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Pregled bibliografske jedinice broj: 1125576

Artificial Neural Networks-Based Prediction of Hardness of Low-Alloy Steels Using Specific Jominy Distance


Smokvina Hanza, Sunčana; Marohnić, Tea; Iljkić, Dario; Basan, Robert
Artificial Neural Networks-Based Prediction of Hardness of Low-Alloy Steels Using Specific Jominy Distance // Metals, 11 (2021), 5; 714, 14 doi:10.3390/met11050714 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1125576 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Artificial Neural Networks-Based Prediction of Hardness of Low-Alloy Steels Using Specific Jominy Distance

Autori
Smokvina Hanza, Sunčana ; Marohnić, Tea ; Iljkić, Dario ; Basan, Robert

Izvornik
Metals (2075-4701) 11 (2021), 5; 714, 14

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
low-alloy steels ; quenching ; mechanical properties ; hardness ; artificial neural networks

Sažetak
Successful prediction of the relevant mechanical properties of steels is of great importance to materials engineering. The aim of this research is to investigate the possibility of reducing the complexity of artificial neural networks-based prediction of total hardness of hypoeutectoid, low-alloy steels based on chemical composition, by introducing the specific Jominy distance as a new input variable. For prediction of total hardness after continuous cooling of steel (output variable), ANNs were developed for different combinations of inputs. Input variables for the first configuration of ANNs were the main alloying elements (C, Si, Mn, Cr, Mo, Ni), the austenitizing temperature, the austenitizing time, and the cooling time to 500 °C, while in the second configuration alloying elements were substituted by the specific Jominy distance. Comparing the results of total hardness prediction, it can be seen that the ANN using the specific Jominy distance as input variable (runseen = 0.873, RMSEunseen = 67, MAPE = 14.8%) is almost as successful as ANN using main alloying elements (runseen = 0.940, RMSEunseen = 46, MAPE = 10.7%). The research results indicate that the prediction of total hardness of steel can be successfully performed only based on four input variables: the austenitizing temperature, the austenitizing time, the cooling time to 500 °C, and the specific Jominy distance.

Izvorni jezik
Engleski

Znanstvena područja
Metalurgija, Strojarstvo, Temeljne tehničke znanosti



POVEZANOST RADA


Projekti:
HRZZ-IP-2020-02-5764 - Razvoj modela za procjenu ponašanja materijala temeljenih na strojnom učenju (MADEIRA) (Basan, Robert, HRZZ - 2020-02) ( POIROT)
NadSve-Sveučilište u Rijeci-uniri-tehnic-18-116 - Istraživanje i razvoj prediktivnih modela ponašanja konstrukcijskih materijala temeljenih na metodama strojnog učenja (Basan, Robert, NadSve - UNIRI PROJEKTI) ( POIROT)

Ustanove:
Tehnički fakultet, Rijeka

Citiraj ovu publikaciju

Smokvina Hanza, Sunčana; Marohnić, Tea; Iljkić, Dario; Basan, Robert
Artificial Neural Networks-Based Prediction of Hardness of Low-Alloy Steels Using Specific Jominy Distance // Metals, 11 (2021), 5; 714, 14 doi:10.3390/met11050714 (međunarodna recenzija, članak, znanstveni)
Smokvina Hanza, S., Marohnić, T., Iljkić, D. & Basan, R. (2021) Artificial Neural Networks-Based Prediction of Hardness of Low-Alloy Steels Using Specific Jominy Distance. Metals, 11 (5), 714, 14 doi:10.3390/met11050714.
@article{article, year = {2021}, pages = {14}, DOI = {10.3390/met11050714}, chapter = {714}, keywords = {low-alloy steels, quenching, mechanical properties, hardness, artificial neural networks}, journal = {Metals}, doi = {10.3390/met11050714}, volume = {11}, number = {5}, issn = {2075-4701}, title = {Artificial Neural Networks-Based Prediction of Hardness of Low-Alloy Steels Using Specific Jominy Distance}, keyword = {low-alloy steels, quenching, mechanical properties, hardness, artificial neural networks}, chapternumber = {714} }
@article{article, year = {2021}, pages = {14}, DOI = {10.3390/met11050714}, chapter = {714}, keywords = {low-alloy steels, quenching, mechanical properties, hardness, artificial neural networks}, journal = {Metals}, doi = {10.3390/met11050714}, volume = {11}, number = {5}, issn = {2075-4701}, title = {Artificial Neural Networks-Based Prediction of Hardness of Low-Alloy Steels Using Specific Jominy Distance}, keyword = {low-alloy steels, quenching, mechanical properties, hardness, artificial neural networks}, chapternumber = {714} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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