Design, Manufacturing and Properties of Refractory Materials
This reprint aims to immerse the reader into the latest developments in the technology of refractory materials. From the application of Artificial Intelligence and computer-aided methods, like machine learning or image analysis and the simulation of refractories’ properties and corrosion phenomena,...
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| Format: | Online |
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| Idioma: | anglès |
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MDPI - Multidisciplinary Digital Publishing Institute
2024
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| Accés en línia: | ONIX_20240704_9783725810895_131 |
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| _version_ | 1869518398151458816 |
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| collection | Directory of Open Access Books |
| description | This reprint aims to immerse the reader into the latest developments in the technology of refractory materials. From the application of Artificial Intelligence and computer-aided methods, like machine learning or image analysis and the simulation of refractories’ properties and corrosion phenomena, to tailoring the properties of refractories to be more environmentally friendly, we aim to elucidate the current global trends and progress being made in refractories technology. This reprint has been created by world-recognized researchers, representing both academia and industry, striving jointly to make refractories safer and working for longer periods of time. Through this reprint, we demonstrate our major collaborative efforts to shift the technology to be more effective for the producers of refractory materials, more efficient for end-users, and, primarily, more sustainable in the interest of protecting our most precious shared asset—the safe planet Earth. |
| format | Online |
| id | doab-20.500.12854ir-139335 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1393352024-07-04T09:43:35Z Design, Manufacturing and Properties of Refractory Materials Jastrz?bska, Ilona Szczerba, Jacek blast furnace carbon refractories molten metal infiltration X-ray computed tomography inorganic chemical binders refractories phosphates water glasses refractory castable hollow corundum microspheres bauxite aggregate thermal shock resistance micronized andalusite antioxidation Al2O3-SiC-C castables hot modulus of rupture metal-ceramic composites alginate gelation refractory metals computed tomography niobium refractory composite aggregate synthesis castable Al2O3-CaO-Cr2O3-O2 system (Al1?xCrx)2O3 Ca(Al12?xCrx)O19 Cr(VI) compounds leaching test dynamic loading fracture mesoscale computer simulation discrete element method (DEM) corrosion MgO Cr2O3 refractory raw materials Cu slag XRD SEM Ti-bearing compounds CA6 spinel castables forsterite fly ash corrosion resistance refractory ceramics oxygen converter wear forecasting Bayesian statistics alumina-spinel metallurgical slag SEM/EDS biomass thermal processing wood ash sol-gel neural networks refractory material ladle modelling ceramic copper digital image computer analysis stereology machine learning MgO-C steel artificial neural networks ANN n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBC Engineering: general This reprint aims to immerse the reader into the latest developments in the technology of refractory materials. From the application of Artificial Intelligence and computer-aided methods, like machine learning or image analysis and the simulation of refractories’ properties and corrosion phenomena, to tailoring the properties of refractories to be more environmentally friendly, we aim to elucidate the current global trends and progress being made in refractories technology. This reprint has been created by world-recognized researchers, representing both academia and industry, striving jointly to make refractories safer and working for longer periods of time. Through this reprint, we demonstrate our major collaborative efforts to shift the technology to be more effective for the producers of refractory materials, more efficient for end-users, and, primarily, more sustainable in the interest of protecting our most precious shared asset—the safe planet Earth. 2024-07-04T09:43:27Z 2024-07-04T09:43:27Z 2024 book ONIX_20240704_9783725810895_131 9783725810895 9783725810901 https://directory.doabooks.org/handle/20.500.12854/139335 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/9332 https://mdpi.com/books/pdfview/book/9332 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-1090-1 10.3390/books978-3-7258-1090-1 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725810895 9783725810901 312 open access |
| spellingShingle | blast furnace carbon refractories molten metal infiltration X-ray computed tomography inorganic chemical binders refractories phosphates water glasses refractory castable hollow corundum microspheres bauxite aggregate thermal shock resistance micronized andalusite antioxidation Al2O3-SiC-C castables hot modulus of rupture metal-ceramic composites alginate gelation refractory metals computed tomography niobium refractory composite aggregate synthesis castable Al2O3-CaO-Cr2O3-O2 system (Al1?xCrx)2O3 Ca(Al12?xCrx)O19 Cr(VI) compounds leaching test dynamic loading fracture mesoscale computer simulation discrete element method (DEM) corrosion MgO Cr2O3 refractory raw materials Cu slag XRD SEM Ti-bearing compounds CA6 spinel castables forsterite fly ash corrosion resistance refractory ceramics oxygen converter wear forecasting Bayesian statistics alumina-spinel metallurgical slag SEM/EDS biomass thermal processing wood ash sol-gel neural networks refractory material ladle modelling ceramic copper digital image computer analysis stereology machine learning MgO-C steel artificial neural networks ANN n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBC Engineering: general Design, Manufacturing and Properties of Refractory Materials |
| title | Design, Manufacturing and Properties of Refractory Materials |
| title_full | Design, Manufacturing and Properties of Refractory Materials |
| title_fullStr | Design, Manufacturing and Properties of Refractory Materials |
| title_full_unstemmed | Design, Manufacturing and Properties of Refractory Materials |
| title_short | Design, Manufacturing and Properties of Refractory Materials |
| title_sort | design manufacturing and properties of refractory materials |
| topic | blast furnace carbon refractories molten metal infiltration X-ray computed tomography inorganic chemical binders refractories phosphates water glasses refractory castable hollow corundum microspheres bauxite aggregate thermal shock resistance micronized andalusite antioxidation Al2O3-SiC-C castables hot modulus of rupture metal-ceramic composites alginate gelation refractory metals computed tomography niobium refractory composite aggregate synthesis castable Al2O3-CaO-Cr2O3-O2 system (Al1?xCrx)2O3 Ca(Al12?xCrx)O19 Cr(VI) compounds leaching test dynamic loading fracture mesoscale computer simulation discrete element method (DEM) corrosion MgO Cr2O3 refractory raw materials Cu slag XRD SEM Ti-bearing compounds CA6 spinel castables forsterite fly ash corrosion resistance refractory ceramics oxygen converter wear forecasting Bayesian statistics alumina-spinel metallurgical slag SEM/EDS biomass thermal processing wood ash sol-gel neural networks refractory material ladle modelling ceramic copper digital image computer analysis stereology machine learning MgO-C steel artificial neural networks ANN n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBC Engineering: general |
| topic_facet | blast furnace carbon refractories molten metal infiltration X-ray computed tomography inorganic chemical binders refractories phosphates water glasses refractory castable hollow corundum microspheres bauxite aggregate thermal shock resistance micronized andalusite antioxidation Al2O3-SiC-C castables hot modulus of rupture metal-ceramic composites alginate gelation refractory metals computed tomography niobium refractory composite aggregate synthesis castable Al2O3-CaO-Cr2O3-O2 system (Al1?xCrx)2O3 Ca(Al12?xCrx)O19 Cr(VI) compounds leaching test dynamic loading fracture mesoscale computer simulation discrete element method (DEM) corrosion MgO Cr2O3 refractory raw materials Cu slag XRD SEM Ti-bearing compounds CA6 spinel castables forsterite fly ash corrosion resistance refractory ceramics oxygen converter wear forecasting Bayesian statistics alumina-spinel metallurgical slag SEM/EDS biomass thermal processing wood ash sol-gel neural networks refractory material ladle modelling ceramic copper digital image computer analysis stereology machine learning MgO-C steel artificial neural networks ANN n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBC Engineering: general |
| url | ONIX_20240704_9783725810895_131 |