No abstract

Major payoffs of new aerospace structures in terms of weight savings, performance, and life-cycle cost are anticipated from successful development of advanced materials. To aid in development of new alloy systems a method has been developed for predicting weight savings resulting from material (property set) improvements for specific failure modes in aircraft structures. Material properties include density, modulus of elasticity, strength, fatigue, crack growth, fracture toughness, and stress corrosion resistance. Weight savings analysis includes consideration of the margins of safety for various failure modes that could affect the size of the aircraft structure. Results of analysis applicable to a carrier-based patrol aircraft and an advanced tactical fighter indicate a weight savings potential of up to 16 percent for advanced aluminum alloys.

Models for mean considered in this study. 4.3. Models for scatter considered in this study. 4.4. Multiple tests of the models on the aluminum 2024-T4 data set .. 4.5. Multiple tests of the models on the Inconel 718 data set. 4.6. Multiple tests of the models on the AAW data set. .. 4.7. Multiple tests of the models on the Ti64 data set .... 4.8. Multiple tests of the models on the Ti64-300 data set. 4.9. Multiple tests of the models on the wire data set .... 4.10. 95 percentile of the chi-square variate X; ........ 4.11. Comparison of the models for the mean among survivors of the LRT 4.12. Comparion of the models for the scatter among survivors of the LRT 4.13.

A statistical analysis was performed on fatigue test data for aluminum, titanium, steel, and nickel materials. The data for the titanium, steel, and nickel were obtained from spectrum fatigue tests, whereas the data for aluminum were obtained from both constant amplitude and spectrum fatigue tests. The analyzed data consisted of a total of 553 S-N test groups with 2417 specimens and 1288 spectrum test groups with approximately 5000 specimens. The distribution of logarithmic standard deviation of fatigue life for these test groups was analyzed with normal, logarithmic, and two-parameter Weibull probability distribution functions and with 2-deg polynominal equations. The best fit was evaluated using the coefficient of correlation and the chi-squared goodness of fit test. None of the distribution functions or polynomial equations provided the best fit for all of the distributions of the logarithmic standard deviation of fatigue life for the selected sets of test groups. A comparison is also made of three methods of calculating scatter factors.

Fracture tests were conducted on precracked panels reinforced with various crack stoppers. Motion pictures and continuous graphical records of load and local strains were taken during the tests. The purpose of these tests was to study variables affecting residual strength of reinforced panels. Results show that, for 2024-T3 aluminum skin panels reinforced with riveted or bonded flat straps made of various alloys, the residual strength increases with the product of reinforcement area and reinforcement strength. Reinforcement stiffness, which is of primary importance for other classes of panel configurations, was found not to be a significant variable for the panel configurations tested. A crack opening displacement model is proposed to illustrate the influence of the reinforcements, the skin fracture toughness, and the slow stable tear characteristics on the arrest of a stably propagating crack. The model helps to elucidate the interactions between skin variables and reinforcement variables.