A new component to the EI is an annual workshop with focus on various aspects of the broad area of damage prognosis. Each year the workshop rotates its focus between three technology areas essential to Damage Prognosis: 1) sensing and data acquisition, 2) data interrogation procedures, and 3) predictive modeling. The goal is to examine the state-of-the-art in research and practice of the various workshop themes through presentations and discussions. The outcome is a summary report documenting the current state-of-the-art in the chosen theme. Workshop reports and presentations will be made available online. As this series of workshops evolves, it is our intent that these documents taken together will provide a comprehensive overview of various research topics associated with damage prognosis.
“Modeling Turbine-Turbine interaction with Experimental Validation”
This workshop is hosted jointly by EI and the LANL Intelligent Wind Turbine (IWT) Project. The IWT Project is an internally funded, multi‐disciplinary wind turbine engineering R&D effort that is developing predictive models, advanced sensing technologies, novel data interrogation techniques, active performance control, and reliability‐based decision‐making algorithms. The workshop focus is modeling realistic turbine‐turbine interactions and validation of these models. One theme of interest is investigating modeling techniques that enable simulation of aeroelastic rotors exposed to realistic operating phenomena (e.g. rotating turbulent wakes, low‐level jets, gravity waves, and Kelvin‐Helmholtz instabilities). Interaction between turbines and surrounding atmosphere can generate highly variable and often cyclic loads on wind turbine blades and life‐reducing asymmetric loads on the rotor and gearbox. These interactions also impact the kinetic energy that is available for harvesting by downstream turbines. Another theme of interest is experimental approaches to obtaining both aerodynamic and structural data needed for system level model validation. Aerodynamic approaches include novel wind tunnel and field measurements of velocity and turbulence around rotating turbines, including PIV, LIDAR, and flow visualization. Structural approaches include the use of low‐ and high‐frequency, fiber optic, and acoustic sensing techniques.
Presentations
LANL IWT Team
Invited Speakers
“UAV, Sensors and Networks Workshop”
The goal of this internal workshop is to identy LANL's niche in unmanned aerial and ground vehicle technologies and their applications. Several presentations and discussion will be made with interests, capabilities, ideas, and customers, in these areas to see if LANL has a unique integrated contribution to make that can be captured in one or more white papers for distribution to possible sponsors.
“Validating Damage Evolution Models for Composite Materials”
The workshop focus for 2007 is the validation of models that simulate damage initiation and evolution in composite materials as well as the influence of that damage on system level performance. Of particular interest are approaches used for modeling damage in composite materials at widely varying length and time scales; experimental approaches to obtaining the material property data needed for such simulations; and system level model validation methodologies. Here validation refers to a broad set of techniques used to verify the accuracy of numerical algorithms; assess the source and level of numerical and experimental uncertainties; and provide quantitative comparisons between predictions and measurements.
Presentations
“Nonlinear System Identification for Damage Detection”
This workshop is intended to provide a review of examples from nonlinear dynamical systems theory and from nonlinear system identification techniques that are used for the feature extraction portion of the damage detection process. In many cases, damage causes a structure that initially behaves in a predominantly linear manner to exhibit nonlinear response when subject to its operating environment. The formation of cracks that subsequently open and close under operating loads is an example of such damage. The damage detection process can be significantly enhanced if one takes advantage of these nonlinear effects when extracting damage-sensitive features from measured data. This workshop is therefore intended to summarize damage detection methods rooted in nonlinear dynamics, and to provide a number of illustrations of complimentary approaches where damage-sensitive data features are based on nonlinear system response. These features, in turn, can either be used as a direct diagnosis of damage or as input to statistical damage classifiers. Finally, the workshop is to identify future research directions for the feature extraction portion of the damage detection process that are based on nonlinear system identification.
Workshop final Report "“Nonlinear system Identification for Damage Detection,” Los Alamos National Laboratory report (LA-14353).
Presentations
“Energy Harvesting for Embedded SHM Sensing Systems”
The focus of the first EI workshop is Energy harvesting for embedded SHM sensing networks. Various approaches to energy harvesting and storage mediums are discussed and limitations associated with the current technology are addressed. Several existing and emerging SHM sensing network paradigms, power requirements for these networks, and power optimization strategies are also discussed. Some future research directions and possible technology demonstrations that are aimed at transitioning the concept of energy harvesting for embedded SHM sensing systems from laboratory research to field-deployed engineering prototypes are finally defined.
The specific discussion topics for this workshop are identified,
1. Common SHM sensor network paradigms and their energy demands, energy harvesting applications, system integration
2. Energy conversion and storage strategies including commercial availability,
3. Grand challenges and future research topics in energy harvesting
Workshop final Report “Energy Harvesting for Structural Health Monitoring Sensor Networks,” Los Alamos National Laboratory report (LA-14314-MS).
Presentations
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