Important menu

Partners

Prof. Jan D. Achenbach

 

Biography of Prof. Jan D. Achenbach


Professor Achenbach has been a faculty member at Northwestern University since 1963, where he is currently Professor of Dept. of Mechanical Engineering and honored as Walter P. Murphy Professor and Distinguished McCormick School Professor. He is Member of National Academy of Engineering. U.S. (since 1982), Member of National Academy of Sciences. U.S. (since 1992) and he gained U.S. National Medal of Technology in 2003, U.S. National Medal of Science in 2005. He is also served as Consulting Professor in Huazhong Institute of Science and Technology, China since September 1981.


Professor Achenbach has developed methods for flaw detection and characterization by using contact transducers, imaging techniques and laser-based ultrasonics. He has also developed methods for thin-layer characterization by acoustic microscopy. Work is both analytical and experimental in nature, with extensive cooperation with investigators from other universities and from industrial organizations on theoretical experimental projects. Work in fracture mechanics has been primarily on dynamic fracture. He also carries out research on structural acoustics and on the mechanical behavior of composite materials.


Homepage of Professor Achenbach


Professor Achenbach will give a lecture on:



Probabilistic Considerations for Growth and Detection of Fatigue Cracks and Impact-Generated Delaminations in Aircraft Structures




Diagnostic techniques provide the input for prognostics. Modeling of constitutive properties, supported by experimental results, provides damage growth laws which in turn provide information on damage evolution and remaining life. Depending on its magnitude, the resulting statement of failure probability may either result in a recommendation for repair or replacement of a structural component, or for an additional cycle in the diagnostics/prognostics loop of the structural health management system.


In this lecture, I will devote particular attention to the probabilistic aspects of diagnostics and prognostics. Probabilistic considerations play a dominant role in the four stages of the diagnostics and prognostics of fatigue damage in metals. Considerable attention has been given to the evolution and detection of pre-crack fatigue damage and probabilistic aspects of subsequent macrocrack formation (Stage 1). For Stage 2 (macrocrack growth and detection), Paris’s law for crack growth under cyclic loading conditions can be useful, particularly if placed in a probabilistic context. By introducing the probability of detection concept, various probabilities related to the existence, after N cycles, of a crack larger than critical size, some based on a Bayesian approach, can be determined in Stage 3 for the purposes of prognostication. An example is given for fatigue cracks emanating from rivet holes in a lap joint. An analogous probabilistic approach will be presented for the generation of delaminations in laminated fiber-epoxy composites by repeated impact loads.


Significant progress in QNDE has been achieved. On the other hand, SHM has not yet broken through in a big way. SHM systems are often not yet affordably maintainable with near-zero false alarm rates. Huge benefits can, however, be achieved if SHM can justify reduced design margins, longer life spans and reduced service interruptions.