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Author: Sudip Dey Publisher: CRC Press ISBN: 1351651641 Category : Mathematics Languages : en Pages : 239
Book Description
Over the last few decades, uncertainty quantification in composite materials and structures has gained a lot of attention from the research community as a result of industrial requirements. This book presents computationally efficient uncertainty quantification schemes following meta-model-based approaches for stochasticity in material and geometric parameters of laminated composite structures. Several metamodels have been studied and comparative results have been presented for different static and dynamic responses. Results for sensitivity analyses are provided for a comprehensive coverage of the relative importance of different material and geometric parameters in the global structural responses.
Author: Sudip Dey Publisher: CRC Press ISBN: 1351651641 Category : Mathematics Languages : en Pages : 239
Book Description
Over the last few decades, uncertainty quantification in composite materials and structures has gained a lot of attention from the research community as a result of industrial requirements. This book presents computationally efficient uncertainty quantification schemes following meta-model-based approaches for stochasticity in material and geometric parameters of laminated composite structures. Several metamodels have been studied and comparative results have been presented for different static and dynamic responses. Results for sensitivity analyses are provided for a comprehensive coverage of the relative importance of different material and geometric parameters in the global structural responses.
Author: Sudip Dey Publisher: CRC Press ISBN: 1498784461 Category : Mathematics Languages : en Pages : 375
Book Description
Over the last few decades, uncertainty quantification in composite materials and structures has gained a lot of attention from the research community as a result of industrial requirements. This book presents computationally efficient uncertainty quantification schemes following meta-model-based approaches for stochasticity in material and geometric parameters of laminated composite structures. Several metamodels have been studied and comparative results have been presented for different static and dynamic responses. Results for sensitivity analyses are provided for a comprehensive coverage of the relative importance of different material and geometric parameters in the global structural responses.
Author: K.Kline Publisher: ISBN: Category : Languages : en Pages :
Book Description
This work presents a survey of five theories to assess the uncertainty of projectile impact induced damage on multi-layered carbon-epoxy composite plates. Because the types of uncertainty dealt with in this application are multiple (variability, ambiguity, and conflict) and because the data sets collected are sparse, characterizing the amount of delamination damage with probability theory alone is possible but incomplete. This motivates the exploration of methods contained within a broad Generalized Information Theory (GIT) that rely on less restrictive assumptions than probability theory. Probability, fuzzy sets, possibility, and imprecise probability (probability boxes (p-boxes) and Dempster-Shafer) are used to assess the uncertainty in composite plate damage. Furthermore, this work highlights the usefulness of each theory. The purpose of the study is not to compare directly the different GIT methods but to show that they can be deployed on a practical application and to compare the assumptions upon which these theories are based. The data sets consist of experimental measurements and finite element predictions of the amount of delamination and fiber splitting damage as multilayered composite plates are impacted by a projectile at various velocities. The physical experiments consist of using a gas gun to impact suspended plates with a projectile accelerated to prescribed velocities, then, taking ultrasound images of the resulting delamination. The nonlinear, multiple length-scale numerical simulations couple local crack propagation implemented through cohesive zone modeling to global stress-displacement finite element analysis. The assessment of damage uncertainty is performed in three steps by, first, considering the test data only; then, considering the simulation data only; finally, performing an assessment of total uncertainty where test and simulation data sets are combined. This study leads to practical recommendations for reducing the uncertainty and improving the prediction accuracy of the damage modeling and finite element simulation.
Book Description
This proceedings book covers a wide range of topics related to uncertainty analysis and its application in various fields of engineering and science. It explores uncertainties in numerical simulations for soil liquefaction potential, the toughness properties of construction materials, experimental tests on cyclic liquefaction potential, and the estimation of geotechnical engineering properties for aerogenerator foundation design. Additionally, the book delves into uncertainties in concrete compressive strength, bio-inspired shape optimization using isogeometric analysis, stochastic damping in rotordynamics, and the hygro-thermal properties of raw earth building materials. It also addresses dynamic analysis with uncertainties in structural parameters, reliability-based design optimization of steel frames, and calibration methods for models with dependent parameters. The book further explores mechanical property characterization in 3D printing, stochastic analysis in computational simulations, probability distribution in branching processes, data assimilation in ocean circulation modeling, uncertainty quantification in climate prediction, and applications of uncertainty quantification in decision problems and disaster management. This comprehensive collection provides insights into the challenges and solutions related to uncertainty in various scientific and engineering contexts.
Author: Yan Wang Publisher: Woodhead Publishing ISBN: 008102942X Category : Technology & Engineering Languages : en Pages : 606
Book Description
Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification (UQ) in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale. This book presents a thorough synthesis of the state-of-the-art in UQ methods for materials modeling, including Bayesian inference, surrogate modeling, random fields, interval analysis, and sensitivity analysis, providing insight into the unique characteristics of models framed at each scale, as well as common issues in modeling across scales. Synthesizes available UQ methods for materials modeling Provides practical tools and examples for problem solving in modeling material behavior across various length scales Demonstrates UQ in density functional theory, molecular dynamics, kinetic Monte Carlo, phase field, finite element method, multiscale modeling, and to support decision making in materials design Covers quantum, atomistic, mesoscale, and engineering structure-level modeling and simulation
Author: Mishal Thapa Publisher: ISBN: Category : Electronic dissertations Languages : en Pages : 0
Book Description
Uncertainty quantification (UQ) is the science of quantifying and characterizing response variation due to the presence of uncertainties in the input parameters and governing models. Among the prevalent methods for UQ, non-intrusive probabilistic techniques such as the perturbation method and Polynomial Chaos Expansion (PCE) are more popular due to their ability to integrate existing deterministic solvers as a black box. However, with the increase in the number of inputs, the number of basis terms in the expansion increases exponentially, also known as the 'curse of dimensionality', thereby requiring a large number of function realizations. Therefore, this dissertation is focused on exploring a new robust algorithms for the perturbation method as well as PCEand their application to composite structures while maintaining a balance between accuracy and computational efficiency. At first, an efficient approach for UQ using a higher-order Taylor series expansion is developed. Then, the local sensitivities in the Taylor series are evaluated using a high-accuracy and computationally efficient approach called modified forward finite difference (ModFFD). The number of function evaluations required for the sensitivity estimation equals the number of expansion terms in the series. Once the sensitivities are evaluated with ModFFD, the stochastic response is obtained for different realizations of the random inputs without additional function evaluations. This approach's main advantage is that it applies to any probability distribution of the inputs and is unrestricted by the nature of random input variables (correlated and uncorrelated). Several analytical and engineering problems were considered with up to twenty-two random variables to test the presented approach. A ten-bar truss problem with twenty-two random variables and buckling of a composite laminate with twenty random variables are considered as engineering problems. The comparison of the results with the reference solution obtained using many Monte Carlo Simulations (MCS) demonstrated its high accuracy and computational efficiency for random inputs with non-standard random inputs and varying correlation. Secondly, to further reduce the number of samples required to build a surrogate model to carry out uncertainty analysis, least-squares Polynomial Chaos Expansion (PCE) with L2 regularization for an under-determined system is presented. Moreover, a new method for selecting the regularization parameter is proposed and compared with the traditional L-curve method with Tikhonov regularization. This work aims to find the best solution from the limited number of function realizations (fewer response samples), thereby directly reducing the computational time required to build the surrogate while maintaining the desired accuracy. The proposed method is applied to several analytical problems and an engineering problem - the stochastic study of Mode-I delamination of a composite structure using Cohesive Zone Element (CZM). The results demonstrated the applicability and computational superiority of the proposed algorithm. Finally, stochastic buckling analysis of an unstiffened composite cylinder with geometric imperfection under axial compression is explored. The effect of random initial geometric imperfections, material properties, ply orientation, and ply thickness on the buckling limit load of thin-walled, composite cylindrical shells is studied. The initial geometric imperfections are modeled using the mode shapes of linear buckling analysis (LBA). In addition, to reduce the number of function evaluations required during the PCE building process for UQ, adaptive-sparse polynomial chaos expansion with L1-norm minimization is utilized based on orthogonal matching pursuit (OMP). Global sensitivity analysis (GSA) based on Sobol indices is used to identify the important parameters of the system. The results showed the uncertainties' significant effect on the buckling eigenvalues of the structures, thereby emphasizing the need to account for geometric imperfections and other sources of uncertainty during the design phase to obtain a robust design.
Author: Robert Barthorpe Publisher: Springer ISBN: 3319747932 Category : Technology & Engineering Languages : en Pages : 303
Book Description
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics, 2018, the third volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Uncertainty Quantification in Material Models Uncertainty Propagation in Structural Dynamics Practical Applications of MVUQ Advances in Model Validation & Uncertainty Quantification: Model Updating Model Validation & Uncertainty Quantification: Industrial Applications Controlling Uncertainty Uncertainty in Early Stage Design Modeling of Musical Instruments Overview of Model Validation and Uncertainty
Author: Sudip Dey
Author: Sudip Dey
Author: Sudip Dey
Author: K.Kline
Author: 
Author: José Eduardo Souza De Cursi
Author: Doo Bo Chung
Author: Yan Wang
Author: Mishal Thapa
Author: Robert Barthorpe
Author: N. Papadimas