Relevant bibliographies by topics / Global response sensitivity analysis

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Global response sensitivity analysis'

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Published: 6 September 2023

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Journal articles on the topic "Global response sensitivity analysis"

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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9

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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10

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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Dissertations / Theses on the topic "Global response sensitivity analysis"

1

Khalid, Adeel S. "Development and Implementation of Rotorcraft Preliminary Design Methodology using Multidisciplinary Design Optimization." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14013.

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A formal framework is developed and implemented in this research for preliminary rotorcraft design using IPPD methodology. All the technical aspects of design are considered including the vehicle engineering, dynamic analysis, stability and control, aerodynamic performance, propulsion, transmission design, weight and balance, noise analysis and economic analysis. The design loop starts with a detailed analysis of requirements. A baseline is selected and upgrade targets are identified depending on the mission requirements. An Overall Evaluation Criterion (OEC) is developed that is used to measure the goodness of the design or to compare the design with competitors. The requirements analysis and baseline upgrade targets lead to the initial sizing and performance estimation of the new design. The digital information is then passed to disciplinary experts. This is where the detailed disciplinary analyses are performed. Information is transferred from one discipline to another as the design loop is iterated. To coordinate all the disciplines in the product development cycle, Multidisciplinary Design Optimization (MDO) techniques e.g. All At Once (AAO) and Collaborative Optimization (CO) are suggested. The methodology is implemented on a Light Turbine Training Helicopter (LTTH) design. Detailed disciplinary analyses are integrated through a common platform for efficient and centralized transfer of design information from one discipline to another in a collaborative manner. Several disciplinary and system level optimization problems are solved. After all the constraints of a multidisciplinary problem have been satisfied and an optimal design has been obtained, it is compared with the initial baseline, using the earlier developed OEC, to measure the level of improvement achieved. Finally a digital preliminary design is proposed. The proposed design methodology provides an automated design framework, facilitates parallel design by removing disciplinary interdependency, current and updated information is made available to all disciplines at all times of the design through a central collaborative repository, overall design time is reduced and an optimized design is achieved.
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Adetula, Bolade Adewale. "Global sensitivity analysis of reactor parameters / Bolade Adewale Adetula." Thesis, North-West University, 2011. http://hdl.handle.net/10394/5561.

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Calculations of reactor parameters of interest (such as neutron multiplication factors, decay heat, reaction rates, etc.), are often based on models which are dependent on groupwise neutron cross sections. The uncertainties associated with these neutron cross sections are propagated to the final result of the calculated reactor parameters. There is a need to characterize this uncertainty and to be able to apportion the uncertainty in a calculated reactor parameter to the different sources of uncertainty in the groupwise neutron cross sections, this procedure is known as sensitivity analysis. The focus of this study is the application of a modified global sensitivity analysis technique to calculations of reactor parameters that are dependent on groupwise neutron cross–sections. Sensitivity analysis can help in identifying the important neutron cross sections for a particular model, and also helps in establishing best–estimate optimized nuclear reactor physics models with reduced uncertainties. In this study, our approach to sensitivity analysis will be similar to the variance–based global sensitivity analysis technique, which is robust, has a wide range of applicability and provides accurate sensitivity information for most models. However, this technique requires input variables to be mutually independent. A modification to this technique, that allows one to deal with input variables that are block–wise correlated and normally distributed, is presented. The implementation of the modified technique involves the calculation of multi–dimensional integrals, which can be prohibitively expensive to compute. Numerical techniques specifically suited to the evaluation of multidimensional integrals namely Monte Carlo, quasi–Monte Carlo and sparse grids methods are used, and their efficiency is compared. The modified technique is illustrated and tested on a two–group cross–section dependent problem. In all the cases considered, the results obtained with sparse grids achieved much better accuracy, while using a significantly smaller number of samples.
Thesis (M.Sc. Engineering Sciences (Nuclear Engineering))--North-West University, Potchefstroom Campus, 2011.
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Koneshwaran, Sivalingam. "Blast response and sensitivity analysis of segmental tunnel." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/78619/1/Sivalingam_Koneshwaran_Thesis.pdf.

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This research treated the response of underground transportation tunnels to surface blast loads using advanced computer simulation techniques. The influences of important parameters, such as tunnel material, geometrical configuration of segments and surrounding soil were investigated. The findings of this research offer significant new information on the blast performance of underground tunnels and will contribute towards future civil engineering applications.
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Dell'Oca, Aronne, Monica Riva, and Alberto Guadagnini. "Moment-based metrics for global sensitivity analysis of hydrological systems." COPERNICUS GESELLSCHAFT MBH, 2017. http://hdl.handle.net/10150/626437.

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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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Chai, Wenqi. "Global sensitivity analysis on vibro-acoustic composite materials with parametric dependency." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEC037/document.

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Avec le développement rapide des modèles mathématiques et des outils de simulation, le besoin des processus de quantification des incertitudes a été bien augmenté. L'incertitude paramétrique et la groupe des nombreux décisions sont aujourd’hui les deux barrières principales dans la résolution des grandes problèmes systématiques.Capable de proportionner l'incertitude de la sortie sur celle des entrées, l’Analyse de Sensibilité Globale (GSA) est une solution fiable pour la quantification de l’incertitude. Parmi plusieurs algorithmes de GSA, Fourier Amplitude Sensitivity Analysis (FAST) est l’un des choix les plus populaires des chercheurs. Basé sur ANOVA-HDMR (ANalysis Of VAriance - High Dimensional Model Representation), il est solide en mathématique est efficace en calcul.Malheureusement, la décomposition unique d’ANOVA-HDMR se dépend sur l’indépendance des entrées. À cause de cela, il y a pas mal de cas industriels qui ne peut pas se traiter par FAST, particulièrement pour ceux qui donnent uniquement les échantillons mais sans lois de distribution. Sous cette demande, deux méthode extensifs de FAST avec design de corrélation sont proposées et étudiées dans la recherche. Parmi les deux méthodes, FAST-c s’est basé sur les distributions et FAST-orig s’est basé sur les échantillons.Comme applications et validations, multiples problèmes vibroacoustiques se sont traités dans la recherche. Les matériaux acoustiques avec soustructures, sont des candidats parfaits pour tester FAST-c et FAST-orig. Deux application sont présentées dans la première partie de la thèse, après l’état de l’arts. Les modèles choisis sont matérial poroélastique et structures composite sandwich, dont les propriétés mécaniques sont tous fortement influencées par les paramètres géométriques microscopique ou mesoscopique. D’avoir la méthode de FAST originale comparée avec les deux nouvelles, on trouve bien plus d’information sur la performance vibroacoustique de ces matériaux.Déjà répondu à la demande de GSA sur les modèles avecs les variables dépendantes, la deuxième partie de la thèse contient plus de recherches reliées avec FAST. D’abord FAST est pris en comparaison avec Random Forest, une algorithme bien connu de data-mining. Leurs erreurs potentiels et la possibilité de fonctioner ensemble sont discutés. Et dans les chapitres suivies, plus d’application de FAST sont présentées. Les méthodes sont appliquées sous plusieurs différente conditions. Une modèle de structure périodique qui contient des corrélation parmi les unités nous a en plus forcé à développer une nouvelle FAST-pe méthode. Dans ces applications, les designs des processus préliminaires et les stratégies d’échantillonages sont des essences à présenter
With rapid development of mathematical models and simulation tools, the need of uncertainty quantification process has grown higher than ever before. Parametric uncertainties and overall decision stacks are nowadays the two main barriers in solving large scale systematic problem.Global Sensitivity Analysis (GSA) is one reliable solution for uncertainty quantification which is capable to assess the uncertainty of model output on its inputs’. Among several GSA algorithms, Fourier Amplitude Sensitivity Test (FAST) is one of the most popular choices of researchers. Based on ANOVA-HDMR (ANalysis Of VAriance - High Dimensional Model Representation), it is both mathematically solid and computationally efficient.One unfortunate fact is that the uniqueness of ANOVA-HDMR relies on the independency of input variables. It makes FAST unable to treat many industrial cases especially for those with only datasets but not distribution functions to be found. To answer the needs, two extended FAST methods with correlation design are proposed and further studied in this research. Among them FAST-c is distribution-based and FAST-orig is data-based.As a frame of validation and application, a number of vibroacoustic problems are dealt with in this research. Vibroacoustic materials with substructures, are perfect test candidates for FAST-c and FAST-orig. Two application cases are presented in the first part of this thesis, following the literature review. The models chosen here are poroelastic material and sandwich composite structures, both having their mechanical properties hugely influenced by their microscopic and mesoscopic geometric parameters. Getting the original FAST method compared to the two with correlation design, many different features on materials’ vibroacoustic performance are latter discovered.Having got an answer for GSA on models with dependent variables, the second part of this thesis contains more extended researches related to FAST. It is taken into comparison with Random Forest, a well-known data-mining algorithm. The potential error of both algorithms are analyzed and the possibility of joint application is discussed. In the following chapters, more applications of FAST-series methods are reported. They are applied under various conditions where another improved version named FAST-pe is developed to treat a model of periodic structures with correlation among each units. Upon these FAST application cases, the design of preliminary process and the sampling strategies is the core part to be introduced
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Eldred, Lloyd B. "Sensitivity analysis of the static aeroelastic response of a wing." Diss., Virginia Tech, 1993. http://hdl.handle.net/10919/40147.

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A technique to obtain the sensitivity of the static aeroelastic response of a three dimensional wing model is designed and implemented. The formulation is quite general and accepts any aerodynamic and structural analysis capability. A program to combine the discipline level, or local, sensitivities into global sensitivity derivatives is developed. A variety of representations of the wing pressure field are developed and tested to determine the most accurate and efficient scheme for representing the field outside of the aerodynamic code. Chebyshev polynomials are used to globally fit the pressure field. This approach had some difficulties in representing local variations in the field, so a variety of local interpolation polynomial pressure representations are also implemented. These panel based representations use a constant pressure value~ a bilinearly interpolated value, or a biquadratic ally interpolated value. The interpolation polynomial approaches do an excellent job of reducing the numerical problems of the global approach for comparable computational effort. Regardless of the pressure representation used, sensitivity and response results with excellent accuracy have been produced for large integrated quantities such as wing tip deflection and trim angle of attack. The sensitivities of such things as individual generalized displacements have been found with fair accuracy. In general, accuracy is found to be proportional to the relative size of the derivatives to the quantity itself.
Ph. D.
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7

Bergen, Frederick D'Oench Jr. "Shape sensitivity analysis of flutter response of a laminated wing." Thesis, Virginia Polytechnic Institute and State University, 1988. http://hdl.handle.net/10919/50074.

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A method is presented for calculating the shape sensitivity of a wing aeroelastic response with respect to changes in geometric shape. Yates’ modified strip method is used in conjunction with Giles' equivalent plate analysis to predict the flutter speed, frequency, and reduced frequency of the wing. Three methods are used to calculate the sensitivity of the eigenvalue. The first method is purely a finite difference calculation of the eigenvalue derivative directly from the solution of the flutter problem corresponding to the two different values of the shape parameters. The second method uses an analytic expression for the eigenvalue sensitivities of a general complex matrix, where the derivatives of the aerodynamic, mass, and stiffness matrices are computed using a finite difference approximation. The third method also uses an analytic expression for the eigenvalue sensitivities but the aerodynamic matrix is computed analytically. All three methods are found to be in good agreement with each other. The sensitivities of the eigenvalues were used to predict flutter speed, frequency , and reduced frequency. These approximations were found to be in good agreement with those obtained using a complete reanalysis. However, it is recommended that higher order terms be used in the calculations in order to assure greater accuracy.
Master of Science
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Bebamzadeh, Armin. "Efficient finite element response sensitivity analysis and applications in composites manufacturing." Thesis, University of British Columbia, 2009. http://hdl.handle.net/2429/7801.

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This thesis presents the development, implementation, and application of response sensitivities in numerical simulation of composite manufacturing. The sensitivity results include both first- and second-order derivatives. Such results are useful in many applications. In this thesis, they are applied in reliability analysis, optimization analysis, model validation, model calibration, as well as stand-alone measures of parameter importance to gain physical insight into the curing and stress development process. In addition to novel derivations and implementations, this thesis is intended to facilitate and foster increased use of response sensitivities in engineering analysis. The work presented in this thesis constitutes an extension of the direct differentiation method (DDM). This is a method that produces response sensitivities in an efficient and accurate manner, at the one-time cost of deriving and implementing sensitivity equations alongside the ordinary response algorithm. In this thesis, novel extensions of the methodology are presented for the composite manufacturing problem. The derivations include all material, geometry, and processing parameters in both the thermochemical and the stress development algorithms. A state-of-the-art simulation software is developed to perform first-order sensitivity analysis for composite manufacturing problems using the DDM. In this software, several novel techniques are employed to minimize the computational cost associated with the response sensitivity computations. This sensitivity-enabled software is also used in reliability, optimization, and model calibration applications. All these applications are facilitated by the availability of efficient and accurate response sensitivities. The derivation and implementation of second-order sensitivity equations is a particular novelty in this thesis. It is demonstrated that it is computationally feasible to obtain second-order sensitivities (the “Hessian matrix”) by the DDM for inelastic finite element problems. It is demonstrated that the direct differentiation approach to the computation of first- and second-order response sensitivities becomes increasingly efficient as the problem size increases, compared with the less accurate and less efficient finite different approach.
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Kent, Edward Lander. "Sensitivity analysis of biochemical systems using high-throughput computing." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/sensitivity-analysis-of-biochemical-systems-using-highthroughput-computing(80eb7aa9-d316-4a72-a6c2-731c6052ea84).html.

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Mathematical modelling is playing an increasingly important role in helping us to understand biological systems. The construction of biological models typically requires the use of experimentally-measured parameter values. However, varying degrees of uncertainty surround virtually all parameters in these models. Sensitivity analysis is one of the most important tools for the analysis of models, and shows how the outputs of a model, such as concentrations and reaction fluxes, are dependent on the parameters which make up the input. Unfortunately, small changes in parameter values can lead to the results of a sensitivity analysis changing significantly. The results of such analyses must therefore be interpreted with caution, particularly if a high degree of uncertainty surrounds the parameter values. Global sensitivity analysis methods can help in such situations by allowing sensitivities to be calculated over a range of possible parameter values. However, these techniques are computationally expensive, particularly for larger, more detailed models. Software was developed to enable a number of computationally-intensive modelling tasks, including two global sensitivity analysis methods, to be run in parallel in a high-throughput computing environment. The use of high-throughput computing enabled the run time of these analyses to be drastically reduced, allowing models to be analysed to a degree that would otherwise be impractical or impossible. Global sensitivity analysis using high-throughput computing was performed on a selection of both theoretical and physiologically-based models. Varying degrees of parameter uncertainty were considered. These analyses revealed instances in which the results of a sensitivity analysis were valid, even under large degrees of parameter variation. Other cases were found for which only a slight change in parameter values could completely change the results of the analysis. Parameter uncertainties are a real problem in biological systems modelling. This work shows how, with the help of high-throughput computing, global sensitivity analysis can become a practical part of the modelling process.
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Lin, Daorui. "Global Sensitivity of Water Quality Modeling in the Gulf of Finland." Thesis, KTH, Mark- och vattenteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-180285.

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The Gulf of Finland is the most eutrophied water body in the Baltic Sea, which is mainly caused by nutrient loads produced by human activities in its surrounding cities. In order to solve this environmental problem, a computational model based on the understanding the relations between eutrophication, water quality and sediments is needed to forecast the water quality variance in response to the natural and anthropogenic influences. A precise water quality model can be useful to assist the policy making in the Gulf of Finland, and even for the whole Baltic Sea. Kiirikki model, as one of these models describing the water quality of Baltic Sea in response of water quality variance, is a sediment and ecosystem based model, treating different sub-basins and layers as boxes. This study aims to assess the parameters’ sensitivity level on the scale of the Gulf of Finland. Firstly, the Morris sampling strategy is applied to generate economic OAT (One factor At a Time) samples before screening 50 out of 100 trajectories with distance as large as possible. In order to assess their sensitivity, index and indicator are needed. EE (elementary effect) is adopted to be the assessment index and four core eutrophication indicators from HELCOM 2009a are to be analyzed. By comparing the (σ,μ) and (σ,μ*) plots of each parameters’ EE values (σ is standard deviation, μ is mean value and μ* is the absolute mean value), some parameters are identified as potential sensitive parameter, such as the minimum biomass of cyanobacteria (Cmin), critical point of CO2 flux (CCr), the optimal temperature for detritus phosphorous mineralization (Toptgamma), maximum loss rate of algae (RAmax), optimal temperature for the growth of other algae (ToptmuA), Coefficient for temperature limiting factor for the growth of cyanobacteria (aTmuC), half-saturation coefficient of radiation for cyanobacteria (KIC) and so on. In contrast, the other parameters are ruled out as having very low values in terms of σ, μ and μ*. This is because the feature of Morris sampling strategy makes it easier to achieve high variance of the outputs, resulting into generally higher σ. Therefore, further investigation with different strategies is needed after the initial screening of the non-sensitive parameters in this study.
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Books on the topic "Global response sensitivity analysis"

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1953-, Saltelli A., ed. Global sensitivity analysis: The primer. Chichester, England: John Wiley, 2008.

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1953-, Saltelli A., ed. Global sensitivity analysis: The primer. Chichester, England: John Wiley, 2008.

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M, Adelman Howard, Haftka Raphael T, Virginia Polytechnic Institute and State University, Langley Research Center, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch, eds. Sensitivity Analysis in Engineering: Proceedings of a symposium. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1987.

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K, Kapania Rakesh, and Langley Research Center, eds. Shape sensitivity analysis of flutter response of a laminated wing. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1988.

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K, Kapania Rakesh, and Langley Research Center, eds. Shape sensitivity analysis of flutter response of a laminated wing. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1988.

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Morante, R. Reevaluation of regulatory guidance on modal response combination methods for seismic response spectrum analysis. Washington, DC: Division of Engineering Technology, Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1999.

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T, Haftka Raphael, and Langley Research Center, eds. A discourse on sensitivity analysis for discretely-modeled structures. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1991.

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T, Haftka Raphael, and Langley Research Center, eds. A discourse on sensitivity analysis for discretely-modeled structures. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1991.

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K, Kapania Rakesh, Barthelemy Jean-Francois M, and United States. National Aeronautics and Space Administration., eds. Sensitivity analysis of flutter response of a wing incorporating finite-span corrections. [Washington, DC: National Aeronautics and Space Administration, 1994.

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Nalecz, Andrzej G. Sensitivity analysis of vehicle design attributes that affect vehicle response in critical accident situations. Washington, D.C.]: U.S. Dept. of Transportation, National Highway Traffic Safety Administration, 1987.

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Book chapters on the topic "Global response sensitivity analysis"

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Shishov, Vladimir V., Alberto Arzac, Margarita I. Popkova, Bao Yang, Minhui He, and Eugene A. Vaganov. "Experimental and Theoretical Analysis of Tree-Ring Growth in Cold Climates." In Advances in Global Change Research, 295–321. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-15988-6_11.

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AbstractThe medium- and long-term projections of global climate models show the effects of global warming will be most pronounced in cold climate areas, especially in the high latitudes of the Northern Hemisphere. The consequences could involve a higher probability of global natural disasters and a higher uncertainty as to plant response to climate risk. In this chapter, we describe life under a cold climate, particularly in relation to forest ecosystems, species distribution, and local conditions in the Northern Hemisphere. We analyze recent climate trends and how the ongoing and future climate changes can affect the sensitivity of conifer species, the most common tree form in the boreal regions. We combine experimental data and theoretical process-based simulations involving tree-ring width, tree-ring density, and wood anatomy. This combined approach permits assessing a longer tree-ring record that overlaps with direct instrumental climate observations. The latter are currently experiencing the divergence problem in which tree-ring growth has diverged from the trends of the main climatic drivers. Given that most process-based models are multidimensional, the parameterization described in this chapter is key for obtaining reliable tree growth simulations connected with a site-specific climate, tree species, and the individual trajectory of tree development. Our approach combining experimental and theoretical approaches in xylogenesis is of interest to forest ecologists, physiologists, and wood anatomists.
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Borgonovo, Emanuele. "Global Sensitivity Analysis." In Sensitivity Analysis, 129–38. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_14.

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Zhou, Xiaobo, Henry Lin, and Henry Lin. "Global Sensitivity Analysis." In Encyclopedia of GIS, 408–9. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_538.

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Zhou, Xiaobo, and Henry Lin. "Global Sensitivity Analysis." In Encyclopedia of GIS, 1. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23519-6_538-2.

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Zhou, Xiaobo, and Henry Lin. "Global Sensitivity Analysis." In Encyclopedia of GIS, 787. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-17885-1_538.

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Chu, Yunfei, and Juergen Hahn. "Global Sensitivity Analysis." In Encyclopedia of Systems Biology, 841–42. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_1283.

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Borgonovo, Emanuele. "Exercising Global Sensitivity Analysis: Test Cases." In Sensitivity Analysis, 211–28. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_20.

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Borgonovo, Emanuele. "Global Sensitivity Analysis with Value of Information." In Sensitivity Analysis, 201–10. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52259-3_19.

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Campolongo, Francesca, Henrik Jönsson, and Wim Schoutens. "Global Sensitivity Analysis for ABS." In Quantitative Assessment of Securitisation Deals, 69–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29721-2_6.

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Saltelli, Andrea, Daniele Vidoni, and Massimiliano Mascherini. "Recommended practices in global sensitivity analysis." In Uncertainties in Environmental Modelling and Consequences for Policy Making, 183–202. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-2636-1_8.

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Conference papers on the topic "Global response sensitivity analysis"

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Opalski, Leszek J. "Variability-based global sensitivity analysis of circuit response." In Symposium on Photonics Applications in Astronomy, Communications, Industry and High-Energy Physics Experiments, edited by Ryszard S. Romaniuk. SPIE, 2014. http://dx.doi.org/10.1117/12.2075203.

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Li, Chenzhao, and Sankaran Mahadevan. "Global Sensitivity Analysis for System Response Prediction Using Auxiliary Variable Method." In 17th AIAA Non-Deterministic Approaches Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2015. http://dx.doi.org/10.2514/6.2015-0661.

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McFarland, John M., John A. Dimeo, and Barron J. Bichon. "GAUSSIAN PROCESS RESPONSE SURFACE MODELING AND GLOBAL SENSITIVITY ANALYSIS USING NESSUS." In 1st International Conference on Uncertainty Quantification in Computational Sciences and Engineering. Athens: Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece, 2017. http://dx.doi.org/10.7712/120217.5365.16997.

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Song, Zhouzhou, Zhao Liu, Can Xu, and Ping Zhu. "Global Sensitivity Analysis for Field Response Based on the Manifold of Feature Covariance Matrix." In ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/detc2021-69086.

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Abstract In real-world applications, it is commonplace that the computational models have field responses, i.e., the temporal or spatial fields. It has become a critical task to develop global sensitivity analysis (GSA) methods to measure the effect of each input variable on the full-field. In this paper, a new sensitivity analysis method based on the manifold of feature covariance matrix (FCM) is developed for quantifying the impact of input variables on the field response. The method firstly performs feature extraction on the field response to obtain a low-dimensional FCM. An adaptive feature selection method is proposed to avoid the FCM from singularity. Thereby, the field response is represented by a FCM, which lies on a symmetric positive-definite matrix manifold. Then, the GSA technique based on the Cramér-von Mises distance for output valued on the Riemannian manifold is introduced for estimating the sensitivity indices for field response. An example of a temporal field and an example of a 2-D displacement field are introduced to demonstrate the applicability of the proposed method in estimating global sensitivity indices for field solution. Results show that the proposed method can distinguish the important input variables correctly and can yield robust index values. Besides, the proposed method can be implemented for GSA for field responses of different dimensionalities.
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Liu, Huibin, Wei Chen, and Agus Sudjianto. "Relative Entropy Based Method for Global and Regional Sensitivity Analysis in Probabilistic Design." In ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/detc2004-57500.

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To overcome the limitations of existing variance-based methods for Probabilistic Sensitivity Analysis (PSA) in design under uncertainty, a new PSA approach based on the concept of relative entropy is proposed. The relative entropy based method evaluates the impact of a random variable by measuring the divergence between two probability density functions of a response. The method can be applied both globally over the whole distribution of a performance response (called global response probabilistic sensitivity analysis–GRPSA) and in any regional range of a response distribution (called regional response probabilistic sensitivity analysis–RRPSA). The former is the most useful for studying variable impact on robust design objective, while the latter provides insight into reliability constraints. The proposed method is applicable to both the prior-design and post-design stages, for variable screening and uncertainty reduction, respectively. The proposed method is verified by numerical examples and industrial design cases.
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Emery, A. F., and D. Bardot. "The Determination of the Sensitivity of Heat Transfer Systems Using Global Sensitivity and Gaussian Processes." In ASME 2005 Summer Heat Transfer Conference collocated with the ASME 2005 Pacific Rim Technical Conference and Exhibition on Integration and Packaging of MEMS, NEMS, and Electronic Systems. ASMEDC, 2005. http://dx.doi.org/10.1115/ht2005-72287.

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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. When there are many variables it is important to restrict the analysis to those variables to which the response is most sensitive. This can be conveniently done using Global sensitivity, that both defines the most critical variables and also quantifies the effects of interacting variables. This 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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Qin, Wei, Zhuang Kang, and Youwei Kang. "Free Standing Hybrid Riser Global Parametric Sensitivity Analysis and Optimum Design." In ASME 2011 30th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2011. http://dx.doi.org/10.1115/omae2011-49606.

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With a rigid pipe for the vertical free standing portion and a flexible pipe for the near surface dynamic motion region, Free Standing Hybrid Riser (FSHR) has been widely accepted within the offshore oil and gas industry, especially in the field of West of Africa, Gulf of Mexico and field of Brazil. So the optimum design of FSHR system is becoming increasingly meaningful and necessary. This paper mainly presents the parametric sensitivity analysis and optimization of deepwater Free Standing Hybrid Riser (FSHR). First of all, a general description about FSHR system is given in the introduction. The components of FSHR and their function are presented in detail. Secondly, the procedure for parameters optimum design is discussed, and in order to make it looks more clearly and directly, a flowchart is illustrated to show the process. Considering the design requirements for a deepwater FSHR, the optimum design mathematic model is presented with the optimal objective - minimum of FSHR total weight which is directly proportional to project cost. Thirdly, a design instance is given to make clear the flow of FSHR optimum design with the best performance. The global strength analysis is carried out with the use of generic FEA tools. Then the parametric sensitivity analysis is performed through Single-Variable Control Method. Based on FSHR global strength analysis, four sensitivity parameters are carried out, and the minimum bending radius (MBR) of Flexible Jumper and the max von Misses stress are checked according to API RP 2RD. The relationship between sensitivity parameters and the response of the riser system is briefly discussed and the regress analysis can be used to quantify the relativity. Finally, the parameters optimum design is analyzed and the optimum results are checked to ensure its validity.
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Rajasekharan, Rahul, and E. P. Petrov. "Analysis of Statistical Characteristics and Global Sensitivity for Forced Response of Bladed Disks Mistuned by Material Anisotropy." In ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gt2019-90632.

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Abstract High-pressure turbines of modern gas-turbine engines use single crystal blades that exhibit material anisotropy. Due to manufacturing tolerances, each blade in the bladed disk will have different crystal anisotropy axis orientation, thereby creating mistuning in the structure. In this paper, the blade anisotropy angles are considered as uncertain design parameters to study the variation in forced response of a mistuned bladed disk. For realistic, high fidelity model of a bladed disk, linear bonded contact conditions at blade roots and shrouds are considered. The following two kinds of analysis are performed: (a) statistical analysis using polynomial chaos expansion and (b) global sensitivity analysis using Sobol indices. An effective strategy based on gradient information is used to minimize the computational cost involved in statistical and sensitivity analysis. For the first time, the possibility of introducing intentional blade material anisotropy mistuning to reduce the amplification of forced response is investigated.
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Korngold, Jacob C., and Gary A. Gabriele. "Multidisciplinary Analysis and Optimization of Discrete Problems Using Response Surface Methods." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0023.

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Abstract The objective of this paper is to present a new algorithm to efficiently optimize multidisciplinary, coupled non-hierarchic 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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Awad, Mahmoud, Agus Sudjianto, and Nanua Singh. "Moment Matching for Sensitivity Analysis of Probabilistic Model Output." In ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/detc2004-57336.

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With the advent of highly complex engineering simulation models that describe the relationship between input variables and output response, the need for an efficient and effective sensitivity analysis is more demanding. In this article, a generalized approach that can provide efficient as well as accurate global sensitivity indices is developed. The approach consists of two steps: running an orthogonal array based experiment using moment-matched levels of the input variables and followed by a variance contribution analysis. The benefits of the approach are demonstrated through three different examples.
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Reports on the topic "Global response sensitivity analysis"

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Harmon, Rebecca, Mohammad Khalil, Habib N. Najm, and Cosmin Safta. Convergence study in global sensitivity analysis. Office of Scientific and Technical Information (OSTI), August 2016. http://dx.doi.org/10.2172/1561829.

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Lers, Amnon, Majid R. Foolad, and Haya Friedman. genetic basis for postharvest chilling tolerance in tomato fruit. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7600014.bard.

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ABSTRACT Postharvest losses of fresh produce are estimated globally to be around 30%. Reducing these losses is considered a major solution to ensure global food security. Storage at low temperatures is an efficient practice to prolong postharvest performance of crops with minimal negative impact on produce quality or human health and the environment. However, many fresh produce commodities are susceptible to chilling temperatures, and the application of cold storage is limited as it would cause physiological chilling injury (CI) leading to reduced produce quality. Further, the primary CI becomes a preferred site for pathogens leading to decay and massive produce losses. Thus, chilling sensitive crops should be stored at higher minimal temperatures, which curtails their marketing life and in some cases necessitates the use of other storage strategies. Development of new knowledge about the biological basis for chilling tolerance in fruits and vegetables should allow development of both new varieties more tolerant to cold, and more efficient postharvest storage treatments and storage conditions. In order to improve the agricultural performance of modern crop varieties, including tomato, there is great potential in introgression of marker-defined genomic regions from wild species onto the background of elite breeding lines. To exploit this potential for improving tomato fruit chilling tolerance during postharvest storage, we have used in this research a recombinant inbred line (RIL) population derived from a cross between the red-fruited tomato wild species SolanumpimpinellifoliumL. accession LA2093 and an advanced Solanum lycopersicumL. tomato breeding line NCEBR-1, developed in the laboratory of the US co-PI. The original specific objectives were: 1) Screening of RIL population resulting from the cross NCEBR1 X LA2093 for fruit chilling response during postharvest storage and estimation of its heritability; 2) Perform a transcriptopmic and bioinformatics analysis for the two parental lines following exposure to chilling storage. During the course of the project, we learned that we could measure greater differences in chilling responses among specific RILs compared to that observed between the two parental lines, and thus we decided not to perform transcriptomic analysis and instead invest our efforts more on characterization of the RILs. Performing the transcriptomic analysis for several RILs, which significantly differ in their chilling tolerance/sensitivity, at a later stage could result with more significant insights. The RIL population, (172 lines), was used in field experiment in which fruits were examined for chilling sensitivity by determining CI severity. Following the field experiments, including 4 harvest days and CI measurements, two extreme tails of the response distribution, each consisting of 11 RILs exhibiting either high sensitivity or tolerance to chilling stress, were identified and were further examined for chilling response in greenhouse experiments. Across the RILs, we found significant (P < 0.01) correlation between field and greenhouse grown plants in fruit CI. Two groups of 5 RILs, whose fruits exhibited reproducible chilling tolerant/sensitive phenotypes in both field and greenhouse experiments, were selected for further analyses. Numerous genetic, physiological, biochemical and molecular variations were investigated in response to postharvest chilling stress in the selected RILs. We confirmed the differential response of the parental lines of the RIL population to chilling stress, and examined the extent of variation in the RIL population in response to chilling treatment. We determined parameters which would be useful for further characterization of chilling response in the RIL population. These included chlorophyll fluorescence Fv/Fm, water loss, total non-enzymatic potential of antioxidant activity, ascorbate and proline content, and expression of LeCBF1 gene, known to be associated with cold acclimation. These parameters could be used in continuation studies for the identification and genetic mapping of loci contributing to chilling tolerance in this population, and identifying genetic markers associated with chilling tolerance in tomato. Once genetic markers associated with chilling tolerance are identified, the trait could be transferred to different genetic background via marker-assisted selection (MAS) and breeding. The collaborative research established in this program has resulted in new information and insights in this area of research and the collaboration will be continued to obtain further insights into the genetic, molecular biology and physiology of postharvest chilling tolerance in tomato fruit. The US Co-PI, developed the RIL population that was used for screening and measurement of the relevant chilling stress responses and conducted statistical analyses of the data. Because we were not able to grow the RIL population under field conditions in two successive generations, we could not estimate heritability of response to chilling temperatures. However, we plan to continue the research, grow the RIL progeny in the field again, and determine heritability of chilling tolerance in a near future. The IS and US investigators interacted regularly and plan to continue and expand on this study, since combing the expertise of the Co-PI in genetics and breeding with that of the PI in postharvest physiology and molecular biology will have great impact on this line of research, given the significant findings of this one-year feasibility project.
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Tong, C., and F. Graziani. A Global Sensitivity Analysis Methodology for Multi-physics Applications. Office of Scientific and Technical Information (OSTI), February 2007. http://dx.doi.org/10.2172/1036842.

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Tong, C. Toward a more robust variance-based global sensitivity analysis of model outputs. Office of Scientific and Technical Information (OSTI), October 2007. http://dx.doi.org/10.2172/923115.

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Hameed, Maysoun. Evaluating Global Sensitivity Analysis Methods for Hydrologic Modeling over the Columbia River Basin. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2395.

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Ye, Ming. Multi-Model and Multi-Scale Global Sensitivity Analysis for Identifying Controlling Processes of Complex Systems. Office of Scientific and Technical Information (OSTI), November 2020. http://dx.doi.org/10.2172/1724677.

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Hardy, Marsh. Review of Cost-Constrained Minimum Runs Algorithm for Response Sensitivity Analysis of the FRACT3DVS Code. Fort Belvoir, VA: Defense Technical Information Center, April 1997. http://dx.doi.org/10.21236/ada327088.

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Keeney, Roman, and Thomas Hertel. GTAP-AGR: A Framework for Assessing the Implications of Multilateral Changes in Agricultural Policies. GTAP Technical Paper, August 2005. http://dx.doi.org/10.21642/gtap.tp24.

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Global models of agricultural trade have a long and distinguished history. The introduction of the GTAP data base and modeling project represented a significant advance forward as it put modelers and trade policy analysts on common ground. After an initial generation of GTAP based modeling of agricultural trade policy using the standard modeling framework, individual researchers have begun introducing agricultural specificity into the standard modeling framework in order to better capture the particular features of the agricultural economy pertinent to their research questions. This technical paper follows in that same tradition by reviewing important linkages between international trade and the farm and food economy and introducing them into the standard GTAP modeling framework, offering a special purpose version of the model nicknamed GTAP-AGR. We introduce this agricultural specificity by introducing new behavioral relationships into the standard GTAP framework. We focus particular attention on the factor markets, which play a critical role in determining the incidence of producer subsidies. This includes modifying both the factor supply and derived demand equations. We also modify the specification of consumer demand, assuming separability of food from non-food commodities. Finally, we introduce the important substitution possibilities amongst feedstuffs used in the livestock sector. Where possible we support these new behavioral relationships with literature-based estimates of both the mean and standard deviation of behavioral parameters. The express purpose of this is to support systematic sensitivity analysis with respect to policy reform scenarios performed with GTAP-AGR. In addition to documenting these extensions to the standard modeling framework, the paper has an additional goal, and that is to gauge the performance of the GTAP-AGR model and how it differs from the standard GTAP framework. We do this primarily by comparing the farm level supply and demand response in terms of policy incidence for the two frameworks. In addition, we evaluate the ability of both models to reproduce observed price volatility in an effort to validate the performance of these models. Finally, we evaluate the results of the two models in a side-by-side comparison of results from full liberalization of agricultural and non-agricultural support.
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Reddy, Anireddy, and Asa Ben-Hur. Global analysis of epigenetic regulation of gene expression in response to drought stress in Sorghum. Office of Scientific and Technical Information (OSTI), November 2017. http://dx.doi.org/10.2172/1409851.

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Hertel, Thomas. Global Applied General Equilibrium Analysis using the GTAP Framework. GTAP Working Paper, January 2012. http://dx.doi.org/10.21642/gtap.wp66.

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Contributed Chapter for Peter B. Dixon and Dale W. Jorgenson (eds.) This chapter provides an overview of the first two decades of the Global Trade Analysis Project (GTAP) – an effort to support a standardized data base and CGE modeling platform for international economic analysis. It characterizes GTAP in four different dimensions: institutional innovation, a network, a database and a standardized modeling platform. Guiding principles for the GTAP modeling framework include flexibility, ease of use, transparency, and symmetric treatment of production and utility fundamentals across regions. The chapter reviews core modeling assumptions relating to the regional household, private consumption behavior, welfare decomposition, the “global bank”, treatment of the international trade and transport sector, and imports. Model validation and sensitivity analysis, as well as software issues receive attention as well. The chapter also offers brief overviews of the two major areas of application: international economic integration and global environmental issues. It closes with a discussion of future directions for the Project.
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