Citation and metadata
Recommended citation
Ajmal M, Rößler T, Katterfeld A (2019). Detailed analysis of cohesive DEM parameter fields using Uniaxial Rapid Flow Low Consolidation test for calibration of cohesive bulk materials. Logistics Journal : Proceedings, Vol. 2019. (urn:nbn:de:0009-14-49946)
Download Citation
Endnote
%0 Journal Article %T Detailed analysis of cohesive DEM parameter fields using Uniaxial Rapid Flow Low Consolidation test for calibration of cohesive bulk materials %A Ajmal, Mohsin %A Rößler, Thomas %A Katterfeld, Andr�� %J Logistics Journal : Proceedings %D 2019 %V 2019 %N 12 %@ 2192-9084 %F ajmal2019 %X Discrete Element Method (DEM) is a broadly accepted and well established tool for simulating bulk materials. However, cohesion and adhesion is one field of DEM where a lot of questions still remain unanswered. One of the methods employed to answer this question is calibration and validation, by performing a detailed study of the DEM parameter fields and comparing them with experimental results, in order to zero in on a unique set of parameters which satisfy the experimental results.A lot of contact models exist which explain cohesion in their own unique ways, however, JKR model is widely used for cohesive simulations due to its robustness and a relatively wide area of application. The JKR model tackles cohesion by introducing Surface Energy Density and increased particle overlap. Cohesive DEM simulations were performed using a combination set of Friction coefficients, Young’s Modulus and Surface Energy Density. These were then compared with the reference experiments to narrow down on a specific set of parameters. Hence a systematic analytically driven calibration protocol will be established which can be used to calibrate different other cohesive materials. Further investigations will be carried out to assess the effect of cohesion and adhesion on rolling resistance. Various parameter calibration and validation endeavours in recent years have been quite successful in answering those questions on a macroscopic level. In this work a Draw Down setup, rightly classified as Uniaxial Rapid Flow Low Consolidation test, was chosen to study the cohesive behavior of under study materials. One of the drawbacks of calibration is that a very large number of simulations should be performed to have an acceptable result. For this purpose High Performance Cluster (HPC) computing is a valuable asset. In this exercise the simulations were done using highly parallel computing ability of ‘‘OvGU HPC Neumann’’. Parallel computing greatly reduces the time required for the whole exercise, which otherwise would have been deemed too computationally intensive to undertake. %L 620 %K DEM %K JKR model %K calibration %K cohesion %K discrete element method %R 10.2195/lj_Proc_ajmal_en_201912_01 %U http://nbn-resolving.de/urn:nbn:de:0009-14-49946 %U http://dx.doi.org/10.2195/lj_Proc_ajmal_en_201912_01Download
Bibtex
@Article{ajmal2019, author = "Ajmal, Mohsin and R{\"o}{\ss}ler, Thomas and Katterfeld, Andr��", title = "Detailed analysis of cohesive DEM parameter fields using Uniaxial Rapid Flow Low Consolidation test for calibration of cohesive bulk materials", journal = "Logistics Journal : Proceedings", year = "2019", volume = "2019", number = "12", keywords = "DEM; JKR model; calibration; cohesion; discrete element method", abstract = "Discrete Element Method (DEM) is a broadly accepted and well established tool for simulating bulk materials. However, cohesion and adhesion is one field of DEM where a lot of questions still remain unanswered. One of the methods employed to answer this question is calibration and validation, by performing a detailed study of the DEM parameter fields and comparing them with experimental results, in order to zero in on a unique set of parameters which satisfy the experimental results.A lot of contact models exist which explain cohesion in their own unique ways, however, JKR model is widely used for cohesive simulations due to its robustness and a relatively wide area of application. The JKR model tackles cohesion by introducing Surface Energy Density and increased particle overlap. Cohesive DEM simulations were performed using a combination set of Friction coefficients, Young's Modulus and Surface Energy Density. These were then compared with the reference experiments to narrow down on a specific set of parameters. Hence a systematic analytically driven calibration protocol will be established which can be used to calibrate different other cohesive materials. Further investigations will be carried out to assess the effect of cohesion and adhesion on rolling resistance. Various parameter calibration and validation endeavours in recent years have been quite successful in answering those questions on a macroscopic level. In this work a Draw Down setup, rightly classified as Uniaxial Rapid Flow Low Consolidation test, was chosen to study the cohesive behavior of under study materials. One of the drawbacks of calibration is that a very large number of simulations should be performed to have an acceptable result. For this purpose High Performance Cluster (HPC) computing is a valuable asset. In this exercise the simulations were done using highly parallel computing ability of ``OvGU HPC Neumann''. Parallel computing greatly reduces the time required for the whole exercise, which otherwise would have been deemed too computationally intensive to undertake.", issn = "2192-9084", doi = "10.2195/lj_Proc_ajmal_en_201912_01", url = "http://nbn-resolving.de/urn:nbn:de:0009-14-49946" }Download
RIS
TY - JOUR AU - Ajmal, Mohsin AU - Rößler, Thomas AU - Katterfeld, Andr�� PY - 2019 DA - 2019// TI - Detailed analysis of cohesive DEM parameter fields using Uniaxial Rapid Flow Low Consolidation test for calibration of cohesive bulk materials JO - Logistics Journal : Proceedings VL - 2019 IS - 12 KW - DEM KW - JKR model KW - calibration KW - cohesion KW - discrete element method AB - Discrete Element Method (DEM) is a broadly accepted and well established tool for simulating bulk materials. However, cohesion and adhesion is one field of DEM where a lot of questions still remain unanswered. One of the methods employed to answer this question is calibration and validation, by performing a detailed study of the DEM parameter fields and comparing them with experimental results, in order to zero in on a unique set of parameters which satisfy the experimental results.A lot of contact models exist which explain cohesion in their own unique ways, however, JKR model is widely used for cohesive simulations due to its robustness and a relatively wide area of application. The JKR model tackles cohesion by introducing Surface Energy Density and increased particle overlap. Cohesive DEM simulations were performed using a combination set of Friction coefficients, Young’s Modulus and Surface Energy Density. These were then compared with the reference experiments to narrow down on a specific set of parameters. Hence a systematic analytically driven calibration protocol will be established which can be used to calibrate different other cohesive materials. Further investigations will be carried out to assess the effect of cohesion and adhesion on rolling resistance. Various parameter calibration and validation endeavours in recent years have been quite successful in answering those questions on a macroscopic level. In this work a Draw Down setup, rightly classified as Uniaxial Rapid Flow Low Consolidation test, was chosen to study the cohesive behavior of under study materials. One of the drawbacks of calibration is that a very large number of simulations should be performed to have an acceptable result. For this purpose High Performance Cluster (HPC) computing is a valuable asset. In this exercise the simulations were done using highly parallel computing ability of ‘‘OvGU HPC Neumann’’. Parallel computing greatly reduces the time required for the whole exercise, which otherwise would have been deemed too computationally intensive to undertake. SN - 2192-9084 UR - http://nbn-resolving.de/urn:nbn:de:0009-14-49946 DO - 10.2195/lj_Proc_ajmal_en_201912_01 ID - ajmal2019 ER -Download
Wordbib
<?xml version="1.0" encoding="UTF-8"?> <b:Sources SelectedStyle="" xmlns:b="http://schemas.openxmlformats.org/officeDocument/2006/bibliography" xmlns="http://schemas.openxmlformats.org/officeDocument/2006/bibliography" > <b:Source> <b:Tag>ajmal2019</b:Tag> <b:SourceType>ArticleInAPeriodical</b:SourceType> <b:Year>2019</b:Year> <b:PeriodicalTitle>Logistics Journal : Proceedings</b:PeriodicalTitle> <b:Volume>2019</b:Volume> <b:Issue>12</b:Issue> <b:Url>http://nbn-resolving.de/urn:nbn:de:0009-14-49946</b:Url> <b:Url>http://dx.doi.org/10.2195/lj_Proc_ajmal_en_201912_01</b:Url> <b:Author> <b:Author><b:NameList> <b:Person><b:Last>Ajmal</b:Last><b:First>Mohsin</b:First></b:Person> <b:Person><b:Last>Rößler</b:Last><b:First>Thomas</b:First></b:Person> <b:Person><b:Last>Katterfeld</b:Last><b:First>Andr��</b:First></b:Person> </b:NameList></b:Author> </b:Author> <b:Title>Detailed analysis of cohesive DEM parameter fields using Uniaxial Rapid Flow Low Consolidation test for calibration of cohesive bulk materials</b:Title> <b:Comments>Discrete Element Method (DEM) is a broadly accepted and well established tool for simulating bulk materials. However, cohesion and adhesion is one field of DEM where a lot of questions still remain unanswered. One of the methods employed to answer this question is calibration and validation, by performing a detailed study of the DEM parameter fields and comparing them with experimental results, in order to zero in on a unique set of parameters which satisfy the experimental results.A lot of contact models exist which explain cohesion in their own unique ways, however, JKR model is widely used for cohesive simulations due to its robustness and a relatively wide area of application. The JKR model tackles cohesion by introducing Surface Energy Density and increased particle overlap. Cohesive DEM simulations were performed using a combination set of Friction coefficients, Young’s Modulus and Surface Energy Density. These were then compared with the reference experiments to narrow down on a specific set of parameters. Hence a systematic analytically driven calibration protocol will be established which can be used to calibrate different other cohesive materials. Further investigations will be carried out to assess the effect of cohesion and adhesion on rolling resistance. Various parameter calibration and validation endeavours in recent years have been quite successful in answering those questions on a macroscopic level. In this work a Draw Down setup, rightly classified as Uniaxial Rapid Flow Low Consolidation test, was chosen to study the cohesive behavior of under study materials. One of the drawbacks of calibration is that a very large number of simulations should be performed to have an acceptable result. For this purpose High Performance Cluster (HPC) computing is a valuable asset. In this exercise the simulations were done using highly parallel computing ability of ‘‘OvGU HPC Neumann’’. Parallel computing greatly reduces the time required for the whole exercise, which otherwise would have been deemed too computationally intensive to undertake.</b:Comments> </b:Source> </b:Sources>Download
ISI
PT Journal AU Ajmal, M Rößler, T Katterfeld, A TI Detailed analysis of cohesive DEM parameter fields using Uniaxial Rapid Flow Low Consolidation test for calibration of cohesive bulk materials SO Logistics Journal : Proceedings PY 2019 VL 2019 IS 12 DI 10.2195/lj_Proc_ajmal_en_201912_01 DE DEM; JKR model; calibration; cohesion; discrete element method AB Discrete Element Method (DEM) is a broadly accepted and well established tool for simulating bulk materials. However, cohesion and adhesion is one field of DEM where a lot of questions still remain unanswered. One of the methods employed to answer this question is calibration and validation, by performing a detailed study of the DEM parameter fields and comparing them with experimental results, in order to zero in on a unique set of parameters which satisfy the experimental results.A lot of contact models exist which explain cohesion in their own unique ways, however, JKR model is widely used for cohesive simulations due to its robustness and a relatively wide area of application. The JKR model tackles cohesion by introducing Surface Energy Density and increased particle overlap. Cohesive DEM simulations were performed using a combination set of Friction coefficients, Young’s Modulus and Surface Energy Density. These were then compared with the reference experiments to narrow down on a specific set of parameters. Hence a systematic analytically driven calibration protocol will be established which can be used to calibrate different other cohesive materials. Further investigations will be carried out to assess the effect of cohesion and adhesion on rolling resistance. Various parameter calibration and validation endeavours in recent years have been quite successful in answering those questions on a macroscopic level. In this work a Draw Down setup, rightly classified as Uniaxial Rapid Flow Low Consolidation test, was chosen to study the cohesive behavior of under study materials. One of the drawbacks of calibration is that a very large number of simulations should be performed to have an acceptable result. For this purpose High Performance Cluster (HPC) computing is a valuable asset. In this exercise the simulations were done using highly parallel computing ability of ‘‘OvGU HPC Neumann’’. Parallel computing greatly reduces the time required for the whole exercise, which otherwise would have been deemed too computationally intensive to undertake. ERDownload
Mods
<mods> <titleInfo> <title>Detailed analysis of cohesive DEM parameter fields using Uniaxial Rapid Flow Low Consolidation test for calibration of cohesive bulk materials</title> </titleInfo> <name type="personal"> <namePart type="family">Ajmal</namePart> <namePart type="given">Mohsin</namePart> </name> <name type="personal"> <namePart type="family">Rößler</namePart> <namePart type="given">Thomas</namePart> </name> <name type="personal"> <namePart type="family">Katterfeld</namePart> <namePart type="given">Andr��</namePart> </name> <abstract>Discrete Element Method (DEM) is a broadly accepted and well established tool for simulating bulk materials. However, cohesion and adhesion is one field of DEM where a lot of questions still remain unanswered. One of the methods employed to answer this question is calibration and validation, by performing a detailed study of the DEM parameter fields and comparing them with experimental results, in order to zero in on a unique set of parameters which satisfy the experimental results. A lot of contact models exist which explain cohesion in their own unique ways, however, JKR model is widely used for cohesive simulations due to its robustness and a relatively wide area of application. The JKR model tackles cohesion by introducing Surface Energy Density and increased particle overlap. Cohesive DEM simulations were performed using a combination set of Friction coefficients, Young’s Modulus and Surface Energy Density. These were then compared with the reference experiments to narrow down on a specific set of parameters. Hence a systematic analytically driven calibration protocol will be established which can be used to calibrate different other cohesive materials. Further investigations will be carried out to assess the effect of cohesion and adhesion on rolling resistance. Various parameter calibration and validation endeavours in recent years have been quite successful in answering those questions on a macroscopic level. In this work a Draw Down setup, rightly classified as Uniaxial Rapid Flow Low Consolidation test, was chosen to study the cohesive behavior of under study materials. One of the drawbacks of calibration is that a very large number of simulations should be performed to have an acceptable result. For this purpose High Performance Cluster (HPC) computing is a valuable asset. In this exercise the simulations were done using highly parallel computing ability of ‘‘OvGU HPC Neumann’’. Parallel computing greatly reduces the time required for the whole exercise, which otherwise would have been deemed too computationally intensive to undertake.</abstract> <subject> <topic>DEM</topic> <topic>JKR model</topic> <topic>calibration</topic> <topic>cohesion</topic> <topic>discrete element method</topic> </subject> <classification authority="ddc">620</classification> <relatedItem type="host"> <genre authority="marcgt">periodical</genre> <genre>academic journal</genre> <titleInfo> <title>Logistics Journal : Proceedings</title> </titleInfo> <part> <detail type="volume"> <number>2019</number> </detail> <detail type="issue"> <number>12</number> </detail> <date>2019</date> </part> </relatedItem> <identifier type="issn">2192-9084</identifier> <identifier type="urn">urn:nbn:de:0009-14-49946</identifier> <identifier type="doi">10.2195/lj_Proc_ajmal_en_201912_01</identifier> <identifier type="uri">http://nbn-resolving.de/urn:nbn:de:0009-14-49946</identifier> <identifier type="citekey">ajmal2019</identifier> </mods>Download
Full Metadata
Bibliographic Citation | Logistics Journal : referierte Veröffentlichungen, Vol. 2019, Iss. 12 |
---|---|
Title |
Detailed analysis of cohesive DEM parameter fields using Uniaxial Rapid Flow Low Consolidation test for calibration of cohesive bulk materials (eng) |
Author | Mohsin Ajmal, Thomas Rößler, Andr�� Katterfeld |
Language | eng |
Abstract | Discrete Element Method (DEM) is a broadly accepted and well established tool for simulating bulk materials. However, cohesion and adhesion is one field of DEM where a lot of questions still remain unanswered. One of the methods employed to answer this question is calibration and validation, by performing a detailed study of the DEM parameter fields and comparing them with experimental results, in order to zero in on a unique set of parameters which satisfy the experimental results. A lot of contact models exist which explain cohesion in their own unique ways, however, JKR model is widely used for cohesive simulations due to its robustness and a relatively wide area of application. The JKR model tackles cohesion by introducing Surface Energy Density and increased particle overlap. Cohesive DEM simulations were performed using a combination set of Friction coefficients, Young’s Modulus and Surface Energy Density. These were then compared with the reference experiments to narrow down on a specific set of parameters. Hence a systematic analytically driven calibration protocol will be established which can be used to calibrate different other cohesive materials. Further investigations will be carried out to assess the effect of cohesion and adhesion on rolling resistance. Various parameter calibration and validation endeavours in recent years have been quite successful in answering those questions on a macroscopic level. In this work a Draw Down setup, rightly classified as Uniaxial Rapid Flow Low Consolidation test, was chosen to study the cohesive behavior of under study materials. One of the drawbacks of calibration is that a very large number of simulations should be performed to have an acceptable result. For this purpose High Performance Cluster (HPC) computing is a valuable asset. In this exercise the simulations were done using highly parallel computing ability of ‘‘OvGU HPC Neumann’’. Parallel computing greatly reduces the time required for the whole exercise, which otherwise would have been deemed too computationally intensive to undertake. Die diskrete Elementmethode (DEM) ist ein weit verbreitetes und etabliertes Tool zur Simulation von Schüttgütern. Kohäsion und Adhäsion sind jedoch ein Bereich von DEM, in dem noch viele Fragen offen sind. Eine der Methoden zur Beantwortung dieser Frage ist die Kalibrierung und Validierung, indem die DEM-Parameterfelder detailliert untersucht und mit den experimentellen Ergebnissen verglichen werden, um einen eindeutigen Parametersatz zu ermitteln, der die experimentellen Ergebnisse erfüllt. Es gibt viele Kontaktmodelle, die die Kohäsion auf ihre eigene Art erklären. Das JKR-Modell wird jedoch aufgrund seiner Robustheit und seines relativ breiten Anwendungsbereichs häufig für Kohäsionssimulationen verwendet. Das JKR-Modell bekämpft die Kohäsion durch Einführung der Oberflächenenergiedichte und einer erhöhten Partikelüberlappung. Cohesive DEM-Simulationen wurden mit einer Kombination aus Reibungskoeffizienten, Young-Modul und Oberflächenenergiedichte durchgeführt. Diese wurden dann mit den Referenzversuchen verglichen, um einen bestimmten Parametersatz einzugrenzen. Daher wird ein systematisches, analytisch gesteuertes Kalibrierungsprotokoll erstellt, mit dem verschiedene andere kohäsive Materialien kalibriert werden können. Weitere Untersuchungen werden durchgeführt, um die Auswirkung des Zusammenhalts und der Haftung auf den Rollwiderstand zu bewerten. Verschiedene Parameterkalibrierungen und Validierungen waren in den letzten Jahren recht erfolgreich bei der Beantwortung dieser Fragen auf makroskopischer Ebene. In dieser Arbeit wurde ein Draw Down-Aufbau ausgewählt, der zu Recht als einachsiger Rapid Flow Low Consolidation-Test eingestuft wurde, um das Kohäsionsverhalten von untersuchten Materialien zu untersuchen. Einer der Nachteile der Kalibrierung besteht darin, dass eine sehr große Anzahl von Simulationen durchgeführt werden sollte, um ein akzeptables Ergebnis zu erzielen. Zu diesem Zweck ist High Performance Cluster (HPC) ein wertvolles Gut. In dieser Übung wurden die Simulationen mit der hochparallelen Rechenfähigkeit von "OvGU HPC Neumann" durchgeführt. Paralleles Rechnen verkürzt den Zeitaufwand für die gesamte Übung erheblich. Andernfalls wäre dies als zu rechenintensiv erachtet worden. |
Subject | DEM, JKR model, calibration, cohesion, discrete element method |
DDC | 620 |
Rights | fDPPL |
URN: | urn:nbn:de:0009-14-49946 |
DOI | https://doi.org/10.2195/lj_Proc_ajmal_en_201912_01 |