Quantitative mapping of service process-microstructural degradation-property deterioration for a Ni-based superalloy based on chord length distribution imaging process
Directionally solidified (DS) and single crystal (SC) Ni-based superalloys inevitably underwent microstructural degradation induced by the harsh operating environment. For the safety service and economic overhaul, constructing a quantitative mapping chain from service process to microstructural degr...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-05-01
|
| Series: | Materials & Design |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0264127521001143 |
| _version_ | 1818863577502580736 |
|---|---|
| author | Y.S. Fan X.G. Yang D.Q. Shi L. Tan W.Q. Huang |
| author_facet | Y.S. Fan X.G. Yang D.Q. Shi L. Tan W.Q. Huang |
| author_sort | Y.S. Fan |
| collection | DOAJ |
| description | Directionally solidified (DS) and single crystal (SC) Ni-based superalloys inevitably underwent microstructural degradation induced by the harsh operating environment. For the safety service and economic overhaul, constructing a quantitative mapping chain from service process to microstructural degradation and to property deterioration is critically essential. The present work started with stress-free and stress-assisted pre-service treatments of a DS Ni-based superalloy to obtain microstructures with different degraded states. An imaging process based on two-phase rotary chord length distributions was established to extract the high dimensional statistical information for identifying the morphology and size features of microstructures. To reduce the dimension of the statistical information and quantitatively characterize the microstructural states in fewer parameters, principal component analysis was employed to capture the core microstructural indicators, which was utilized to establish the response surface between the deterioration of fatigue resistance and the microstructural degradation. Finally, a multi-output support vector regression (SVR) model was constructed to map between service process and microstructural degradation. The results showed acceptable accuracy to estimate the microstructural degradation of pre-serviced alloys. Meanwhile, the framework provides a technical chain for the waste determination and microstructural degradation estimation of the hot section components made by DS and SC Ni-based superalloys. |
| first_indexed | 2024-12-19T10:17:58Z |
| format | Article |
| id | doaj.art-2f4281bd442348399ccea432f581ffbd |
| institution | Directory Open Access Journal |
| issn | 0264-1275 |
| language | English |
| last_indexed | 2024-12-19T10:17:58Z |
| publishDate | 2021-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Materials & Design |
| spelling | doaj.art-2f4281bd442348399ccea432f581ffbd2022-12-21T20:26:10ZengElsevierMaterials & Design0264-12752021-05-01203109561Quantitative mapping of service process-microstructural degradation-property deterioration for a Ni-based superalloy based on chord length distribution imaging processY.S. Fan0X.G. Yang1D.Q. Shi2L. Tan3W.Q. Huang4School of Energy and Power Engineering, Beihang University, Beijing 100191, ChinaSchool of Energy and Power Engineering, Beihang University, Beijing 100191, China; Corresponding author.School of Energy and Power Engineering, Beihang University, Beijing 100191, ChinaSchool of Energy and Power Engineering, Beihang University, Beijing 100191, ChinaSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaDirectionally solidified (DS) and single crystal (SC) Ni-based superalloys inevitably underwent microstructural degradation induced by the harsh operating environment. For the safety service and economic overhaul, constructing a quantitative mapping chain from service process to microstructural degradation and to property deterioration is critically essential. The present work started with stress-free and stress-assisted pre-service treatments of a DS Ni-based superalloy to obtain microstructures with different degraded states. An imaging process based on two-phase rotary chord length distributions was established to extract the high dimensional statistical information for identifying the morphology and size features of microstructures. To reduce the dimension of the statistical information and quantitatively characterize the microstructural states in fewer parameters, principal component analysis was employed to capture the core microstructural indicators, which was utilized to establish the response surface between the deterioration of fatigue resistance and the microstructural degradation. Finally, a multi-output support vector regression (SVR) model was constructed to map between service process and microstructural degradation. The results showed acceptable accuracy to estimate the microstructural degradation of pre-serviced alloys. Meanwhile, the framework provides a technical chain for the waste determination and microstructural degradation estimation of the hot section components made by DS and SC Ni-based superalloys.http://www.sciencedirect.com/science/article/pii/S0264127521001143Ni-based superalloyMicrostructural degradationService processProperty deteriorationChord length distributionMulti-output SVR |
| spellingShingle | Y.S. Fan X.G. Yang D.Q. Shi L. Tan W.Q. Huang Quantitative mapping of service process-microstructural degradation-property deterioration for a Ni-based superalloy based on chord length distribution imaging process Materials & Design Ni-based superalloy Microstructural degradation Service process Property deterioration Chord length distribution Multi-output SVR |
| title | Quantitative mapping of service process-microstructural degradation-property deterioration for a Ni-based superalloy based on chord length distribution imaging process |
| title_full | Quantitative mapping of service process-microstructural degradation-property deterioration for a Ni-based superalloy based on chord length distribution imaging process |
| title_fullStr | Quantitative mapping of service process-microstructural degradation-property deterioration for a Ni-based superalloy based on chord length distribution imaging process |
| title_full_unstemmed | Quantitative mapping of service process-microstructural degradation-property deterioration for a Ni-based superalloy based on chord length distribution imaging process |
| title_short | Quantitative mapping of service process-microstructural degradation-property deterioration for a Ni-based superalloy based on chord length distribution imaging process |
| title_sort | quantitative mapping of service process microstructural degradation property deterioration for a ni based superalloy based on chord length distribution imaging process |
| topic | Ni-based superalloy Microstructural degradation Service process Property deterioration Chord length distribution Multi-output SVR |
| url | http://www.sciencedirect.com/science/article/pii/S0264127521001143 |
| work_keys_str_mv | AT ysfan quantitativemappingofserviceprocessmicrostructuraldegradationpropertydeteriorationforanibasedsuperalloybasedonchordlengthdistributionimagingprocess AT xgyang quantitativemappingofserviceprocessmicrostructuraldegradationpropertydeteriorationforanibasedsuperalloybasedonchordlengthdistributionimagingprocess AT dqshi quantitativemappingofserviceprocessmicrostructuraldegradationpropertydeteriorationforanibasedsuperalloybasedonchordlengthdistributionimagingprocess AT ltan quantitativemappingofserviceprocessmicrostructuraldegradationpropertydeteriorationforanibasedsuperalloybasedonchordlengthdistributionimagingprocess AT wqhuang quantitativemappingofserviceprocessmicrostructuraldegradationpropertydeteriorationforanibasedsuperalloybasedonchordlengthdistributionimagingprocess |