You are here: Home Proceedings
Document Actions

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_01

Download

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.
ER

Download

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