The DOI matches its Crossref record.
Feasibility Study for Recovering Waste Heat in the Steelmaking Industry Using a Chemical Recuperator
Open accessAbstract
This paper studies the possibility of developing a new heat recovery system from various hot wastes generated by the steelmaking industry, by utilizing the endothermic heat of reaction instead of sensible heat. In the proposed system, the waste heat of the gas was first stored using a Phase Change Material (PCM), and then supplied to an endothermic, methane-steam reforming reaction (MSR) as a heat source. The molten slag was granulated using a rotary cup atomizer (RCA) and the sensible heat of the slag was recovered using MSR. A heat and material balance model was developed to evaluate this system and to predict all its operating data. An exergy analysis and an economic evaluation were conducted on the basis of the predicted data. The results showed that the exergy loss in the proposed system was only 15% from the total exergy losses in the conventional system, and that the annual cost benefit of the proposed system totaled US 409 million from heat recovery, and US 1 945 million from slag granulation.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Nanoencapsulation of phase change materials for advanced thermal energy storage systems
Shchukina, E. M., Graham, M., Zheng, Z., & Shchukin, D. G. (2018) · Chemical Society Reviews · doi:10.1039/c8cs00099a · Cited by 579
How to recuperate industrial waste heat beyond time and space
Zhang, L., & Akiyama, T. (2009) · International Journal of Exergy · doi:10.1504/ijex.2009.023999 · Cited by 41
Self-citation
Metadata
- Authors
- Maruoka, N., Mizuochi, T., Purwanto, H., & Akiyama, T.
- Venue
- ISIJ International
- Publisher
- Iron and Steel Institute of Japan
- Published
- 2004
- Volume
- 44
- Issue
- 2
- Pages
- 257-262
- ISSN
- 0915-1559 (ISSN-L)
- OpenAlex
- W2010581114
- Cited by
- 162
- References
- 0
- FWCI
- 1.78
- Type
- journal article
- Language
- en
- Open access
- gold
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Feasibility Study for Recovering Waste Heat in the Steelmaking Industry Using a Chemical Recuperator. https://app.cochat.ai/papers/10.2355/isijinternational.44.257
- The paper
- Maruoka, N., Mizuochi, T., Purwanto, H., & Akiyama, T. (2004). Feasibility Study for Recovering Waste Heat in the Steelmaking Industry Using a Chemical Recuperator. ISIJ International. https://doi.org/10.2355/isijinternational.44.257
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.