This four-hour short course provides an introduction to fluids for aerospace hydraulic systems. Topics covered include an introduction to basics fluid properties, rheology, tribology, and fluid product development. In addition, the history and performance of different classes of fluids are discussed in detail, and specific failure modes such as erosion and sludge formation will be described. Along with an introduction to fluid degradation, information on used oil analysis test methods and interpretation will be provided.
Performance evaluation of martensitic press-hardened steels by VDA 238-100 three-point bend testing has become commonplace. Significant influences on bending performance exist from both surface considerations related to both decarburization and substrate-coating interaction and base martensitic steel considerations such as structural heterogeneity, i.e., banding, prior austenite grain size, titanium nitride (TiN) dispersion, mobile hydrogen, and the extent of martensite tempering as result auto-tempering upon quenching or paint baking during vehicle manufacturing. Deconvolution of such effects is challenging in practice, but it is increasingly accepted that surface considerations play an outsized role in bending performance. For specified surface conditions, however, the base steel microstructure can greatly influence bending performance and associated crash ductility to meet safety and mass-efficiency targets.
The importance of true fracture strain was initially highlighted in the context of local versus global formability considerations used in material selection among advanced high strength steels (AHSSs) of similar tensile strength. Inspired by the relative studies, a precedent work had compared the discrepant fracture strain results from the digital image correlation (DIC) and the optical measurement techniques. This work further investigated various factors, such as the measurement techniques, the effective strain formula, and the fracture surface morphology, which could affect the true fracture strain measurement and derivation results, and subsequently the calibration of the Generalized Incremental Stress State dependent damage Model (GISSMO) used in crash simulations. In the meantime, explanations and discussions on the possible mechanisms behind these effects were also presented.
The compression fatigue behavior of sheet metal trimming die is studied. The trim dies were manufactured or reconditions through different fabrication processes and heat treatment conditions. An accelerated lab testing method is developed to evaluate die damage resistance under compressive cyclic load applied at the tool edge, analogous to sheet metal trimming die operation. The metal removal volume at the sheared edges were measured by image processing to quantify the degree of fatigue damage as a function of loading cycle number. The fatigue microstructural damage were examined with optical and scanning electron microscopies. The simulated die performances are compared among different die processing routes. A phenomenological trim die damage rate model in Paris law form was obtained and tuned with experimental data for tool life prediction.
Padded self-piercing riveting (P-SPR) is a newly developed multi-material joining technology to enable less ductile materials to be joined by self-piercing riveting (SPR) without cracking. A deformable and disposable pad was employed to reduce the stress distribution on the bottom surface by supporting the whole bottom sheet continuously during rivet setting process. To verify the P-SPR process, 2.0mm thick 6061-T6 wrought aluminum was joined with 3.2mm thick coated AM60B magnesium high pressure die casting (HPDC) by using 1.0mm thick dual-phase 600 (DP600) steel as the pad. Regular SPR processes with 2 different die geometries were studied as a comparison. Compared to the regular SPR processes, P-SPR demonstrated advantages on coating protection, crack mitigation and joint strength.
Nowadays simulation of the fatigue life is an essential part of the development of components in the automotive and machinery industry. Weak points can be identified fast and reliable with respect to stiffness, strength and lightweight. A pure virtual optimization of the design can be performed without the need of prototypes. Only for the production release a final test is necessary. A lot of parameters influence the fatigue life as the local stress, material, surface roughness, size of the component, temperature etc. Notches have the strongest impact on fatigue life, depending on radius and shape. Stresses at the notch base are increased because the load flow is forced through a reduced cross section, or changes its direction around an inwardly curved edge. But notches cause not only an increase of the local stress. Also, the local fatigue strength is increased because of a support effect from the neighboring areas, where the stress is already reduced.
In engineering applications, rubber isolators are subjected to continuous alternating loads, resulting in fatigue failure. Although some theoretical models are used for the fatigue life estimation of rubber materials, they do not comprehensively consider the influences of multiple factors. In the present study, a model based on the extreme learning machine (ELM) is established to estimate fatigue life of natural rubber (NR) specimens. The mechanical load (engineering strain peak), ambient temperature (23℃, 60℃ and 90℃) and shore hardness (N45 and N50) of NR specimens are used as the input variables while the measure average fatigue life as the output variable of the ELM. The regression results and predicted life distribution of the established ELM model are encouraging. For comparison, the back propagation neural network (BPNN) model and the support vector machine (SVM) model are also implemented.
In order to enhance the efficiency of durability testing of automobile parts, a time-frequency domain accelerated editing method of road load time series of rubber mount on powertrain was discussed. Based on Stockwell Transform method and Accumulative Power Spectral Density, a new time-frequency domain accelerated editing method (ST-APSD) was proposed. The accumulative power spectral density was obtained by ST of the load time series signal of automobile powertrain rubber mounting force which is acquired by the real vehicle in the test field. Based on the accumulative power spectral density, the threshold value was proposed to identify and delete the small damage load fragments, and then the acceleration spectrum was obtained.