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Advances on Links Between Mathematics and Industry : CTMI 2019 / edited by Peregrina Quintela Estévez, Bartomeu Coll, Rosa M. Crujeiras, José Durany, Laureano Escudero
(SxI - Springer for Innovation / SxI - Springer per l'Innovazione. ISSN:22392696 ; 15)
版 | 1st ed. 2021. |
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出版者 | (Cham : Springer International Publishing : Imprint: Springer) |
出版年 | 2021 |
大きさ | IX, 154 p. 97 illus., 89 illus. in color : online resource |
著者標目 | Quintela Estévez, Peregrina editor Coll, Bartomeu editor Crujeiras, Rosa M editor Durany, José editor Escudero, Laureano editor SpringerLink (Online service) |
件 名 | LCSH:Mathematics LCSH:Mathematics—Data processing LCSH:Engineering mathematics LCSH:Engineering—Data processing LCSH:Mathematical models LCSH:Statistics FREE:Applications of Mathematics FREE:Computational Science and Engineering FREE:Mathematical and Computational Engineering Applications FREE:Mathematical Modeling and Industrial Mathematics FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
一般注記 | 1. Perez, Hector D. and Grossmann, Ignacio E., Recent Advances in Computational Models for the Discrete and Continuous Optimization of Industrial Process Systems -- 2 Casal, G. at al., Optimal Design of a Railway Bypass at Parga, Northwest of Spain -- 3. Parolini, N. et al., Reduced models for liquid food packaging systems -- 4. Martín, E. et al., Reduced order modelling in the manufacturing process of wire rod: Applications for fast temperature predictions and optimal selection of process parameters -- 5. Coroas, C. and Martín, Elena B., Modelling and numerical simulation of the quenching heat treatment. Application to the industrial quenching of automotive spindles -- 6. Alborés, Alfredo R. and Rodríguez, J., Single Particle Models for the Numerical Simulation of Lithium-ion Cells -- 7. Casasnovas, D. and Rivero, Á., Fracture propagation using a phase field approach -- 8. López García, J. and Rivero, Á., Phase space learning with neural networks This book results from the talks presented at the First Conference on Transfer between Mathematics & Industry (CTMI 2019). Its goal is to promote and disseminate the mathematical tools for Statistics & Big Data, MSO (Modeling, Simulation and Optimization) and their industrial applications. In this volume, the reader will find innovative advances in the automotive, energy, railway, logistics, and materials sectors. In addition, Advances CTMI 2019 promotes the opening of new research lines aiming to provide suitable solutions for the industrial and societal challenges. Fostering effective interaction between Academia and Industry is our main purpose with this book. CTMI conferences are one of the main forums where significant advances in industrial mathematics are presented, bringing together outstanding leaders from business, science and Academia to promote the use of mathematics for an innovative industry HTTP:URL=https://doi.org/10.1007/978-3-030-59223-3 |
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電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
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電子ブック | オンライン | 電子ブック |
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Springer eBooks | 9783030592233 |
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電子リソース |
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EB00201022 |