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In the course of only a few decades computers have revolutionized scientific research and more and more scientists are writing computer programs for doing their work. In spite of the ubiquitous use of computers in science, few researchers in the natural sciences have any schooling in computer science, software engineering, or numerical analysis. They usually acquire their computing knowledge 'on the job' and often feel overwhelmed by the amount of computing knowledge they must absorb. Computation in Science provides a background in computation for scientists who use computational methods. The book explains how computing is used in the natural sciences and provides a high-level overview of relevant aspects of computer science and software engineering with a focus on concepts, results, and applications. The goal of this book is to explain these basic principles, and to show how they relate to the tasks of a scientist's daily work in a language familiar to them. Its unique feature is in connecting the dots between computational science, the theory of computation and information, and software engineering. It will compensate for the general lack of any formal training in computer science and information theory allowing readers to better understand how they use computers in their work, and how computers work. Readers will learn to use computers with more confidence, and to see computing technologies in a different light, evaluating them based on how they contribute to doing science. This new edition has been significantly updated and extended to reflect developments in scientific computing, including new examples and references. It also includes a new chapter on reproducibility which reflects the importance that computational reproducibility plays. Accompanied by a website maintained by the author which hosts companion code and supplementary material, it is intended for both graduate students and experienced scientists. Some hands-on experience with computing is highly desirable, but no competence in any specific computing technology is expected.

Simulation and Optimization of Internal Combustion Engines provides the fundamentals and up-to-date progress in multidimensional simulation and optimization of internal combustion engines. While it is impossible to include all the models in a single book, this book intends to introduce the pioneer and/or the often-used models and the physics behind them providing readers with ready-to-use knowledge. Key issues, useful modeling methodology and techniques, as well as instructive results, are discussed through examples. Readers will understand the fundamentals of these examples and be inspired to explore new ideas and means for better solutions in their studies and work. Topics include combustion basis of IC engines, mathematical descriptions of reactive flow with sprays, engine in-cylinder turbulence, fuel sprays, combustions and pollutant emissions, optimization of direct-injection gasoline engines, and optimization of diesel and alternative fuel engines.

Although, the basic concept of a fuel cell is quite simple, creating new designs and optimizing their performance takes serious work and a mastery of several technical areas. PEM Fuel Cell Modeling and Simulation Using Matlab, provides design engineers and researchers with a valuable tool for understanding and overcoming barriers to designing and building the next generation of PEM Fuel Cells. With this book, engineers can test components and verify designs in the development phase, saving both time and money. Easy to read and understand, this book provides design and modelling tips for fuel cell components such as: modelling proton exchange structure, catalyst layers, gas diffusion, fuel distribution structures, fuel cell stacks and fuel cell plant. This book includes design advice and MATLAB and FEMLAB codes for Fuel Cell types such as: polymer electrolyte, direct methanol and solid oxide fuel cells. This book also includes types for one, two and three dimensional modeling and two-phase flow phenomena and microfluidics.

This work presents the Purification Water Process Algorithm (PWPA), a metaheuristic framework grounded in the physical principles of industrial water treatment rather than metaphorical inspiration. The algorithm explicitly models three canonical stages—sedimentation, filtration and final purification—as distinct search operators: a gravity-based mechanism for global exploration, a stochastic filtering process to sustain diversity and a refinement phase that promotes convergence towards high-quality solutions. This direct physical correspondence yields a transparent and analytically tractable optimization process. Empirical evaluation on 30 benchmark functions, including high-dimensional instances up to 1000 variables, demonstrates that PWPA consistently matches or exceeds the performance of established metaheuristics in terms of solution quality, convergence behaviour and robustness. In particular, it achieves the known global optimum on the 1000-dimensional Schwefel function with negligible variance, highlighting its scalability. In a real-world application, PWPA was applied to hyperparameter optimization of a support vector machine (SVM) for the modified national institute of standards (MNIST) digit classification, reducing cross-validation error by 61.1% and attaining a test accuracy of 94.60% (σ=0.0041). The results suggest that anchoring metaheuristic design in well-understood physical processes can offer a viable path towards more interpretable and reliable optimization algorithms.

Air pollution assessment in the Tropical Andes requires a multidisciplinary approach. This can be supported from the understanding of the underlying biological dynamics and atmospheric behavior, to the mathematical approach for the proper use of all available information. This review paper touches on several aspects in which mathematical models can help to solve challenging problems regarding air pollution in reviewing the state-of-the-art at the global level and assessing the corresponding state of development as applied to the Tropical Andes. We address the complexities and challenges that modelling atmospheric dynamics in a mega-diverse region with abrupt topography entails. Understanding the relevance of monitoring and facing the problems of data scarcity, we call attention to the usefulness of data assimilation for uncertainty reduction, and how these techniques could help tackle the scarcity of regional monitoring networks to accelerate the implementation and development of modelling systems for air quality in the Tropical Andes. Finally, we suggest a cyberphysical framework for decision-making processes based on the data assimilation of chemical transport models, the forecast of scenarios, and their use in regulation and policy making.

First-principle calculation reveals that N containing carbon nanotubes (CNTs) can support the functionalization of transition metals such as Sc on the CNT surface. For N-substituted CNTs without a vacancy, the enhanced adsorption results from large electron affinity difference of the N adjacent to C atom. In this case, the N atom activates nearby C atom and enhances its interaction with the Sc metal on the CNT surface. Meanwhile, the formation of a vacancy in CNTs causes local reconstruction of the surface near the vacancy site. Simulation and analysis show that vacancy mediated N substitution is a more favored scheme for Sc functionalization on the surface of CNTs that suppresses the clustering of Sc. The enhanced Sc adsorption in N-doped CNTs with mono- and di-vacancy defects was attributed to strong hybridization between the Scandium d orbital and nitrogen p orbital. The results explain theoretically the mechanism of enhanced functionalization of metals on N doped CNTs and suggests that Sc functionalized nitrogen doped CNTs with vacancies is an excellent candidate for the adsorption of small molecules.

\"Addressing building owners, developers, and managers, this text covers how building information management (BIM) complements facility management (FM) systems to achieve significant lifecycle advantages. It includes coverage of the guidelines for BIM in FM as developed by owners such as the General Services Administration, the COBie2 (BIM document standard) used to collect and communicate facility equipment information, and a list of software for BIM/FM integration. It also offers six real-life case studies including the Texas A&M Health Science Center, the USC School of Cinematic Arts, and the State of WI Facilities\"--

In this work, the possibility of limiting energy consumption in the manufacturing process of bioethanol to obtain biofuel was analysed. For this purpose, a control algorithm has been optimised while retaining the good quality of the control signals. New in this study is the correlation of the control algorithm not only with the signal’s quality, but also with the energy consumption in such an energy-intensive process as rectification. The rectification process in a periodic production system has been researched. The process was modelled on a test station with the distillation mixture capacity of 25 dm3. For the optimization, the following control algorithms have been applied: relay, PID and PID after modification to I-PD. The simulation was carried out on a transfer function model of the plant that has been verified on a real object, a rectification column. The simulations of energy consumption and control signal’s quality have been carried out in the Matlab®-Simulink environment after implementing the model of the research subject and control algorithms. In the simulation process, an interference signal with an amplitude of 3% and frequency of 2 mHz was used. The executed analyses of the control signal quality and the influence of the control algorithm on the energy consumption has shown some essential mutual relationships. The lowest energy consumption in the rectification process can be achieved using the I-PD controller—however, the signal quality deteriorates. The energy savings are slightly lower while using the PID controller, but the control signal quality improves significantly. From a practical point of view, in the considered problem the best control solution is the classic PID controller—the obtained energy effect was only slightly lower while retaining the good quality of the control signals.

Abstract Although several European law instruments specifically promote the development of orphan medicines, rare disease patients still suffer from an excessive lack of access to orphan drugs. In order to base a claim for equity of access to research benefits, health vulnerability is introduced as a human rights-based public health concept. It represents a potentially valuable and powerful means in European law for rare disease patients to claim for an improved public action to develop innovative orphan drugs, including through the use of novel data-driven technologies such as computer modelling and simulation, as they have the potential to palliate some of the obstacles in the current development process of orphan medicines. The human rights-based approach would be all the more valuable, as it would simultaneously draw attention on privacy aspects of vulnerability for orphan disease patients, especially regarding increased risks stemming from the processing of highly sensitive health data.

This book is on urban resilience - how to design and operate cities that can withstand major threats such as natural disasters and economic downturns and how to recover from them. It is a collection of latest research results from two separate but collaborating research groups, namely, researchers in urban design and those on general resilience theory. The book systematically deals with the core aspects of urban resilience: systems, management issues and populations.The taxonomy can be broken down into threats, systems, resilience cycles and recovery types in the context of urban resilience. It starts with a discussion of systems resilience models, focusing on the central idea that resilience is a moving average of costs (a set of trajectories in a two-player game paradigm). The second section explores management issues, including planning, operating and emergency response in cities with specific examples such as land-use planning and carbon-neutral scenarios for urban planning. The next section focuses on urban dwellers and specific people-related issues in the context of resilience. Agent-based simulation of behaviour and perception-based resilience, as well as brand crisis management are representative examples of the topics discussed. A further section examines systems like public utilities - including managing power supplies, cyber-security issues and models for pandemics. It concludes with a discussion of the future challenges and risks facing complex systems, for example in resilient power grids, making it essential reading for a wide range of researchers and policymakers.