Correction

Correction: An experimental and analytical study of the effect of cold compression on the thermophysical properties of a granular medium

  • Received: 31 July 2020 Accepted: 22 August 2020 Published: 28 August 2020
  • Citation: Mohamed Filali, Kacim Hadjadj, Lakhdar Hachani, Ahmed Mechraoui, Mohamed El-Amine Slimani, Mounir Sakmeche. Correction: An experimental and analytical study of the effect of cold compression on the thermophysical properties of a granular medium[J]. AIMS Materials Science, 2020, 7(5): 581-582. doi: 10.3934/matersci.2020.5.581

    Related Papers:

    [1] Satoshi Kumabe, Tianyu Song, Tôn Việt Tạ . Stochastic forest transition model dynamics and parameter estimation via deep learning. Mathematical Biosciences and Engineering, 2025, 22(5): 1243-1262. doi: 10.3934/mbe.2025046
    [2] Sebastien Motsch, Mehdi Moussaïd, Elsa G. Guillot, Mathieu Moreau, Julien Pettré, Guy Theraulaz, Cécile Appert-Rolland, Pierre Degond . Modeling crowd dynamics through coarse-grained data analysis. Mathematical Biosciences and Engineering, 2018, 15(6): 1271-1290. doi: 10.3934/mbe.2018059
    [3] Manal M. Yousef, Rehab Alsultan, Said G. Nassr . Parametric inference on partially accelerated life testing for the inverted Kumaraswamy distribution based on Type-II progressive censoring data. Mathematical Biosciences and Engineering, 2023, 20(2): 1674-1694. doi: 10.3934/mbe.2023076
    [4] Walid Emam, Khalaf S. Sultan . Bayesian and maximum likelihood estimations of the Dagum parameters under combined-unified hybrid censoring. Mathematical Biosciences and Engineering, 2021, 18(3): 2930-2951. doi: 10.3934/mbe.2021148
    [5] Katrine O. Bangsgaard, Morten Andersen, James G. Heaf, Johnny T. Ottesen . Bayesian parameter estimation for phosphate dynamics during hemodialysis. Mathematical Biosciences and Engineering, 2023, 20(3): 4455-4492. doi: 10.3934/mbe.2023207
    [6] Miguel Ángel Rodríguez-Parra, Cruz Vargas-De-León, Flaviano Godinez-Jaimes, Celia Martinez-Lázaro . Bayesian estimation of parameters in viral dynamics models with antiviral effect of interferons in a cell culture. Mathematical Biosciences and Engineering, 2023, 20(6): 11033-11062. doi: 10.3934/mbe.2023488
    [7] Gianni Gilioli, Sara Pasquali, Fabrizio Ruggeri . Nonlinear functional response parameter estimation in a stochastic predator-prey model. Mathematical Biosciences and Engineering, 2012, 9(1): 75-96. doi: 10.3934/mbe.2012.9.75
    [8] Azmy S. Ackleh, Jeremy J. Thibodeaux . Parameter estimation in a structured erythropoiesis model. Mathematical Biosciences and Engineering, 2008, 5(4): 601-616. doi: 10.3934/mbe.2008.5.601
    [9] Alex Capaldi, Samuel Behrend, Benjamin Berman, Jason Smith, Justin Wright, Alun L. Lloyd . Parameter estimation and uncertainty quantification for an epidemic model. Mathematical Biosciences and Engineering, 2012, 9(3): 553-576. doi: 10.3934/mbe.2012.9.553
    [10] Blaise Faugeras, Olivier Maury . An advection-diffusion-reaction size-structured fish population dynamics model combined with a statistical parameter estimation procedure: Application to the Indian Ocean skipjack tuna fishery. Mathematical Biosciences and Engineering, 2005, 2(4): 719-741. doi: 10.3934/mbe.2005.2.719




  • [1] Hadjadj K, Hachani L, Mechraoui A, et al. (2020) An experimental and analytical study of the effect of cold compression on the thermophysical properties of a granular medium. AIMS Mater Sci 7: 116-129. doi: 10.3934/matersci.2020.1.116
  • This article has been cited by:

    1. Mohamad Baydoun, Damian Campo, Divya Kanapram, Lucio Marcenaro, Carlo S. Regazzoni, 2019, Prediction of Multi-target Dynamics Using Discrete Descriptors: an Interactive Approach, 978-1-4799-8131-1, 3342, 10.1109/ICASSP.2019.8682272
    2. N. Bellomo, D. Clarke, L. Gibelli, P. Townsend, B.J. Vreugdenhil, Human behaviours in evacuation crowd dynamics: From modelling to “big data” toward crisis management, 2016, 18, 15710645, 1, 10.1016/j.plrev.2016.05.014
    3. Antoine Tordeux, Gregor Lämmel, Flurin S. Hänseler, Bernhard Steffen, A mesoscopic model for large-scale simulation of pedestrian dynamics, 2018, 93, 0968090X, 128, 10.1016/j.trc.2018.05.021
    4. Luca Bruno, Alessandro Corbetta, Andrea Tosin, From individual behaviour to an evaluation of the collective evolution of crowds along footbridges, 2016, 101, 0022-0833, 153, 10.1007/s10665-016-9852-z
    5. Alessandro Corbetta, Andrea Tosin, Comparing First-Order Microscopic and Macroscopic Crowd Models for an Increasing Number of Massive Agents, 2016, 2016, 1687-9120, 1, 10.1155/2016/6902086
    6. Bouchra Aylaj, Nicola Bellomo, Livio Gibelli, Damián Knopoff, Crowd Dynamics by Kinetic Theory Modeling: Complexity, Modeling,, 2020, 12, 1938-1743, 1, 10.2200/S01055ED1V01Y202009MAS036
    7. Qipin Chen, Wenrui Hao, A homotopy training algorithm for fully connected neural networks, 2019, 475, 1364-5021, 20190662, 10.1098/rspa.2019.0662
    8. G. Albi, N. Bellomo, L. Fermo, S.-Y. Ha, J. Kim, L. Pareschi, D. Poyato, J. Soler, Vehicular traffic, crowds, and swarms: From kinetic theory and multiscale methods to applications and research perspectives, 2019, 29, 0218-2025, 1901, 10.1142/S0218202519500374
    9. Simone Göttlich, Stephan Knapp, 2020, Chapter 2, 978-3-030-50449-6, 11, 10.1007/978-3-030-50450-2_2
    10. Nicola Bellomo, Livio Gibelli, Damian Knopoff, 2020, Chapter 1, 978-3-030-50449-6, 1, 10.1007/978-3-030-50450-2_1
    11. Bouchra Aylaj, Nicola Bellomo, Livio Gibelli, Alessandro Reali, A unified multiscale vision of behavioral crowds, 2020, 30, 0218-2025, 1, 10.1142/S0218202520500013
    12. Francesc Valls, Ernest Redondo, David Fonseca, Pilar Garcia-Almirall, Jordi Subirós, 2016, Chapter 41, 978-3-319-39512-8, 436, 10.1007/978-3-319-39513-5_41
    13. Milad Haghani, Majid Sarvi, Simulating pedestrian flow through narrow exits, 2019, 383, 03759601, 110, 10.1016/j.physleta.2018.10.029
    14. Fiammetta Venuti, Vitomir Racic, Alessandro Corbetta, Modelling framework for dynamic interaction between multiple pedestrians and vertical vibrations of footbridges, 2016, 379, 0022460X, 245, 10.1016/j.jsv.2016.05.047
    15. Alessandro Corbetta, Chung-Min Lee, Adrian Muntean, Federico Toschi, 2016, Chapter 7, 978-3-319-33481-3, 49, 10.1007/978-3-319-33482-0_7
    16. Alessandro Corbetta, Chung-min Lee, Roberto Benzi, Adrian Muntean, Federico Toschi, Fluctuations around mean walking behaviors in diluted pedestrian flows, 2017, 95, 2470-0045, 10.1103/PhysRevE.95.032316
    17. Zhiqiang Wan, Xuemin Hu, Haibo He, Yi Guo, 2017, A learning based approach for social force model parameter estimation, 978-1-5090-6182-2, 4058, 10.1109/IJCNN.2017.7966368
    18. Marion Gödel, Rainer Fischer, Gerta Köster, 2020, Chapter 12, 978-3-030-55972-4, 93, 10.1007/978-3-030-55973-1_12
    19. I.M. Sticco, G.A. Frank, C.O. Dorso, Social Force Model parameter testing and optimization using a high stress real-life situation, 2021, 561, 03784371, 125299, 10.1016/j.physa.2020.125299
    20. Simon Rahn, Marion Gödel, Rainer Fischer, Gerta Köster, Dynamics of a Simulated Demonstration March: An Efficient Sensitivity Analysis, 2021, 13, 2071-1050, 3455, 10.3390/su13063455
    21. Ahmed Elaiw, Yusuf Al-Turki, Mohamed Alghamdi, A Critical Analysis of Behavioural Crowd Dynamics—From a Modelling Strategy to Kinetic Theory Methods, 2019, 11, 2073-8994, 851, 10.3390/sym11070851
    22. Alessandro Corbetta, Jasper A. Meeusen, Chung-min Lee, Roberto Benzi, Federico Toschi, Physics-based modeling and data representation of pairwise interactions among pedestrians, 2018, 98, 2470-0045, 10.1103/PhysRevE.98.062310
    23. Nicola Bellomo, Livio Gibelli, 2018, Chapter 1, 978-3-030-05128-0, 1, 10.1007/978-3-030-05129-7_1
    24. Bouchra Aylaj, Nicola Bellomo, Livio Gibelli, Damián Knopoff, 2021, Chapter 2, 978-3-031-01300-3, 17, 10.1007/978-3-031-02428-3_2
    25. Bouchra Aylaj, Nicola Bellomo, Livio Gibelli, Damián Knopoff, 2021, Chapter 1, 978-3-031-01300-3, 1, 10.1007/978-3-031-02428-3_1
    26. Siyuan Ma, Yongqing Guo, Fulu Wei, Qingyin Li, Zhenyu Wang, An Improved Social Force Model of Pedestrian Twice–Crossing Based on Spatial–Temporal Trajectory Characteristics, 2022, 14, 2071-1050, 16615, 10.3390/su142416615
    27. Marion Gödel, Nikolai Bode, Gerta Köster, Hans-Joachim Bungartz, Bayesian inference methods to calibrate crowd dynamics models for safety applications, 2022, 147, 09257535, 105586, 10.1016/j.ssci.2021.105586
    28. Raphael Korbmacher, Antoine Tordeux, Review of Pedestrian Trajectory Prediction Methods: Comparing Deep Learning and Knowledge-Based Approaches, 2022, 23, 1524-9050, 24126, 10.1109/TITS.2022.3205676
    29. Nicola Bellomo, Livio Gibelli, 2021, Chapter 1, 978-3-030-91645-9, 1, 10.1007/978-3-030-91646-6_1
    30. 2021, 978-3-031-01300-3, 10.1007/978-3-031-02428-3
    31. Bouchra Aylaj, Nicola Bellomo, Livio Gibelli, Damián Knopoff, 2021, Chapter 5, 978-3-031-01300-3, 71, 10.1007/978-3-031-02428-3_5
    32. Simone Göttlich, Claudia Totzeck, Parameter calibration with stochastic gradient descent for interacting particle systems driven by neural networks, 2022, 34, 0932-4194, 185, 10.1007/s00498-021-00309-8
    33. Alexandra Würth, Mickaël Binois, Paola Goatin, Simone Göttlich, Data-driven uncertainty quantification in macroscopic traffic flow models, 2022, 48, 1019-7168, 10.1007/s10444-022-09989-5
    34. Bin Li, Muhammad Shahzad, Hafiz Mudassir Munir, Asif Nawaz, Nabeel Abdelhadi Mohamed Fahal, Muhammad Yousaf Ali Khan, Sheeraz Ahmed, Probabilistic Analysis To Analyze Uncertainty Incorporating Copula Theory, 2022, 17, 1975-0102, 61, 10.1007/s42835-021-00863-w
    35. Nicola Bellomo, Livio Gibelli, Annalisa Quaini, Alessandro Reali, Towards a mathematical theory of behavioral human crowds, 2022, 32, 0218-2025, 321, 10.1142/S0218202522500087
    36. Bouchra Aylaj, Nicola Bellomo, Livio Gibelli, Damián Knopoff, 2021, Chapter 4, 978-3-031-01300-3, 51, 10.1007/978-3-031-02428-3_4
    37. Diletta Burini, Nadia Chouhad, Nicola Bellomo, Waiting for a Mathematical Theory of Living Systems from a Critical Review to Research Perspectives, 2023, 15, 2073-8994, 351, 10.3390/sym15020351
    38. Nicola Bellomo, Jie Liao, Annalisa Quaini, Lucia Russo, Constantinos Siettos, Human behavioral crowds review, critical analysis and research perspectives, 2023, 33, 0218-2025, 1611, 10.1142/S0218202523500379
    39. Milad Haghani, Majid Sarvi, Crowd model calibration at strategic, tactical, and operational levels: Full-spectrum sensitivity analyses show bottleneck parameters are most critical, followed by exit-choice-changing parameters, 2023, 1942-7867, 1, 10.1080/19427867.2023.2195729
    40. Fabio Parisi, Claudio Feliciani, Ruggiero Lovreglio, What do we head for while exiting a room? a novel parametric distance map for pedestrian dynamic simulations, 2023, 156, 0968090X, 104335, 10.1016/j.trc.2023.104335
    41. Chen Cheng, Linjie Wen, Jinglai Li, Parameter estimation from aggregate observations: a Wasserstein distance-based sequential Monte Carlo sampler, 2023, 10, 2054-5703, 10.1098/rsos.230275
    42. F. Al Reda, S. Faure, B. Maury, E. Pinsard, Faster is Slower effect for evacuation processes: a granular standpoint, 2024, 00219991, 112861, 10.1016/j.jcp.2024.112861
    43. Nicola Bellomo, Livio Gibelli, 2023, Chapter 1, 978-3-031-46358-7, 1, 10.1007/978-3-031-46359-4_1
  • Reader Comments
  • © 2020 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(3661) PDF downloads(54) Cited by(0)

Article outline

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog