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1
Greegar, G., and C. S. Manohar. "Global response sensitivity analysis of uncertain structures." Structural Safety 58 (January 2016): 94–104. http://dx.doi.org/10.1016/j.strusafe.2015.09.006.
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Abhinav, S., and C. S. Manohar. "Global Response Sensitivity Analysis of Randomly Excited Dynamic Structures." Journal of Engineering Mechanics 142, no. 3 (March 2016): 04015094. http://dx.doi.org/10.1061/(asce)em.1943-7889.0001019.
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Douthe, Cyril, Chloé Girardon, and Romain Boulaud. "Sensitivity Analysis of the Global Response of Flexible Rockfall Barriers." Geosciences 12, no. 2 (February 6, 2022): 75. http://dx.doi.org/10.3390/geosciences12020075.
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Protection barriers against the fall of boulders and rocks are structures with non-linear mechanical behaviour that make the study particularly complex. In this study, the understanding of an experimentally observed variability was investigated numerically using a non-linear spring-mass equivalence. First, key figures of the experiments on which this study is based are detailed. Then, the numerical model for the dynamic simulation of the barrier deformation under impact is presented. Finally, the variability due to block-related parameters and then net-related parameters are explored and evidence the role of the cables’ geometric stiffness in the global response of the fence.
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Soliman, Hatem, Izhar Ahmed Khan, and Yasir Hussain. "Global Sensitivity Analysis for Fuzzy RDF Data." International Journal of Software Engineering and Knowledge Engineering 31, no. 08 (August 2021): 1119–44. http://dx.doi.org/10.1142/s0218194021500352.
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The resource description framework (RDF) was adopted by the World Wide Web (W3C) as an essential semantic web standard and the RDF scheme. It accords the hard semantics in the description and wields the crisp metadata. However, it usually produces vague or ambiguous information. Consequently, fuzzy RDF helps deal with such special data by transforming the crisp values into a fuzzy set. A method for analyzing fuzzy RDF data is proposed in this paper. To this end, first, we decompose the RDF into fuzzy RDF variables. Second, we are designing a model for global sensitivity analysis based on the decomposition of fuzzy RDF. It figures out the ambiguities of fuzzy RDF data. The proposed global sensitivity analysis model provides the importance of fuzzy RDF data by considering the response function’s structure and reselects it to a certain degree. A practical tool for sensitivity analysis of fuzzy RDF data has also been implemented based on the proposed model.
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Araya-Melo, P. A., M. Crucifix, and N. Bounceur. "Global sensitivity analysis of Indian Monsoon during the Pleistocene." Climate of the Past Discussions 10, no. 2 (April 11, 2014): 1609–51. http://dx.doi.org/10.5194/cpd-10-1609-2014.
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Abstract. The sensitivity of Indian Monsoon to the full spectrum of climatic conditions experienced during the Pleistocene is estimated using the climate model HadCM3. The methodology follows a global sensitivity analysis based on the emulator approach of Oakley and O'Hagan (2004) implemented following a three-step strategy: (1) develop an experiment plan, designed to efficiently sample a 5-dimensional input space spanning Pleistocene astronomical configurations (3 parameters), CO2 concentration and a Northern Hemisphere glaciation index, (2) develop, calibrate and validate an emulator of HadCM3, in order to estimate the response of the Indian Monsoon over the full input space spanned by the experiment design, and (3) estimate and interpret sensitivity diagnostics, including sensitivity measures, in order to synthesize the relative importance of input factors on monsoon dynamics, estimate the phase of the monsoon intensity response with respect to that of insolation, and detect potential non-linear phenomena. Specifically, we focus on four variables: summer (JJAS) temperature and precipitation over North India, and JJAS sea-surface temperature and mixed-layer depth over the north-western side of the Indian ocean. It is shown that precession controls the response of four variables: continental temperature in phase with June to July insolation, high glaciation favouring a late-phase response, sea-surface temperature in phase with May insolation, and continental precipitation in phase with July insolation, and mixed-layer depth in antiphase with the latter. CO2 variations controls temperature variance with an amplitude similar to that of precession. The effect of glaciation is dominated by the albedo forcing, and its effect on precipitation competes with that of precession. Obliquity is a secondary effect, negligible on most variables except sea-surface temperature. It is also shown that orography forcing reduces the glacial cooling, and even has a positive effect on precipitation. As regards the general methodology, it is shown that the emulator provides a powerful approach, not only to express model sensitivity, but also to estimate internal variability (based on the nugget term introduced in the correlation function of the emulator) and detect anomalous simulations.
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Jensen, Hector A. "Global Approximation of Response Surfaces and Application to Design Sensitivity Analysis." Applied Mechanics Reviews 48, no. 11S (November 1, 1995): S181—S188. http://dx.doi.org/10.1115/1.3005069.
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An approach based on global approximations to obtain response surfaces of structural systems is presented. The response surfaces are then used to evaluate the sensitivity of the system by considering the global behavior of the system response when the design parameters vary within a bounded region. The formulation of the method is based on the determination of approximated response surfaces, which are computed by minimizing a residual function over the design space. Different coefficients of sensitivity are introduced to measure the global variability of the system response. A numerical example is considered in order to show the usefulness of this technique. Great insight into the behavior of the system can be gained using this methodology. Finally, some extensions of the present work are presented.
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Greegar, G., and C. S. Manohar. "Global response sensitivity analysis using probability distance measures and generalization of Sobol's analysis." Probabilistic Engineering Mechanics 41 (July 2015): 21–33. http://dx.doi.org/10.1016/j.probengmech.2015.04.003.
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Mingliang, Zheng. "Robust Global Sensitivity Analysis for Robust Design under Parameter Uncertainty." Journal of Modern Mechanical Engineering and Technology 9 (September 4, 2022): 50–54. http://dx.doi.org/10.31875/2409-9848.2022.09.6.
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Abstract: Based on the theory and method of robust design, the robust global sensitivity analysis of products or systems under parameter uncertainty is discussed. A basic idea of the author is to define the robust sensitivity that is the importance measure of the design variables for product functional response function distribution. The Taylor series of moments of the functional response function is carried out, and the approximate analytical formulas of robust global sensitivity are obtained by using the importance measure model based on variance. Finally, a numerical example is given to illustrate the operation principle of this method, and an engineering example is given to verify the correctness of this method.
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Bhonsale, Satyajeet, Carlos André Muñoz López, and Jan Van Impe. "Global Sensitivity Analysis of a Spray Drying Process." Processes 7, no. 9 (August 23, 2019): 562. http://dx.doi.org/10.3390/pr7090562.
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Spray drying is a key unit operation used to achieve particulate products of required properties. Despite its widespread use, the product and process design, as well as the process control remain highly empirical and depend on trial and error experiments. Studying the effect of operational parameters experimentally is tedious, time consuming, and expensive. In this paper, we carry out a model-based global sensitivity analysis (GSA) of the process. Such an exercise allows us to quantify the impact of different process parameters, many of which interact with each other, on the product properties and conditions that have an impact on the functionality of the final drug product. Moreover, classical sensitivity analysis using the Sobol-based sensitivity indices was supplemented by a polynomial chaos-based sensitivity analysis, which proved to be an efficient method to reduce the computational cost of the GSA. The results obtained demonstrate the different response dependencies of the studied variables, which helps to identify possible control strategies that can result in major robustness for the spray drying process.
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Araya-Melo, P. A., M. Crucifix, and N. Bounceur. "Global sensitivity analysis of the Indian monsoon during the Pleistocene." Climate of the Past 11, no. 1 (January 12, 2015): 45–61. http://dx.doi.org/10.5194/cp-11-45-2015.
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Abstract. The sensitivity of the Indian monsoon to the full spectrum of climatic conditions experienced during the Pleistocene is estimated using the climate model HadCM3. The methodology follows a global sensitivity analysis based on the emulator approach of Oakley and O'Hagan (2004) implemented following a three-step strategy: (1) development of an experiment plan, designed to efficiently sample a five-dimensional input space spanning Pleistocene astronomical configurations (three parameters), CO2 concentration and a Northern Hemisphere glaciation index; (2) development, calibration and validation of an emulator of HadCM3 in order to estimate the response of the Indian monsoon over the full input space spanned by the experiment design; and (3) estimation and interpreting of sensitivity diagnostics, including sensitivity measures, in order to synthesise the relative importance of input factors on monsoon dynamics, estimate the phase of the monsoon intensity response with respect to that of insolation, and detect potential non-linear phenomena. By focusing on surface temperature, precipitation, mixed-layer depth and sea-surface temperature over the monsoon region during the summer season (June-July-August-September), we show that precession controls the response of four variables: continental temperature in phase with June to July insolation, high glaciation favouring a late-phase response, sea-surface temperature in phase with May insolation, continental precipitation in phase with July insolation, and mixed-layer depth in antiphase with the latter. CO2 variations control temperature variance with an amplitude similar to that of precession. The effect of glaciation is dominated by the albedo forcing, and its effect on precipitation competes with that of precession. Obliquity is a secondary effect, negligible on most variables except sea-surface temperature. It is also shown that orography forcing reduces the glacial cooling, and even has a positive effect on precipitation. As regards the general methodology, it is shown that the emulator provides a powerful approach, not only to express model sensitivity but also to estimate internal variability and detect anomalous simulations.
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Wei, Xiaojun, Jingwei Zhang, Hao Zhou, and Stana Živanović. "Sensitivity Analysis for Pedestrian-Induced Vibration in Footbridges." Buildings 12, no. 7 (June 22, 2022): 883. http://dx.doi.org/10.3390/buildings12070883.
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This paper aims to provide a novel insight into the influence of uncertainties in system- and pedestrian-induced load parameters on the vibration response of footbridges. The study begins with a sensitivity analysis for the vertical vibration response of a representative footbridge to two loading cases: a single pedestrian and a crowd. Two methods are utilized: the Sobol’-based global sensitivity analysis method and the local sensitivity analysis method. Uncertainties in all model parameters (which include bridge and human body dynamics in a walking posture, as well as dynamic force generated by humans) are considered in stochastic response estimation. Parametric analysis is then performed to investigate the influence of the variation of the mean values of the bridge modal mass, damping ratio, and natural frequency on the results of global and local sensitivity analysis. Systematic comparison of the results of global and local sensitivity analysis is performed to identify their similarities and differences. It has been found that the sensitive parameters and their importance ranking strongly depend on bridge modal properties and loading scenarios (i.e., a single pedestrian or a crowd crossing). The damping ratio and natural frequency of the human body are found to be the only two insensitive parameters. Therefore, they could be treated as deterministic parameters in the stochastic estimation of human-induced vibration. Global sensitivity analysis is recommended as a choice for the sensitivity analysis of pedestrian-induced vibration of footbridges as it leads to more reliable results, owing to the advantage of characterizing model sensitivity over the entire input spaces.
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Emery, A. F., and D. Bardot. "Determination of the Sensitivity of Heat Transfer Systems Using Global Sensitivity and Gaussian Processes." Journal of Heat Transfer 129, no. 8 (September 26, 2006): 1075–81. http://dx.doi.org/10.1115/1.2737478.
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A critical aspect of the design of systems or experiments is a sensitivity analysis to determine the effects of the different variables. This is usually done by representing the response by a Taylor series and evaluating the first-order derivatives at a nominal operating point. When there is uncertainty about the operating point, the common approach is the construction of a response surface and Monte Carlo sampling based on the probability distribution of these uncertain variables. Because of the expense of Monte Carlo sampling, it is important to restrict the analysis to those variables to which the response is most sensitive. Identification of the most sensitive parameters can be conveniently done using Global sensitivity, which both defines the most critical variables and also quantifies the effects of interacting variables. This also can be a computationally expensive process and, for complex models, is generally prohibitively expensive. A solution is the use of Gaussian processes that allows one to create a response surface using easy-to-evaluate functions. This paper describes the use of these ideas for a heat transfer problem.
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Bokov, Pavel M. "Asymptotic Analysis for the Variance-Based Global Sensitivity Indices." Science and Technology of Nuclear Installations 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/253045.
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We discuss the estimation of the uncertainty and sensitivity parameters for a model response under the assumption that the input variables are normally distributed and block-wise correlated with the covariance matrix, which is small in some norm. These conditions may arise when considering the impact of the group-wise neutron cross-sections' uncertainties on the uncertainty of some reactor parameters such as the neutron multiplication factor. The variance-based global sensitivity analysis, considered in our work, involves the calculation of multidimensional integrals. When the input uncertainties are small, the values of these integrals can be estimated using an asymptotic analysis method called the Laplace approximation. The asymptotic formulas for the output variance and for the global sensitivity indices have been obtained using the Laplace approximation method. It is demonstrated that the asymptotic formula for uncertainty propagation matches the uncertainty propagation formula being used in the local sensitivity analysis. The applicability of the obtained asymptotic approximations was successfully demonstrated on a test problem with realistic cross-section and covariance matrix values.
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Liu, Fuchao, Pengfei Wei, Chenghu Tang, Pan Wang, and Zhufeng Yue. "Global sensitivity analysis for multivariate outputs based on multiple response Gaussian process model." Reliability Engineering & System Safety 189 (September 2019): 287–98. http://dx.doi.org/10.1016/j.ress.2019.04.039.
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Yang, Fan, Weihua Xie, and Songhe Meng. "Global sensitivity analysis of low-velocity impact response of bio-inspired helicoidal laminates." International Journal of Mechanical Sciences 187 (December 2020): 106110. http://dx.doi.org/10.1016/j.ijmecsci.2020.106110.
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Zhou, Bing, Yuan Geng, and Xiaoting Huang. "Global sensitivity analysis of hydraulic system parameters to hydraulically interconnected suspension dynamic response." International Journal of Vehicle Noise and Vibration 11, no. 2 (2015): 185. http://dx.doi.org/10.1504/ijvnv.2015.070030.
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Su, Lei, Xiaoyu Zhang, Libo Xie, Peng Zhang, Anqi Zhang, Zhijian Qiu, and Xianzhang Ling. "Response characteristic of crane-wharf interaction system: Numerical simulation and global sensitivity analysis." Ocean Engineering 266 (December 2022): 113011. http://dx.doi.org/10.1016/j.oceaneng.2022.113011.
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Zhang, Feng, Xiayu Xu, Lu Wang, Zhongbing Liu, and Ling Zhang. "Global sensitivity analysis of two‐stage thermoelectric refrigeration system based on response variance." International Journal of Energy Research 44, no. 8 (April 7, 2020): 6623–30. http://dx.doi.org/10.1002/er.5398.
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Zhao, Zhihong, and Huanqin Hu. "Boundedness, stability and pattern formation for a predator-prey model with Sigmoid functional response and prey-taxis." Electronic Journal of Differential Equations 2023, no. 01-37 (May 4, 2023): 37. http://dx.doi.org/10.58997/ejde.2023.37.
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This article concerns the structure of the nonconstant steady states for a predator-prey model of Leslie-Gower type with Sigmoid functional and prey-taxis subject to the homogeneous Neumann boundary condition. The existence of bounded classical global solutions is discussed in bounded domains with arbitrary spatial dimension and any prey-taxis sensitivity coefficient. The local stability of the homogeneous steady state is analyzed to show that the prey-taxis sensitivity coefficient destabilizes the stability of the homogeneous steady state when prey defends. Then we study the existence and stability of the nonconstant positive steady state of the system over 1D domain by applying the bifurcation theory and present properties of local branches such as pitchfork and turning direction. Moreover, we discuss global bifurcation, homogeneous steady state solutions, nonconstant steady states solutions, spatio-temporal periodic solutions and spatio-temporal irregular solutions which demonstrate the coexistence and spatial distribution of prey and predator species. Finally, we perform numerical simulations to illustrate and support our theoretical analysis.
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Bounceur, N., M. Crucifix, and R. D. Wilkinson. "Global sensitivity analysis of the climate–vegetation system to astronomical forcing: an emulator-based approach." Earth System Dynamics Discussions 5, no. 2 (July 23, 2014): 901–43. http://dx.doi.org/10.5194/esdd-5-901-2014.
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Abstract. A global sensitivity analysis is used to describe the response of the Earth Climate Model of Intermediate Complexity LOVECLIM to components of the astronomical forcing (longitude of perihelion, obliquity, and eccentricity) assuming interglacial boundary conditions. Compared to previous studies, the sensitivity is global in the sense that it considers the full range of astronomical forcing that occurred during the Quaternary. We provide a geographical description of the variance due to the different components and their combinations and identify non-linear responses. The methodology relies on the estimation of sensitivity measures, which due to the computational cost of LOVECLIM cannot be obtained directly. Instead, we use a fast surrogate of the climate model, called an emulator, in place of the simulator. A space filling design (a maximin Latin hypercube constrained to span the range of astronomical forcings characterising the Pleistocene) is used to determine a set of experiments to run, which are then used to train a reduced-rank Gaussian process emulator. The simulator outputs considered are the principal modes of the annual mean temperature, precipitation, and the growing degree days, extracted using a principal component analysis. The experiments are run on two distinct land surface schemes to address the effect of vegetation response on climate. Sensitivity to initial conditions is also explicitly assessed. Precession and obliquity are found to contribute equally to growing degree days (GDD) in the Northern Hemisphere, and the effects of obliquity on the response of Southern Hemisphere temperature dominate precession effects. Further, compared to the original land-surface scheme with fixed vegetation, the LOVECLIM interactive vegetation induces non-linear responses in the Sahel-Sahara and Arctic sea-ice area. Finally, we find that there is no synergy between obliquity and precession.
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Nguyen, Τ. Η. "Global Sensitivity Analysis Of In-Plane Elastic Buckling Of Steel Arches." Engineering, Technology & Applied Science Research 10, no. 6 (December 20, 2020): 6476–80. http://dx.doi.org/10.48084/etasr.3833.
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Steel arches are widely used in civil engineering and industrial structures. Their response depends on material properties, geometric dimensions, and boundary conditions. The objective of the current study is to perform global sensitivity analysis and to assess the influence of random input parameters on the in-plane elastic buckling of steel arches. The in-plane elastic buckling load of steel arches under uniform compression proposed in previous studies is adopted. The influence of the random input variables of the structure is evaluated using Sobol’s global sensitivity analysis. Monte Carlo simulation is also employed to rank the influence of input random variables.
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Longfei, Tian, Lu Zhenzhou, and Hao Wenrui. "Investigation of the uncertainty of the in-plane mechanical properties of composite laminates." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 226, no. 7 (November 7, 2011): 1739–50. http://dx.doi.org/10.1177/0954406211426638.
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The uncertainty of the in-plane mechanical properties of the laminate used in an aircraft wing structure is investigated. Global sensitivity analysis is used to identify the source of the uncertainties of the response performance. Due to the limitations of the existing global sensitivity analysis method for nonlinear models with correlated input variables, a new one using nonlinear regression is proposed. Furthermore, a contribution matrix is defined for engineering convenience. Two nonlinear numerical examples are employed in this article to demonstrate the ability of the proposed global sensitivity analysis method. After applying the proposed global sensitivity analysis method to the laminate model, the contribution matrices are obtained; from these matrices, researchers can identify the dominant variance contributions that contribute the most to the response variance. Factor analysis is then employed to analyze the global sensitivity analysis results and determine the most efficient methods to decrease the variances of the in-plane elastic constants. Monte Carlo simulation is used to demonstrate the efficiency of the methods in decreasing the variances.
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Dell'Oca, Aronne, Monica Riva, and Alberto Guadagnini. "Moment-based metrics for global sensitivity analysis of hydrological systems." Hydrology and Earth System Sciences 21, no. 12 (December 8, 2017): 6219–34. http://dx.doi.org/10.5194/hess-21-6219-2017.
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Abstract. We propose new metrics to assist global sensitivity analysis, GSA, of hydrological and Earth systems. Our approach allows assessing the impact of uncertain parameters on main features of the probability density function, pdf, of a target model output, y. These include the expected value of y, the spread around the mean and the degree of symmetry and tailedness of the pdf of y. Since reliable assessment of higher-order statistical moments can be computationally demanding, we couple our GSA approach with a surrogate model, approximating the full model response at a reduced computational cost. Here, we consider the generalized polynomial chaos expansion (gPCE), other model reduction techniques being fully compatible with our theoretical framework. We demonstrate our approach through three test cases, including an analytical benchmark, a simplified scenario mimicking pumping in a coastal aquifer and a laboratory-scale conservative transport experiment. Our results allow ascertaining which parameters can impact some moments of the model output pdf while being uninfluential to others. We also investigate the error associated with the evaluation of our sensitivity metrics by replacing the original system model through a gPCE. Our results indicate that the construction of a surrogate model with increasing level of accuracy might be required depending on the statistical moment considered in the GSA. The approach is fully compatible with (and can assist the development of) analysis techniques employed in the context of reduction of model complexity, model calibration, design of experiment, uncertainty quantification and risk assessment.
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Liverman, Diana M. "The response of a global food model to possible climate changes: A sensitivity analysis." Journal of Climatology 6, no. 4 (1986): 355–73. http://dx.doi.org/10.1002/joc.3370060403.
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Tsokanas, Nikolaos, Roland Pastorino, and Božidar Stojadinović. "A Comparison of Surrogate Modeling Techniques for Global Sensitivity Analysis in Hybrid Simulation." Machine Learning and Knowledge Extraction 4, no. 1 (December 24, 2021): 1–21. http://dx.doi.org/10.3390/make4010001.
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Hybrid simulation is a method used to investigate the dynamic response of a system subjected to a realistic loading scenario. The system under consideration is divided into multiple individual substructures, out of which one or more are tested physically, whereas the remaining are simulated numerically. The coupling of all substructures forms the so-called hybrid model. Although hybrid simulation is extensively used across various engineering disciplines, it is often the case that the hybrid model and related excitation are conceived as being deterministic. However, associated uncertainties are present, whilst simulation deviation, due to their presence, could be significant. In this regard, global sensitivity analysis based on Sobol’ indices can be used to determine the sensitivity of the hybrid model response due to the presence of the associated uncertainties. Nonetheless, estimation of the Sobol’ sensitivity indices requires an unaffordable amount of hybrid simulation evaluations. Therefore, surrogate modeling techniques using machine learning data-driven regression are utilized to alleviate this burden. This study extends the current global sensitivity analysis practices in hybrid simulation by employing various different surrogate modeling methodologies as well as providing comparative results. In particular, polynomial chaos expansion, Kriging and polynomial chaos Kriging are used. A case study encompassing a virtual hybrid model is employed, and hybrid model response quantities of interest are selected. Their respective surrogates are developed, using all three aforementioned techniques. The Sobol’ indices obtained utilizing each examined surrogate are compared with each other, and the results highlight potential deviations when different surrogates are used.
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Sun, Wei, Maolin Shi, Jieling Li, Xin Ding, Lintao Wang, and Xueguan Song. "Surrogate-Based Multisource Sensitivity Analysis of TBM Driving System." Shock and Vibration 2018 (July 3, 2018): 1–14. http://dx.doi.org/10.1155/2018/5187535.
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TBM cutterhead driving system is generally an extraordinarily large and complex machine containing lots of parameters; understanding and assessment of its dynamic characteristics are a great challenge as each of these parameters has uncertainty. In this work, a hierarchical modeling method for the dynamic model of the complex gear transmission system is proposed based on the generalized finite element modeling idea. On this basis, the whole machine dynamic model of cutterhead driving system is established; both the characteristics of vibration responses and the meshing force are revealed. Vibration responses under the action of simulated load are estimated and verified by comparing with the data measured on the tunneling field, where the error is about 18%~50%. With the vibration response of the key nodes and the dynamic meshing force for the system dynamic characteristic evaluation index, considering the change of input parameters such as external loads, material parameters, meshing parameters, and coupling parameters, the global parameter sensitivity of system dynamic characteristics is analyzed based on the technology of surrogate model. Finally, variation of dynamic characteristics considering the interaction of polytypic parameters is obtained.
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Korngold, J. C., and G. A. Gabriele. "Multidisciplinary Analysis and Optimization of Discrete Problems Using Response Surface Methods." Journal of Mechanical Design 119, no. 4 (December 1, 1997): 427–33. http://dx.doi.org/10.1115/1.2826386.
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The objective of this paper is to present a new algorithm to efficiently optimize multidisciplinary, coupled nonhierarchic systems with discrete variables. The algorithm decomposes the system into contributing disciplines, and uses designed experiments within the disciplines to build local response surface approximations to the discipline analysis. First and second order Global Sensitivity Equations are formulated and approximated by experimental data to build approximations to the global design space. The global approximation is optimized using branch and bound or simulated annealing. Convergence is rapid for systems with near quadratic behavior. The algorithm is demonstrated on a unique multidisciplinary learning tool, the Design and Manufacturing Learning Environment. This environment provides multimedia simulation for product life cycle disciplines, including design, manufacturing, marketing, and sales.
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Jensen, H. A., and A. O. Cifuentes. "A Global Multidimensional Sensitivity Analysis of Electronic Systems Subjected to Time-Dependent Excitations." Journal of Electronic Packaging 120, no. 4 (December 1, 1998): 391–94. http://dx.doi.org/10.1115/1.2792652.
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This technical note presents a global sensitivity analysis method for the dynamic response of electronic systems considering several design parameters at the same time. The method is an extension of a previous method presented by the authors for the one-dimensional case (only one design variable at a time was considered subjected to uncertainty). The method is expected to be useful in the design, analysis and qualification of electronic components.
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Ruiz, Rafael O., and Viviana Meruane. "Uncertainties propagation and global sensitivity analysis of the frequency response function of piezoelectric energy harvesters." Smart Materials and Structures 26, no. 6 (May 2, 2017): 065003. http://dx.doi.org/10.1088/1361-665x/aa6cf3.
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Brunner, Patrick C., Tryggvi S. Stefansson, James Fountaine, Veronica Richina, and Bruce A. McDonald. "A Global Analysis of CYP51 Diversity and Azole Sensitivity in Rhynchosporium commune." Phytopathology® 106, no. 4 (April 2016): 355–61. http://dx.doi.org/10.1094/phyto-07-15-0158-r.
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CYP51 encodes the target site of the azole class of fungicides widely used in plant protection. Some ascomycete pathogens carry two CYP51 paralogs called CYP51A and CYP51B. A recent analysis of CYP51 sequences in 14 European isolates of the barley scald pathogen Rhynchosporium commune revealed three CYP51 paralogs, CYP51A, CYP51B, and a pseudogene called CYP51A-p. The same analysis showed that CYP51A exhibits a presence/absence polymorphism, with lower sensitivity to azole fungicides associated with the presence of a functional CYP51A. We analyzed a global collection of nearly 400 R. commune isolates to determine if these findings could be extended beyond Europe. Our results strongly support the hypothesis that CYP51A played a key role in the emergence of azole resistance globally and provide new evidence that the CYP51A gene in R. commune has further evolved, presumably in response to azole exposure. We also present evidence for recent long-distance movement of evolved CYP51A alleles, highlighting the risk associated with movement of fungicide resistance alleles among international trading partners.
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Dommenget, Dietmar. "Analysis of the Model Climate Sensitivity Spread Forced by Mean Sea Surface Temperature Biases." Journal of Climate 25, no. 20 (May 9, 2012): 7147–62. http://dx.doi.org/10.1175/jcli-d-11-00600.1.
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Abstract Uncertainties in the numerical realization of the physical climate system in coarse-resolution climate models in the Coupled Model Intercomparison Project phase 3 (CMIP3) cause large spread in the global mean and regional response amplitude to a given anthropogenic forcing scenario, and they cause the climate models to have mean state climates different from the observed and different from each other. In a series of sensitivity simulations with an atmospheric general circulation model coupled to a Slab Ocean Model, the role of differences in the control mean sea surface temperature (SST) in simulating the global mean and regional response amplitude is explored. The model simulations are forced into the control mean state SST of 24 CMIP3 climate models, and 2xCO2 forcing experiments are started from the different control states. The differences in the SST mean state cause large differences in other climate variables, but they do not reproduce most of the large spread in the mean state climate over land and ice-covered regions found in the CMIP3 model simulations. The spread in the mean SST climatology leads to a spread in the global mean and regional response amplitude of about 10%, which is about half as much as the spread in the response of the CMIP3 climate models and is therefore of considerable size. Since the SST climatology biases are only a small part of the models’ mean state climate biases, it is likely that the climate model’s mean state climate biases are accounting for a large part of the model’s climate sensitivity spread.
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Nordström, Karin, and David C. O'Carroll. "The motion after-effect: local and global contributions to contrast sensitivity." Proceedings of the Royal Society B: Biological Sciences 276, no. 1662 (February 25, 2009): 1545–54. http://dx.doi.org/10.1098/rspb.2008.1932.
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Motion adaptation is a widespread phenomenon analogous to peripheral sensory adaptation, presumed to play a role in matching responses to prevailing current stimulus parameters and thus to maximize efficiency of motion coding. While several components of motion adaptation (contrast gain reduction, output range reduction and motion after-effect) have been described, previous work is inconclusive as to whether these are separable phenomena and whether they are locally generated. We used intracellular recordings from single horizontal system neurons in the fly to test the effect of local adaptation on the full contrast-response function for stimuli at an unadapted location. We show that contrast gain and output range reductions are primarily local phenomena and are probably associated with spatially distinct synaptic changes, while the antagonistic after-potential operates globally by transferring to previously unadapted locations. Using noise analysis and signal processing techniques to remove ‘spikelets’, we also characterize a previously undescribed alternating current component of adaptation that can explain several phenomena observed in earlier studies.
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Shafer, S. R., R. A. Reinert, G. Eason, and S. E. Spruill. "Analysis of ozone concentration–biomass response relationships among open-pollinated families of loblolly pine." Canadian Journal of Forest Research 23, no. 4 (April 1, 1993): 706–15. http://dx.doi.org/10.1139/x93-092.
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Tropospheric ozone may contribute to the reported growth decline of pines in the southeastern United States. Ozone concentration–response relationships were quantified for open-pollinated families of loblolly pine (Pinustaeda L.) seedlings. Seedlings from 30 families were exposed to ozone (0, 80, 160, 240, or 320 nL O3/L air) in greenhouse chambers for 6 h per day, 4 days per week, for 12 weeks. Top (shoot) and root biomass were determined for each of 900 plants. Twelve families were selected for a subsequent experiment to examine consistency of results (360 plants). For each response variable, statistical models consisting of fixed and random effects were based on combined data for all families and both experiments. Data were fit to both polynomial and Weibull model types. The maximum suppression of any biomass variable (top, root, or total dry weight) predicted by a regression model for plants exposed for 12 weeks to 320 nL/L was 25% for total dry weight (Weibull model based on data representing all 42 family–year combinations, total of 1260 plants). Families were ranked for sensitivity based on estimates of a single parameter from the models, and model type had no effect on the order of sensitivity rankings of the 42 family–experiment combinations. The same families represented the extremes in sensitivity among the 12 families that were exposed in both experiments.
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Nuñez, Eduardo, Ramón Mata, Jorge Castro, Nelson Maureira, Néstor Guerrero, and Ángel Roco. "Influence of Global Slenderness and Sliding Pallets on Seismic Design of Steel Storage Racks: A Sensitivity Analysis." Buildings 12, no. 11 (October 31, 2022): 1826. http://dx.doi.org/10.3390/buildings12111826.
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In this research, the influence of global slenderness and sliding pallets factor on the seismic design of steel storage racks are assessed. Variations in span length, the height of storage levels, live load, and percentage of live load considered in the seismic mass are studied for different levels of seismic zone and soil type. The models were designed according to the Chilean Code NCh2369. Subsequently, a global sensitivity analysis was developed to analyze the influence of each studied parameter in the seismic design response in terms of fundamental period, drift, and base shear from a response spectral analysis approach. A total of 12000 simulations were performed. Two-hundred additional models were performed to evaluate the variation of seismic mass in the structural response. Results indicate a significant influence of live loads and seismic mass on steel racks designed for soft soils and unbrace conditions. The stiffness also modifies the performance of the racks, mainly in models using braces in the down-aisle direction and cross-aisle direction. In these cases, the seismic mass factor does not have a strong influence on structural response in comparison to the global slenderness.
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Fläschner, Dagmar, Thorsten Mauritsen, and Bjorn Stevens. "Understanding the Intermodel Spread in Global-Mean Hydrological Sensitivity*." Journal of Climate 29, no. 2 (January 12, 2016): 801–17. http://dx.doi.org/10.1175/jcli-d-15-0351.1.
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Abstract This paper assesses intermodel spread in the slope of global-mean precipitation change ΔP with respect to surface temperature change. The ambiguous estimates in the literature for this slope are reconciled by analyzing four experiments from phase 5 of CMIP (CMIP5) and considering different definitions of the slope. The smallest intermodel spread (a factor of 1.5 between the highest and lowest estimate) is found when using a definition that disentangles temperature-independent precipitation changes (the adjustments) from the slope of the temperature-dependent precipitation response; here this slope is referred to as the hydrological sensitivity parameter η. The estimates herein show that η is more robust than stated in most previous work. The authors demonstrate that adjustments and η estimated from a steplike quadrupling CO2 experiment serve well to predict ΔP in a transient CO2 experiment. The magnitude of η is smaller in the coupled ocean–atmosphere quadrupling CO2 experiment than in the noncoupled atmosphere-only experiment. The offset in magnitude due to coupling suggests that intermodel spread may undersample uncertainty. Also assessed are the relative contribution of η, the surface warming, and the adjustment on the spread in ΔP on different time scales. Intermodel variation of both η and the adjustment govern the spread in ΔP in the years immediately after the abrupt forcing change. In equilibrium, the uncertainty in ΔP is dominated by uncertainty in the equilibrium surface temperature response. A kernel analysis reveals that intermodel spread in η is dominated by intermodel spread in tropical lower tropospheric temperature and humidity changes and cloud changes.
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Huang, Y. Y., and S. Gerber. "Global soil nitrous oxide emissions in a dynamic carbon–nitrogen model." Biogeosciences Discussions 12, no. 3 (February 11, 2015): 3101–43. http://dx.doi.org/10.5194/bgd-12-3101-2015.
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Abstract. Nitrous oxide (N2O) is an important greenhouse gas that also contributes to the depletion of stratospheric ozone. With high temporal and spatial heterogeneity, a quantitative understanding of terrestrial N2O emission, its variabilities and reponses to climate change is challenging. We added a soil N2O emission module to the dynamic global land model LM3V-N, and tested its sensitivity to soil moisture regime and responses to elevated CO2 and temperature. The model was capable of reproducing the average of cross-site observed annual mean emissions, although differences remained across individual sites if stand-level measurements were representative of gridcell emissions. Modelled N2O fluxes were highly sensitive to water filled pore space (WFPS), with a global sensitivity of approximately 0.25 Tg N year−1 per 0.01 change in WFPS. We found that the global response of N2O emission to CO2 fertilization was largely determined by the response of tropical emissions, whereas the extratropical response was weaker and different, highlighting the need to expand field studies in tropical ecosystems. Warming generally enhanced N2O efflux, and the enhancement was greatly dampened when combined with elevated CO2, although CO2 alone had a small effect. Our analysis suggests caution when extrapolation from current field CO2 enrichment and warming studies to the global scale.
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Bounceur, N., M. Crucifix, and R. D. Wilkinson. "Global sensitivity analysis of the climate–vegetation system to astronomical forcing: an emulator-based approach." Earth System Dynamics 6, no. 1 (May 4, 2015): 205–24. http://dx.doi.org/10.5194/esd-6-205-2015.
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Abstract. A global sensitivity analysis is performed to describe the effects of astronomical forcing on the climate–vegetation system simulated by the model of intermediate complexity LOVECLIM in interglacial conditions. The methodology relies on the estimation of sensitivity measures, using a Gaussian process emulator as a fast surrogate of the climate model, calibrated on a set of well-chosen experiments. The outputs considered are the annual mean temperature and precipitation and the growing degree days (GDD). The experiments were run on two distinct land surface schemes to estimate the importance of vegetation feedbacks on climate variance. This analysis provides a spatial description of the variance due to the factors and their combinations, in the form of "fingerprints" obtained from the covariance indices. The results are broadly consistent with the current under-standing of Earth's climate response to the astronomical forcing. In particular, precession and obliquity are found to contribute in LOVECLIM equally to GDD in the Northern Hemisphere, and the effect of obliquity on the response of Southern Hemisphere temperature dominates precession effects. Precession dominates precipitation changes in subtropical areas. Compared to standard approaches based on a small number of simulations, the methodology presented here allows us to identify more systematically regions susceptible to experiencing rapid climate change in response to the smooth astronomical forcing change. In particular, we find that using interactive vegetation significantly enhances the expected rates of climate change, specifically in the Sahel (up to 50% precipitation change in 1000 years) and in the Canadian Arctic region (up to 3° in 1000 years). None of the tested astronomical configurations were found to induce multiple steady states, but, at low obliquity, we observed the development of an oscillatory pattern that has already been reported in LOVECLIM. Although the mathematics of the analysis are fairly straightforward, the emulation approach still requires considerable care in its implementation. We discuss the effect of the choice of length scales and the type of emulator, and estimate uncertainties associated with specific computational aspects, to conclude that the principal component emulator is a good option for this kind of application.
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Thorsen, Tyler J., Richard A. Ferrare, Seiji Kato, and David M. Winker. "Aerosol Direct Radiative Effect Sensitivity Analysis." Journal of Climate 33, no. 14 (July 15, 2020): 6119–39. http://dx.doi.org/10.1175/jcli-d-19-0669.1.
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AbstractBoth to reconcile the large range in satellite-based estimates of the aerosol direct radiative effect (DRE) and to optimize the design of future observing systems, this study builds a framework for assessing aerosol DRE uncertainty. Shortwave aerosol DRE radiative kernels (Jacobians) were derived using the MERRA-2 reanalysis data. These radiative kernels give the differential response of the aerosol DRE to perturbations in the aerosol extinction coefficient, aerosol single-scattering albedo, aerosol asymmetry factor, surface albedo, cloud fraction, and cloud optical depth. This comprehensive set of kernels provides a convenient way to consistently and accurately assess the aerosol DRE uncertainties that result from observational or model-based uncertainties. The aerosol DRE kernels were used to test the effect of simplifying the full vertical profile of aerosol scattering properties into column-integrated quantities. This analysis showed that, although the clear-sky aerosol DRE can be had fairly accurately, more significant errors occur for the all-sky DRE. The sensitivity in determining the broadband spectral dependencies of the aerosol scattering properties directly from a limited set of wavelengths was quantified. These spectral dependencies can be reasonably constrained using column-integrated aerosol scattering properties in the midvisible and near-infrared wavelengths. Separating the aerosol DRE and its kernels by scene type shows that accurate aerosol properties in the clear sky are the most crucial component of the global aerosol DRE. In cloudy skies, determining aerosol properties in the presence of optically thin cloud is more radiatively important than doing so when optically thick cloud is present.
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Zhu, Chao, Ping Zhu, and Jiahai Lu. "Global Sensitivity Analysis for the Elastic Properties of Unidirectional Carbon Fibre Reinforced Composites Based on Metamodels." Polymers and Polymer Composites 26, no. 3 (March 2018): 205–21. http://dx.doi.org/10.1177/096739111802600301.
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A fast and effective numerical method to predict mechanical properties of carbon fibre reinforced polymer (CFRP) composites, even elastic properties, is complicated due to the mismatch of mechanical properties among the constituents. Furthermore, it is not possible to completely characterise the influence of multiple parameters including mechanical and structural parameters on the bulk properties of CFRP by experiments. In this study, a three-phase finite-element model consisting of matrix, carbon fibre and interface was developed to predict the elastic mechanical behaviour of unidirectional CFRP. The elastic properties in terms of two Young's moduli, two Poisson's ratios and a shear modulus were calculated by means of a homogenisation method. High-accuracy Kriging surrogate models were constructed to fast-calculate the elastic responses for a large number of samples. Combining Kriging and high-dimensional model representation (HDMR) methods, a global sensitivity analysis was performed to study how the microscopic parameters influence the elastic responses to get a deeper understanding of elastic property-structure relationship. Eleven parameters, including mechanical and geometry properties of constituent phases, were chosen as inputs. Independent and cooperative effects of input parameters on the elastic properties of the studied composites were surveyed via first- and second-order sensitivity indices, respectively. An importance ranking of these parameters for each elastic response was derived directly by these indices. The procedure proposed in this work could serve as a theoretical guide for further design optimisation of CFRP.
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Liepert, Beate G., and Michael Previdi. "Do Models and Observations Disagree on the Rainfall Response to Global Warming?" Journal of Climate 22, no. 11 (June 1, 2009): 3156–66. http://dx.doi.org/10.1175/2008jcli2472.1.
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Abstract Recently analyzed satellite-derived global precipitation datasets from 1987 to 2006 indicate an increase in global-mean precipitation of 1.1%–1.4% decade−1. This trend corresponds to a hydrological sensitivity (HS) of 7% K−1 of global warming, which is close to the Clausius–Clapeyron (CC) rate expected from the increase in saturation water vapor pressure with temperature. Analysis of two available global ocean evaporation datasets confirms this observed intensification of the atmospheric water cycle. The observed hydrological sensitivity over the past 20-yr period is higher by a factor of 5 than the average HS of 1.4% K−1 simulated in state-of-the-art coupled atmosphere–ocean climate models for the twentieth and twenty-first centuries. However, the analysis shows that the interdecadal variability in HS in the models is high—in particular in the twentieth-century runs, which are forced by both increasing greenhouse gas (GHG) and tropospheric aerosol concentrations. About 12% of the 20-yr time intervals of eight twentieth-century climate simulations from the third phase of the Coupled Model Intercomparison Project (CMIP3) have an HS magnitude greater than the CC rate of 6.5% K−1. The analysis further indicates different HS characteristics for GHG and tropospheric aerosol forcing agents. Aerosol-forced HS is a factor of 2 greater, on average, and the interdecadal variability is significantly larger, with about 23% of the 20-yr sensitivities being above the CC rate. By thermodynamically constraining global precipitation changes, it is shown that such changes are linearly related to the difference in the radiative imbalance at the top of the atmosphere (TOA) and the surface (i.e., the atmospheric radiative energy imbalance). The strength of this relationship is controlled by the modified Bowen ratio (here, global sensible heat flux change divided by latent heat flux change). Hydrological sensitivity to aerosols is greater than the sensitivity to GHG because the former have a stronger effect on the shortwave transmissivity of the atmosphere, and thus produce a larger change in the atmospheric radiative energy imbalance. It is found that the observed global precipitation increase of 13 mm yr−1 decade−1 from 1987 to 2006 would require a trend of the atmospheric radiative imbalance (difference between the TOA and the surface) of 0.7 W m−2 decade−1. The recovery from the El Chichón and Mount Pinatubo volcanic aerosol injections in 1982 and 1991, the satellite-observed reductions in cloudiness during the phase of increasing ENSO events in the 1990s, and presumably the observed reduction of anthropogenic aerosol concentrations could have caused such a radiative imbalance trend over the past 20 years. Observational evidence, however, is currently inconclusive, and it will require more detailed investigations and longer satellite time series to answer this question.
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Carey, Joanna C., Jianwu Tang, Pamela H. Templer, Kevin D. Kroeger, Thomas W. Crowther, Andrew J. Burton, Jeffrey S. Dukes, et al. "Temperature response of soil respiration largely unaltered with experimental warming." Proceedings of the National Academy of Sciences 113, no. 48 (November 14, 2016): 13797–802. http://dx.doi.org/10.1073/pnas.1605365113.
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The respiratory release of carbon dioxide (CO2) from soil is a major yet poorly understood flux in the global carbon cycle. Climatic warming is hypothesized to increase rates of soil respiration, potentially fueling further increases in global temperatures. However, despite considerable scientific attention in recent decades, the overall response of soil respiration to anticipated climatic warming remains unclear. We synthesize the largest global dataset to date of soil respiration, moisture, and temperature measurements, totaling >3,800 observations representing 27 temperature manipulation studies, spanning nine biomes and over 2 decades of warming. Our analysis reveals no significant differences in the temperature sensitivity of soil respiration between control and warmed plots in all biomes, with the exception of deserts and boreal forests. Thus, our data provide limited evidence of acclimation of soil respiration to experimental warming in several major biome types, contrary to the results from multiple single-site studies. Moreover, across all nondesert biomes, respiration rates with and without experimental warming follow a Gaussian response, increasing with soil temperature up to a threshold of ∼25 °C, above which respiration rates decrease with further increases in temperature. This consistent decrease in temperature sensitivity at higher temperatures demonstrates that rising global temperatures may result in regionally variable responses in soil respiration, with colder climates being considerably more responsive to increased ambient temperatures compared with warmer regions. Our analysis adds a unique cross-biome perspective on the temperature response of soil respiration, information critical to improving our mechanistic understanding of how soil carbon dynamics change with climatic warming.
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Höllering, Simon, Jan Wienhöfer, Jürgen Ihringer, Luis Samaniego, and Erwin Zehe. "Regional analysis of parameter sensitivity for simulation of streamflow and hydrological fingerprints." Hydrology and Earth System Sciences 22, no. 1 (January 11, 2018): 203–20. http://dx.doi.org/10.5194/hess-22-203-2018.
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Abstract. Diagnostics of hydrological models are pivotal for a better understanding of catchment functioning, and the analysis of dominating model parameters plays a key role for region-specific calibration or parameter transfer. A major challenge in the analysis of parameter sensitivity is the assessment of both temporal and spatial differences of parameter influences on simulated streamflow response. We present a methodological approach for global sensitivity analysis of hydrological models. The multilevel approach is geared towards complementary forms of streamflow response targets, and combines sensitivity analysis directed to hydrological fingerprints, i.e. temporally independent and temporally aggregated characteristics of streamflow (INDPAS), with the conventional analysis of the temporal dynamics of parameter sensitivity (TEDPAS). The approach was tested in 14 mesoscale headwater catchments of the Ruhr River in western Germany using simulations with the spatially distributed hydrological model mHM. The multilevel analysis with diverse response characteristics allowed us to pinpoint parameter sensitivity patterns much more clearly as compared to using TEDPAS alone. It was not only possible to identify two dominating parameters, for soil moisture dynamics and evapotranspiration, but we could also disentangle the role of these and other parameters with reference to different streamflow characteristics. The combination of TEDPAS and INDPAS further allowed us to detect regional differences in parameter sensitivity and in simulated hydrological functioning, despite the rather small differences in the hydroclimatic and topographic setting of the Ruhr headwaters.
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Zhangchun, Tang, Lu Zhenzhou, Pan Wang, and Zhang Feng. "An entropy-based global sensitivity analysis for the structures with both fuzzy variables and random variables." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 227, no. 2 (May 29, 2012): 195–212. http://dx.doi.org/10.1177/0954406212448575.
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Based on the entropy of the uncertain variable, a novel importance measure is proposed to identify the effect of the uncertain variables on the system, which is subjected to the combination of random variables and fuzzy variables. For the system with the mixture of random variables and fuzzy variables, the membership function of the failure probability can be obtained by the uncertainty propagation theory first. And then the effect of each input variable on the output response of the system can be evaluated by measuring the shift between entropies of two membership functions of the failure probability, obtained before and after the uncertainty elimination of the input variable. The intersecting effect of the multiple input variables can be calculated by the similar measure. The mathematical properties of the proposed global sensitivity indicators are investigated and proved in detail. A simple example is first employed to demonstrate the procedure of solving the proposed global sensitivity indicators and then the influential variables of four practical applications are identified by the proposed global sensitivity indicators.
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Quetin, Gregory R., and Abigail L. S. Swann. "Empirically Derived Sensitivity of Vegetation to Climate across Global Gradients of Temperature and Precipitation." Journal of Climate 30, no. 15 (August 2017): 5835–49. http://dx.doi.org/10.1175/jcli-d-16-0829.1.
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The natural composition of terrestrial ecosystems can be shaped by climate to take advantage of local environmental conditions. Ecosystem functioning (e.g., interaction between photosynthesis and temperature) can also acclimate to different climatological states. The combination of these two factors thus determines ecological–climate interactions. A global empirical map of the sensitivity of vegetation to climate is derived using the response of satellite-observed greenness to interannual variations in temperature and precipitation. Mechanisms constraining ecosystem functioning are inferred by analyzing how the sensitivity of vegetation to climate varies across climate space. Analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate at large spatial scales. In hot and wet locations, vegetation is greener in warmer years despite temperatures likely exceeding thermally optimum conditions. However, sunlight generally increases during warmer years, suggesting that the increased stress from higher atmospheric water demand is offset by higher rates of photosynthesis. The sensitivity of vegetation transitions in sign (greener when warmer or drier to greener when cooler or wetter) along an emergent line in climate space with a slope of about 59 mm yr−1 °C−1, twice as steep as contours of aridity. The mismatch between these slopes is evidence at a global scale of the limitation of both water supply due to inefficiencies in plant access to rainfall and plant physiological responses to atmospheric water demand. This empirical pattern can provide a functional constraint for process-based models, helping to improve predictions of the global-scale response of vegetation to a changing climate.
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Gordon, N. D., and J. R. Norris. "Cluster analysis of midlatitude oceanic cloud regimes – Part 2: Temperature sensitivity of cloud properties." Atmospheric Chemistry and Physics Discussions 10, no. 1 (January 20, 2010): 1595–629. http://dx.doi.org/10.5194/acpd-10-1595-2010.
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Abstract. Clouds have a large impact on Earth's radiation budget by reflecting incoming solar radiation and trapping longwave radiation emitted from the surface. The present balance could change as the atmosphere warms from increasing anthropogenic greenhouse gases, thus altering the net radiation flux and mitigating or exacerbating the initial temperature increase. To ascertain the sign and magnitude of cloud-climate feedback, we must better understand the way in which clouds interact with their environment and how temperature modifies cloud and radiative properties. Since global climate models do not consistently and correctly simulate clouds, we undertake an observational analysis of how midlatitude oceanic clouds change with temperature when dynamical processes are held constant (i.e., partial derivative with respect to temperature). For each of the seven cloud regimes identified through k-means clustering of daily satellite data in the companion study, we examine the difference in cloud and radiative properties between warm and cold subsets. To avoid misinterpreting a cloud response to large-scale dynamical forcing as a cloud response to temperature, we require horizontal and vertical temperature advection in the warm and cold subsets to have near-median values in three layers of the troposphere. Across all of the seven clusters, we find that cloud fraction is smaller and cloud optical thickness is mostly larger for the warm subset. Cloud top pressure is higher for the three low-level cloud regimes and lower for the cirrus regime. The net upwelling radiation flux at the top of the atmosphere is larger for the warm subset in every cluster except cirrus, and larger when averaged over all clusters. This implies that the direct response of midlatitude oceanic clouds to increasing temperature acts as a negative feedback on the climate system. Note that the cloud response to atmospheric dynamical changes produced by global warming, which we do not consider in this study, may differ, and the total cloud feedback may be positive.
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BACH, EVIATAR, VALENTINA RADIĆ, and CHRISTIAN SCHOOF. "How sensitive are mountain glaciers to climate change? Insights from a block model." Journal of Glaciology 64, no. 244 (March 8, 2018): 247–58. http://dx.doi.org/10.1017/jog.2018.15.
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ABSTRACTSimple models of glacier volume evolution are important in understanding features of glacier response to climate change, due to the scarcity of data adequate for running more complex models on a global scale. Two quantities of interest in a glacier's response to climate changes are its response time and its volume sensitivity to changes in the equilibrium line altitude (ELA). We derive a simplified, computationally inexpensive model of glacier volume evolution based on a block model with volume–area–length scaling. After analyzing its steady-state properties, we apply the model to each mountain glacier worldwide and estimate regionally differentiated response times and sensitivities to ELA changes. We use a statistical method from the family of global sensitivity analysis methods to determine the glacier quantities, geometric and climatic, that most influence the model output. The response time is dominated by the climatic setting reflected in the mass-balance gradient in the ablation zone, followed by the surface slope, while volume sensitivity is mainly affected by glacier size, followed by the surface slope.
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Saldaña, Manuel, Luis Ayala, David Torres, and Norman Toro. "Global sensitivity analyses of a neural networks model for a flotation circuit." Chemical Industry 74, no. 4 (2020): 247–56. http://dx.doi.org/10.2298/hemind20060523s.
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Modeling of flotation processes is complex due to the large number of variables involved and the lack of knowledge on the impact of operational parameters on the response(s), and given this problem, machine learning algorithms emerge as an alternative interesting when modeling dynamic processes. In this work, different artificial neural network (ANN) architectures for modeling the mineral concentrate in a rougher-cleaner-scavenger (RCS) circuit based on the main process variables are generated (variables as the recovery of the rougher, cleaner and scavenger cells, along with disaggregated variables). Analysis of the global sensitivity was performed to study the importance of the individual and joint performances of the stages of the flotation circuit, reflected by sensitivity indicators that allow to infer the impact that the stages and operational parameters produce on the dependent variables (mineral concentrate in rougher, cleaner and scavenger cells, in addition to the global concentration in the RCS circuit). It should be noted that the ANN is a useful tool for modeling dynamic systems such as flotation, while sensitivity analysis shows that the operation of the three threads turns out to be crucial for the subsequent evaluation of the circuit, while the Unbundled variables that most interact with the overall recovery are gas flow rate, bubble and particle diameters, bubble velocity, particle density, and surface tension.
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Nabi, Khondoker Nazmoon, and Chandra N. Podder. "Sensitivity analysis of chronic hepatitis C virus infection with immune response and cell proliferation." International Journal of Biomathematics 13, no. 03 (March 16, 2020): 2050017. http://dx.doi.org/10.1142/s1793524520500175.
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A new mathematical model of chronic hepatitis C virus (HCV) infection incorporating humoral and cell-mediated immune responses, distinct cell proliferation rates for both uninfected and infected hepatocytes, and antiviral treatment all at once, is formulated and analyzed meticulously. Analysis of the model elucidates the existence of multiple equilibrium states. Moreover, the model has a locally asymptotically stable disease-free equilibrium (DFE) whenever the basic reproduction number is less than unity. Local sensitivity analysis (LSA) result exhibits that the most influential (negatively sensitive) parameters on the epidemic threshold are the drug efficacy of blocking virus production and the drug efficacy of removing infection. However, LSA does not accurately assess uncertainty and sensitivity in the system and may mislead us since by default this technique holds all other parameters fixed at baseline values. To overcome this pitfall, one of the most robust and efficient global sensitivity analysis (GSA) methods, which is Latin hypercube sampling-partial rank correlation coefficient technique, elucidates that the proliferation rate of infected hepatocytes and the drug efficacy of killing infected hepatocytes are highly sensitive parameters that affect the transmission dynamics of HCV in any population. Our study suggests that cell proliferation of the infected hepatocytes can be very crucial in controlling disease outbreak. Thus, a future HCV drug that boosts cell-mediated immune response is expected to be quite effective in controlling disease outbreak.
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Leon, Lider, Ralph C. Smith, William S. Oates, and Paul Miles. "Analysis of a multi-axial quantum-informed ferroelectric continuum model: Part 2—sensitivity analysis." Journal of Intelligent Material Systems and Structures 29, no. 13 (July 10, 2018): 2840–60. http://dx.doi.org/10.1177/1045389x18781024.
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We illustrate the use of global sensitivity analysis, and a parameter subset selection algorithm based on local sensitivity analysis, to quantify the relative influence of parameters in polarization and electrostrictive energy relations for a quantum-informed, single-domain, ferroelectric material model. A motivating objective is to determine which parameters are identifiable or influential in the sense that they are uniquely determined by density functional theory–generated data. Noninfluential parameters will be fixed at nominal values for subsequent Bayesian inference, uncertainty propagation, and material design since variations in these parameters are minimally reflected in responses. Whereas global sensitivity analysis is typically based on the assumption of mutually independent, uniformly distributed parameters, we demonstrate that inherent parameter correlations must be accommodated to achieve correct interpretations of parameter influence. For the considered energy functionals, we demonstrate that all of the parameters are influential and will be informed by density functional theory–simulated data.
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Villarini, Gabriele, David A. Lavers, Enrico Scoccimarro, Ming Zhao, Michael F. Wehner, Gabriel A. Vecchi, Thomas R. Knutson, and Kevin A. Reed. "Sensitivity of Tropical Cyclone Rainfall to Idealized Global-Scale Forcings*." Journal of Climate 27, no. 12 (June 5, 2014): 4622–41. http://dx.doi.org/10.1175/jcli-d-13-00780.1.
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Abstract Heavy rainfall and flooding associated with tropical cyclones (TCs) are responsible for a large number of fatalities and economic damage worldwide. Despite their large socioeconomic impacts, research into heavy rainfall and flooding associated with TCs has received limited attention to date and still represents a major challenge. The capability to adapt to future changes in heavy rainfall and flooding associated with TCs is inextricably linked to and informed by understanding of the sensitivity of TC rainfall to likely future forcing mechanisms. Here a set of idealized high-resolution atmospheric model experiments produced as part of the U.S. Climate Variability and Predictability (CLIVAR) Hurricane Working Group activity is used to examine TC response to idealized global-scale perturbations: the doubling of CO2, uniform 2-K increases in global sea surface temperature (SST), and their combined impact. As a preliminary but key step, daily rainfall patterns of composite TCs within climate model outputs are first compared and contrasted to the observational records. To assess similarities and differences across different regions in response to the warming scenarios, analyses are performed at the global and hemispheric scales and in six global TC ocean basins. The results indicate a reduction in TC daily precipitation rates in the doubling CO2 scenario (on the order of 5% globally) and an increase in TC rainfall rates associated with a uniform increase of 2 K in SST (both alone and in combination with CO2 doubling; on the order of 10%–20% globally).