| Literature DB >> 35893943 |
Zhenhui Wang1,2, Rongxin Guo1,2, Guoshou Liu1, Luxin Guo1,2, Yong Yan1,2.
Abstract
Polyoxymethylene (POM) fiber is a new polymer fiber with the potential to improve the performance of airport pavement concrete. The effect of POM fiber on the flexural fatigue properties of concrete is an important issue in its application for airport pavement concrete. In this study, four-point flexural fatigue experiments were conducted using ordinary performance concrete (OPC) and POM fiber airport pavement concrete (PFAPC) with fiber volume contents of 0.6% and 1.2%, at four stress levels, to examine the flexural fatigue characteristics of these materials. A two-parameter Weibull distribution test of flexural fatigue life was performed, after examining the change in flexural fatigue deformation using the cycle ratio (n/N). A flexural fatigue life equation was then constructed considering various failure probabilities (survival rate). The results show that POM fiber had no discernible impact on the static load strength of airport pavement concrete, and the difference between PFAPC and OPC in terms of static load strength was less than 5%. POM fiber can substantially increase the flexural fatigue deformation capacity of airport pavement concrete by almost 100%, but POM fiber had a different degree of detrimental impact on the fatigue life of airport pavement concrete compared to OPC, with a maximum decrease of 85%. The fatigue lives of OPC and PFAPC adhered to the two-parameter Weibull distribution, the single- and double-log fatigue equations considering various failure probabilities had a high fitting degree based on the two-parameter Weibull distribution, and their R2 was essentially over 0.90. The ultimate fatigue strength of PFAPC was roughly 4% lower than that of OPC. This study on the flexural fatigue properties of POM fiber airport pavement concrete has apparent research value for the extension of POM fiber to the construction of long-life airport pavements.Entities:
Keywords: Weibull distribution function; airport pavement concrete; flexural fatigue; life prediction equation; polyoxymethylene fiber
Year: 2022 PMID: 35893943 PMCID: PMC9331626 DOI: 10.3390/polym14152979
Source DB: PubMed Journal: Polymers (Basel) ISSN: 2073-4360 Impact factor: 4.967
Comparison of fiber properties.
| Fiber Type | Density (g/cm3) | Strength (MPa) | Elongation Rate (%) | Modulus (GPa) |
|---|---|---|---|---|
| POM | 1.41 | 1000 | 15 | 8.5 |
| Glass | 2.7 | 736 | 2.45 | 80 |
| Carbon | 1.85 | 1770 | 0.1–0.2 | 180 |
| PP | 0.91 | 285–570 | 15–25 | 3.85 |
| Steel | 7.85 | 1100–1300 | 0.2 | 200 |
| Basalt | 2.65 | 4500 | 2.4–3.0 | 95–115 |
Physical and mechanical properties of POM fiber.
| Classification | Density (g/cm3) | Diameter (mm) | Strength (MPa) | Modulus (GPa) | Elongation Rate (%) | Length (mm) |
|---|---|---|---|---|---|---|
| Straight | 1.41 | 0.2 | 1000 | 8.5 | 15 | 12 |
Figure 1(a) Macro and (b) micro morphologies of POM fibers.
Mix ratio of airport pavement concrete.
| Specimen Type | W/B | Dosage by Volume Fraction (%) | Mix Ratio (kg·m−3) | |||||
|---|---|---|---|---|---|---|---|---|
| Binding Material | Water | Sand | Rough Stone (16~26.5 mm) | Fine Stone | Water Reducer | |||
| OPC | 0.37 | 0.0 | 383.23 | 155.97 | 565.87 | 886.53 | 433.84 | 2.11 |
| PFAPC-0.6 | 0.37 | 0.6 | 383.23 | 155.97 | 565.87 | 886.53 | 433.84 | 2.11 |
| PFAPC-1.2 | 0.37 | 1.2 | 383.23 | 155.97 | 565.87 | 886.53 | 433.84 | 2.11 |
Figure 2Loading setup photograph.
Figure 3Experimental flowchart.
Static mechanical properties of airport pavement concrete.
| Specimen Type | Compressive Strength (MPa) | Flexural Strength (MPa) | ||
|---|---|---|---|---|
| 28 d | 90 d | 28 d | 90 d | |
| OPC | 54.9 | 61.5 | 5.98 | 6.58 |
| PFAPC-0.6 | 50.4 | 67.8 | 6.06 | 6.72 |
| PFAPC-1.2 | 49.6 | 67.0 | 5.80 | 6.45 |
Figure 4Curves of specimen deformation with cyclic ratio: (a) maximum deflection at midspan; (b) average strain.
Fatigue test results.
| Specimen Type | Stress Level ( | Fatigue Life ( | ln | Stress Level ( | Fatigue Life ( | ln | Reliability ( | ln[ln(1/ |
|---|---|---|---|---|---|---|---|---|
| OPC | 0.65 | 1,857,013 | 14.43 | 0.70 | 678,544 | 13.43 | 0.833 | −1.7 |
| 2,134,386 | 14.57 | 810,497 | 13.61 | 0.667 | −0.904 | |||
| 2,721,339 | 14.82 | 1,049,851 | 13.86 | 0.5 | −0.367 | |||
| 3,148,897 | 14.96 | 1,126,098 | 13.93 | 0.333 | 0.095 | |||
| 3,799,215 | 15.15 | 1,964,998 | 14.49 | 0.167 | 0.582 | |||
| 0.75 | 143,424 | 11.87 | 0.80 | 2874 | 7.96 | 0.833 | −1.7 | |
| 160,161 | 11.98 | 3983 | 8.29 | 0.667 | −0.904 | |||
| 297,665 | 12.6 | 5791 | 8.66 | 0.5 | −0.367 | |||
| 495,713 | 13.11 | 8816 | 9.08 | 0.333 | 0.095 | |||
| 526,866 | 13.17 | 11,205 | 9.32 | 0.167 | 0.582 | |||
| PFAPC-0.6 | 0.65 | 1,587,895 | 14.28 | 0.70 | 200,820 | 12.21 | 0.833 | −1.7 |
| 1,783,115 | 14.39 | 222,100 | 12.31 | 0.667 | −0.904 | |||
| 1,906,017 | 14.46 | 498,761 | 13.12 | 0.5 | −0.367 | |||
| 2,390,813 | 14.69 | 579,841 | 13.27 | 0.333 | 0.095 | |||
| 2,743,466 | 14.82 | 667,508 | 13.41 | 0.167 | 0.582 | |||
| 0.75 | 20,921 | 9.95 | 0.80 | 1290 | 7.16 | 0.833 | −1.7 | |
| 45,949 | 10.74 | 1556 | 7.35 | 0.667 | −0.904 | |||
| 61,921 | 11.03 | 2798 | 7.94 | 0.5 | −0.367 | |||
| 63,512 | 11.06 | 3615 | 8.19 | 0.333 | 0.095 | |||
| 77,928 | 11.26 | 3862 | 8.26 | 0.167 | 0.582 | |||
| PFAPC-1.2 | 0.65 | 899,331 | 13.71 | 0.70 | 148,758 | 11.91 | 0.833 | −1.7 |
| 1,098,774 | 13.91 | 177,894 | 12.09 | 0.667 | −0.904 | |||
| 1,367,851 | 14.13 | 387,642 | 12.87 | 0.5 | −0.367 | |||
| 1,426,593 | 14.17 | 591,324 | 13.29 | 0.333 | 0.095 | |||
| 1,754,092 | 14.38 | 622,321 | 13.34 | 0.167 | 0.582 | |||
| 0.75 | 20,924 | 9.95 | 0.80 | 1395 | 7.24 | 0.833 | −1.7 | |
| 38,705 | 10.56 | 1775 | 7.48 | 0.667 | −0.904 | |||
| 41,334 | 10.63 | 2509 | 7.83 | 0.5 | −0.367 | |||
| 68,429 | 11.13 | 4559 | 8.42 | 0.333 | 0.095 | |||
| 71,754 | 11.18 | 5081 | 8.53 | 0.167 | 0.582 |
Figure 5Average fatigue life.
Figure 6Two-parameter Weibull distribution of fatigue life test results.
Linear regression analysis results.
| Specimen Type |
|
|
|
|
|
|---|---|---|---|---|---|
| OPC | 0.80 | 1.5765 | 14.1144 | 7731 | 0.9815 |
| 0.75 | 1.3832 | 17.8123 | 391,445 | 0.9073 | |
| 0.70 | 2.0635 | 29.0677 | 1,311,392 | 0.8811 | |
| 0.65 | 3.0131 | 45.0098 | 3,072,493 | 0.9762 | |
| PFAPC-0.6 | 0.80 | 1.7136 | 13.7908 | 3127 | 0.9299 |
| 0.75 | 1.6312 | 18.0887 | 65,460 | 0.8972 | |
| 0.70 | 1.4844 | 19.5544 | 526,128 | 0.8872 | |
| 0.65 | 3.8471 | 56.3491 | 2,297,196 | 0.9279 | |
| PFAPC-1.2 | 0.80 | 1.5133 | 12.4142 | 3653 | 0.9375 |
| 0.75 | 1.7214 | 18.8608 | 57,337 | 0.9463 | |
| 0.70 | 1.268 | 16.5623 | 470,617 | 0.9137 | |
| 0.65 | 3.41 | 48.4032 | 1,460,807 | 0.98 |
KS test results.
| Specimen Type |
|
|
| Result |
|---|---|---|---|---|
| OPC | 0.80 | 0.166 | 0.563 | Accept |
| 0.75 | 0.2213 | |||
| 0.70 | 0.2818 | |||
| 0.65 | 0.1502 | |||
| PFAPC-0.6 | 0.80 | 0.2379 | 0.563 | Accept |
| 0.75 | 0.2648 | |||
| 0.70 | 0.2408 | |||
| 0.65 | 0.2141 | |||
| PFAPC-1.2 | 0.80 | 0.1925 | 0.563 | Accept |
| 0.75 | 0.2296 | |||
| 0.70 | 0.2405 | |||
| 0.65 | 0.1976 |
Figure 7Average life S–N curve: (a) single-logarithm and (b) double-logarithm fatigue equations.
Equivalent fatigue life calculation results.
| Specimen Type |
| Fatigue Life | |||||
|---|---|---|---|---|---|---|---|
| 0.05 | 0.10 | 0.20 | 0.30 | 0.40 | 0.50 | ||
| OPC | 0.80 | 1175 | 1855 | 2986 | 4020 | 5049 | 6127 |
| 0.75 | 45,719 | 76,932 | 132,350 | 185,772 | 240,859 | 300,327 | |
| 0.70 | 310,893 | 440,665 | 633,939 | 795,715 | 947,016 | 1,097,980 | |
| 0.65 | 1,146,517 | 1,455,906 | 1,867,654 | 2,182,214 | 2,458,506 | 2,720,592 | |
| PFAPC-0.6 | 0.80 | 553 | 841 | 1303 | 1713 | 2113 | 2525 |
| 0.75 | 10,597 | 16,475 | 26,099 | 34,794 | 43,364 | 52,287 | |
| 0.70 | 71,137 | 115,530 | 191,536 | 262,706 | 334,628 | 411,017 | |
| 0.65 | 1,061,442 | 1,279,843 | 1,555,506 | 1,757,185 | 1,929,157 | 2,088,444 | |
| PFAPC-1.2 | 0.80 | 513 | 826 | 1356 | 1848 | 2344 | 2867 |
| 0.75 | 10,211 | 15,513 | 23,989 | 31,502 | 38,812 | 46,341 | |
| 0.70 | 45,224 | 79,783 | 144,189 | 208,723 | 277,076 | 352,481 | |
| 0.65 | 611,380 | 755,072 | 940,940 | 1,079,679 | 1,199,616 | 1,311,940 | |
Regression coefficients considering failure probability.
| Specimen Type |
|
|
|
| lg |
|
|
|---|---|---|---|---|---|---|---|
| OPC | 0.05 | 0.9577 | −0.0483 | 0.9461 | −0.0021 | −0.0288 | 0.9315 |
| 0.10 | 0.9715 | −0.0494 | 0.9328 | 0.0061 | −0.0295 | 0.9169 | |
| 0.20 | 0.9861 | −0.0505 | 0.9164 | 0.0146 | −0.0301 | 0.8991 | |
| 0.30 | 0.9952 | −0.0512 | 0.9047 | 0.0199 | −0.0305 | 0.8864 | |
| 0.40 | 1.0022 | −0.0517 | 0.8948 | 0.024 | −0.0308 | 0.8759 | |
| 0.50 | 1.008 | −0.0521 | 0.8859 | 0.0274 | −0.031 | 0.8664 | |
| PFAPC-0.6 | 0.05 | 0.9303 | −0.0465 | 0.9939 | −0.0176 | −0.028 | 0.9916 |
| 0.10 | 0.9438 | −0.0478 | 0.9934 | −0.0096 | −0.0287 | 0.9892 | |
| 0.20 | 0.958 | −0.049 | 0.9903 | −0.0012 | −0.0294 | 0.984 | |
| 0.30 | 0.967 | −0.0498 | 0.9869 | 0.004 | −0.0298 | 0.9793 | |
| 0.40 | 0.9738 | −0.0503 | 0.9834 | 0.008 | −0.0301 | 0.9748 | |
| 0.50 | 0.9796 | −0.0508 | 0.9798 | 0.0114 | −0.0304 | 0.9703 | |
| PFAPC-1.2 | 0.05 | 0.9391 | −0.0499 | 0.9855 | −0.0124 | −0.03 | 0.9824 |
| 0.10 | 0.9552 | −0.0515 | 0.9879 | −0.0028 | −0.0309 | 0.9828 | |
| 0.20 | 0.9721 | −0.053 | 0.9864 | 0.0071 | −0.0318 | 0.9791 | |
| 0.30 | 0.9826 | −0.0539 | 0.9831 | 0.0133 | −0.0323 | 0.9744 | |
| 0.40 | 0.9905 | −0.0545 | 0.9791 | 0.0179 | −0.0326 | 0.9694 | |
| 0.50 | 0.9971 | −0.055 | 0.9748 | 0.0218 | −0.0329 | 0.964 |
Figure 8P-S-N curve when survival probability P = 50% is considered under two-parameter Weibull distribution.
Figure 9P-S-N curve when survival probability P = 95% is considered under two-parameter Weibull distribution.
Ultimate fatigue strength under two-parameter Weibull distribution.
| Specimen Type | Equation Form | Ultimate Fatigue Strength (% | |
|---|---|---|---|
| OPC | 50 | Single logarithm | 68 |
| Double logarithm | 68 | ||
| 95 | Single logarithm | 65 | |
| Double logarithm | 65 | ||
| PFAPC-0.6 | 50 | Single logarithm | 66 |
| Double logarithm | 66 | ||
| 95 | Single logarithm | 64 | |
| Double logarithm | 64 | ||
| PFAPC-1.2 | 50 | Single logarithm | 65 |
| Double logarithm | 65 | ||
| 95 | Single logarithm | 63 | |
| Double logarithm | 63 |