Source: https://groups.oist.jp/nnp/fy2016-annual-report
Timestamp: 2019-04-22 02:40:47+00:00

Document:
Dr. Makoto Araki, Neuronal Mechanism for Critical Period Unit, OIST Graduate University.
Mahesh M. Bandi, Collective Interactions Unit, OIST Graduate University.
Bird song prosody concerns emergence of species-specific learning from the basic features of bird song. Songbirds must simultaneously meet two competing demands: their song must be similar enough to one's own species, yet unique from that of other males within one's species to attract a mate. In a behavioral neuroscience experiment co-designed with my colleague Y. Yazaki-Sugiyama (OIST), we discovered a class of neurons in the Zebra finch auditory cortex, that register silent temporal gaps between song syllables, and were distinct from neurons encoding syllable morphology of the song. Combining behavioral experiments and electrophysiological measurements with information theory, we showed gaps between song syllables are genetically hardwired for inter-species discrimination, whereas song syllables learned from tutors provide the necessary intra-species diversity among songbirds. The experiments were conducted by Prof. Yazaki-Sugiyama's group with data analysis and theoretical contributions from our group.
Wind Energy is a timely and relevant problem, where the fluid dynamics community's efforts have been primarily engaged towards improving individual turbine or collective plant efficiency. We have undertaken a critical analysis of wind power fluctuations. The power generated by a wind turbine fluctuates with varying wind speed and indeed, its spectrum reflects the Kolmogorov spectrum of atmospheric turbulence; both vary with fluctuation time scale τ as τ2/3 . This variability decreases when geographically distributed wind farms feed power to the grid and aggregate power fluctuations are averaged (geographic smoothing). Despite costs associated with variability, neither the τ2/3 wind power fluctuation scaling nor the geographic smoothing mechanism are understood. In this work, we have explained the wind power fluctuation spectrum from the turbine through grid scales. In particular, we theoretically deduced, and experimentally validated that the τ2/3 scaling of wind power fluctuations results from the largest length scales of atmospheric turbulence (~100s of km) influencing the small scales where individual turbines operate. This long-range influence correlates geographically distributed wind farm power outputs over a range of time scales that falls with the inter-farm distance. Consequently, we deduced that aggregate grid-scale power fluctuations smooth until they reach a limiting τ4/3 spectrum, and showed that regional grids have already hit this spectral bound. Through this theoretical framework it becomes possible to tackle several engineering and policy questions in renewable energy such as what are the fluctuation magnitudes that grid operators must account for in the design of smartgrids, or what are the back up storage options one must plan for to further smooth out fluctuations etc.
Mahesh M. Bandi and Jay Apt, "Variability of the Wind Turbine Power Curve, Appl. Sci. 6, 262 (2016).
N. Iikawa, M. M. Bandi, and H. Katsuragi, "Sensivity of Granular Force Chain Orientation to Disorder-induced Metastable Relaxation", Phys. Rev. Lett. 116, 128001 (2016).
G. Bel, C. P. Connaughton, M. Toots, and MM Bandi, "Grid-scale fluctuations and forecast error in wind power, "New J. Phys. 18, 023015 (2016).
Akella, V. S., Singh, D. K., Singh, R. S., Mandre, S., Bandi, M. M. (2016, 2016.12.12). Dynamics of a camphoric acid boat at the air-water interface, Hyderabad, India.
Bandi, M. M. (2016). (Hydro)Dynamics of self-propelled camphor boats. Paper presented at the Micro and Macro scale flows in Soft Matter, OIST Graduate University, Japan.
Bandi, M. M. (2016). Self-propelled Active Matter. Paper presented at the Hands-On Research in Complex Systems 2016, International Centre for Theoretical Physics, Trieste, Italy.
Bandi, M. M. (2016, 2016.07.21). The Spectrum of Wind Power Fluctuations. Paper presented at the Statphys 2016, Lyon, France.
Bandi, M. M. (2016, 2016.11.21). Spectrum of wind power fluctuations, Portland, Oregon, USA.
Bandi, M. M., Akella, V. S. (2016, 2016.12.13). The Granular Pebble Game, Hyderabad, India.
Bandi, M. M., Akella, V. S., Singh, D. K. (2016, 2016.11.20). Around a Camphoric Acid boat, is the surfactant adsorbed on to the interface or dissolved in the bulk?, Portland, Oregon, USA.
Bandi, M. M., Nguyen, K. D. (2016, 2016.11.21). Stiffness modulation of Rayed fins by curvature, Portland, Oregon, USA.
Akella, V. S., Singh, D. K., Singh, R. K., Mandre, S., Bandi, M. M. (2016). Dynamics of Camphoric Acid Boat at the Air-Water Interface. TIFR Mumbai, India.
Akella, V. S., Singh, D. K., Singh, R. K., Mandre, S., Bandi, M. M. (2016). Dynamics of Camphoric Acid Boat at the Air-Water Interface. IISc Bangalore, India.
Akella, V. S., Singh, D. K., Singh, R. K., Mandre, S., Bandi, M. M. (2016). Dynamics of Camphoric Acid Boat at the Air-Water Interface. TIFR Hyderabad, India.
Bandi, M. M. (2016). Spectrum of wind power fluctuation. Tata Institute of Fundamental Research, Mumbai, India.
Bandi, M. M. (2016). The Spectrum of Wind Power Fluctuations. Physics of Complex Systems, Department of Physics, Phillips University, Marburg, Germany.
Singh, D. K., Bandi, M. M. (2016). Use of 3D photoelastic model to extract three components of traction. EMU, JNCASR, Bangalore, India.
Singh, D. K., Bandi, M. M. (2016). Use of 3D photoelastic model to extract three components of traction. Mechanical department, iisc, Bangalore, India.

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