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Model Systems in Catalysis
by Robert RiouxThe book concentrates on heterogeneous catalysis, but extends well beyond the most obvious model system - the single crystal. The book builds upon increasing complexity into catalyst models - that is building catalysts with controlled properties that begin to rival the complexity found in industrial based heterogeneous catalysts. This includes the deposition of clusters on flat, thin oxide surfaces amenable to characterize by electron, ion and photon based spectroscopic techniques, the thermal decomposition of organometallic clusters on surfaces with well-defined stoichiometry, to the tethering of homogeneous catalysts to metal oxide surfaces (i.e. heterogenized homogeneous catalysis) and finally evolving to a supported structural and functional mimic of the ultimate catalyst, the enzyme.
Model Tests and Numerical Simulations of Liquefaction and Lateral Spreading II: LEAP-ASIA-2019
by Tetsuo Tobita Koji Ichii Kyohei UedaThis open access book presents work collected through the Liquefaction Experiments and Analysis Projects (LEAP) in 2019 (LEAP-ASIA-2019) following the LEAP-UCD-2017 whose results have been published as a first volume. In addition to the research targets set in the previous one, such as the repeatability, variability, and sensitivity of lateral spreading on mildly sloping liquefiable sand, this volume includes research efforts to validate the generalized scaling law (hereafter “GSL”) for the identical prototype with the one employed in UCD-2017. In LEAP-ASIA-2019, 10 institutes around the world conducted 23 tests in total. It was the first multi-institutional attempts to investigate the validity of the generalized scaling law for the saturated sandy sloping deposit with wide range of initial conditions. The experimental data provided a unique basis for assessing the capabilities of six different simulation platforms for numerical simulation of soil liquefaction. The results of the experiments and the numerical simulations are presented and discussed in papers submitted by the project participants.
Model Tests and Numerical Simulations of Liquefaction and Lateral Spreading: LEAP-UCD-2017
by Bruce L. Kutter Majid T. Manzari Mourad ZeghalThis open access book presents work collected through the Liquefaction Experiments and Analysis Projects (LEAP) in 2017. It addresses the repeatability, variability, and sensitivity of lateral spreading observed in twenty-four centrifuge model tests on mildly sloping liquefiable sand. The centrifuge tests were conducted at nine different centrifuge facilities around the world. For the first time, a sufficient number of experiments were conducted to enable assessment of variability of centrifuge test results. The experimental data provided a unique basis for assessing the capabilities of twelve different simulation platforms for numerical simulation of soil liquefaction. The results of the experiments and the numerical simulations are presented and discussed in papers submitted by the project participants. The work presented in this book was followed by LEAP-Asia that included assessment of a generalized scaling law and culminated in a workshop in Osaka, Japan in March 2019. LEAP-2020, ongoing at the time of printing, is addressing the validation of soil-structure interaction analyses of retaining walls involving a liquefiable soil. A workshop is planned at RPI, USA in 2020.
Model Uncertainties in Foundation Design
by Kok-Kwang Phoon Chong TangModel Uncertainties in Foundation Design is unique in the compilation of the largest and the most diverse load test databases to date, covering many foundation types (shallow foundations, spudcans, driven piles, drilled shafts, rock sockets and helical piles) and a wide range of ground conditions (soil to soft rock). All databases with names prefixed by NUS are available upon request. This book presents a comprehensive evaluation of the model factor mean (bias) and coefficient of variation (COV) for ultimate and serviceability limit state based on these databases. These statistics can be used directly for AASHTO LRFD calibration. Besides load test databases, performance databases for other geo-structures and their model factor statistics are provided. Based on this extensive literature survey, a practical three-tier scheme for classifying the model uncertainty of geo-structures according to the model factor mean and COV is proposed. This empirically grounded scheme can underpin the calibration of resistance factors as a function of the degree of understanding – a concept already adopted in the Canadian Highway Bridge Design Code and being considered for the new draft for Eurocode 7 Part 1 (EN 1997-1:202x). The helical pile research in Chapter 7 was recognised by the 2020 ASCE Norman Medal.
Model Validation and Uncertainty Quantification, Vol. 3: Proceedings of the 42nd IMAC, A Conference and Exposition on Structural Dynamics 2024 (Conference Proceedings of the Society for Experimental Mechanics Series)
by Roland Platz Garrison Flynn Kyle Neal Scott OuelletteModel Validation and Uncertainty Quantification, Volume 3: Proceedings of the 42nd IMAC, A Conference and Exposition on Structural Dynamics, 2024, the third volume of ten 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 Dynamics Fusion of Test and Analysis Model Form Uncertainty: Round Robin Challenge UQVI (Uncertainty Quantification in Vibration Isolation) Recursive Bayesian System Identification Virtual Sensing & Realtime Monitoring Surrogate Modeling and Reduced Order Models
Model Validation and Uncertainty Quantification, Volume 3
by Costas Papadimitriou Babak Moaveni Sez Atamturktur Tyler SchoenherrModel Validation and Uncertainty Quantifi cation, Volume 3. Proceedings of the 34th IMAC, A Conference and Exposition on Dynamics of Multiphysical Systems: From Active Materials to Vibroacoustics, 2016, the third volume of ten from the Conference brings together contributions to this important area of research and engineering. Th e collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: * Uncertainty Quantifi cation & Model Validation * Uncertainty Propagation in Structural Dynamics * Bayesian & Markov Chain Monte Carlo Methods * Practical Applications of MVUQ * Advances in MVUQ & Model Updating * Robustness in Design & Validation * Verifi cation & Validation Methods
Model Validation and Uncertainty Quantification, Volume 3
by Costas Papadimitriou Babak Moaveni Tyler Schoenherr H. Sezer AtamturkturThis third volume of eight from the IMAC - XXXII 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 Structural Dynamics, including papers on: Linear Systems Substructure Modelling Adaptive Structures Experimental Techniques Analytical Methods Damage Detection Damping of Materials & Members Modal Parameter Identification Modal Testing Methods System Identification Active Control Modal Parameter Estimation Processing Modal Data
Model Validation and Uncertainty Quantification, Volume 3
by Costas Papadimitriou Babak Moaveni Robert Barthorpe Roland Platz Israel LopezModel Validation and Uncertainty Quantification, Volume 3: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics, 2017, the third volume of ten 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
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics 2018 (Conference Proceedings of the Society for Experimental Mechanics Series)
by Robert BarthorpeModel 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 ModelsUncertainty Propagation in Structural DynamicsPractical Applications of MVUQAdvances in Model Validation & Uncertainty Quantification: Model UpdatingModel Validation & Uncertainty Quantification: Industrial ApplicationsControlling UncertaintyUncertainty in Early Stage DesignModeling of Musical InstrumentsOverview of Model Validation and Uncertainty
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019 (Conference Proceedings of the Society for Experimental Mechanics Series)
by Robert BarthorpeModel Validation and Uncertainty Quantification, Volume 3: Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics, 2019, the third volume of eight 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: Inverse Problems and Uncertainty Quantification Controlling Uncertainty Validation of Models for Operating Environments Model Validation & Uncertainty Quantification: Decision Making Uncertainty Quantification in Structural Dynamics Uncertainty in Early Stage Design Computational and Uncertainty Quantification Tools
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics 2020 (Conference Proceedings of the Society for Experimental Mechanics Series)
by Zhu MaoModel Validation and Uncertainty Quantification, Volume 3: Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020, 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 ModelsUncertainty Propagation in Structural DynamicsPractical Applications of MVUQAdvances in Model Validation & Uncertainty Quantification: Model UpdatingModel Validation & Uncertainty Quantification: Industrial ApplicationsControlling UncertaintyUncertainty in Early Stage DesignModeling of Musical InstrumentsOverview of Model Validation and Uncertainty
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics 2021 (Conference Proceedings of the Society for Experimental Mechanics Series)
by Zhu MaoModel Validation and Uncertainty Quantification, Volume 3: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics, 2021, 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:Inverse Problems and Uncertainty QuantificationControlling UncertaintyValidation of Models for Operating EnvironmentsModel Validation & Uncertainty Quantification: Decision MakingUncertainty Quantification in Structural DynamicsUncertainty in Early Stage DesignComputational and Uncertainty Quantification Tools
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics 2022 (Conference Proceedings of the Society for Experimental Mechanics Series)
by Zhu MaoModel Validation and Uncertainty Quantification, Volume 3: Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022, 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 and Propagation in Structural DynamicsBayesian Analysis for Real-Time Monitoring and MaintenanceUncertainty in Early Stage DesignQuantification of Model-Form UncertaintiesFusion of Test and AnalysisMVUQ in Action
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023 (Conference Proceedings of the Society for Experimental Mechanics Series)
by Roland Platz Garrison Flynn Kyle Neal Scott OuelletteModel Validation and Uncertainty Quantification, Volume 3: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023, the third volume of ten 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:Introduction of Uncertainty QuantificationUncertainty Quantification in DynamicsModel Form Uncertainty and Selection incl. Round Robin ChallengeSensor and Information FusionVirtual Sensing, Certification, and Real-Time MonitoringSurrogate Modeling
Model Validation for Power System Frequency Analysis (SpringerBriefs in Energy)
by Hossein Seifi Hamed DelkhoshThis book examines the role of model validation of power system planning and operation to optimize its performance in terms of frequency control. It presents the detailed model validation for the Iranian Power Grid system, where the frequency performance was analysed and improved using existing and new standard models to identify the influencing parameters. Although the model validation was employed for a specific, practical large-scale system, the framework (concepts, methods, and formulations) can be used for by any type of power system. As such, this book describing a generalized framework for model validation with a real case study is useful for both power industry experts and academia.
Model-Based Approaches to the Internet of Things
by Pascal HirmerThis book gives an overview of existing models that cover the whole lifecycle of an IoT application, ranging from its design, implementation, deployment, operation, and monitoring to its final termination and retirement. Models provide abstraction and can help IoT application developers into creating more robust, secure, and reliable applications. Furthermore, adaptation of applications can be eased by using these models, leading to an increased dynamic of the developed IoT applications.In the book, research of the last years in the area of model based approaches to the Internet of Things is described and these approaches are incorporated into the lifecycle of IoT applications.Finally, use cases from different domains are introduced that show how these models could be applied in real-world applications.
Model-Based Control of Flying Robots for Robust Interaction Under Wind Influence (Springer Tracts in Advanced Robotics #151)
by Teodor TomićThis book addresses the topic of autonomous flying robots physically interacting with the environment under the influence of wind. It aims to make aerial robots aware of the disturbance, interaction, and faults acting on them. This requires reasoning about the external wrench (force and torque) acting on the robot and distinguishing between wind, interactions, and collisions. The book takes a model-based approach and covers a systematic approach to parameter identification for flying robots. The book aims to provide a wind speed estimate independent of the external wrench, including estimating the wind speed using motor power measurements. Aerodynamics modeling is approached in a data-driven fashion, using ground-truth measurements from a 4D wind tunnel. Finally, the book bridges the gap between trajectory tracking and interaction control, to allow physical interaction under wind influence. Theoretical results are accompanied by extensive simulation and experimental results.
Model-Based Design for Embedded Systems (Computational Analysis, Synthesis, and Design of Dynamic Systems)
by Gabriela Nicolescu Pieter J. MostermanThe demands of increasingly complex embedded systems and associated performance computations have resulted in the development of heterogeneous computing architectures that often integrate several types of processors, analog and digital electronic components, and mechanical and optical components—all on a single chip. As a result, now the most prominent challenge for the design automation community is to efficiently plan for such heterogeneity and to fully exploit its capabilities.A compilation of work from internationally renowned authors, Model-Based Design for Embedded Systems elaborates on related practices and addresses the main facets of heterogeneous model-based design for embedded systems, including the current state of the art, important challenges, and the latest trends. Focusing on computational models as the core design artifact, this book presents the cutting-edge results that have helped establish model-based design and continue to expand its parameters.The book is organized into three sections: Real-Time and Performance Analysis in Heterogeneous Embedded Systems, Design Tools and Methodology for Multiprocessor System-on-Chip, and Design Tools and Methodology for Multidomain Embedded Systems. The respective contributors share their considerable expertise on the automation of design refinement and how to relate properties throughout this refinement while enabling analytic and synthetic qualities. They focus on multi-core methodological issues, real-time analysis, and modeling and validation, taking into account how optical, electronic, and mechanical components often interface. Model-based design is emerging as a solution to bridge the gap between the availability of computational capabilities and our inability to make full use of them yet. This approach enables teams to start the design process using a high-level model that is gradually refined through abstraction levels to ultimately yield a prototype. When executed well, model-based design encourages enhanced performance and quicker time to market for a product. Illustrating a broad and diverse spectrum of applications such as in the automotive aerospace, health care, consumer electronics, this volume provides designers with practical, readily adaptable modeling solutions for their own practice.
Model-Based Design of Adaptive Embedded Systems
by Roelof Hamberg Jacques Verriet Twan Basten Frans ReckersThis book describes model-based development of adaptive embedded systems, which enable improved functionality using the same resources. The techniques presented facilitate design from a higher level of abstraction, focusing on the problem domain rather than on the solution domain, thereby increasing development efficiency. Models are used to capture system specifications and to implement (manually or automatically) system functionality. The authors demonstrate the real impact of adaptivity on engineering of embedded systems by providing several industrial examples of the models used in the development of adaptive embedded systems.
Model-Based Enterprise: Achieving Lasting Value with MBD and MBE
by Bryan R. FischerModel-Based Enterprise describes Model-Based Enterprise (MBE) and Model-Based Definition (MBD) in detail, focusing on how to obtain significant business value from MBE.This book presents MBE from technical and business perspectives, focusing on process improvement, productivity, quality, and obtaining greater value from our information and how we work. The evolution of MBD and MBE, from computer-aided design (CAD) topics to current approaches and to their future roles, is discussed. Following the progression from manual drawings to 2D CAD, 3D CAD, and to digital data and digital information models, MBE is presented as the method to achieve productivity and profitability by understanding the cost of how we work and refining our approaches to creating and using information. Many MBD and MBE implementations have changed how we work but yield little real business value – processes changed, engineering drawings were replaced with 3D models, but the organization achieved minor benefits from their efforts. This book provides methods to become an MBE and achieve the full value possible from digital transformation.Model-Based Enterprise is essential reading for anyone who creates or uses product-related information in original equipment manufacturers (OEMs) and suppliers, in the private sector, and in government procurement and development activities. This book is also essential for students in all engineering disciplines, manufacturing, quality, information management, product lifecycle management (PLM), and related business disciplines.
Model-Based Fault Diagnosis Techniques
by Steven X. DingGuaranteeing a high system performance over a wide operating range is an important issue surrounding the design of automatic control systems with successively increasing complexity. As a key technology in the search for a solution, advanced fault detection and identification (FDI) is receiving considerable attention. This book introduces basic model-based FDI schemes, advanced analysis and design algorithms, and mathematical and control-theoretic tools. This second edition of Model-Based Fault Diagnosis Techniques contains: * new material on fault isolation and identification and alarm management; * extended and revised treatment of systematic threshold determination for systems with both deterministic unknown inputs and stochastic noises; * addition of the continuously-stirred tank heater as a representative process-industrial benchmark; and * enhanced discussion of residual evaluation which now deals with stochastic processes. Model-based Fault Diagnosis Techniques will interest academic researchers working in fault identification and diagnosis and as a text it is suitable for graduate students in a formal university-based course or as a self-study aid for practising engineers working with automatic control or mechatronic systems from backgrounds as diverse as chemical process and power engineering.
Model-Based Optimization for Petroleum Refinery Configuration Design
by Cheng Seong KhorModel-Based Optimization for Petroleum Refinery Configuration Design An accessible, easy-to-read introduction to the methods of mixed-integer optimization, with practical applications, real-world operational data, and case studies Interest in model-based approaches for optimizing the design of petroleum refineries has increased throughout the industry in recent years. Mathematical optimization based on mixed-integer programming has brought about the superstructure optimization method for synthesizing petroleum refinery configurations from multiple topological alternatives. Model-Based Optimization for Petroleum Refinery Configuration Design presents a detailed introduction to the use of mathematical optimization to solve both linear and nonlinear problems in the refining industry. The book opens with an overview of petroleum refining processes, basic concepts in mathematical programming, and applications of mathematical programming for refinery optimization. Subsequent chapters address superstructure representations of topological alternatives, mathematical formulation, solution strategies, and various modeling frameworks. Practical case studies demonstrate refinery configuration design, refinery retrofitting, and real-world issues and considerations. Presents linear, nonlinear, and mixed-integer programming approaches applicable to both new and existing petroleum refineriesHighlights the benefits of model-based solutions to refinery configuration design problemsFeatures detailed case studies of the development and implementation of optimization modelsDiscusses economic considerations of heavy oil processing, including cash flow analysis of refinery costs and return on capitalIncludes numerical examples based on real-world operational data and various commercial technologies Model-Based Optimization for Petroleum Refinery Configuration Design is an invaluable resource for researchers, chemical engineers, process and energy engineers, other refining professionals, and advanced chemical engineering students.
Model-Based Predictive Control: A Practical Approach (Control Series)
by J. A. RossiterModel Predictive Control (MPC) has become a widely used methodology across all engineering disciplines, yet there are few books which study this approach. Until now, no book has addressed in detail all key issues in the field including apriori stability and robust stability results. Engineers and MPC researchers now have a volume that provides a complete overview of the theory and practice of MPC as it relates to process and control engineering.Model-Based Predictive Control, A Practical Approach, analyzes predictive control from its base mathematical foundation, but delivers the subject matter in a readable, intuitive style. The author writes in layman's terms, avoiding jargon and using a style that relies upon personal insight into practical applications.This detailed introduction to predictive control introduces basic MPC concepts and demonstrates how they are applied in the design and control of systems, experiments, and industrial processes. The text outlines how to model, provide robustness, handle constraints, ensure feasibility, and guarantee stability. It also details options in regard to algorithms, models, and complexity vs. performance issues.
Model-Based Processing for Underwater Acoustic Arrays
by Edmund J. SullivanThis monograph presents a unified approach to model-based processing for underwater acoustic arrays. The use of physical models in passive array processing is not a new idea, but it has been used on a case-by-case basis, and as such, lacks any unifying structure. This work views all such processing methods as estimation procedures, which then can be unified by treating them all as a form of joint estimation based on a Kalman-type recursive processor, which can be recursive either in space or time, depending on the application. This is done for three reasons. First, the Kalman filter provides a natural framework for the inclusion of physical models in a processing scheme. Second, it allows poorly known model parameters to be jointly estimated along with the quantities of interest. This is important, since in certain areas of array processing already in use, such as those based on matched-field processing, the so-called mismatch problem either degrades performance or, indeed, prevents any solution at all. Thirdly, such a unification provides a formal means of quantifying the performance improvement. The term model-based will be strictly defined as the use of physics-based models as a means of introducing a priori information. This leads naturally to viewing the method as a Bayesian processor. Short expositions of estimation theory and acoustic array theory are presented, followed by a presentation of the Kalman filter in its recursive estimator form. Examples of applications to localization, bearing estimation, range estimation and model parameter estimation are provided along with experimental results verifying the method. The book is sufficiently self-contained to serve as a guide for the application of model-based array processing for the practicing engineer.
Model-Based Processing: An Applied Subspace Identification Approach (Adaptive And Cognitive Dynamic Systems: Signal Processing, Learning, Communications And Control Ser. #36)
by James V. CandyA bridge between the application of subspace-based methods for parameter estimation in signal processing and subspace-based system identification in control systems Model-Based Processing: An Applied Subspace Identification Approach provides expert insight on developing models for designing model-based signal processors (MBSP) employing subspace identification techniques to achieve model-based identification (MBID) and enables readers to evaluate overall performance using validation and statistical analysis methods. Focusing on subspace approaches to system identification problems, this book teaches readers to identify models quickly and incorporate them into various processing problems including state estimation, tracking, detection, classification, controls, communications, and other applications that require reliable models that can be adapted to dynamic environments. The extraction of a model from data is vital to numerous applications, from the detection of submarines to determining the epicenter of an earthquake to controlling an autonomous vehicles—all requiring a fundamental understanding of their underlying processes and measurement instrumentation. Emphasizing real-world solutions to a variety of model development problems, this text demonstrates how model-based subspace identification system identification enables the extraction of a model from measured data sequences from simple time series polynomials to complex constructs of parametrically adaptive, nonlinear distributed systems. In addition, this resource features: Kalman filtering for linear, linearized, and nonlinear systems; modern unscented Kalman filters; as well as Bayesian particle filters Practical processor designs including comprehensive methods of performance analysis Provides a link between model development and practical applications in model-based signal processing Offers in-depth examination of the subspace approach that applies subspace algorithms to synthesized examples and actual applications Enables readers to bridge the gap from statistical signal processing to subspace identification Includes appendices, problem sets, case studies, examples, and notes for MATLAB Model-Based Processing: An Applied Subspace Identification Approach is essential reading for advanced undergraduate and graduate students of engineering and science as well as engineers working in industry and academia.