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Previous article Blending-Function Methods of Bivariate and Multivariate Interpolation and ApproximationWilliam J. GordonWilliam J. Gordonhttps://doi.org/10.1137/0708019PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] J. H. Ahlberg, , E. N. Nilson and , J. L. Walsh, The theory of splines and their applications, Academic Press, New York, 1967xi+284 MR0239327 0158.15901 Google Scholar[2] A. C. Ahlin, A bivariate generalization of Hermite's interpolation formula, Math. Comp., 18 (1964), 264–273 MR0164428 0122.12501 CrossrefISIGoogle Scholar[3] R. E. Barnhill, , W. J. Gordon and , D. H. Thomas, Decomposition methods for the approximate integration of multivariate functions, Res. Rep., General Motors, Warren, Mich., in preparation Google Scholar[4] Garrett Birkhoff and , Carl R. De Boor, H. L. Garabedian, Piecewise polynomial interpolation and approximation, Approximation of Functions (Proc. Sympos. General Motors Res. Lab., 1964 ), Elsevier Publ. 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Previous article Next article Convergence Conditions for Ascent MethodsPhilip WolfePhilip Wolfehttps://doi.org/10.1137/1011036PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstractLiberal conditions on the steps of a “descent” method for finding extrema of a function are given; most known results are special cases.[1] Haskell B. Curry, The method of steepest descent for non-linear minimization problems, Quart. Appl. Math., 2 (1944), 258–261 MR0010667 0061.26801 CrossrefGoogle Scholar[2] Augustine Cauchy, Méthode générale pour la résolution des systèmes d'équations simultanées, C.R. Acad. Sci., 25 (1847), 536–538 Google Scholar[3] A. A. Goldstein, Minimizing functionals on normed-linear spaces, SIAM J. Control, 4 (1966), 81–89 10.1137/0304008 MR0196900 0147.12701 LinkGoogle Scholar[4] A. A. Goldstein, Cauchy's method of minimization, Numer. 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Previous article Next article On the Construction and Comparison of Difference SchemesGilbert StrangGilbert Stranghttps://doi.org/10.1137/0705041PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] J. Barkley Rosser, A Runge-Kutta for all seasons, SIAM Rev., 9 (1967), 417–452 10.1137/1009069 MR0219242 0243.65041 LinkISIGoogle Scholar[2] Robert D. Richtmyer and , K. W. Morton, Difference methods for initial-value problems, Second edition. Interscience Tracts in Pure and Applied Mathematics, No. 4, Interscience Publishers John Wiley & Sons, Inc., New York-London-Sydney, 1967xiv+405 MR0220455 0155.47502 Google Scholar[3] Peter D. Lax and , Burton Wendroff, Difference schemes for hyperbolic equations with high order of accuracy, Comm. Pure Appl. Math., 17 (1964), 381–398 MR0170484 0233.65050 CrossrefISIGoogle Scholar[4] Samuel Z. 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Previous article Next article Fractional Brownian Motions, Fractional Noises and ApplicationsBenoit B. Mandelbrot and John W. Van NessBenoit B. Mandelbrot and John W. Van Nesshttps://doi.org/10.1137/1010093PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] I. Adelman, Long cycles—fact or artifact?, Amer. Economic Rev., 60 (1965), 444–463 Google Scholar[2] William Feller, The asymptotic distribution of the range of sums of independent random variables, Ann. Math. Statistics, 22 (1951), 427–432 MR0042626 0043.34201 CrossrefISIGoogle Scholar[3] I. M. Gel'fand and , N. Ya. Vilenkin, Generalized functions. Vol. 4, Academic Press [Harcourt Brace Jovanovich Publishers], New York, 1964 [1977]xiv+384 MR0435834 Google Scholar[4] C. W. J. Granger, The typical spectral shape of an economic variable, Econometrica, 34 (1966), 150–161 CrossrefISIGoogle Scholar[5] G. A. Hunt, Random Fourier transforms, Trans. Amer. Math. 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2022 IEEE International Conference on and Signal | 23 May 2022 Cross Ref estimation for the model driven by the complex fractional Brownian Vol. No. 4 | 28 July 2021 Cross Ref Anomalous diffusion and memory in Computational Biology, Vol. 18, No. 5 | 18 May 2022 Cross Ref OF OF A | 13 May 2022 Cross Ref On the of Vol. 10, No. 9 | 22 April 2022 Cross Ref Convergence of for for with of Computing, Vol. No. 2 | 21 March 2022 Cross Ref Entropy of in a Review E, Vol. No. 5 | 2 May 2022 Cross Ref Analysis of during 26 August Vol. 24, No. 5 | 14 May 2022 Cross Ref stability of stochastic A and Dynamics, Vol. 22, No. | 18 April 2022 Cross Ref behavior in a model with A, Vol. | 1 May 2022 Cross Ref Asymptotic for driven by fractional Brownian motion in the of Mathematical Analysis and Applications, Vol. No. 1 | 1 May 2022 Cross Ref Generalized and rough Ornstein–Uhlenbeck Vol. | 30 April 2022 Cross Ref The the distribution of processes for the estimation of the Sciences Journal, Vol. No. 6 | 12 April 2022 Cross Ref and Application of Some Fractional Driven by Fractional Economics, Vol. 2 | April 2022 Cross Ref for processes and to Vol. No. 4 | 1 March 2022 Cross Ref Stochastic with to fractional processes in of Analysis, Vol. No. 8 | 1 2022 Cross Ref of and in Hurst exponents from spectral analysis of atomic force microscopy topographic Science, Vol. | 1 2022 Cross Ref in Distribution to Stochastic Driven by a Fractional Brownian Journal of Mathematics, Vol. No. 2 | 21 2022 Cross Ref a Under Random and Stochastic and Transactions on Science and Engineering, Vol. No. 2 | 1 2022 Cross Ref A new fractional based on nonlinear structure to systems with and of and Vol. No. | 30 January 2021 Cross Ref and The Transactions on and Systems, Vol. No. 2 | 1 2022 Cross Ref Analysis on with of and Fractional, Vol. 6, No. 4 | 14 April 2022 Cross Ref The of the Fractional and Fractional, Vol. 6, No. 4 | 15 April 2022 Cross Ref A and for complex Review E, Vol. No. 4 | 18 April 2022 Cross Ref of under in Review E, Vol. No. 4 | April 2022 Cross Ref theory of of an Review A, Vol. No. 4 | 26 April 2022 Cross Ref method for model in fractal Solitons & Fractals, Vol. | 1 2022 Cross Ref Time fractional equation with a based fractional Solitons & Fractals, Vol. | 1 2022 Cross Ref stochastic and of with complex in Applied Mechanics and Engineering, Vol. | 1 2022 Cross Ref OF Journal, Vol. No. 2 | 18 August 2022 Cross Ref The of of Fractional by in Vol. 2 | 24 March 2022 Cross Ref Bayesian of scaled fractional Brownian motionJournal of Physics A: Mathematical and | 24 March 2022 Cross Ref Anomalous diffusion: fractional Brownian motion fractional motionJournal of Physics A: Mathematical and Theoretical, Vol. 55, No. 11 | 23 2022 Cross Ref process with noise as a anomalous diffusion of Physics A: Mathematical and | 8 March 2022 Cross Ref by and Analysis and Vol. | 4 March 2022 Cross Ref Stochastic for the stochastic differential equations with & Probability Letters, Vol. | 1 Mar 2022 Cross Ref Multivariate range A: Statistical Mechanics and its Applications, Vol. | 1 Mar 2022 Cross Ref the memory for and time with Vol. No. 3 | 31 January 2022 Cross Ref for the Fractional Ornstein–Uhlenbeck of Vol. No. 1 | 22 October 2020 Cross Ref Properties of a Generalized Fractional Brownian of Vol. No. 1 | 9 January 2021 Cross Ref The for Time of Stochastic Vol. 10, No. 3 | 23 2022 Cross Ref A for Long in Higher Vol. 10, No. 5 | 24 2022 Cross Ref The of time Journal of Statistics, Vol. No. 1 | 14 August 2021 Cross Ref Estimation on of time generalized Dynamics, Vol. No. 4 | 12 January 2022 Cross Ref of the in the of fields by the of the Vol. | 1 Mar 2022 Cross Ref Statistical of nonlinear time and application to Review Research, Vol. 4, No. 1 | 17 March 2022 Cross Ref Price Modeling of under for Vol. 13, No. 3 | 18 March 2022 Cross Ref and in Advances of Physical Sciences, Vol. 06 | 27 April 2022 Cross Ref of of under fractional Brownian motionStatistics & Probability Letters, Vol. | 1 Mar 2022 Cross Ref Fractional and Statistical An of the Indian of Science, Vol. 29 | 24 2022 Cross Ref diffusion with stochastic of Physics A: Mathematical and Theoretical, Vol. 55, No. 7 | 28 January 2022 Cross Ref On the fractional stochastic for random Analysis and Applications, Vol. | 2 2022 Cross Ref of and Systems to
A Complete Reference Covering the Latest Technology in Metal Cutting Tools, Processes, and Equipment Metal Cutting Theory and Practice, Third Edition shapes the future of material removal in new and lasting ways. Centered on metallic work materials and traditional chip-forming cutting methods, the book provides a physical understanding of conventional and high-speed machining processes applied to metallic work pieces, and serves as a basis for effective process design and troubleshooting. This latest edition of a well-known reference highlights recent developments, covers the latest research results, and reflects current areas of emphasis in industrial practice. Based on the authors’ extensive automotive production experience, it covers several structural changes, and includes an extensive review of computer aided engineering (CAE) methods for process analysis and design. Providing updated material throughout, it offers insight and understanding to engineers looking to design, operate, troubleshoot, and improve high quality, cost effective metal cutting operations. The book contains extensive up-to-date references to both scientific and trade literature, and provides a description of error mapping and compensation strategies for CNC machines based on recently issued international standards, and includes chapters on cutting fluids and gear machining. The authors also offer updated information on tooling grades and practices for machining compacted graphite iron, nickel alloys, and other hard-to-machine materials, as well as a full description of minimum quantity lubrication systems, tooling, and processing practices. In addition, updated topics include machine tool types and structures, cutting tool materials and coatings, cutting mechanics and temperatures, process simulation and analysis, and tool wear from both chemical and mechanical viewpoints. Comprised of 17 chapters, this detailed study: Describes the common machining operations used to produce specific shapes or surface characteristics Contains conventional and advanced cutting tool technologies Explains the properties and characteristics of tools which influence tool design or selection Clarifies the physical mechanisms which lead to tool failure and identifies general strategies for reducing failure rates and increasing tool life Includes common machinability criteria, tests, and indices Breaks down the economics of machining operations Offers an overview of the engineering aspects of MQL machining Summarizes gear machining and finishing methods for common gear types, and more Metal Cutting Theory and Practice, Third Edition emphasizes the physical understanding and analysis for robust process design, troubleshooting, and improvement, and aids manufacturing engineering professionals, and engineering students in manufacturing engineering and machining processes programs.
1R1. Boundary Element Programming in Mechanics. - Xiao-Wei Gao (Dept of Mech and Aerospace Eng, Arizona State Univ, Tempe AZ) and TG Davies (Glasgow Univ, UK). Cambridge UP, Cambridge, UK. 2002. 254 pp. (CD-Rom included). ISBN 0-521-77359-8. $69.95. Reviewed by DE Beskos (Dept of Civil Eng, Univ of Patras, Patras, GR-26500, Greece).This is a really excellent textbook as well as a reference book on the numerical implementation and computer programing of the direct boundary element method as applied to two and three-dimensional problems of linear elasticity and nonlinear elastoplasticity. The book is aimed at both graduate students and researchers as well as practicing engineers in mechanical, aeronautical, and civil engineering fields. The book consists of 254 pages plus a CD-Rom with the computer programs described. The whole book can be divided in two main components: The first one dealing with linear problems (elasticity) and the second one with nonlinear problems (time independent elastostoplasticity). In both parts, the chapter breakdown is the same and consists of the theory (of elasticity or plasticity), the corresponding boundary integral formulation of the problem, the numerical implementation, the detailed (subroutine by subroutine) description of the computer program and a number of applications—numerical examples to illustrate the code and demonstrate its accuracy. The book is completed by an introduction and an epilogue, eight appendices, a list of references, and a subject index. The figures and tables are of very good quality. The list of references is comprehensive, but selective, and the subject index is informative, but somewhat short. The unusual features of this book, in order of importance, are the following: the book is very clearly written and the English language is not just correct and easy to understand, but lively and enjoyable. The authors have proved they are not just very good on technical matters, but they also know to handle the English language superbly. The various computational aspects of the boundary element method, such as singular integration, treatment of edges and corners, computation of boundary stresses, solution of systems of linear equations, return mapping algorithms in plasticity, etc, are all treated in detail. In particular, the authors in every case, first discuss the problem, mention the work of others, and then offer their solution which they consider to be the most effective. The computer programs are explained in detail on a subroutine-by-subroutine basis and serve to illustrate the implementation of the method in the best possible way. In addition, they can be modified by the user, if he wishes to add or replace things. There is an emphasis on three-dimensional problems both in elasticity and plasticity, which cannot be found in other books on the subject. The book succeeds completely relative to the author’s stated aims and the subject matter. As a matter of fact, the book can be the ideal vehicle to teach the boundary element method to engineers who want the theory to go hand-in-hand with the numerical implementation and are not so much interested in mathematical details. Thus, the book can be used either as an ideal introductory text on boundary elements, in general, or as a specialized book on boundary element methods in plasticity. There are many introductory books available on boundary elements, but most of them deal with potential theory and elasticity, and they do not emphasize either the numerical implementation of the method nor 3D problems. This reviewer predicts that this book will prove to be, for boundary element programing, what has been the case with the two texts by Hinton and Owen on finite elements. The only slightly negative about this book has to do with the title, which employs the general and misleading term mechanics instead of the more appropriate term solid mechanics, which would more exactly reflect the contents of the book. Boundary Element Programming in Mechanics is highly recommended for purchase by both individuals and libraries.
Nonlinear continuum mechanics of solids is a fascinating subject. All the assumptions inherited from an overexposure to linear behaviour and analysis must be re-examined. The standard definitions of strain designed for small deformation linear problems may be totally misleading when finite motion or large deformations are considered. Nonlinear behaviour includes phenomena like `snap-through', where bifurcation theory is applied to engineering design. Capabilities in this field are growing at a fantastic speed; for example, modern automobiles are presently being designed to crumple in the most energy absorbing manner in order to protect the occupants. The combination of nonlinear mechanics and the finite element method is a very important field. Most engineering designs encountered in the fusion effort are strictly limited to small deformation linear theory. In fact, fusion devices are usually kept in the low stress, long life regime that avoids large deformations, nonlinearity and any plastic behaviour. The only aspect of nonlinear continuum solid mechanics about which the fusion community now worries is that rare case where details of the metal forming process must be considered. This text is divided into nine sections: introduction, mathematical preliminaries, kinematics, stress and equilibrium, hyperelasticity, linearized equilibrium equations, discretization and solution, computer implementation and an appendix covering an introduction to large inelastic deformations. The authors have decided to use vector and tensor notation almost exclusively. This means that the usual maze of indicial equations is avoided, but most readers will therefore be stretched considerably to follow the presentation, which quickly proceeds to the heart of nonlinear behaviour in solids. With great speed the reader is led through the material (Lagrangian) and spatial (Eulerian) co-ordinates, the deformation gradient tensor (an example of a two point tensor), the right and left Cauchy-Green tensors, the Eulerian or Almansi strain tensor, distortional components, strain rate tensors, rate of deformation tensors, spin tensors and objectivity. The standard Cauchy stress tensor is mentioned in passing, and then virtual work and work conjugacy lead to alternative stress representations such as the Piola-Kirchoff representation. Chapter 5 concentrates on hyperelasticity (where stresses are derived from a stored energy function) and its subvarieties. Chapter 6 proceeds by linearizing the virtual work statement prior to discretization and Chapter 7 deals with approaches to solving the formulation. In Chapter 8 the FORTRAN finite element code written by Bonet (available via the world wide web) is described. In summary this book is written by experts, for future experts, and provides a very fast review of the field for people who already know the topic. The authors assume the reader is familiar with `elementary stress analysis' and has had some exposure to `the principle of the finite element method'. Their goals are summarized by the statement, `If the reader is prepared not to get too hung up on details, it is possible to use the book to obtain a reasonable overview of the subject'. This is a very nice summary of what is going on in the field but as a stand-alone text it is much too terse. The total bibliography is a page and a half. It would be an improvement if there were that much reference material for each chapter.
This book is the first on the topic and explains the most cutting-edge methods needed for precise calculations and explores the development of powerful algorithms to solve research problems. Multipoint methods have an extensive range of practical applications significant in research areas such as signal processing, analysis of convergence rate, fluid mechanics, solid state physics, and many others. The book takes an introductory approach in making qualitative comparisons of different multipoint methods from various viewpoints to help the reader understand applications of more complex methods. Evaluations are made to determine and predict efficiency and accuracy of presented models useful to wide a range of research areas along with many numerical examples for a deep understanding of the usefulness of each method. This book will make it possible for the researchers to tackle difficult problems and deepen their understanding of problem solving using numerical methods. Multipoint methods are of great practical importance, as they determine sequences of successive approximations for evaluative purposes. This is especially helpful in achieving the highest computational efficiency. The rapid development of digital computers and advanced computer arithmetic have provided a need for new methods useful to solving practical problems in a multitude of disciplines such as applied mathematics, computer science, engineering, physics, financial mathematics, and biology. Provides a succinct way of implementing a wide range of useful and important numerical algorithms for solving research problems Illustrates how numerical methods can be used to study problems which have applications in engineering and sciences, including signal processing, and control theory, and financial computation Facilitates a deeper insight into the development of methods, numerical analysis of convergence rate, and very detailed analysis of computational efficiencyProvides a powerful means of learning by systematic experimentation with some of the many fascinating problems in scienceIncludes highly efficient algorithms convenient for the implementation into the most common computer algebra systems such as Mathematica, MatLab, and Maple
Abstract This paper presents a new linear tetrahedral element that overcomes the shortcomings in bending dominated problems of the average nodal pressure element presented in Bonet and Burton ( Communications in Numerical Methods in Engineering 1998; 14 :437–439) Zienkiewicz et al. ( Internatinal Journal for Numerical Methods in Engineering 1998; 43 :565–583) and Bonet et al. ( Internatinal Journal for Numerical Methods in Engineering 2001; 50 (1):119–133). This is achieved by extending some of the ideas proposed by Dohrmann et al. ( Internatinal Journal for Numerical Methods in Engineering 2000; 47 :1549–1568) to the large strain nonlinear kinematics regime. In essence, a nodal deformation gradient is defined by weighted average of the surrounding element values. The associated stresses and internal forces are then derived by differentiation of the corresponding simplified strain energy term. The resulting element is intended for use in explicit dynamic codes (Goudreau and Hallquist, Computer Methods in Applied Mechanics and Engineering 1982; 33 ) where the use of quadratic tetrahedral elements can present significant difficulties. Copyright © 2001 John Wiley & Sons, Ltd.
Abstract Although there is a consensus on the instructional potential of S erious G ames ( SG s), there is still a lack of methodologies and tools not only for design but also to support analysis and assessment. Filling this gap is one of the main aims of the G ames and L earning A lliance ( http://www.galanoe.eu ) E uropean N etwork of E xcellence on S erious G ames, which has a focus upon pedagogy‐driven SG s . This paper relies on the assumption that the fundamental aspect of SG design consists in the translation of learning goals/practices into mechanical element of gameplay, serving to an instructional purpose beside that of play and fun. This paper proposes the L earning M echanics– G ame M echanics ( LM‐GM ) model, which supports SG analysis and design by allowing reflection on the various pedagogical and game elements in an SG . The LM‐GM model includes a set of pre‐defined game mechanics and pedagogical elements that we have abstracted from literature on game studies and learning theories. Designers and analysts can exploit these mechanics to draw the LM‐GM map for a game, so as to identify and highlight its main pedagogical and entertainment features, and their interrelations. The tool may also be useful for teachers to evaluate the effectiveness of a given game and better understand how to implement it in educational settings. A case study is reported to illustrate the framework's support in determining how gameplay and pedagogy intertwine in an SG . Finally, the paper presents the results of two comparative user tests demonstrating the advantages of the proposed model with respect to a similar state‐of‐the‐art framework.
Mechanical Engineering Design, Third Edition strikes a balance between theory and application, and prepares students for more advanced study or professional practice. Updated throughout, it outlines basic concepts and provides the necessary theory to gain insight into mechanics with numerical methods in design. Divided into three sections, the text presents background topics, addresses failure prevention across a variety of machine elements, and covers the design of machine components as well as entire machines. Optional sections treating special and advanced topics are also included. Features: Places a strong emphasis on the fundamentals of mechanics of materials as they relate to the study of mechanical design Furnishes material selection charts and tables as an aid for specific uses Includes numerous practical case studies of various components and machines Covers applied finite element analysis in design, offering this useful tool for computer-oriented examples Addresses the ABET design criteria in a systematic manner Presents independent chapters that can be studied in any order Introduces optional MATLAB® solutions tied to the book and student learning resources Mechanical Engineering Design, Third Edition allows students to gain a grasp of the fundamentals of machine design and the ability to apply these fundamentals to various new engineering problems.
The Journal of Engineering Mechanics covers activity and development in the field of applied mechanics as it relates to civil engineering. Research on bioengineering, computational mechanics, computer-aided engineering, dynamics of structures, elasticity, experimental analysis and instrumentation, fluid mechanics, flow of granular media, inelastic behavior of solids and structures, probabilistic methods, properties of materials, fracture mechanics, stability of structural elements and systems, and turbulence is reported. Typically, published papers describe the development and implementation of new analytical models, innovative numerical methods, and novel experimental methods and results.
Soon after the discovery of carbon nanotubes, it was realized that the theoretically predicted mechanical properties of these interesting structures–including high strength, high stiffness, low density and structural perfection–could make them ideal for a wealth of technological applications. The experimental verification, and in some cases refutation, of these predictions, along with a number of computer simulation methods applied to their modeling, has led over the past decade to an improved but by no means complete understanding of the mechanics of carbon nanotubes. We review the theoretical predictions and discuss the experimental techniques that are most often used for the challenging tasks of visualizing and manipulating these tiny structures. We also outline the computational approaches that have been taken, including ab initio quantum mechanical simulations, classical molecular dynamics, and continuum models. The development of multiscale and multiphysics models and simulation tools naturally arises as a result of the link between basic scientific research and engineering application; while this issue is still under intensive study, we present here some of the approaches to this topic. Our concentration throughout is on the exploration of mechanical properties such as Young’s modulus, bending stiffness, buckling criteria, and tensile and compressive strengths. Finally, we discuss several examples of exciting applications that take advantage of these properties, including nanoropes, filled nanotubes, nanoelectromechanical systems, nanosensors, and nanotube-reinforced polymers. This review article cites 349 references.
Abstract Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves 1 and in the first imaging of a black hole 2 . Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.
The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatiotemporal scales. Machine learning (ML) offers a wealth of techniques to extract information from data that can be translated into knowledge about the underlying fluid mechanics. Moreover, ML algorithms can augment domain knowledge and automate tasks related to flow control and optimization. This article presents an overview of past history, current developments, and emerging opportunities of ML for fluid mechanics. We outline fundamental ML methodologies and discuss their uses for understanding, modeling, optimizing, and controlling fluid flows. The strengths and limitations of these methods are addressed from the perspective of scientific inquiry that considers data as an inherent part of modeling, experiments, and simulations. ML provides a powerful information-processing framework that can augment, and possibly even transform, current lines of fluid mechanics research and industrial applications.
Core Ideas Review of selected capabilities of HYDRUS implemented since 2008 New standard and nonstandard specialized add‐on modules significantly expanded capabilities of the software Review of selected applications of the HYDRUS models published in VZJ and elsewhere in recent years The HYDRUS‐1D and HYDRUS (2D/3D) computer software packages are widely used finite‐element models for simulating the one‐ and two‐ or three‐dimensional movement of water, heat, and multiple solutes in variably saturated media, respectively. In 2008, Šimůnek et al. (2008b) described the entire history of the development of the various HYDRUS programs and related models and tools such as STANMOD, RETC, ROSETTA, UNSODA, UNSATCHEM, HP1, and others. The objective of this manuscript is to review selected capabilities of HYDRUS that have been implemented since 2008. Our review is not limited to listing additional processes that were implemented in the standard computational modules, but also describes many new standard and nonstandard specialized add‐on modules that significantly expanded the capabilities of the two software packages. We also review additional capabilities that have been incorporated into the graphical user interface (GUI) that supports the use of HYDRUS (2D/3D). Another objective of this manuscript is to review selected applications of the HYDRUS models such as evaluation of various irrigation schemes, evaluation of the effects of plant water uptake on groundwater recharge, assessing the transport of particle‐like substances in the subsurface, and using the models in conjunction with various geophysical methods.
This is a textbook written for mechanical engineering students at first-year graduate level. As such, it emphasizes the development of finite element methods used in applied mechanics. The book starts with fundamental formulations of heat conduction and linear elasticity and derives the weak form (i.e. the principle of virtual work in elasticity) from a boundary value problem that represents the mechanical behaviour of solids and fluids. Finite element approximations are then derived from this weak form. The book contains many useful exercises and the author appropriately provides the student with computer programs in both BASIC and FORTRAN for solving them. Furthermore, a workbook is available with additional computer listings, and also an accompanying disc that contains the BASIC programs for use on IBM-PC microcomputers and their compatibles. Thus the usefulness and versatility of this text is enhanced by the student's ability to practise problem solving on accessible microcomputers.
201-F6, was shown to exhibit the rare ability to grow on PET as a major carbon and energy source. Central to its PET biodegradation capability is a secreted PETase (PET-digesting enzyme). Here, we present a 0.92 Å resolution X-ray crystal structure of PETase, which reveals features common to both cutinases and lipases. PETase retains the ancestral α/β-hydrolase fold but exhibits a more open active-site cleft than homologous cutinases. By narrowing the binding cleft via mutation of two active-site residues to conserved amino acids in cutinases, we surprisingly observe improved PET degradation, suggesting that PETase is not fully optimized for crystalline PET degradation, despite presumably evolving in a PET-rich environment. Additionally, we show that PETase degrades another semiaromatic polyester, polyethylene-2,5-furandicarboxylate (PEF), which is an emerging, bioderived PET replacement with improved barrier properties. In contrast, PETase does not degrade aliphatic polyesters, suggesting that it is generally an aromatic polyesterase. These findings suggest that additional protein engineering to increase PETase performance is realistic and highlight the need for further developments of structure/activity relationships for biodegradation of synthetic polyesters.
SUMMARY A computational homogenization procedure for cohesive and adhesive crack modeling of materials with a heterogeneous microstructure has been recently presented in Computer Methods in Applied Mechanics and Engineering (2010, DOI: 10.1016/j.cma.2010.10.013 ). The macroscopic material properties of the cohesive cracks are obtained from the inelastic deformation manifested in a localization band (modeled with a continuum damage theory) at the microscopic scale. The macroscopic behavior of the adhesive crack is derived from the response of a microscale sample representing the microstructure inside the adhesive crack. In this manuscript, we extend the theory presented in Computer Methods in Applied Mechanics and Engineering (2010, DOI: 10.1016/j.cma.2010.10.013 ) with implementation details, solutions for cyclic loading, crack propagation, numerical analysis of the convergence characteristics of the multiscale method, and treatment of macroscopic snapback in a multiscale simulation. Numerical examples including crack growth simulations with extended finite elements are given to demonstrate the performance of the method. Copyright © 2011 John Wiley & Sons, Ltd.