Uncertainty Quantification in Multiscale Materials Modeling

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 ...

Uncertainty Quantification in Multiscale Materials Modeling

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.

Multiscale Modeling and Uncertainty Quantification of Materials and Structures

This book contains the proceedings of the IUTAM Symposium on Multiscale Modeling and Uncertainty Quantification of Materials and Structures that was held at Santorini, Greece, September 9 – 11, 2013.

Multiscale Modeling and Uncertainty Quantification of Materials and Structures

This book contains the proceedings of the IUTAM Symposium on Multiscale Modeling and Uncertainty Quantification of Materials and Structures that was held at Santorini, Greece, September 9 – 11, 2013. It consists of 20 chapters which are divided in five thematic topics: Damage and fracture, homogenization, inverse problems–identification, multiscale stochastic mechanics and stochastic dynamics. Over the last few years, the intense research activity at micro scale and nano scale reflected the need to account for disparate levels of uncertainty from various sources and across scales. As even over-refined deterministic approaches are not able to account for this issue, an efficient blending of stochastic and multiscale methodologies is required to provide a rational framework for the analysis and design of materials and structures. The purpose of this IUTAM Symposium was to promote achievements in uncertainty quantification combined with multiscale modeling and to encourage research and development in this growing field with the aim of improving the safety and reliability of engineered materials and structures. Special emphasis was placed on multiscale material modeling and simulation as well as on the multiscale analysis and uncertainty quantification of fracture mechanics of heterogeneous media. The homogenization of two-phase random media was also thoroughly examined in several presentations. Various topics of multiscale stochastic mechanics, such as identification of material models, scale coupling, modeling of random microstructures, analysis of CNT-reinforced composites and stochastic finite elements, have been analyzed and discussed. A large number of papers were finally devoted to innovative methods in stochastic dynamics.

Uncertainty Quantification and Management for Multi scale Nuclear Materials Modeling

Understanding and improving microstructural mechanical stability in metals and alloys is central to the development of high strength and high ductility materials for cladding and cores structures in advanced fast reactors.

Uncertainty Quantification and Management for Multi scale Nuclear Materials Modeling

Understanding and improving microstructural mechanical stability in metals and alloys is central to the development of high strength and high ductility materials for cladding and cores structures in advanced fast reactors. Design and enhancement of radiation-induced damage tolerant alloys are facilitated by better understanding the connection of various unit processes to collective responses in a multiscale model chain, including: dislocation nucleation, absorption and desorption at interfaces; vacancy production, radiation-induced segregation of Cr and Ni at defect clusters (point defect sinks) in BCC Fe-Cr ferritic/martensitic steels; investigation of interaction of interstitials and vacancies with impurities (V, Nb, Ta, Mo, W, Al, Si, P, S); time evolution of swelling (cluster growth) phenomena of irradiated materials; and energetics and kinetics of dislocation bypass of defects formed by interstitial clustering and formation of prismatic loops, informing statistical models of continuum character with regard to processes of dislocation glide, vacancy agglomeration and swelling, climb and cross slip.

Stochastic Multiscale Modeling of Polycrystalline Materials

The uncertainty quantification framework developed in this work integrates information science and materials science, and provides a new outlook to multiscale materials modeling accounting for microstructure and process uncertainties.

Stochastic Multiscale Modeling of Polycrystalline Materials

Mechanical properties of engineering materials are sensitive to the underlying random microstructure. Quantification of mechanical property variability induced by microstructure variation is essential for the prediction of extreme properties and microstructure-sensitive design of materials. Recent advances in high throughput characterization of polycrystalline microstructures have resulted in huge data sets of microstructural descriptors and image snapshots. To utilize these large scale experimental data for computing the resulting variability of macroscopic properties, appropriate mathematical representation of microstructures is needed. By exploring the space containing all admissible microstructures that are statistically similar to the available data, one can estimate the distribution/envelope of possible properties by employing efficient stochastic simulation methodologies along with robust physics-based deterministic simulators. The focus of this thesis is on the construction of lowdimensional representations of random microstructures and the development of efficient physics-based simulators for polycrystalline materials. By adopting appropriate stochastic methods, such as Monte Carlo and Adaptive Sparse Grid Collocation methods, the variability of microstructure-sensitive properties of polycrystalline materials is investigated. The primary outcomes of this thesis include: - Development of data-driven reduced-order representations of microstruc- ture variations to construct the admissible space of random polycrystalline microstructures. - Development of accurate and efficient physics-based simulators for the estimation of material properties based on mesoscale microstructures. - Investigating property variability of polycrystalline materials using efficient stochastic simulation methods in combination with the above two developments. The uncertainty quantification framework developed in this work integrates information science and materials science, and provides a new outlook to multiscale materials modeling accounting for microstructure and process uncertainties. Predictive materials modeling will accelerate the development of new materials and processes for critical applications in industry.

Multiscale Modeling of Heterogeneous Structures

Matthies, H.G., Ibrahimbegovic, A.: Stochastic multiscale coupling of inelastic processes in solid mechanic. In: Papadrakakis, M., Stefanou, G. (eds.) Multiscale Modelling and Uncertainty Quantification of Materials and Structures, vol.

Multiscale Modeling of Heterogeneous Structures

This book provides an overview of multiscale approaches and homogenization procedures as well as damage evaluation and crack initiation, and addresses recent advances in the analysis and discretization of heterogeneous materials. It also highlights the state of the art in this research area with respect to different computational methods, software development and applications to engineering structures. The first part focuses on defects in composite materials including their numerical and experimental investigations; elastic as well as elastoplastic constitutive models are considered, where the modeling has been performed at macro- and micro levels. The second part is devoted to novel computational schemes applied on different scales and discusses the validation of numerical results. The third part discusses gradient enhanced modeling, in particular quasi-brittle and ductile damage, using the gradient enhanced approach. The final part addresses thermoplasticity, solid-liquid mixtures and ferroelectric models. The contents are based on the international workshop “Multiscale Modeling of Heterogeneous Structures” (MUMO 2016), held in Dubrovnik, Croatia in September 2016.

Uncertainty Quantification

This book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale computational models in sciences and engineering.

Uncertainty Quantification

This book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale computational models in sciences and engineering. In particular, it focuses in parametric uncertainties, and non-parametric uncertainties with applications from the structural dynamics and vibroacoustics of complex mechanical systems, from micromechanics and multiscale mechanics of heterogeneous materials. Resulting from a course developed by the author, the book begins with a description of the fundamental mathematical tools of probability and statistics that are directly useful for uncertainty quantification. It proceeds with a well carried out description of some basic and advanced methods for constructing stochastic models of uncertainties, paying particular attention to the problem of calibrating and identifying a stochastic model of uncertainty when experimental data is available. This book is intended to be a graduate-level textbook for students as well as professionals interested in the theory, computation, and applications of risk and prediction in science and engineering fields.

Model Validation and Uncertainty Quantification Volume 3

Bogdanor, M.J., Mahadevan, S., Oskay, C.: Uncertainty quantification in damage modeling ... Int. J. Multiscale Comput. ... Impact Excitations 30 Uncertainty Quantification in Nanoscale Impact Experiment in Energetic Materials 263.

Model Validation and Uncertainty Quantification  Volume 3

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

Integrated Computational Materials Engineering ICME for Metals

Model. that. Included. the. Hierarchical. Multiscale. Analysis. and. Associated. Microstructures. from. the. Different. Length. Scales. In this case study, we employ the optimization, uncertainty, and metamodeling approaches that were ...

Integrated Computational Materials Engineering  ICME  for Metals

State-of-the-technology tools for designing, optimizing, and manufacturing new materials Integrated computational materials engineering (ICME) uses computational materials science tools within a holistic system in order to accelerate materials development, improve design optimization, and unify design and manufacturing. Increasingly, ICME is the preferred paradigm for design, development, and manufacturing of structural products. Written by one of the world's leading ICME experts, this text delivers a comprehensive, practical introduction to the field, guiding readers through multiscale materials processing modeling and simulation with easy-to-follow explanations and examples. Following an introductory chapter exploring the core concepts and the various disciplines that have contributed to the development of ICME, the text covers the following important topics with their associated length scale bridging methodologies: Macroscale continuum internal state variable plasticity and damage theory and multistage fatigue Mesoscale analysis: continuum theory methods with discrete features and methods Discrete dislocation dynamics simulations Atomistic modeling methods Electronics structures calculations Next, the author provides three chapters dedicated to detailed case studies, including "From Atoms to Autos: A Redesign of a Cadillac Control Arm," that show how the principles and methods of ICME work in practice. The final chapter examines the future of ICME, forecasting the development of new materials and engineering structures with the help of a cyberinfrastructure that has been recently established. Integrated Computational Materials Engineering (ICME) for Metals is recommended for both students and professionals in engineering and materials science, providing them with new state-of-the-technology tools for selecting, designing, optimizing, and manufacturing new materials. Instructors who adopt this text for coursework can take advantage of PowerPoint lecture notes, a questions and solutions manual, and tutorials to guide students through the models and codes discussed in the text.

Assessment of the In House Laboratory Independent Research at the Army s Research Development and Engineering Centers

Future directions include research on uncertainty quantification analysis to investigate the robustness of multiscale simulation. The results obtained within this project show that the predictions of the coupled multiscale FE-DE model ...

Assessment of the In House Laboratory Independent Research at the Army s Research  Development  and Engineering Centers

This report evaluates the In-House Laboratory Independent Research (ILIR) conducted at the Research, Development, and Engineering Centers (RDECs) of the U.S. Army's Research, Development, and Engineering Command (RDECOM) during 2018. It reviews and offers recommendations for each of the eight areas of ILIR research: chemistry, computational sciences, electronics, life sciences, materials science, mechanical sciences, network sciences, and physics.

Predictive Theoretical and Computational Approaches for Additive Manufacturing

COMPUTATIONAL AND ANALYTICAL METHODS 55 The third issue is the use of data science in predictive modeling. He wondered if high-throughput material testing could be utilized for uncertainty quantification, statistical learning, ...

Predictive Theoretical and Computational Approaches for Additive Manufacturing

Additive manufacturing (AM) methods have great potential for promoting transformative research in many fields across the vast spectrum of engineering and materials science. AM is one of the leading forms of advanced manufacturing which enables direct computer-aided design (CAD) to part production without part-specific tooling. In October 2015 the National Academies of Sciences, Engineering, and Medicine convened a workshop of experts from diverse communities to examine predictive theoretical and computational approaches for various AM technologies. While experimental workshops in AM have been held in the past, this workshop uniquely focused on theoretical and computational approaches and involved areas such as simulation-based engineering and science, integrated computational materials engineering, mechanics, materials science, manufacturing processes, and other specialized areas. This publication summarizes the presentations and discussions from the workshop.

Applied Spectroscopy and the Science of Nanomaterials

When graphene is doped with other plasmonic materials or included in a multilayer structure, the result is extremely ... Predictive modeling frameworks (with capabilities for uncertainty quantification as well as parameter sensitivity ...

Applied Spectroscopy and the Science of Nanomaterials

This book focuses on several areas of intense topical interest related to applied spectroscopy and the science of nanomaterials. The eleven chapters in the book cover the following areas of interest relating to applied spectroscopy and nanoscience: · Raman spectroscopic characterization, modeling and simulation studies of carbon nanotubes, · Characterization of plasma discharges using laser optogalvanic spectroscopy, · Fluorescence anisotropy in understanding protein conformational disorder and aggregation, · Nuclear magnetic resonance spectroscopy in nanomedicine, · Calculation of Van der Waals interactions at the nanoscale, · Theory and simulation associated with adsorption of gases in nanomaterials, · Atom-precise metal nanoclusters, · Plasmonic properties of metallic nanostructures, two-dimensional materials, and their composites, · Applications of graphene in optoelectronic devices and transistors, · Role of graphene in organic photovoltaic device technology, · Applications of nanomaterials in nanomedicine.

Uncertainty Quantification and Model Calibration

The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from ...

Uncertainty Quantification and Model Calibration

Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating.

Multiscale Methods

The primary objective of this volume is to reflect the state-of-the-art in multiscale mathematics, modeling, and simulations and to address the following barriers: What is the information that needs to be transferred from one model or scale ...

Multiscale Methods

Small scale features and processes occurring at nanometer and femtosecond scales have a profound impact on what happens at a larger scale and over an extensive period of time. The primary objective of this volume is to reflect the state-of-the-art in multiscale mathematics, modeling, and simulations and to address the following barriers: What is the information that needs to be transferred from one model or scale to another and what physical principles must be satisfied during thetransfer of information? What are the optimal ways to achieve such transfer of information? How can variability of physical parameters at multiple scales be quantified and how can it be accounted for to ensure design robustness?The multiscale approaches in space and time presented in this volume are grouped into two main categories: information-passing and concurrent. In the concurrent approaches various scales are simultaneously resolved, whereas in the information-passing methods the fine scale is modeled and its gross response is infused into the continuum scale. The issue of reliability of multiscale modeling and simulation tools which focus on a hierarchy of multiscale models and an a posteriori model of errorestimation including uncertainty quantification, is discussed in several chapters. Component software that can be effectively combined to address a wide range of multiscale simulations is also described. Applications range from advanced materials to nanoelectromechanical systems (NEMS), biologicalsystems, and nanoporous catalysts where physical phenomena operates across 12 orders of magnitude in time scales and 10 orders of magnitude in spatial scales.This volume is a valuable reference book for scientists, engineers and graduate students practicing in traditional engineering and science disciplines as well as in emerging fields of nanotechnology, biotechnology, microelectronics and energy.

Mesoscale Models

Modeling dislocations in multi-component material systems (cf. Rao et al. 2017), including appropriate interatomic potentials for atomistic methods that include uncertainty quantification. • Improving fidelity and accuracy of simulation ...

Mesoscale Models

The book helps to answer the following questions: How far have the understanding and mesoscale modeling advanced in recent decades, what are the key open questions that require further research and what are the mathematical and physical requirements for a mesoscale model intended to provide either insight or a predictive engineering tool? It is addressed to young researchers including doctoral students, postdocs and early career faculty,

Structural Integrity and Durability of Advanced Composites

Innovative Modelling Methods and Intelligent Design Peter Beaumont, C. Soutis, Alma Hodzic. Carpinteri, A. (1989). ... Uncertainty quantification in computational stochastic multiscale analysis of nonlinear elastic materials.

Structural Integrity and Durability of Advanced Composites

Structural Integrity and Durability of Advanced Composites: Innovative Modelling Methods and Intelligent Design presents scientific and technological research from leading composite materials scientists and engineers that showcase the fundamental issues and practical problems that affect the development and exploitation of large composite structures. As predicting precisely where cracks may develop in materials under stress is an age old mystery in the design and building of large-scale engineering structures, the burden of testing to provide "fracture safe design" is imperative. Readers will learn to transfer key ideas from research and development to both the design engineer and end-user of composite materials. This comprehensive text provides the information users need to understand deformation and fracture phenomena resulting from impact, fatigue, creep, and stress corrosion cracking and how these phenomena can affect reliability, life expectancy, and the durability of structures. Presents scientific and technological research from leading composite materials scientists and engineers that showcase fundamental issues and practical problems Provides the information users need to understand deformation and fracture phenomena resulting from impact, fatigue, creep, and stress corrosion cracking Enables readers to transfer key ideas from research and development to both the design engineer and end-user of composite materials

SIAM Journal on Scientific Computing

The expertise may encompass computational methods including multiscale modeling , uncertainty quantification , or nonlinear ... for simulation of challenging problems in application areas such as biology , climate or materials science .

SIAM Journal on Scientific Computing


Integrated Design of Multiscale Multifunctional Materials and Products

This book presents the motivation for pursuing concurrent design of materials and products, thoroughly discussing the details of multiscale modeling and multilevel robust design and provides details of the design methods/strategies along ...

Integrated Design of Multiscale  Multifunctional Materials and Products

Integrated Design of Multiscale, Multifunctional Materials and Products is the first of its type to consider not only design of materials, but concurrent design of materials and products. In other words, materials are not just selected on the basis of properties, but the composition and/or microstructure iw designed to satisfy specific ranged sets of performance requirements. This book presents the motivation for pursuing concurrent design of materials and products, thoroughly discussing the details of multiscale modeling and multilevel robust design and provides details of the design methods/strategies along with selected examples of designing material attributes for specified system performance. It is intended as a monograph to serve as a foundational reference for instructors of courses at the senior and introductory graduate level in departments of materials science and engineering, mechanical engineering, aerospace engineering and civil engineering who are interested in next generation systems-based design of materials. First of its kind to consider not only design of materials, but concurrent design of materials and products Treatment of uncertainty via robust design of materials Integrates the "materials by design approach" of Olson/Ques Tek LLC with the "materials selection" approach of Ashby/Granta Distinquishes the processes of concurrent design of materials and products as an overall systems design problem from the field of multiscale modeling Systematic mathematical algorithms and methods are introduced for robust design of materials, rather than ad hoc heuristics--it is oriented towards a true systems approach to design of materials and products

Proceedings of the 2nd World Congress on Integrated Computational Materials Engineering ICME

2ndWorld Congress on Integrated Computational Materials Engineering Edited by: Mei Li, Carelyn Campbell, ... Aleatory and epistemic uncertainties need to be differentiated in validating multiscale models, where measurement data for ...

Proceedings of the 2nd World Congress on Integrated Computational Materials Engineering  ICME

This book represents a collection of papers presented at the 2nd World Congress on Integrated Computational Materials Engineering (ICME), a specialty conference organized by The Minerals, Metals & Materials Society (TMS).