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Proceedings of the Third International Workshop on Jointed Structures

Starr, Michael J.; Brake, Matthew R.; Segalman, Daniel J.

The Third International Workshop on Jointed Structures was held from August 16th to 17th, 2012, in Chicago Illinois, following the ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Thirty two researchers from both the United States and international locations convened to discuss the recent progress of mechanical joints related research and associated efforts in addition to developing a roadmap for the challenges to be addressed over the next five to ten years. These proceedings from the workshop include the minutes of the discussions and follow up from the 2009 workshop [1], presentations, and outcomes of the workshop. Specifically, twelve challenges were formulated from the discussions at the workshop, which focus on developing a better understanding of uncertainty and variability in jointed structures, incorporating high fidelity models of joints in simulations that are tractable/efficient, motivating a new generation of researchers and funding agents as to the importance of joint mechanics research, and developing new insights into the physical phenomena that give rise to energy dissipation in jointed structures. The ultimate goal of these research efforts is to develop a predictive model of joint mechanics.

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TYPE SAND Report YEAR 2013
OSTIDOI

Probability distribution of von Mises stress in the presence of pre-load

Segalman, Daniel J.; Field, Richard V.; Reese, Garth M.

Random vibration under preload is important in multiple endeavors, including those involving launch and re-entry. There are some methods in the literature to begin to address this problem, but there is nothing that accommodates the existence of preloads and the necessity of making probabilistic statements about the stress levels likely to be encountered. An approach to achieve to this goal is presented along with several simple illustrations.

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TYPE SAND Report YEAR 2013
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A robust approach to QMU, validation, and conservative prediction

Segalman, Daniel J.; Bauman, Lara E.

A systematic approach to defining margin in a manner that incorporates statistical information and accommodates data uncertainty, but does not require assumptions about specific forms of the tails of distributions is developed. This approach extends to calculations underlying validation assessment and quantitatively conservative predictions.

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TYPE SAND Report YEAR 2013
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An empirical relationship for extrapolating sparse experimental lap joint data

Journal of Applied Mechanics, Transactions ASME

Starr, Michael J.; Segalman, Daniel J.

Correctly incorporating the influence of mechanical joints in built-up mechanical systems is a critical element for model development for structural dynamics predictions. Quality experimental data are often difficult to obtain and is rarely sufficient to determine fully parameters for relevant mathematical models. On the other hand, fine-mesh finite element (FMFE) modeling facilitates innumerable numerical experiments at modest cost. Detailed FMFE analysis of built-up structures with frictional interfaces reproduces trends among problem parameters found experimentally, but there are qualitative differences. Those differences are currently ascribed to the very approximate nature of the friction model available in most finite element codes. Though numerical simulations are insufficient to produce qualitatively correct behavior of joints, some relations, developed here through observations of a multitude of numerical experiments, suggest interesting relationships among joint properties measured under different loading conditions. These relationships can be generalized into forms consistent with data from physical experiments. One such relationship, developed here, expresses the rate of energy dissipation per cycle within the joint under various combinations of extensional and clamping load in terms of dissipation under other load conditions. The use of this relationship - though not exact - is demonstrated for the purpose of extrapolating a representative set of experimental data to span the range of variability observed from real data. © 2011 American Society of Mechanical Engineers.

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TYPE Conference YEAR 2011
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Results 1–25 of 72
Results 1–25 of 72