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SK GINOP_PLUSZ-2.1.3-24-2024-00028
The current literature suggests that both tools primarily excel at predicting trends, while the final accuracy is significantly influenced by scaling factors and sub-parameters—particularly mesh quality, material data, and process settings. These aspects become increasingly uncertain with the growing use of regranulated materials, especially in the automotive industry. For such materials, comprehensive material data is typically not available, unlike for traditional, well-established, and thoroughly tested compounds.
GINOP_Plusz-3.2.1-21
The current literature suggests that both tools primarily excel at predicting trends, while the final accuracy is significantly influenced by scaling factors and sub-parameters—particularly mesh quality, material data, and process settings. These aspects become increasingly uncertain with the growing use of regranulated materials, especially in the automotive industry. For such materials, comprehensive material data is typically not available, unlike for traditional, well-established, and thoroughly tested compounds.
GINOP-5.2.4-16
The current literature suggests that both tools primarily excel at predicting trends, while the final accuracy is significantly influenced by scaling factors and sub-parameters—particularly mesh quality, material data, and process settings. These aspects become increasingly uncertain with the growing use of regranulated materials, especially in the automotive industry. For such materials, comprehensive material data is typically not available, unlike for traditional, well-established, and thoroughly tested compounds.
GINOP-1.2.8-20
The current literature suggests that both tools primarily excel at predicting trends, while the final accuracy is significantly influenced by scaling factors and sub-parameters—particularly mesh quality, material data, and process settings. These aspects become increasingly uncertain with the growing use of regranulated materials, especially in the automotive industry. For such materials, comprehensive material data is typically not available, unlike for traditional, well-established, and thoroughly tested compounds.
GINOP-8.3.5-18
The current literature suggests that both tools primarily excel at predicting trends, while the final accuracy is significantly influenced by scaling factors and sub-parameters—particularly mesh quality, material data, and process settings. These aspects become increasingly uncertain with the growing use of regranulated materials, especially in the automotive industry. For such materials, comprehensive material data is typically not available, unlike for traditional, well-established, and thoroughly tested compounds.
