References for Data and Journal Articles
This neural network model uses data that was collected from multiple sources. Listed below are all the sources from where data was used to train the model shown on the home page. In each dropdown is a table providing context for each data source, a link to obtain the collective data file, and a list of references to journal articles discussed in the paper.
PPgNN v1
The complete data set used to train this model is accessible through Zenodo from here. Listed below is all the \(\langle 001 \rangle \) data collected from open literature.
Summary of \(\langle 001 \rangle \) data
| Reference | Material | SX or DS | Test Type | Dwell Type |
|---|---|---|---|---|
| Rodas, Gorgannejad, Neu9 | CMSX-8 | SX | IF | None, T, C |
| Amaro, Antolovich, Neu10 | PWA1484 | SX | TMF | None, C |
| Segersäll, Leidermark, Moverare11 | STAL-15 | SX | TMF | C |
| Segersäll, Deng12 | STAL-15 | SX | TMF | T |
| Lafata, Rettberg, He, Pollock13 | René N5 | SX | IF | C |
| Hong, Choi, Kim, Yoo, Jo14 | CMSX-4 | SX | IF | T&C |
| Hong, Kang, Choi, Kim, Yoo, Jo15 | CMSX-4 | SX | TMF | None |
| Hong, Yoon, Choi, Kim, Yoo, Jo16 | CMSX-4 | SX | TMF | None |
| Egly, Lang, Löhe17 | CMSX-4 | SX | TMF | T |
| Moverare, Johansson, Reed18 | CMSX-4 | SX | TMF | C |
| Ott, Mughrabi19 | CMSX-4, CSMX-6 | SX | IF | None |
| Okazaki, Take, Kakehi, Yamazaki, Sakane, Arai, et al.20 | CMSX-4, CM247LC | SX, DS | IF, TMF | None, C |
| Wahl, Harris21 | CMSX-4 PLUS | SX | IF | None |
| Yandt, Wu, Tsuno, Sato22 | LSC-11, CSMX-4 | SX | IF | None, C |
| Okazaki, Sakaguchi23 | CMSX-2, CSMX-4 | SX | IF, TMF | None |
| Wahl, Harris24 | CMSX-7, CMSX-8 | SX | IF | None |
| Reed, Moverare, Sato, Karlsson, Hasselqvist25 | STAL-15 | SX | TMF | C |
| Sato, Moverare, Hasselqvist, Reed26 | STAL-15 | SX | TMF | C |
| Segersäll, Kontis, Pedrazzini, Bagot, Moody, Moverare, et al.27 | STAL-15, STAL-15-Si, STAL-15-Re | SX | TMF | C |
| Moverare, Johansson28 | SCA425Hf | SX | TMF | C |
| Gabb, Gayda, Miner29 | René N4 | SX | IF | None |
| Yu, Sun, Jin, Zhao, Guan, Hu30 | SRR99 | SX | IF | None |
| Han, Yu, Sun, Hu31 | SRR99 | SX | TMF | None |
| Fleury, Rémy32 | AM1 | SX | IF | None |
| Estrada Rodas33 | CMSX-8 | SX | TMF | None |
| Shenoy, Gordon, McDowell, Neu34 | GTD-111 | DS | IF | None, T, C |
| Gordon35 | GTD-111 | DS | IF | None, T, C |
| Engler-Pinto, Jr., Noseda, Nazmy, Fezai-Aria36 | CM247LC | DS | TMF | None |
| Kirka37 | CM247LC | DS | IF, TMF | None, T, C |
| Kirka, Brindley, Neu, Antolovich, Shinde, Gravett38 | CM247LC | DS | IF, TMF | None, T, C |
| Guth, Petráš, Škorík, Kruml, Man, Lang, et al.39 | CM247LC | DS | TMF | None, T, C |
| Okazaki, Tabata, Nohmi40 | René 80H, CM247LC | DS | IF | None |
| Rai, Sahu, Das, Paulose, Fernando41 | CM247LC | DS | IF | None, T |
| Moore, Neu42 | CM247LC | DS | IF | None, C |
References
[1] Chen J, Liu Y. Fatigue modeling using neural networks: A comprehensive review. Fatigue Fract Eng Mater Struct. 2022;45: 945–979.
[2] Venkatesh V. A neural network approach to elevated temperature creep–fatigue life prediction. Int J Fatigue. 1999;21: 225–234.
[3] Zhang X-C, Gong J-G, Xuan F-Z. A deep learning based life prediction method for components under creep, fatigue and creep-fatigue conditions. Int J Fatigue. 2021;148: 106236.
[4] Chen CLP, Jinwoo Kim, Ten-Huei Guo. Monte Carlo Simulation for System Damage Prediction: An Example from Thermo-Mechanical Fatigue (TMF) Damage for a Turbine Engine. In: 2006 IEEE/SMC International Conference on System of Systems Engineering. IEEE; 2006:30–34.
[5] Schooling JM, Brown M, Reed PAS. An example of the use of neural computing techniques in materials science—the modelling of fatigue thresholds in Ni-base superalloys. Materials Science and Engineering: A. 1999;260: 222–239.
[6] Chen J, Liu Y. Probabilistic physics-guided machine learning for fatigue data analysis. Expert Syst Appl. 2021;168: 114316.
[7] Chen J, Liu Y. Physics-guided machine learning for multi-factor fatigue analysis and uncertainty quantification. In: AIAA Scitech 2021 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics; 2021.
[8] Chen J, Liu Y. Fatigue property prediction of additively manufactured Ti-6Al-4V using probabilistic physics-guided learning. Addit Manuf. 2021;39: 101876.
[9] Estrada Rodas EA, Gorgannejad S, Neu RW. Creep‐fatigue behaviour of single‐crystal Ni‐base superalloy CMSX‐8. Fatigue Fract Eng Mater Struct. 2019;42: 2155–2171.
[10] Amaro RL, Antolovich SD, Neu RW. Mechanism-based life model for out-of-phase thermomechanical fatigue in single crystal Ni-base superalloys. Fatigue Fract Eng Mater Struct. 2012;35: 658–671.
[11] Segersäll M, Leidermark D, Moverare JJ. Influence of crystal orientation on the thermomechanical fatigue behaviour in a single-crystal superalloy. Materials Science and Engineering: A. 2015;623: 68–77.
[12] Segersäll M, Deng D. A comparative study between in- and out-of-phase thermomechanical fatigue behaviour of a single-crystal superalloy. Int J Fatigue. 2021;146: 106162.
[13] Lafata MA, Rettberg LH, He MY, Pollock TM. Oxidation-Assisted Crack Growth in Single-Crystal Superalloys during Fatigue with Compressive Holds. Metallurgical and Materials Transactions A. 2018;49: 105–116.
[14] Hong HU, Choi BG, Kim IS, Yoo YS, Jo CY. Characterization of deformation mechanisms during low cycle fatigue of a single crystal nickel-based superalloy. J Mater Sci. 2011;46: 5245–5251.
[15] Hong HU, Kang JG, Choi BG, Kim IS, Yoo YS, Jo CY. A comparative study on thermomechanical and low cycle fatigue failures of a single crystal nickel-based superalloy. Int J Fatigue. 2011;33: 1592–1599.
[16] Hong HU, Yoon JG, Choi BG, Kim IS, Yoo YS, Jo CY. Localized microtwin formation and failure during out-of-phase thermomechanical fatigue of a single crystal nickel-based superalloy. Int J Fatigue. 2014;69: 22–27.
[17] Egly T, Lang K, Lohe D. Influence of phase shift and strain path on the thermomechanical fatigue behavior of CMSX-4 specimens. Int J Fatigue. 2008;30: 249–256.
[18] Moverare JJ, Johansson S, Reed RC. Deformation and damage mechanisms during thermal–mechanical fatigue of a single-crystal superalloy. Acta Mater. 2009;57: 2266–2276.
[19] Ott M, Mughrabi H. Dependence of the high-temperature low-cycle fatigue behaviour of the monocrystalline nickel-base superalloys CMSX-4 and CMSX-6 on the γ/γ′-morphology. Materials Science and Engineering: A. 1999;272: 24–30.
[20] Okazaki Masakazu, Take K, Kakehi K, Yamazaki Y. Collaborative research on thermo-mechanical and isothermal low-cycle fatigue strength of Ni-base superalloys and protective coatings at elevated temperatures in the society of materials science, Japan (JSMS). ASTM Special Technical Publication. 2003;4: 180–194.
[21] Wahl JB, Harris K. CMSX-4® Plus Single Crystal Alloy Development, Characterization and Application Development. In: Superalloys 2016. Hoboken, NJ, USA: John Wiley & Sons, Inc.; 2016:25–33.
[22] Yandt S, Wu X-J, Tsuno N, Sato A. Cyclic Dwell Fatigue Behaviour of Single Crystal Ni-Base Superalloys with/without Rhenium. In: Superalloys 2012. Hoboken, NJ, USA: John Wiley & Sons, Inc.; 2012:501–508.
[23] Okazaki M, Sakaguchi M. Thermo-mechanical fatigue failure of a single crystal Ni-based superalloy. Int J Fatigue. 2008;30: 318–323.
[24] Wahl JB, Harris K. New Single Crystal Superalloys, CMSX-7 and CMSX-8. In: Superalloys 2012. Hoboken, NJ, USA: John Wiley & Sons, Inc.; 2012:177–188.
[25] Reed RC, Moverare JJ, Sato A, Karlsson F, Hasselqvist M. A New Single Crystal Superalloy for Power Generation Applications. In: Superalloys 2012. Hoboken, NJ, USA: John Wiley & Sons, Inc.; 2012:197–204.
[26] Sato A, Moverare JJ, Hasselqvist M, Reed RC. On the Mechanical Behavior of a New Single-Crystal Superalloy for Industrial Gas Turbine Applications. Metallurgical and Materials Transactions A. 2012;43: 2302–2315.
[27] Segersäll M, Kontis P, Pedrazzini S, et al. Thermal–mechanical fatigue behaviour of a new single crystal superalloy: Effects of Si and Re alloying. Acta Mater. 2015;95: 456–467.
[28] Moverare JJ, Johansson S. Damage mechanisms of a high-Cr single crystal superalloy during thermomechanical fatigue. Materials Science and Engineering: A. 2010;527: 553–558.
[29] Gabb TP, Gayda J, Miner R v. Orientation and temperature dependence of some mechanical properties of the single-crystal nickel-base superalloy René N4: Part II. Low cycle fatigue behavior. Metallurgical Transactions A. 1986;17: 497–505.
[30] Yu J, Sun X, Jin T, Zhao N, Guan H, Hu Z. High temperature creep and low cycle fatigue of a nickel-base superalloy. Materials Science and Engineering: A. 2010;527: 2379–2389.
[31] Han GM, Yu JJ, Sun XF, Hu ZQ. Thermo-mechanical fatigue behavior of a single crystal nickel-based superalloy. Materials Science and Engineering: A. 2011;528: 6217–6224.
[32] Fleury E, Rémy L. Low cycle fatigue damage in nickel-base superalloy single crystals at elevated temperature. Materials Science and Engineering: A. 1993;167: 23–30.
[33] Estrada Rodas AE. Microstructure-Sensitive Creep-Fatigue Interaction Crystal-Viscoplasticity Model for Single-Crystal Nickel-Base Superalloys. Ph.D Dissertation, Georgia Institute of Technology, Atlanta, GA, USA. 2017.
[34] Shenoy MM, Gordon AP, McDowell DL, Neu RW. Thermomechanical Fatigue Behavior of a Directionally Solidified Ni-Base Superalloy. J Eng Mater Technol. 2005;127: 325–336.
[35] Gordon AP. Crack Initiation Modeling of a Directionally-Solidified Nickel-base Superalloy. Ph.D Dissertation, Georgia Institute of Technology, Atlanta, GA, USA. 2006.
[36] Engler-Pinto JCC, Noseda C, Nazmy MY, Rezai-Aria F. Interaction Between Creep and Thermo-Mechanical Fatigue of CM247LC-DS. In: Superalloys 1996 (Eighth International Symposium). TMS; 1996:319–325.
[37] Kirka M. Thermomechanical Behavior of a Directionally Solidified Nickel-base Superalloy in the Aged State. Ph.D Dissertation, Georgia Institute of Technology, Atlanta, GA, USA. 2014.
[38] Kirka MM, Brindley KA, Neu RW, Antolovich SD, Shinde SR, Gravett PW. Parameters influencing thermomechanical fatigue of a directionally-solidified Ni-base superalloy. Int J Fatigue. 2015;81: 48–60.
[39] Guth S, Petráš R, Škorík V, et al. Influence of dwell times on the thermomechanical fatigue behavior of a directionally solidified Ni-base superalloy. Int J Fatigue. 2015;80: 426–433.
[40] Okazaki M, Tabata T, Nohmi S. Intrinsic stage i crack growth of directionally solidified Ni-Base superalloys during low-cycle fatigue at elevated temperature. Metallurgical Transactions A. 1990;21: 2201–2208.
[41] Rai RK, Sahu JK, Das SK, Paulose N, Fernando C. Creep‐fatigue deformation micromechanisms of a directionally solidified nickel‐base superalloy at 850°C. Fatigue Fract Eng Mater Struct. 2020;43: 51–62.
[42] Moore ZJ, Neu RW. Creep fatigue of a directionally solidified Ni-base superalloy - smooth and cylindrically notched specimens. Fatigue Fract Eng Mater Struct. 2011;34: 17–31.
[43] Kingma D, Ba J. Adam: A Method for Stochastic Optimization. In: International Conference on Learning Representations. San Diego: 3rd International Conference on Learning Representations; 2014.
[44] Ruder S. An Overview of Gradient Descent Optimization Algorithms. arXiv preprint arXiv:1609.04747. September 2016.
[45] Scardapane S, Wang D. Randomness in neural networks: an overview. WIREs Data Mining and Knowledge Discovery. 2017;7: 18.
[46] Arrell D, Hasselqvist M, Sommer C, Moverare J. On TMF Damage, Degradation Effects, and the Associated T-Min Influence on TMF Test Results in y/y Al. In: Superalloys 2004 (Tenth International Symposium). TMS; 2004:291–294.
[47] Arakere NK, Orozco E. Analysis of Low Cycle Fatigue Properties of Single Crystal Nickel-Base Turbine Blade Superalloys. High Temperature Materials and Processes. 2001;20: 403–419.
[48] Segersäll M, Moverare JJ, Simonsson K, Johansson S. Deformation and Damage Mechanisms during Thermomechanical Fatigue of a Single-crystal Superalloy in the <001> and <011> Directions. In: Superalloys 2012 (Twelfth International Symposium). John Wiley & Sons, Inc.; 2012:215–223.
[49] Liu L, Meng J, Liu J, Zhang H, Sun X, Zhou Y. Investigation on low cycle fatigue behaviors of the [001] and [011] oriental single crystal superalloy at 760 °C. Materials Science and Engineering: A. 2018;734: 1–6.
[50] Kirka MM, Brindley KA, Neu RW, Antolovich SD, Shinde SR, Gravett PW. Influence of coarsened and rafted microstructures on the thermomechanical fatigue of a Ni-base superalloy. Int J Fatigue. 2015;81: 191–201.
PPgNN v2
The complete data set used to train this version of the model is accessible through Zenodo from here. This version uses the same \(\langle 001 \rangle \) data from the PPgNN v1 model. Listed below is all the non-\(\langle 001 \rangle \) data collected from open literature.
Summary of non-\(\langle 001 \rangle \) data
| Reference | Material | SX or DS | Orientation | Test Type | Dwell Type |
|---|---|---|---|---|---|
| Rodas, Gorgannejad, Neu6 | CMSX-8 | SX | \(\langle 111 \rangle \) | IF | None, T, C |
| Amaro, Antolovich, Neu45 | PWA1484 | SX | \(\langle 111 \rangle \langle 123 \rangle \) | TMF | None |
| Segersäll, Leidermark, Moverare9 | STAL-15 | SX | \(\langle 122 \rangle \langle 023 \rangle \) | TMF | C |
| Segersäll, Deng10 | STAL-15 | SX | \(\langle 122 \rangle \) | TMF | T |
| Gabb, Gayda, Miner3 | René N5 | SX | \(\langle 011 \rangle \langle 111 \rangle \langle 236 \rangle \langle 023 \rangle \langle 145 \rangle \) | IF | None |
| Fleury, Rémy4 | AM1 | SX | \(\langle 111 \rangle \langle 011 \rangle \langle 213 \rangle \) | IF | None |
| Gordon 66 | GTD-111 | DS | 90° | IF, TMF | None, T, C |
| Kirka68 | CM247LC | DS | 90° | TMF | None, T, C |
| Kirka, Brindley, Neu, Antolovich, Shinde, Gravett14 | CM247LC | DS | 90° | TMF | None, T, C |
| Moverare, Johansson, Reed13 | CM247LC | DS | 90° | IF | None, T, C |
References
[1] Manson, S.S. and G.R. Halford, Fatigue and Durability of Metals at High Temperature. 2009, Materials Park, OH, USA: ASM International.
[2] Acharya R, Caputo AN, Neu RW. Predicting creep-fatigue and thermomechanical fatigue life of Ni-base superalloys using a probabilistic physics-guided neural network. Fatigue Fract Eng Mater Struct 2023;46(4):1554–71.
[3] ] Gabb TP, Gayda J, Miner RV. Orientation and temperature dependence of some mechanical properties of the single-crystal nickel-base superalloy Rene N4: part ii. low cycle fatigue behavior. Metall Trans A 1986;17A:497–505.
[4] Fleury E, Remy L. Low cycle fatigue damage in nickel-base superalloy single crystals at elevated temperature. Mater Sci Eng A 1993;167(1–2):23–30.
[5] Segersall M, et al. Deformation and damage mechanisms during thermomechanical fatigue of a single-crystal superalloy in the <001> and <011> directions. In: Huron ES, editor. Superalloys 2012: 12th International Symposium on Superalloys. Seven Springs, PA: TMS; 2012. p. 215–23.
[6] Estrada Rodas EA, Gorgannejad S, Neu RW. Creep-fatigue behaviour of singlecrystal Ni-base superalloy CMSX-8. Fatigue Fract Eng Mater Struct 2019;42(9): 2155–71.
[7] Reed RC. The Superalloys: Fundamentals and Applications. Cambridge: Cambridge University Press; 2006.
[8] Estrada Rodas EA, Neu RW. Crystal viscoplasticity model for the creep-fatigue interactions in single-crystal Ni-base superalloy CMSX-8. Int J Plast 2018;100 (Supplement C):14–33.
[9] Segersall M, Leidermark D, Moverare JJ. Influence of crystal orientation on the thermomechanical fatigue behaviour in a single-crystal superalloy. Mater Sci Eng A 2015;623:68–77.
[10] Segersall M, Deng D. A comparative study between in- and out-of-phase thermomechanical fatigue behaviour of a single-crystal superalloy. Int J Fatigue 2021;146:106162.
[11] Hasebe T, Sakane M, Ohnami M. High temperature low cycle fatigue and cyclic constitutive relation of Mar-M247 directionally solidified superalloy. J Eng Mater Technol 1992;114:162–7.
[12] Kupkovits RA, Neu RW. Thermomechanical fatigue of a directionally-solidified Nibase superalloy: smooth and cylindrically-notched specimens. Int J Fatigue 2010; 32:1330–42.
[13] Moore ZJ, Neu RW. Creep fatigue of a directionally solidified Ni-base superalloy - smooth and cylindrically notched specimens. Fatigue Fract Eng Mater Struct 2010; 34:17–31.
[14] Kirka MM, et al. Parameters influencing thermomechanical fatigue of a directionally-solidified Ni-base superalloy. Int J Fatigue 2015;81:48–60.
[15] Barnard NC, et al. Low cycle fatigue of CMSX-4 in off-axis orientations and the effect of a multi-axial stress state. In: Huron ES, editor. Superalloys 2012: 12the International Symposium on Superalloys. Seven Springs, PA: TMS; 2012.p. 293–300.
[16] Venkatesh V, Rack HJ. A neural network approach to elevated temperature creep–fatigue life prediction. Int J Fatigue 1999;21(3):225–34.
[17] Zhang X-C, Gong J-G, Xuan F-Z. A deep learning based life prediction method for components under creep, fatigue and creep-fatigue conditions. Int J Fatigue 2021; 148:106236.
[18] Xu L, et al. A data-driven low-cycle fatigue life prediction model for nickel-based superalloys. Comput Mater Sci 2023;229:112434.
[19] Bartosak M. Using machine learning to predict lifetime under isothermal low-cycle fatigue and thermo-mechanical fatigue loading. Int J Fatigue 2022;163:107067.
[20] Chen CLP, Kim J, Guo TH. Monte Carlo simulation for system damage prediction: an example from thermo-mechanical fatigue (TMF) damage for a turbine engine. 2006 IEEE/SMC International Conference on System of Systems Engineering. IEEE; 2006.
[21] Pinz M, et al. Data-driven Bayesian model-based prediction of fatigue crack nucleation in Ni-based superalloys. npj Comput Mater 2022;8(1):39.
[22] Liu Y, et al. Predicting creep rupture life of Ni-based single crystal superalloys using divide-and-conquer approach based machine learning. Acta Mater 2020;195:454–67.
[23] Wang X, Chen H, Xuan F. Neural network-assisted probabilistic creep-fatigue assessment of hydrogenation reactor with physics-based surrogate model. Int J Pressure Vessels Piping 2023;206:105051.
[24] Zhang X-C, Gong J-G, Xuan F-Z. A physics-informed neural network for creepfatigue life prediction of components at elevated temperatures. Eng Fract Mech 2021;258:108130.
[25] Deng X, et al. Physics-informed machine learning framework for creep-fatigue life prediction of a Ni-based superalloy using ensemble learning. Mater Today Commun 2024;41:110260.
[26] Zhang S, et al. Physics-informed neural network for creep-fatigue life prediction of Inconel 617 and interpretation of influencing factors. Mater Des 2024;245:113267.
[27] Chen J, Liu Y. Probabilistic physics-guided machine learning for fatigue data analysis. Expert Syst Appl 2021;168:114316.
[28] Chen J, Liu Y. Fatigue property prediction of additively manufactured Ti-6Al-4V using probabilistic physics-guided learning. Addit Manuf 2021;39:101876.
[29] Zhou T, et al. A physically consistent framework for fatigue life prediction using probabilistic physics-informed neural network. Int J Fatigue 2023;166:107234.
[30] Wang L, et al. Physics-guided machine learning frameworks for fatigue life prediction of AM materials. Int J Fatigue 2023;172:107658.
[31] Chen J, Liu Y. Fatigue modeling using neural networks: A comprehensive review. Fatigue Fract Eng Mater Struct 2022;45:945–79.
[32] He L, et al. Fatigue life evaluation model for various austenitic stainless steels at elevated temperatures via alloy features-based machine learning approach. Fatigue Fract Eng Mater Struct 2023;46(2):699–714.
[33] Liu Y-K, et al. Data-driven approach to very high cycle fatigue life prediction. Eng Fract Mech 2023;292:109630.
[34] Raissi M, Perdikaris P, Karniadakis GE. Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. J Comput Phys 2019;378:686–707.
[35] Jiang L, et al. Physics-informed machine learning for low-cycle fatigue life prediction of 316 stainless steels. Int J Fatigue 2024;182:108187.
[36] Chen J, Liu Y. Physics-guided machine learning for multi-factor fatigue analysis and uncertainty quantification. Virtual: AIAA; 2021.
[37] Chen D, et al. A physics-informed neural network approach to fatigue life prediction using small quantity of samples. Int J Fatigue 2023;166:107270.
[38] Ciampaglia A, et al. Data driven method for predicting the effect of process parameters on the fatigue response of additive manufactured AlSi10Mg parts. Int J Fatigue 2023;170:107500.
[39] ASTM E606/E606M-21, Standard Test Method for Strain-Controlled Fatigue Testing. 2021, ASTM International.
[40] Rai RK, et al. Creep-fatigue deformation micromechanisms of a directionally solidified nickel-base superalloy at 850◦C. Fatigue Fract Eng Mater Struct 2020;43 (1):51–62.
[41] Astm. E2714-13, Standard Test Method for Creep-Fatigue Testing. ASTM International; 2013.
[42] ASTM E2368-10, Standard Practice for Strain Controlled Thermomechanical Fatigue Testing. 2010, ASTM International.
[43] ISO, ISO 12111:2011 Metallic materials - Fatigue testing - Strain-controlled thermomechanical fatigue testing method. 2011.
[44] Neu, R.W., Compilation of LCF and TMF Data for Single-Crystal and DirectionallySolidified Ni-base Superalloys (All Orientations). 2024: Zenodo (https://doi.org/10.5281/zenodo.13152005).
[45] Amaro RL, Antolovich SD, Neu RW. Mechanism-based life model for out-of-phase thermomechanical fatigue in single crystal Ni-base superalloys. Fatigue Fract Eng Mater Struct 2012;35:658–71.
[46] Lafata MA, et al. Oxidation-assisted crack growth in single-crystal superalloys during fatigue with compressive holds. Metall Mater Trans A 2018;49(1):105–16.
[47] Hong HU, et al. Characterization of deformation mechanisms during low cycle fatigue of a single crystal nickel-based superalloy. J Mater Sci 2011;46(15):5245–51.
[48] Hong HU, et al. A comparative study on thermomechanical and low cycle fatigue failures of a single crystal nickel-based superalloy. Int J Fatigue 2011;33(12):1592–9.
[49] Hong HU, et al. Localized microtwin formation and failure during out-of-phase thermomechanical fatigue of a single crystal nickel-based superalloy. Int J Fatigue 2014;69:22–7.
[50] Egly TA, Lang KH, Lohe ¨ D. Influence of phase shift and strain path on the thermomechanical fatigue behavior of CMSX-4 specimens. Int J Fatigue 2008;30(2):249–56.
[51] Moverare JJ, Johansson S, Reed RC. Deformation and damage mechanisms during thermal–mechanical fatigue of a single-crystal superalloy. Acta Mater 2009;57(7):2266–76.
[52] Ott M, Mughrabi H. Dependence of the high-temperature low-cycle fatigue behaviour of the monocrystalline nickel-base superalloys CMSX-4 and CMSX-6 on the [gamma]/[gamma]’-morphology. Mater Sci Eng A 1999;272(1):24–30.
[53] Okazaki M, et al. Collaborative Research on Thermo-Mechanical and Isothermal Low-Cycle Fatigue Strength of Ni-Base Superalloys and Protective Coatings at Elevated Temperatures in The Society of Materials Science, Japan (JSMS). In: McGaw MA, editor. Thermomechanical Fatigue Behavior of Materials: 4th Volume, ASTM STP 1428. West Conshohocken, PA: ASTM International; 2002. p. 180–94.
[54] Wahl JB, Harris K. CMSX-4 Plus Single Crystal Alloy Development, Characterization and Application Development. Superalloys. PA, USA: TMS: Seven Springs; 2016.
[55] Yandt, S., et al., Cyclic dwell fatigue behaviour of single crystal Ni-base superalloys with/without rhenium, in Superalloys 2012, E.S. Huron, et al., Editors. 2012, TMS: Seven Springs Mountain Resort, Seven Springs, PA. p. 501-508.
[56] Okazaki M, Sakaguchi M. Thermo-mechanical fatigue failure of a single crystal Nibased superalloy. Int J Fatigue 2008;30:318–23.
[57] Wahl, J.B. and K. Harris. New single crystal superalloys, CMSX-7 and CMSX-8. in Superalloys 2012: 12th International Symposium on Superalloys. 2012. Seven Springs Mountain Resort, Champion, PA: TMS.
[58] Reed RC, et al. A new single crystal superalloy for power generation applications. Superalloys. PA TMS: Seven Springs; 2012.
[59] Sato A, et al. On the mechanical behavior of a new single-crystal superalloy for industrial gas turbine applications: physical metallurgical and materials science. Metall Mater Trans 2012;43(7):2302–15.
[60] Segersall M, et al. Thermal–mechanical fatigue behaviour of a new single crystal superalloy: effects of Si and Re alloying. Acta Mater 2015;95:456–67.
[61] Moverare JJ, Johansson S. Damage mechanisms of a high-Cr single crystal superalloy during thermomechanical fatigue. Mater Sci Eng A 2010;527(3):553–8.
[62] Yu J, et al. High temperature creep and low cycle fatigue of a nickel-base superalloy. Mater Sci Eng A 2010;527(9):2379–89.
[63] Han GM, et al. Thermo-mechanical fatigue behavior of a single crystal nickel-based superalloy. Mater Sci Eng A 2011;528(19):6217–24.
[64] Estrada Rodas EA. Microstructure-Sensitive Creep-Fatigue Interaction CrystalViscoplasticity Model for Single-Crystal Nickel-Base Superalloys. Woodruff School of Mechanical Engineering. Atlanta, GA: Georgia Institute of Technology; 2017.
[65] Shenoy MM, et al. Thermomechanical fatigue behavior of a directionally solidified Ni-base superalloy. J Eng Mater Technol 2005;127:325–36.
[66] Gordon, A.P., Crack Initiation Modeling of a Directionally-Solidified Nickel-base Superalloy, in Mechanical Engineering. 2006, Georgia Institute of Technology: Atlanta, GA, USA.
[67] Engler-Pinto, C.C., Jr., et al., Interaction between Creep and Thermo-Mechanical Fatigue of CM247LC-DS, in Superalloys 1996, R.D. Kissinger, et al., Editors. 1996, The Minerals, Metals & Materials Society. p. 319-325.
[68] Kirka MM. Thermomechanical Behavior of a Directionally Solidified Nickel-base Superalloy in the Aged State. Atlanta GA USA: Mechanical Engineering. Georgia Institute of Technology; 2014.
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