The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Modeling Partial Charging and Discharging of Area-Constrained Ice Storage Tanks
Abstract
Although several models have been developed and validated for predicting the performance of indirect, area-constrained, ice-on-pipe storage tanks, none have fully considered operation involving partial charging or discharging. In this case, multiple layers of ice and water may coexist around the heat exchanger tubes. This paper presents two models for predicting the behavior of tanks with partial charging and discharging processes. One model is based upon physical principles and is useful for studying design and control issues through simulation. The second model involves the use of an empirical correlation and is useful for simulating an existing design or could be appropriate for on-line control. Both models were validated using experimental results for a range of charging and discharging scenarios.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“For instance, consecutive days with high nighttime outdoor temperatures deteriorate the cooling capacity of TES systems significantly [165].”
From Resilient cooling strategies – A critical review and qualitative assessment (2021) · cites this paper as [165]
In the citing paper
“Kuczyn ´ski & Staszczuk [166] indicated that the cooling effect and efficiency of increased thermal mass do not change during the heatwaves and remain independent of the duration and distribution of heatwaves.”
From Resilient cooling strategies – A critical review and qualitative assessment (2021) · cites this paper as [166]
In the citing paper
“TES cooling performance under extreme conditions is highly sensitive to the temperature gradient between cyclic cold (e.g., night) and warm (e.g., day) periods.”
From Resilient cooling strategies – A critical review and qualitative assessment (2021) · cites this paper as [165]
Citations
Cites
Development and Evaluation of a Rule-Based Control Strategy for Ice Storage Systems
Drees, K. H., & Braun, J. E. (1996) · Science and Technology for the Built Environment · doi:10.1080/10789669.1996.10391352 · Cited by 61
Self-citationModeling of Area-Constrained Ice Storage Tanks
Drees, K. H., & Braun, J. E. (1995) · Science and Technology for the Built Environment · doi:10.1080/10789669.1995.10391315 · Cited by 38
Self-citationDeterministic model for an internal melt ice-on-coil thermal storage tank
Neto, J. H. M., & Krarti, M. (1997) · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · Cited by 20
Development of direct and indirect ice-storage models for energy analysis calculations
Strand, R. K., PEDERSEN, C. O., & Coleman, G. N. (1994) · ASHRAE winter conference papers · Cited by 16
Experimental validation of a numerical model for an internal melt ice-on-coil thermal storage tank
Neto, J. H. M., & Krarti, M. (1997) · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · Cited by 13
Validation of the algorithm for ice-on-pipe brine thermal storage systems
Nelson, D. J., Vick, B., & Yu, X. (1996) · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · Cited by 10
Research works printed but not linked: 3
- Jekel , T. B. , Mitchell , J. W. and Klein , S. A. 1993 . Modeling of Ice Storage Tanks . ASHRAE Transactions , 99 ( 1 ) : 1016 – 1023 .
- Vick , B. , Nelson , D. J. and Yu , X. 1996 . Model of an Ice-on-Pipe Brine Thermal Storage Component . ASH-RAE Transactions , 102 ( 1 ) : 45 – 54 .
- West , J. D. 1997 . Evaluation of Methods for Controlling Ice Storage Systems , M.S. thesis W. Lafayette, IN : Purdue University. .
Cited by
Sorted by citations
Review of building energy modeling for control and operation
Li, X., & Wen, J. (2014) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2014.05.056 · Cited by 632
Resilient cooling strategies – A critical review and qualitative assessment
Zhang, C., Kazanci, O. B., Levinson, R., Heiselberg, P., Olesen, B. W., Chiesa, G., Sodagar, B., Ai, Z., Selkowitz, S., Zinzi, M., et al. (2021) · Energy and Buildings · doi:10.1016/j.enbuild.2021.111312 · Cited by 180
Model-based predictive control of an ice storage device in a building cooling system
Candanedo, J. A., Dehkordi, V. R., & Stylianou, M. (2013) · Applied Energy · doi:10.1016/j.apenergy.2013.05.081 · Cited by 142
Economic feasibility of thermal energy storage systems
Habeebullah, B. A. (2006) · Energy and Buildings · doi:10.1016/j.enbuild.2006.07.006 · Cited by 94
Olsthoorn, D., Haghighat, F., Moreau, A., & Lacroix, G. (2017) · Building and Environment · doi:10.1016/j.buildenv.2017.03.029 · Cited by 83
Hu, M., Weir, J. D., & Wu, T. (2011) · European Journal of Operational Research · doi:10.1016/j.ejor.2011.09.008 · Cited by 79
Li, X., Wen, J., & Malkawi, A. M. (2016) · Applied Energy · doi:10.1016/j.apenergy.2016.06.030 · Cited by 71
Sanaye, S., & Hekmatian, M. (2015) · International Journal of Refrigeration · doi:10.1016/j.ijrefrig.2015.10.014 · Cited by 71
Energy and exergy analyses of an ice-on-coil thermal energy storage system
Ezan, M. A., Erek, A., & Dinçer, İ. (2011) · Energy · doi:10.1016/j.energy.2011.09.036 · Cited by 66
A Near-Optimal Control Strategy for Cool Storage Systems with Dynamic Electric Rates (RP-1252)
Braun, J. E. (2007) · Science and Technology for the Built Environment · doi:10.1080/10789669.2007.10390972 · Cited by 44
Self-citationTam, A., Ziviani, D., Braun, J. E., & Jain, N. (2019) · Energy and Buildings · doi:10.1016/j.enbuild.2019.05.040 · Cited by 31
Self-citationJia, L., Liu, J., Chong, A., & Dai, X. (2022) · Applied Energy · doi:10.1016/j.apenergy.2022.119443 · Cited by 29
Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory
Henze, G. P., & Krarti, M. (2005) · doi:10.2172/894509 · Cited by 26
Thiem, S., Born, A., Danov, V., Vandersickel, A., Schäfer, J., & Hamacher, T. (2017) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2017.04.149 · Cited by 24
Sizing and Operation of an Isolated Microgrid With Building Thermal Dynamics and Cold Storage
Dakir, S., Boukas, I., Lemort, V., & Cornélusse, B. (2020) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2020.3005370 · Cited by 19
Hierarchical Hybrid MPC for Management of Distributed Phase Change Thermal Energy Storage
Pangborn, H. C., Laird, C. E., & Alleyne, A. G. (2020) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.23919/acc45564.2020.9147698 · Cited by 16
Dynamic modelling of ice‐based thermal energy storage for cooling applications
Bastida, H., Ugalde‐Loo, C. E., Abeysekera, M., & Jenkins, N. (2022) · IET Energy Systems Integration · doi:10.1049/esi2.12061 · Cited by 14
Venegas, T. P., Ugarte-Larraguibel, G., Vasco, D. A., Rouault, F., & Pérez, R. (2019) · International Journal of Refrigeration · doi:10.1016/j.ijrefrig.2019.01.028 · Cited by 14
Adaptive Operation Decisions in Net Zero Building Clusters
Odonkor, P., & Lewis, K. E. (2015) · doi:10.1115/detc2015-47290 · Cited by 13
Ice thermal energy storage modeling: A review
Aljuneidi, N., Heine, K., Rodriguez, R. M., & Boetcher, S. K. S. (2024) · Advances in heat transfer · doi:10.1016/bs.aiht.2024.05.002 · Cited by 10
International Energy Agency EBC Annex 80 - Resilient Cooling of Buildings - State of the Art Review
Zhengtao, A., Akander, J., Arens, E. A., Arghand, T., Attia, S., Bogatu, D., Bozonnet, E., Breesch, H., Cehlin, M., Chiesa, G., et al. (2022) · doi:10.52776/coxk4763 · Cited by 15
Adaptive Energy Optimization Toward Net-Zero Energy Building Clusters
Odonkor, P., Lewis, K. E., Wen, J., & Wu, T. (2016) · Journal of Mechanical Design · doi:10.1115/1.4033395 · Cited by 9
Hao, K., Kim, D., & Braun, J. E. (2022) · Journal of Building Performance Simulation · doi:10.1080/19401493.2022.2084161 · Cited by 8
Self-citationHabeebullah, B. A. (2005) · Journal of King Abdulaziz University-Engineering Sciences · doi:10.4197/eng.16-2.4 · Cited by 8
A Model-Based Predictive Control Approach for a Building Cooling System With Ice Storage
Dehkordi, V. R., & Candanedo, J. A. (2013) · doi:10.1115/dscc2013-3897 · Cited by 6
Guittet, D., Bonnema, E., Mitchell, M., Mahvi, A. J., & Woods, J. (2025) · Energy and Buildings · doi:10.1016/j.enbuild.2025.115828 · Cited by 5
Aljuneidi, N., Troxler, C. J., Williams, J. C., Melendez, I., & Boetcher, S. K. S. (2026) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2026.131024 · Cited by 3
Sizing and Operation of an Isolated Microgrid with Cold Storage
Dakir, S., Boukas, I., Lemort, V., & Cornélusse, B. (2019) · doi:10.1109/ptc.2019.8810700 · Cited by 3
NUMERICAL STUDY OF ICE LAYER GROWTH AROUND A VERTICAL TUBE
Stampa, C. S., & Nieckeleb, A. O. (2005) · Revista de Engenharia Térmica · doi:10.5380/reterm.v4i2.5402 · Cited by 2
Li, X., & Wen, J. (2015) · doi:10.17918/etd-6594 · Cited by 2
NUMERICAL STUDY OF ICE LAYER GROWTH AROUND A VERTICAL TUBE
Stampa, C. S., & Nieckeleb, A. O. (2005) · Revista de Engenharia Térmica · doi:10.5380/ret.v4i2.5402
NUMERICAL ANALYSIS OF INDIRECT ICE STORAGE SYSTEMS PERFORMANCE
Stampa, C. S., & Nieckele, A. O. (2006) · Revista de Engenharia Térmica · doi:10.5380/reterm.v5i1.61677
Development of a Generalized Control Strategy for Thermal Energy Storage in Residential Buildings
Tam, A., Braun, J. E., Jain, N., & Ziviani, D. (2018) · Purdue e-Pubs (Purdue University System)
Self-citation
Metadata
- Authors
- West, J., & Braun, J. E.
- Affiliations
- Johnson Controls (United States) (US)
- Purdue University West Lafayette (US)
- Venue
- HVAC&R Research
- Publisher
- Informa UK Limited
- Published
- 1999-07
- Volume
- 5
- Issue
- 3
- Pages
- 209-228
- ISSN
- 1078-9669 (ISSN-L)
- 1938-5587
- OpenAlex
- W2038978788
- Cited by
- 33
- References
- 6
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2022: 4 · 2021: 1 · 2020: 2 · 2019: 3 · 2018: 1 · 2017: 2 · 2016: 2 · 2015: 3 · 2014: 1 · 2013: 2
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science and Technology for the Built Environment (publishedVersion)
- Funders
- Electric Power Research Institute
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Phase Change Materials Research
- Physical Sciences › Engineering › Mechanical Engineering › Adsorption and Cooling Systems
- Physical Sciences › Engineering › Mechanical Engineering › Refrigeration and Air Conditioning Technologies
- Keywords
- ice storage tank, partial charging, empirical correlations, thermal energy storage, online control
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review