- Volumes 84-95 (2024)
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Volumes 72-83 (2023)
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Volume 83
Pages 1-258 (December 2023)
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Volume 82
Pages 1-204 (November 2023)
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Volume 81
Pages 1-188 (October 2023)
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Volume 80
Pages 1-202 (September 2023)
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Volume 79
Pages 1-172 (August 2023)
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Volume 78
Pages 1-146 (July 2023)
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Volume 77
Pages 1-152 (June 2023)
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Volume 76
Pages 1-176 (May 2023)
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Volume 75
Pages 1-228 (April 2023)
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Volume 74
Pages 1-200 (March 2023)
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Volume 73
Pages 1-138 (February 2023)
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Volume 72
Pages 1-144 (January 2023)
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Volume 83
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Volumes 60-71 (2022)
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Volume 71
Pages 1-108 (December 2022)
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Volume 70
Pages 1-106 (November 2022)
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Volume 69
Pages 1-122 (October 2022)
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Volume 68
Pages 1-124 (September 2022)
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Volume 67
Pages 1-102 (August 2022)
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Volume 66
Pages 1-112 (July 2022)
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Volume 65
Pages 1-138 (June 2022)
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Volume 64
Pages 1-186 (May 2022)
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Volume 63
Pages 1-124 (April 2022)
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Volume 62
Pages 1-104 (March 2022)
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Volume 61
Pages 1-120 (February 2022)
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Volume 60
Pages 1-124 (January 2022)
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Volume 71
- Volumes 54-59 (2021)
- Volumes 48-53 (2020)
- Volumes 42-47 (2019)
- Volumes 36-41 (2018)
- Volumes 30-35 (2017)
- Volumes 24-29 (2016)
- Volumes 18-23 (2015)
- Volumes 12-17 (2014)
- Volume 11 (2013)
- Volume 10 (2012)
- Volume 9 (2011)
- Volume 8 (2010)
- Volume 7 (2009)
- Volume 6 (2008)
- Volume 5 (2007)
- Volume 4 (2006)
- Volume 3 (2005)
- Volume 2 (2004)
- Volume 1 (2003)
• An inverse-problem method was used to estimate solid concentration.
• The method is applicable to solid–liquid two-phase flow systems.
• A correction method was used for estimations based on forward problem error.
In this study, an inverse-problem method was applied to estimate the solid concentration in a solid–liquid two-phase flow. An algebraic slip mixture model was introduced to solve the forward problem of solid–liquid convective heat transfer. The time-average conservation equations of mass, momentum, energy, as well as the volume fraction equation were computed in a computational fluid dynamics (CFD) simulation. The solid concentration in the CFD model was controlled using an external program that included the inversion iteration, and an optimal estimation was performed via experimental measurements. Experiments using a fly-ash–water mixture and sand–water mixture with different solid concentrations in a horizontal pipeline were conducted to verify the accuracy of the inverse-problem method. The estimated results were rectified using a method based on the relationship between the estimated results and estimation error; consequently, the accuracy of the corrected inversion results improved significantly. After a verification through experiments, the inverse-problem method was concluded to be feasible for predicting the solid concentration, as the estimation error of the corrected results was within 7% for all experimental samples for a solid concentration of less than 50%. The inverse-problem method is expected to provide accurate predictions of the solid concentration in solid–liquid two-phase flow systems.