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We have performed an in-depth concept study of a gravitational wave dataanalysis method which targets repeated long quasi-monochromatic transients(triggers) from cosmic sources. The algorithm concept can be applied tomulti-trigger data sets in which the detector-source orientation and thestatistical properties of the data stream change with time, and does notrequire the assumption that the data is Gaussian. Reconstructing or limitingthe energetics of potential gravitational wave emissions associated withquasi-periodic oscillations (QPOs) observed in the X-ray lightcurve tails ofsoft gamma repeater flares might be an interesting endeavour of the future.Therefore we chose this in a simplified form to illustrate the flow,capabilities, and performance of the method. We investigate performance aspectsof a multi-trigger based data analysis approach by using O(100 s) longstretches of mock data in coincidence with the times of observed QPOs, and byusing the known sky location of the source. We analytically derive the PDF ofthe background distribution and compare to the results obtained by applying theconcept to simulated Gaussian noise, as well as off-source playground datacollected by the 4-km Hanford detector (H1) during LIGO's fifth science run(S5). We show that the transient glitch rejection and adaptive differentialenergy comparison methods we apply succeed in rejecting outliers in the S5background data. Finally, we discuss how to extend the method to a networkcontaining multiple detectors, and as an example, tune the method to maximizesensitivity to SGR 1806-20 flare times.

Detecting Long-Duration Narrow-Band Gravitational Wave Transients Associated with Soft Gamma Repeater Quasi-Periodic Oscillations