnt area. Finally, the uncertainty assessment of losses for this study zone is presented. We conclude by discussing this new method, which has a high level of traceable uncertainty and how fire risk insurance can deal with it, as well as the progress of future research that will benefit from this method.
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Kubíček, Petr, Milan Konečný, Jie Shen, Zdeněk Stachoň, Radim Štampach, Xinqian Wu, Lukáš Herman, Karel Staněk, and Tomáš Řezník. "Coincident Visualization of Uncertainty and Value for Point Symbols." Abstracts of the ICA 1 (July 15, 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-194-2019.
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<p><strong>Abstract.</strong> The issue of uncertainty as a generic phenomenon in the natural world has been at the centre of both the cartographic and GI communities since the beginning of geographic data quality research. In accordance with the development of theoretical aspects of cartographic visualization and methods of uncertainty propagation in models, the generally accepted opinion is that uncertainty has to be presented to users in an unambiguous and understandable way. Despite reasonable amounts of work done in the field of uncertainty visualization methods (MacEachren1992, Leitner and Buttenfield 2000) and the testing of impact of visualization on decision making (Senaratne et al. 2012; Kinkeldy et al. 2015), there is still a wide gap between the uncertainty visualization theory and widely accepted use of uncertainty representation within decision making process. MacEachren et al. (2012), Fabrikant et al. (2010) initiated the discussion towards optimization of uncertainty visualization regarding visual semiotics and use of specific representations of uncertainty within complex mapping compositions and application context. However, their studies left also some open questions to be solved regarding the international audience of users.</p><p>The presented study focused on two unresolved topics, namely how would users perceive the uncertainty point map signs within a complex map field and what would be the appropriate visualization in case if there is a need to combine value and uncertainty together. Moreover, we performed the testing in two different cultural environments in Brno (Czech Republic, Europe) and Nanjing (China).</p>
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Zulqarnain, Rana Muhammad, Wen-Xiu Ma, Sayed M. Eldin, Khush Bukht Mehdi, and Waqas Ali Faridi. "New Explicit Propagating Solitary Waves Formation and Sensitive Visualization of the Dynamical System." Fractal and Fractional 7, no. 1 (January 9, 2023): 71. http://dx.doi.org/10.3390/fractalfract7010071.
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This work discusses the soliton solutions for the fractional complex Ginzburg–Landau equation in Kerr law media. It is a particularly fascinating model in this context as it is a dissipative variant of the Hamiltonian nonlinear Schrödinger equation with solutions that create localized singularities in finite time. The ϕ6-model technique is one of the generalized methodologies exerted on the fractional complex Ginzburg–Landau equation to find the new solitary wave profiles. As a result, solitonic wave patterns develop, including Jacobi elliptic function, periodic, dark, bright, single, dark-bright, exponential, trigonometric, and rational solitonic structures, among others. The assurance of the practicality of the solitary wave results is provided by the constraint condition corresponding to each achieved solution. The graphical 3D and contour depiction of the attained outcomes is shown to define the pulse propagation behaviors while imagining the pertinent data for the involved parameters. The sensitive analysis predicts the dependence of the considered model on initial conditions. It is a reliable and efficient technique used to generate generalized solitonic wave profiles with diverse soliton families. Furthermore, we ensure that all results are innovative and mark remarkable impacts on the prevailing solitary wave theory literature.
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Ahmed, Shabbir, and Fotis Kopsaftopoulos. "Stochastic Identification of Guided Wave Propagation under Ambient Temperature via Non-Stationary Time Series Models." Sensors 21, no. 16 (August 23, 2021): 5672. http://dx.doi.org/10.3390/s21165672.
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In the context of active-sensing guided-wave-based acousto-ultrasound structural health monitoring, environmental and operational variability poses a considerable challenge in the damage diagnosis process as they may mask the presence of damage. In this work, the stochastic nature of guided wave propagation due to the small temperature variation, naturally occurring in the ambient or environment, is rigorously investigated and modeled with the help of stochastic time-varying time series models, for the first time, with a system identification point of view. More specifically, the output-only recursive maximum likelihood time-varying auto-regressive model (RML-TAR) is employed to investigate the uncertainty in guided wave propagation by analyzing the time-varying model parameters. The steps and facets of the identification procedure are presented, and the obtained model is used for modeling the uncertainty of the time-varying model parameters that capture the underlying dynamics of the guided waves. The stochasticity inherent in the modal properties of the system, such as natural frequencies and damping ratios, is also analyzed with the help of the identified RML-TAR model. It is stressed that the narrow-band high-frequency actuation for guided wave propagation excites more than one frequency in the system. The values and the time evolution of those frequencies are analyzed, and the associated uncertainties are also investigated. In addition, a high-fidelity finite element (FE) model was established and Monte Carlo simulations on that FE model were carried out to understand the effect of small temperature perturbation on guided wave signals.
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Forget, Gaël. "Mapping Ocean Observations in a Dynamical Framework: A 2004–06 Ocean Atlas." Journal of Physical Oceanography 40, no. 6 (June 1, 2010): 1201–21. http://dx.doi.org/10.1175/2009jpo4043.1.
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Abstract This paper exploits a new observational atlas for the near-global ocean for the best-observed 3-yr period from December 2003 through November 2006. The atlas consists of mapped observations and derived quantities. Together they form a full representation of the ocean state and its seasonal cycle. The mapped observations are primarily altimeter data, satellite SST, and Argo profiles. GCM interpolation is used to synthesize these datasets, and the resulting atlas is a fairly close fit to each one of them. For observed quantities especially, the atlas is a practical means to evaluate free-running GCM simulations and to put field experiments into a broader context. The atlas-derived quantities include the middepth dynamic topography, as well as ocean fluxes of heat and salt–freshwater. The atlas is publicly available online (www.ecco-group.org). This paper provides insight into two oceanographic problems that are the subject of vigorous ongoing research. First, regarding ocean circulation estimates, it can be inferred that the RMS uncertainty in modern surface dynamic topography (SDT) estimates is only on the order of 3.5 cm at scales beyond 300 km. In that context, it is found that assumptions of “reference-level” dynamic topography may yield significant errors (of order 2.2 cm or more) in SDT estimates using in situ data. Second, in the perspective of mode water investigations, it is estimated that ocean fluxes (advection plus mixing) largely contribute to the seasonal fluctuation in heat content and freshwater/salt content. Hence, representing the seasonal cycle as a simple interplay of air–sea flux and ocean storage would not yield a meaningful approximation. For the salt–freshwater seasonal cycle especially, contributions from ocean fluxes usually exceed direct air–sea flux contributions.
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Hoes, O. A. C., R. W. Hut, N. C. van de Giesen, and M. Boomgaard. "Reconstruction of the 1945 Wieringermeer Flood." Natural Hazards and Earth System Sciences Discussions 1, no. 2 (March 11, 2013): 417–41. http://dx.doi.org/10.5194/nhessd-1-417-2013.
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Abstract. The present state-of-the-art in flood risk assessment focuses on breach models, flood propagation models, and economic modelling of flood damage. However, models need to be validated with real data to avoid erroneous conclusions. Such reference data can either be historic data, or can be obtained from controlled experiments. The inundation of the Wieringermeer polder in the Netherlands in April 1945 is one of the few examples for which sufficient historical information is available. The objective of this article is to compare the flood simulation with flood data from 1945. The context, the breach growth process and the flood propagation are explained. Key findings for current flood risk management addresses the importance of the drainage canal network during the inundation of a polder, and the uncertainty that follows from not knowing the breach growth parameters. This case study shows that historical floods provide valuable data for the validation of models and reveal lessons that are applicable in current day flood risk management.
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Lages Martins, Luis, Álvaro Ribeiro, Catarina Simões, and Ricardo Mendes. "Measurement uncertainty evaluation of equivalent roughness in hydraulic pipes." Acta IMEKO 13, no. 3 (August 24, 2024): 1–6. http://dx.doi.org/10.21014/actaimeko.v13i3.1766.
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This paper addresses the quantification of the dispersion of equivalent roughness values obtained from the experimental study of hydraulic pipes used, for example, in water supply networks. This quantity is mainly used in the determination of the friction factor related to pipe fluid flow. In this context, non-linear and complex mathematical models, such as the Colebrook-White equation, are applied to characterize the equivalent roughness of hydraulic pipes composed of different types of materials. However, knowledge about the measurement uncertainty of the obtained estimates is still reduced, having a direct impact in the conformity assessment of this type of hydraulic component and in the technical comparison between different types of pipes (materials and manufacturers). The paper describes the application of a Monte Carlo method (MCM) in the measurement uncertainty evaluation of equivalent roughness. In addition to presenting the theoretical and experimental background, the paper describes the measurement uncertainty propagation, from the probabilistic formulation of the input quantities up to the output quantity. A numerical example, based on experimental data retrieved from field testing of hydraulic pipes integrated in a large-scale agricultural irrigation network, is shown in the paper, illustrating the suitability, advantages, and limitations of the proposed approach.
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Bona, Jerry L., S. M. Sun, and Bing-Yu Zhang. "Forced Oscillations of a Damped Korteweg-de Vries Equation in a Quarter Plane." Communications in Contemporary Mathematics 05, no. 03 (June 2003): 369–400. http://dx.doi.org/10.1142/s021919970300104x.
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Laboratory experiments have shown that when nonlinear, dispersive waves are forced periodically from one end of an undisturbed stretch of the medium of propagation, the signal eventually becomes temporally periodic at each spatial point. It is our purpose here to establish this as a fact at least in the context of a damped Korteweg-de Vries equation. Thus, consideration is given to the initial-boundary-value problem [Formula: see text] For this problem, it is shown that if the small amplitude, boundary forcing h is periodic of period T, say, then the solution u of (*) is eventually periodic of period T. More precisely, we show for each x > 0, that u(x, t + T) - u(x, t) converges to zero exponentially as t → ∞. Viewing (*) (without the initial condition) as an infinite dimensional dynamical system in the Hilbert space Hs(R+) for suitable values of s, we also demonstrate that for a given, small amplitude time-periodic boundary forcing, the system (*) admits a unique limit cycle, or forced oscillation (a solution of (*) without the initial condition that is exactly periodic of period T). Furthermore, we show that this limit cycle is globally exponentially stable. In other words, it comprises an exponentially stable attractor for the infinite-dimensional dynamical system described by (*).
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Guillory, Joffray, Daniel Truong, and Jean-Pierre Wallerand. "Multilateration with Self-Calibration: Uncertainty Assessment, Experimental Measurements and Monte-Carlo Simulations." Metrology 2, no. 2 (May 11, 2022): 241–62. http://dx.doi.org/10.3390/metrology2020015.
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Large-volume metrology is essential to many high-value industries and contributes to the factories of the future. In this context, we have developed a tri-dimensional coordinate measurement system based on a multilateration technique with self-calibration. In practice, an absolute distance meter, traceable to the SI metre, is shared between four measurement heads by fibre-optic links. From these stations, multiple distance measurements of several target positions are then performed to, at the end, determine the coordinates of these targets. The uncertainty on these distance measurements has been determined with a consistent metrological approach and it is better than 5 µm. However, the propagation of this uncertainty into the measured positions is not a trivial task. In this paper, an analytical solution for the uncertainty assessment of the positions of both targets and heads under a multilateration scenario with self-calibration is provided. The proposed solution is then compared to Monte-Carlo simulations and to experimental measurements: it follows that all three approaches are well agreed, which suggests that the proposed analytical model is accurate. The confidence ellipsoids provided by the analytical solution described well the geometry of the errors.