Advanced composite material simulation

A computational methodology is presented for modeling the non-linear mechanical behavior of composite structures made of FRP (Fiber-Reinforced Polymers) laminates. The model is based on the appropriate combination of the constitutive models of compounding materials, considered to behave as isolated continua, together with additional “closure equations” that characterize the micro-mechanics of the composite from a morphological point of view. To this end, any appropriate constitutive model may be selected for each phase. Each component is modeled separately and the global response is obtained by assembling all contributions taking into account the interactions between components in a general phenomenological way. To model the behavior of a single uni-directional (UD) composite laminated, a Serial-Parallel continuum approach has been developed assuming that components behave as parallel materials in the fibers alignment direction and as serial materials in orthogonal directions. Taking into account the internal morphology of the composite material, it is devised a strategy for decoupling and coupling component phases. This methodology [Rastellini 2006], named "compounding of behavior", allows to take into consideration local non linear phenomenon in the compounding materials, like damage, plasticity, etc. in a coupled manner. It is based on the proper management of homogenous constitutive models, already available for each component. In this way, it is used all developments achieved in constitutive modeling for plain materials, what makes possible the transference of this technology to composites. A laminated theory complemented with the proposed UD model is employed to describe the mechanical behavior of multi-directional laminates. A specific solution strategy for the general non linear case is proposed. It provides quick local and global convergences, what makes the model suitable for large scale structures. The model brings answers on the non-linear behavior of composites, where classical micro-mechanics formulas are restricted to their linear elastic part. The methodology is validated through several numerical analyses and contrasted against experimental data and benchmark tests

Simple networks on complex cellular automata: From de Bruijn diagrams to jump-graphs

We overview networks which characterise dynamics in cellular automata. These networks are derived from one-dimensional cellular automaton rules and global states of the automaton evolution: de Bruijn diagrams, subsystem diagrams, basins of attraction, and jump-graphs. These networks are used to understand properties of spatially-extended dynamical systems: emergence of non-trivial patterns, self-organisation, reversibility and chaos. Particular attention is paid to networks determined by travelling self-localisations, or gliders.Comment: 25 pages, 14 figure

Deformation forecasting of a hydropower dam by hybridizing a long short-term memory deep learning network with the coronavirus optimization algorithm

The safety operation and management of hydropower dam play a critical role in social-economic development and ensure people’s safety in many countries; therefore, modeling and forecasting the hydropower dam’s deformations with high accuracy is crucial. This research aims to propose and validate a new model based on deep learning long short-term memory (LSTM) and the coronavirus optimization algorithm (CVOA), named CVOA-LSTM, for forecasting the defor mations of the hydropower dam. The second-largest hydropower dam of Viet nam, located in the Hoa Binh province, is focused. Herein, we used the LSTM to establish the deformation model, whereas the CVOA was utilized to opti mize the three parameters of the LSTM, the number of hidden layers, the learn ing rate, and the dropout. The efficacy of the proposed CVOA-LSTM model is assessed by comparing its forecasting performance with state-of-the-art bench marks, sequential minimal optimization for support vector regression, Gaussian process, M5’ model tree, multilayer perceptron neural network, reduced error pruning tree, random tree, random forest, and radial basis function neural net work. The result shows that the proposed CVOA-LSTM model has high fore casting capability (R2 = 0.874, root mean square error = 0.34, mean absolute error = 0.23) and outperforms the benchmarks. We conclude that CVOA-LSTM is a new tool that can be considered to forecast the hydropower dam’s deforma tions.Ministerio de Ciencia, Innovación y Universidades PID2020-117954RB-C2

Monitoring blood potassium concentration in hemodialysis patients by quantifying T-wave morphology dynamics.

We investigated the ability of time-warping-based ECG-derived markers of T-wave morphology changes in time ([Formula: see text]) and amplitude ([Formula: see text]), as well as their non-linear components ([Formula: see text] and [Formula: see text]), and the heart rate corrected counterpart ([Formula: see text]), to monitor potassium concentration ([Formula: see text]) changes ([Formula: see text]) in end-stage renal disease (ESRD) patients undergoing hemodialysis (HD). We compared the performance of the proposed time-warping markers, together with other previously proposed [Formula: see text] markers, such as T-wave width ([Formula: see text]) and T-wave slope-to-amplitude ratio ([Formula: see text]), when computed from standard ECG leads as well as from principal component analysis (PCA)-based leads. 48-hour ECG recordings and a set of hourly-collected blood samples from 29 ESRD-HD patients were acquired. Values of [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] were calculated by comparing the morphology of the mean warped T-waves (MWTWs) derived at each hour along the HD with that from a reference MWTW, measured at the end of the HD. From the same MWTWs [Formula: see text] and [Formula: see text] were also extracted. Similarly, [Formula: see text] was calculated as the difference between the [Formula: see text] values at each hour and the [Formula: see text] reference level at the end of the HD session. We found that [Formula: see text] and [Formula: see text] showed higher correlation coefficients with [Formula: see text] than [Formula: see text]-Spearman's ([Formula: see text]) and Pearson's (r)-and [Formula: see text]-Spearman's ([Formula: see text])-in both SL and PCA approaches being the intra-patient median [Formula: see text] and [Formula: see text] in SL and [Formula: see text] and [Formula: see text] in PCA respectively. Our findings would point at [Formula: see text] and [Formula: see text] as the most suitable surrogate of [Formula: see text], suggesting that they could be potentially useful for non-invasive monitoring of ESRD-HD patients in hospital, as well as in ambulatory settings. Therefore, the tracking of T-wave morphology variations by means of time-warping analysis could improve continuous and remote [Formula: see text] monitoring of ESRD-HD patients and flagging risk of [Formula: see text]-related cardiovascular events

On an efficient k-step iterative method for nonlinear equations

[EN] This paper is devoted to the construction and analysis of an efficient k-step iterative method for nonlinear equations. The main advantage of this method is that it does not need to evaluate any high order Frechet derivative. Moreover, all the k-step have the same matrix, in particular only one LU decomposition is required in each iteration. We study the convergence order, the efficiency and the dynamics in order to motivate the proposed family. We prove, using some recurrence relations, a semilocal convergence result in Banach spaces. Finally, a numerical application related to nonlinear conservative systems is presented. (C) 2016 Elsevier B.V. All rights reserved.This work was supported in part by the project MTM2011-28636-C02-01-{01,02} of the Spanish Ministry of Science and Innovation.Amat, S.; Bermúdez, C.; Hernández-Verón, MA.; Martínez Molada, E. (2016). On an efficient k-step iterative method for nonlinear equations. Journal of Computational and Applied Mathematics. 302:258-271. https://doi.org/10.1016/j.cam.2016.02.003S25827130

Pragmatic economic valuation of adaptation risk and responses across scales Case study in Vietnam

Vietnam is one of the countries particularly vulnerable to climate change. Increased temperatures, increased salinity intrusion due to sea-level rise and altering precipitation patterns significantly affect livelihood options of smallholder farmers, resulting in losses in agricultural production. These impacts are projected to become increasingly severe, hence, adaptation to climate change and sensitivity needs to be assessed and adaptation measures taken. This study provides a vulnerability assessment based on the results for exposure, sensitivity and adaptive capacity. This includes present and projected future climatic conditions and hazards, crop suitability analyses and socioeconomic assessments on a district scale. In addition, a case study is presented focusing on the two provinces of Tra Vinh and Ben Tre, identified as highly vulnerable in the Mekong Delta area. The case study shows opportunities, economic trade-offs and barriers of adoption of climate-smart agriculture (CSA) practices to adapt to progressive climate change

Selection for environmental variance of litter size in rabbits

[EN] Background: In recent years, there has been an increasing interest in the genetic determination of environmental variance. In the case of litter size, environmental variance can be related to the capacity of animals to adapt to new environmental conditions, which can improve animal welfare. Results: We developed a ten-generation divergent selection experiment on environmental variance. We selected one line of rabbits for litter size homogeneity and one line for litter size heterogeneity by measuring intra-doe phenotypic variance. We proved that environmental variance of litter size is genetically determined and can be modified by selection. Response to selection was 4.5% of the original environmental variance per generation. Litter size was consistently higher in the Low line than in the High line during the entire experiment. Conclusions: We conclude that environmental variance of litter size is genetically determined based on the results of our divergent selection experiment. This has implications for animal welfare, since animals that cope better with their environment have better welfare than more sensitive animals. We also conclude that selection for reduced environmental variance of litter size does not depress litter size.This research was funded by the Ministerio de Economía y Competitividad (Spain), Projects AGL2014-55921, C2-1-P and C2-2-P. Marina Martínez-Alvaro has a Grant from the same funding source, BES-2012-052655.Blasco Mateu, A.; Martínez Álvaro, M.; García Pardo, MDLL.; Ibáñez Escriche, N.; Argente, MJ. (2017). Selection for environmental variance of litter size in rabbits. Genetics Selection Evolution. 49(48):1-8. https://doi.org/10.1186/s12711-017-0323-4S184948Morgante F, Sørensen P, Sorensen DA, Maltecca C, Mackay TFC. Genetic architecture of micro-environmental plasticity in Drosophila melanogaster. Sci Rep. 2015;5:9785.Sørensen P, de los Campos G, Morgante F, Mackay TFC, Sorensen D. 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Canalization analysis of birth weight in Bruna dels Pirineus beef cattle. J Anim Sci. 2013;91:3070–8.Mulder HA, Rönnegård L, Fikse WF, Veerkamp RF, Strandberg E. Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models. Genet Sel Evol. 2013;45:23.Janhunen M, Kause A, Vehviläinen H, Järvisalom O. Genetics of microenvironmental sensitivity of body weight in rainbow trout (Oncorhynchus mykiss) selected for improved growth. PLoS One. 2012;7:e38766.Sonesson AK, Ødegård J, Rönnegård L. Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar). Genet Sel Evol. 2013;45:41.Garreau H, Bolet G, Larzul C, Robert-Granie C, Saleil G, SanCristobal M, et al. Results of four generations of a canalising selection for rabbit birth weight. Livest Sci. 2008;119:55–62.Pun A, Cervantes I, Nieto B, Salgado C, Pérez-Cabal MA, Ibáñez-Escriche N, et al. 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Coherent master equation for laser modelocking

Modelocked lasers constitute the fundamental source of optically-coherent ultrashort-pulsed radiation, with huge impact in science and technology. Their modeling largely rests on the master equation (ME) approach introduced in 1975 by Hermann A. Haus. However, that description fails when the medium dynamics is fast and, ultimately, when light-matter quantum coherence is relevant. Here we set a rigorous and general ME framework, the coherent ME (CME), that overcomes both limitations. The CME predicts strong deviations from Haus ME, which we substantiate through an amplitude-modulated semiconductor laser experiment. Accounting for coherent effects, like the Risken-Nummedal-Graham-Haken multimode instability, we envisage the usefulness of the CME for describing self-modelocking and spontaneous frequency comb formation in quantum-cascade and quantum-dot lasers. Furthermore, the CME paves the way for exploiting the rich phenomenology of coherent effects in laser design, which has been hampered so far by the lack of a coherent ME formalism