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Tsunami Science and Engineering II

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ISBN: 9783039216727 / 9783039216734 Year: Pages: 194 DOI: 10.3390/books978-3-03921-673-4 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:16
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Earthquake-tsunamis, including the 2004 Indian Ocean Tsunami and the 2011 T?hoku Tsunami in Japan, serve as tragic reminders that such waves pose a major natural hazard. Landslide-tsunamis, including the 1958 Lituya Bay case, may exceed 150 m in height, and similar waves generated in lakes and reservoirs may overtop dams and cause significant devastation. This book includes nine peer-review articles from some of the leading experts in the field of tsunami research. The collection represents a wide range of topics covering (i) wave generation, (ii) wave propagation, and (iii) their effects. Within (i), a tsunami source combining an underwater fault rupture and a landslide are addressed in the laboratory. Within (ii), frequency dispersion with the nonlinear shallow-water equations is considered and a detailed account of the 1755 Lisbon earthquake, tsunami, and fire in downtown Lisbon is presented. Two articles involve all three phases (i) to (iii), including runup and dam over-topping. Within (iii), a new semi-empirical equation for runup is introduced and the interaction of tsunamis with bridges and pipelines is investigated in large laboratory experiments. This state-of-the-art collection of articles is expected to improve modelling and mitigate the destructive effects of tsunamis and inspire many future research activities in this challenging and exciting research field.

Process Modelling and Simulation

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ISBN: 9783039214556 / 9783039214563 Year: Pages: 298 DOI: 10.3390/books978-3-03921-456-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
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Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.

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process model validation --- partial least square regression --- phytochemicals --- natural extracts --- wheat germ --- fluidized bed drying --- mathematical model --- moisture content --- condensation --- simulation --- Pharmaceutical Processes --- Mammalian Cell Culture --- sensitivity analysis --- parameter estimation --- Design of Experiments --- algebraic modeling language --- dynamic optimization --- model predictive control --- moving horizon estimation --- fluid bed granulation --- heat and mass balance --- population balance model --- binder dissolution --- kernel development --- robust optimization --- uncertainty --- point estimation method --- equality constraints --- parameter correlation --- barley --- simulation --- hydration --- swelling --- cooking --- porridge --- extents --- graph theory --- model identification --- observability --- optimal clustering --- parameter estimation --- state decoupling --- data-mining --- machine learning --- neural networks --- chemistry --- materials --- engineering --- energy --- grey-box model --- machine learning --- SOS programming --- process modeling --- scrap dissolution --- scrap melting --- thermodynamics --- kinetics --- dynamic converter modelling --- Combined Heat and Power --- gray-box model --- utility management --- CHP legislation --- optimization --- polyacrylonitrile-based carbon fiber --- coagulation bath --- dry-jet wet spinning process --- computational fluid dynamics --- wave resonance --- maximum wave amplitude --- reactor coolant pump --- vane --- costing stopping --- mathematical model --- idling test --- n/a

Symmetry in Quantum Optics Models

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ISBN: 9783039218585 / 9783039218592 Year: Pages: 92 DOI: 10.3390/books978-3-03921-859-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Physics (General)
Added to DOAB on : 2019-12-09 16:39:37
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Prototypical quantum optics models, such as the Jaynes–Cummings, Rabi, Tavis–Cummings, and Dicke models, are commonly analyzed with diverse techniques, including analytical exact solutions, mean-field theory, exact diagonalization, and so on. Analysis of these systems strongly depends on their symmetries, ranging, e.g., from a U(1) group in the Jaynes–Cummings model to a Z2 symmetry in the full-fledged quantum Rabi model. In recent years, novel regimes of light–matter interactions, namely, the ultrastrong and deep-strong coupling regimes, have been attracting an increasing amount of interest. The quantum Rabi and Dicke models in these exotic regimes present new features, such as collapses and revivals of the population, bounces of photon-number wave packets, as well as the breakdown of the rotating-wave approximation. Symmetries also play an important role in these regimes and will additionally change depending on whether the few- or many-qubit systems considered have associated inhomogeneous or equal couplings to the bosonic mode. Moreover, there is a growing interest in proposing and carrying out quantum simulations of these models in quantum platforms such as trapped ions, superconducting circuits, and quantum photonics. In this Special Issue Reprint, we have gathered a series of articles related to symmetry in quantum optics models, including the quantum Rabi model and its symmetries, Floquet topological quantum states in optically driven semiconductors, the spin–boson model as a simulator of non-Markovian multiphoton Jaynes–Cummings models, parity-assisted generation of nonclassical states of light in circuit quantum electrodynamics, and quasiprobability distribution functions from fractional Fourier transforms.

Selected Papers from the 15th Estuarine and Coastal Modeling Conference

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ISBN: 9783039212699 / 9783039212705 Year: Pages: 432 DOI: 10.3390/books978-3-03921-270-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2019-08-28 11:21:27
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The 15th Estuarine and Coastal Modeling Conference provides a venue for commercial, academic, and government scientists and engineers from around the world to present and discuss the latest results and techniques in applied estuarine and coastal modeling. Prospective authors are invited to submit papers on a wide range of topic areas, including:• Pollutant Transport and Water Quality Prediction• Coastal Response to Climate Change• Modeling Techniques and Sensitivity Studies• Model Assessment• Modeling Specific Estuarine and Coastal Systems• Visualization and Analysis• Wave and Sediment Transport Modeling• Modeling of Chemicals and Floatables• Oil Spill Transport and Fate Modeling• Inverse Methods• Circulation Modeling• Facility Siting and CSO Studies• Data Assimilation• Nowcast/Forecast Modeling Systems• Modeling Systems with Strong Buoyancy Forcing• Modeling of Coupled Systems• Risk Analysis (Nuclear Reactors, Flood Forecasting)

Keywords

British Columbia --- environmental assessment --- marine construction --- circulation --- numerical model --- sediment model --- tidal current --- wind-driven current --- stratification --- initial dilution zone --- property-carrying particle model --- coupled models --- ecosystem simulation --- biophysical modeling --- Sandusky Bay --- Great Lakes --- tides --- tidal datums --- VDatum --- spatially varying uncertainty (SVU) --- north-east Gulf of Mexico --- Brown Passage --- Chatham Sound --- internal tides --- circulation --- numerical model --- stratification --- barotropic --- baroclinic --- Hood Canal --- floating bridge --- Salish Sea --- hydrodynamics --- Finite-Volume Community Ocean Model (FVCOM) --- circulation --- anthropogenic impact --- zone of influence --- Salish Sea model --- ice modeling --- operational forecast --- FVCOM --- CICE --- hydrodynamic modeling --- Great Lakes --- hydrodynamic numerical model --- H3D --- agriculture --- salt wedge --- climate change --- sea level rise --- river discharge --- channel deepening --- tidal constituent database --- ADvanced CIRCulation model (ADCIRC) --- Eastern North Pacific Ocean (ENPAC) --- coastal ocean modeling --- Gulf of Mexico --- operational nowcast and forecast system --- Finite Volume Community Ocean Model --- water level --- temperature --- salinity --- water quality --- model calibration --- estuary --- eutrophication --- CE-QUAL-W2 --- phytoplankton --- algal growth kinetics --- wave energy --- wind forcing --- large-wave hindcast --- multi-level nested-grid modeling --- CFSR --- NARR --- WaveWatch III --- SWAN --- hydrodynamics --- feasibility assessments --- nearshore restoration --- FVCOM --- Puget Sound --- Salish Sea --- numerical model --- sediment transport --- marine --- short-lived radioisotopes --- wave hindcast --- breakwater --- harbor --- estuary --- SWAN --- MIKE21SW --- unstructured grid --- storm surge --- coastal storm --- flooding --- compound events --- estuarine modeling --- lateral circulation --- tidal currents --- momentum balance --- coastal and estuarine modeling --- ADCIRC --- water level time series --- VDatum --- tidal datums --- statistical interpolation --- spatially varying uncertainty --- non-tidal zones --- marine grid population --- Texas --- western Louisiana --- Gulf of Mexico --- ocean modeling --- cloud computing --- data analysis --- geospatial data visualization

Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics

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ISBN: 9783039214099 / 9783039214105 Year: Pages: 254 DOI: 10.3390/books978-3-03921-410-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
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The use of machine learning in mechanics is booming. Algorithms inspired by developments in the field of artificial intelligence today cover increasingly varied fields of application. This book illustrates recent results on coupling machine learning with computational mechanics, particularly for the construction of surrogate models or reduced order models. The articles contained in this compilation were presented at the EUROMECH Colloquium 597, « Reduced Order Modeling in Mechanics of Materials », held in Bad Herrenalb, Germany, from August 28th to August 31th 2018. In this book, Artificial Neural Networks are coupled to physics-based models. The tensor format of simulation data is exploited in surrogate models or for data pruning. Various reduced order models are proposed via machine learning strategies applied to simulation data. Since reduced order models have specific approximation errors, error estimators are also proposed in this book. The proposed numerical examples are very close to engineering problems. The reader would find this book to be a useful reference in identifying progress in machine learning and reduced order modeling for computational mechanics.

Keywords

parameter-dependent model --- surrogate modeling --- tensor-train decomposition --- gappy POD --- heterogeneous data --- elasto-viscoplasticity --- archive --- model reduction --- 3D reconstruction --- inverse problem plasticity --- data science --- model order reduction --- POD --- DEIM --- gappy POD --- GNAT --- ECSW --- empirical cubature --- hyper-reduction --- reduced integration domain --- computational homogenisation --- model order reduction (MOR) --- low-rank approximation --- proper generalised decomposition (PGD) --- PGD compression --- randomised SVD --- nonlinear material behaviour --- machine learning --- artificial neural networks --- computational homogenization --- nonlinear reduced order model --- elastoviscoplastic behavior --- nonlinear structural mechanics --- proper orthogonal decomposition --- empirical cubature method --- error indicator --- symplectic model order reduction --- proper symplectic decomposition (PSD) --- structure preservation of symplecticity --- Hamiltonian system --- reduced order modeling (ROM) --- proper orthogonal decomposition (POD) --- enhanced POD --- a priori enrichment --- modal analysis --- stabilization --- dynamic extrapolation --- computational homogenization --- large strain --- finite deformation --- geometric nonlinearity --- reduced basis --- reduced-order model --- sampling --- Hencky strain --- microstructure property linkage --- unsupervised machine learning --- supervised machine learning --- neural network --- snapshot proper orthogonal decomposition

Dynamical Models of Biology and Medicine

Authors: --- --- ---
ISBN: 9783039212170 / 9783039212187 Year: Pages: 294 DOI: 10.3390/books978-3-03921-218-7 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology
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Mathematical and computational modeling approaches in biological and medical research are experiencing rapid growth globally. This Special Issue Book intends to scratch the surface of this exciting phenomenon. The subject areas covered involve general mathematical methods and their applications in biology and medicine, with an emphasis on work related to mathematical and computational modeling of the complex dynamics observed in biological and medical research. Fourteen rigorously reviewed papers were included in this Special Issue. These papers cover several timely topics relating to classical population biology, fundamental biology, and modern medicine. While the authors of these papers dealt with very different modeling questions, they were all motivated by specific applications in biology and medicine and employed innovative mathematical and computational methods to study the complex dynamics of their models. We hope that these papers detail case studies that will inspire many additional mathematical modeling efforts in biology and medicine

Keywords

hemodynamic model --- microcirculation load --- liquid-solid-porous media seepage coupling --- 2-combination --- graphical representation --- cell-based vector --- numerical characterization --- phylogenetic analysis --- intraguild predation --- random perturbations --- persistence --- stationary distribution --- global asymptotic stability --- quorum sensing --- chemostat --- mathematical model --- differential equations --- delay --- bifurcations --- dynamical system --- numerical simulation --- predator-prey model --- switched harvest --- limit cycle --- rich dynamics --- algae growth models --- uncertainty quantification --- asymptotic theory --- bootstrapping --- model comparison tests --- Raphidocelis subcapitata --- Daphnia magna --- spotting --- wildfire --- transport equations --- spotting distribution --- obesity --- mechano-electrochemical model --- articular cartilage --- cartilage degeneration --- cartilage loading --- optimal control --- hepatitis B --- delay differential equations (DDE) --- immune response --- drug therapy --- dynamic model --- flocculation --- global stability --- uniform persistence --- epidermis --- mathematical model --- bacterial inflammation --- bacterial competition --- chronic myeloid leukemia --- tyrosine kinase inhibitors --- immunomodulatory therapies --- combination therapy --- equilibrium points --- mathematical modeling --- prostate cancer --- androgen deprivation therapy --- data fitting --- generalized pseudo amino acid composition --- numerical characterization --- phylogenetic analysis --- identification of DNA-binding proteins --- n/a

Methods in Computational Biology

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ISBN: 9783039211630 / 9783039211647 Year: Pages: 214 DOI: 10.3390/books978-3-03921-164-7 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
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Modern biology is rapidly becoming a study of large sets of data. Understanding these data sets is a major challenge for most life sciences, including the medical, environmental, and bioprocess fields. Computational biology approaches are essential for leveraging this ongoing revolution in omics data. A primary goal of this Special Issue, entitled “Methods in Computational Biology”, is the communication of computational biology methods, which can extract biological design principles from complex data sets, described in enough detail to permit the reproduction of the results. This issue integrates interdisciplinary researchers such as biologists, computer scientists, engineers, and mathematicians to advance biological systems analysis. The Special Issue contains the following sections:•Reviews of Computational Methods•Computational Analysis of Biological Dynamics: From Molecular to Cellular to Tissue/Consortia Levels•The Interface of Biotic and Abiotic Processes•Processing of Large Data Sets for Enhanced Analysis•Parameter Optimization and Measurement

The Great Debate: General Ability and Specific Abilities in the Prediction of Important Outcomes

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ISBN: 9783039211678 / 9783039211685 Year: Pages: 108 DOI: 10.3390/books978-3-03921-168-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Psychology
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There are many different theories of intelligence. Although these theories differ in their nuances, nearly all agree that there are multiple cognitive abilities and that they differ in the breadth of content they are typically associated with. There is much less agreement about the relative importance of cognitive abilities of differing generality for predicting important real-world outcomes, such as educational achievement, career success, job performance, and health. Some investigators believe that narrower abilities hold little predictive power once general abilities have been accounted for. Other investigators contend that specific abilities are often as—or even more—effective in forecasting many practical variables as general abilities. These disagreements often turn on differences of theory and methodology that are both subtle and complex. The five cutting-edge contributions in this volume, both empirical and theoretical, advance the conversation in this vigorous, and highly important, scientific debate.

Remote Sensing of Evapotranspiration (ET)

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ISBN: 9783039216024 / 9783039216031 Year: Pages: 240 DOI: 10.3390/books978-3-03921-603-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Biotechnology
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Evapotranspiration (ET) is a critical component of the water and energy balances, and the number of remote sensing-based ET products and estimation methods has increased in recent years. Various aspects of remote sensing of ET are reported in the 11 papers published in this book. The major research areas covered by this book include inter-comparison and performance evaluation of widely used one- and two-source energy balance models, a new dual-source model (Soil Plant Atmosphere and Remote Sensing Evapotranspiration, SPARSE), and a process-based model (ETMonitor); assessment of multi-source (e.g., remote sensing, reanalysis, and land surface model) ET products; development or improvement of data fusion frameworks to predict continuous daily ET at a high spatial resolution (field-scale or 30 m) by fusing the advanced spaceborne thermal emission reflectance radiometer (ASTER), the moderate resolution imaging spectroradiometer (MODIS), and Landsat data; and investigating uncertainties in ET estimates using an ET ensemble composed of several land surface models and diagnostic datasets. The effects of the differences between ET products on water resources and ecosystem management were also investigated. More accurate ET estimates and improved understanding of remotely sensed ET products are crucial for maximizing crop productivity while minimizing water losses and management costs.

Advanced Memristor Modeling: Memristor Circuits and Networks

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ISBN: 9783038971047/9783038971030 Year: Pages: 172 DOI: doi.org/10.3390/books978-3-03897-103-0 Language: en
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General)
Added to DOAB on : 2019-05-22 16:48:48
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The investigation of new memory schemes, neural networks, computer systems, and many other improved electronic devices is very important for the future generation’s electronic circuits and for their widespread application in all the areas of industry. In this respect, the analysis of new efficient and advanced electronic elements and circuits is an essential field of highly developed electrical and electronic engineering. The resistance-switching phenomenon, observed in many amorphous oxides, has been investigated since 1970 and is a promising technology for constructing new electronic memories. It has been established that such oxide materials have the ability for changing their conductance in accordance with the applied voltage, and for memorizing their state for long-time interval. Similar behaviour has been predicted for the memristor element by Leon Chua in 1971. The memristor is proposed in accordance with symmetry considerations and the relationships between the four basic electric quantities—electric current i, voltage v, charge q, and magnetic flux Ψ. The memristor is an essential passive one-port element together with the resistor, inductor, and capacitor. The Williams HP research group has made a link between resistive switching devices and the memristor proposed by Chua. A number of scientific papers related to memristors and memristor devices have been issued, and several memristor models have been proposed. The memristor is a highly nonlinear component. It relates the electric charge q and the flux linkage, expressed as a time integral of the voltage. The memristor element has the important capability for remembering the electric charge passed through its cross-section and its respective resistance, when the electrical signals are switched off. Due to its nano-scale dimensions, non-volatility, and memorizing properties, the memristor is a sound potential candidate for application in computer high-density memories, artificial neural networks, and many other electronic devices.

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